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Examination of the Explanatory Role
of Self-Evaluation Motives when Studying
Feedback-Seeking Behavior in Organizations
Frederik Anseel
Promotor: Prof. Dr. Filip Lievens
Proefschrift ingediend tot het behalen van de academische graad
van Doctor in de Psychologische Wetenschappen
2005
Examination of the Explanatory Role
of Self-Evaluation Motives when Studying
Feedback-Seeking Behavior in Organizations
Frederik Anseel
Promotor: Prof. Dr. Filip Lievens
Proefschrift ingediend tot het behalen van de academische graad
van Doctor in de Psychologische Wetenschappen
2005
CONTENTS
CONTENTS 5
ACKNOWLEDGEMENTS 9
INTRODUCTION 11
REFERENCES 15
CHAPTER 1 THE INTEGRAL ROLE OF SELF-MOTIVES IN
THE FEEDBACK-SEEKING PROCESS: TOWARDS A MORE
COMPREHENSIVE MODEL 17
ABSTRACT 17
INTRODUCTION 18
METHOD 20
RESULTS OF THE REVIEW 21
Model Underlying Previous Studies 21
Antecedents 22
Outcomes 28
MOTIVES OF THE SELF 30
Background, Assumptions, and Motives 30
Implications of Self-Motives for Antecedents of Feedback-seeking Behavior 33
Implications of Self-Motives for Outcomes of Feedback-seeking Behavior 37
Underlying Model for Future Research 41
CONCLUSIONS 44
THE PRESENT DISSERTATION 45
REFERENCES 49
APPENDIX: SUMMARY OF STUDIES WHICH INVESTIGATED FEEDBACK-SEEKING
BEHAVIOR IN ORGANIZATIONS 60
6 CONTENTS
CHAPTER 2 AN EXAMINATION OF STRATEGIES FOR
DIRECTING FEEDBACK-SEEKING TOWARDS SPECIFIC
PERFORMANCE DIMENSIONS 67
ABSTRACT 68
INTRODUCTION 68
THEORETICAL BACKGROUND 70
Importance Beliefs 70
Modifiability Beliefs 72
OVERVIEW OF CURRENT STUDY 74
Method 75
Results 81
DISCUSSION 86
Boundary Conditions and Future Research 89
REFERENCES 93
CHAPTER 3 A CLOSER LOOK AT THE RELATIONSHIP
BETWEEN UNCERTAINTY AND FEEDBACK-SEEKING 99
ABSTRACT 100
INTRODUCTION 100
THEORETICAL BACKGROUND 102
Uncertainty Reduction Theory 102
Self-Verification Theory 103
Uncertainty Reduction and Self-verification Theory 104
Integrating Uncertainty Reduction and Self-Verification 105
BETWEEN- AND WITHIN-PERSONS APPROACHES 107
STUDY 1 109
Method 109
Results and Discussion 111
STUDY 2 114
Method 114
Results and Discussion 116
GENERAL DISCUSSION 121
CONTENTS 7
Curvilinear Relationship 121
Feedback-seeking Strategies 122
Individual Differences as Moderators 124
Practical Implications 125
Limitations 127
CONCLUSION 128
REFERENCES 129
APPENDIX 135
CHAPTER 4 CERTAINTY AS A MODERATOR OF
FEEDBACK REACTIONS: A TEST OF THE STRENGTH OF
THE SELF-VERIFICATION MOTIVE 137
ABSTRACT 138
INTRODUCTION 138
THEORETICAL BACKGROUND 140
Integrating Self-Verification and Self-Enhancement Motives 141
UNIQUE CONTRIBUTIONS OF CURRENT STUDY 143
STUDY 1 145
Method 145
Results 149
STUDY 2 152
Method 152
Results 154
GENERAL DISCUSSION 158
REFERENCES 165
CHAPTER 5 DOES ELABORATION OF FEEDBACK
ENHANCE THE FEEDBACK – TASK PERFORMANCE
RELATIONSHIP? 171
ABSTRACT 172
INTRODUCTION 172
BACKGROUND 173
Recent Research on the Feedback-Performance Relationship 173
8 CONTENTS
Theoretical Basis of Elaboration 175
Practical Basis of Elaboration 177
STUDY 179
Method 179
Results 184
DISCUSSION 188
Practical Implications, Limitations, and Directions for Future Research 191
CONCLUSION 194
REFERENCES 196
APPENDIX A EXAMPLE OF AN IN-BASKET ITEM AND THE CORRESPONDING
PARALLEL ITEM 201
APPENDIX B EXAMPLE OF FEEDBACK REPORT FOR COMPETENCY
“COORDINATING” 203
CHAPTER 6 GENERAL CONCLUSIONS 205
ABSTRACT 205
RESEARCH OVERVIEW 206
Objective 1: Identifying New Antecedents of Feedback-seeking Behavior 206
Objective 2: A Closer Look at Unresolved Issues in the Feedback-Seeking
Process 207
Objective 3: Understanding and Enhancing the Feedback - Performance
Relationship 209
CONTRIBUTIONS, LIMITATIONS, AND RESEARCH OPPORTUNITIES 211
From a Theoretical Perspective 211
From a Methodological Perspective 215
From a Practical Perspective 218
REFERENCES 224
ACKNOWLEDGEMENTS
This doctoral thesis was accomplished while I was working as a Research
Assistant of the Special Research Fund at the Department of Personnel
Management, Work and Organizational Psychology of Ghent University,
Ghent, Belgium. I would like to thank these institutions for their support.
First of all, I want to thank my advisor Prof. Dr. Filip Lievens for his
excellent guidance on my first steps in academia. Actually, “excellent” is
somewhat of an understatement. He introduced me to the field and taught me
all the ins and outs of doing research in I/O psychology. He encouraged me
to seek my own research path, and generously shared his incredible
expertise. His drive and enthusiasm has proven to be dangerously infectious.
A second person who played a key role is Prof. Dr. Rita Claes. As head of
the department, she provided the ideal conditions to complete this
dissertation. Her help in contacting the Flemish Public Employment Service
for conducting the field studies was very valuable. Her advice and comments
on various papers and proposals were much appreciated and helped me to
stay focused.
I’m very grateful to Marc Covents who did all the programming work for the
in-basket exercise. I couldn’t dream of a better programmer to develop this
management simulation. Marc combines great technical skills with a drive
for perfection, and an inexhaustible patience to put up with my sheer endless
requests for modifications. I’m sure there were times he cursed the day we
met. Thanks for your excellent work, Marc.
Very special thanks go to Dr. Wouter Duyck, who was my help-desk deluxe
during the past four years. He provided assistance in writing research
proposals, solving lay-out problems, conducting statistical analyses, getting
me alive out of a taxi in Beijing, and saving me from starvation during work
hours.
10 ACKNOWLEDGMENTS
I would like to thank and acknowledge the following people for their
valuable suggestions on my work in the past four years and for making the
empirical studies possible: Y. Bostyn (VDAB), Prof. Dr. S. Brutus
(Concordia University), Prof. Dr. J. Edwards (University of North Carolina),
Prof. Dr. J. Fontaine (UGent), Prof. Dr. W. Fias (UGent), M. Gillebeert
(VDAB), Prof. Dr. M. Harris (University of Missouri - St.-Louis), D.
Houbrechts (VDAB), Prof. Dr. A. Kluger (The Hebrew University of
Jerusalem), Prof. Dr. P. Levy (University of Akron), S. Maertens (VDAB),
K. Naessens (KATHO), Dr. M. Schittekatte (UGent), Prof. Dr. L. Sels
(KUL), Prof. Dr. W. Swann (University of Texas), Prof. Dr. R. Tett
(University of Tulsa), Prof. Dr. I. Van Den Brande (VLEKHO), I.
Vandamme (KATHO), Prof. Dr. A. Van Hiel (UGent), C. Van Rillaer
(VDAB).
I would also like to thank all my colleagues and former colleagues of the
Department of Personnel Management, Work and Organizational
Psychology for making this department such a great place to work and for
their continuous encouragements during these last months. Special thanks go
to Stefaan, Helga, Colin and Greet for reviewing and editing my papers, to
Hans for his computer savvy and to Bart for his indispensable problem-
solving skills.
Finally, I should not forget the moral support I received during all those
years from my father, my mother, my sister, and, of course, from my
girlfriend. Jane, thanks for being there from start to finish. Whatever analysis
I conducted, you always turned out to be the most significant factor with the
widest confidence interval. I hope I can help you as much as you helped me.
You’re up next!
Frederik Anseel, Ghent, February 2nd, 2005
INTRODUCTION
“How am I doing ?!!” - In a recent speech, endorsing the sitting president’s
re-election campaign, former New York City mayor Ed Koch could not
resist tapping into his trademark “how am I doing”-line. The crowd roared
with applause and cheering. In the 1980s, mayor Ed Koch became famous
for walking the streets of New York, and asking citizens the same question
over and over, “How am I doing?” Apparently, gathering feedback about his
administration was important to him, and as you would expect, New York
City voters were happy to provide him with feedback. This unorthodox
feedback-seeking strategy attracted worldwide attention, as it appealed to a
basic human need, the need for obtaining feedback about one’s own
performance.
Providing feedback to people, that is, informing people about the results of
their performance to stimulate development and improvement, has become
one of the most widely accepted and applied psychological interventions.
Across a wide range of settings, feedback is believed to direct, motivate, and
reward behavior. The assumption that giving feedback is beneficial for
individual and group performance has also been widely supported in
organizations. This assumption is well reflected in a number of statements of
prominent researchers in the performance feedback domain:
“Numerous studies have examined the effect of feedback on
performance, and practically all of these investigations have
supported the existence of such a relationship” (Becker &
Klimoski, 1989, p. 343)
“The positive effect of feedback on performance has become one of
the most accepted principles in psychology” (Pritchard, Jones,
Roth, Stuebing, & Ekeberg, 1988, p. 338)
12
“The importance of feedback as a tool for enhancing performance
in organizations can hardly be overestimated” (Larson, 1989, p.
408)
As described by Kluger & DeNisi (1996, 1998), feedback research dates
back more than 100 years. In the beginning of the previous century, several
scholars experimented with providing individuals “knowledge of
results”(KR) about task performance to improve subsequent performance.
Thorndike (1927) provided the initial theoretical arguments for the
effectiveness of feedback with his law of effect. Based on the law of effect,
positive feedback was equated with reinforcement and negative feedback
with punishment. Reinforcement and punishment facilitate learning and thus,
both positive and negative feedback should improve performance because
one reinforces the correct behavior and the other punishes the incorrect
behavior. The first feedback studies suffered from methodological problems
and often did not pay attention to inconsistent results. Still, these flawed
studies installed the first vague though persistent notions about the beneficial
role of giving feedback. The wonder years of feedback research were
summarized by Ammons (1956) in a review of the effectiveness of
“knowledge of results” interventions. Ammons’ most important conclusions
were (a) that knowledge of results increases learning, and (b) that knowledge
of results increases motivation. Although the evidence Ammons reported
was highly questionable and ignored contradictory studies, his conclusions
had substantial impact on the psychological literature of its time. The
conviction that feedback always has a strong enhancing effect on
performance was further spread and became generally accepted knowledge
for years, as illustrated in the above cited statements.
However, in the 80s several studies began reporting that “there was
something rotten in the state of Denmark”, suggesting that the relationship
between feedback and performance was more complicated than had
previously been assumed (Balcazar, Hopkins, & Suarez, 1985; Salomi,
Schmidt, & Walter, 1984; Taylor, Fisher, & Ilgen, 1984). Ilgen, Fisher, and
INTRODUCTION 13
Taylor (1979) were among the first to note that relating feedback directly to
feedback was very confusing and that results were contradictory and seldom
straightforward. In their review paper, they argued that the effects of
feedback interventions on performance could only be understood if research
gained more insight in how feedback recipients responded to feedback.
Around the same time, a new and innovating perspective on the feedback
process was articulated. In this perspective, organizations were depicted as
feedback-rich environments, wherein employees were not condemned to
passively wait for feedback, but acted as active monitors and seekers of
feedback (Ashford & Cummings, 1983; Hanser & Muchinsky, 1978; Herold
& Parsons, 1985). This new perspective radically differed from previous
feedback process conceptualizations as it portrayed the feedback recipient no
longer as a passive information-processor, but as an active information-
seeker. The stage was set for the study of feedback-seeking behavior, which
would become the most dominant and prolific research theme in the
feedback domain in years to come. One of the aspirations of feedback-
seeking research was to shed new light on the troubling feedback –
performance relationship by examining the active role of the feedback-
seeker. It was assumed that people would be more willing to act on feedback
they had sought themselves, leading to more likely performance
improvement. Consequentially, organizations were adviced to look for
managerial strategies to promote feedback-seeking if they wanted to improve
individual and organizational performance. The feedback-seeking entreprise
received additional impetus when an extensive quantitative review of
feedback interventions demonstrated that the effects of giving feedback on
performance were still far from understood (Kluger & DeNisi, 1996, 1998).
This meta-analysis showed that in more than one third of the cases feedback
impaired performance and that there was no general principle that could
predict the effectiveness of feedback interventions. As it became clear that
giving feedback to people often produced detrimental effects on
performance, research looking for practical strategies to encourage feedback-
14
seeking and examining outcomes of feedback-seeking, grew even more in
importance.
The first chapter of this dissertation presents an overview of past feedback-
seeking research by systematically reviewing 49 studies that examined
organizational feedback-seeking behavior. On the basis of this review, the
main limitations of previous feedback-seeking research are summarized. An
alternative model that, on the one hand, might increase understanding of
feedback-seeking behavior in organizations, and, on the other hand, provides
several new avenues for future research, is presented. At the same time, this
model depicts the broad framework that connects the various empirical
studies that are presented in this dissertation. At the end of this first chapter,
a general outline of these empirical studies is provided with specific
attention to how these studies relate to the framework that has been
presented.
INTRODUCTION 15
REFERENCES
Ammons, R. B. (1956). Effects of knowledge of performance: A survey and
tentative theoretical formulation. Journal of General Psychology, 54, 279-299.
Ashford, S. J., & Cummings, L. L. (1983). Feedback as an individual resource:
Personal strategies of creating information. Organizational Behavior and Human
Performance, 32, 370-398.
Balcazar, F., Hopkins, B. L., & Suarez, Y. (1985). A critical, objective review of
performance feedback. Journal of Organizational Behavior Management, 7, 65-
89.
Becker, T. E., & Klimoski, R . J. (1989). A field study of the relationship between
the organizational feedback environment and performance. Personnel Psychology,
42, 343-358.
Hanser, L. M., & Muchinsky, P. M. (1978). Work as an information environment.
Organizational Behavior and Human Performance, 13, 244-256.
Herold, D. M., & Parson, C. K. (1985). Assessing the feedback environment in
work organizations: Development of the job feedback survey. Journal of Applied
Psychology, 70, 290-305.
Ilgen, D. R., Fisher, C. D., & Taylor, M. S. (1979). Consequences of individual
feedback on behavior in organizations. Journal of Applied Psychology, 64, 349-
371.
Kluger, A. N., & DeNisi, A. S. (1996). The effects of feedback interventions on
performance: A historical review, a meta-analysis, and a preliminary feedback
intervention theory. Psychological Bulletin, 119, 254-284.
Kluger, A. N., & DeNisi, A. S. (1998). Feedback interventions: Toward the
understanding of a double- edged sword. Current Directions in Psychological
Science, 7, 67-72.
Pritchard, R. D., Jones, S. D., Roth, P. L., Stuebing, K. K., & Ekeberg, S. E. (1988).
Effects of group feedback, goal setting, and incentives on organizational
productivity. Journal of Applied Psychology, 73, 337-358.
Salmoni, A. W., Schmidt, R. A., & Walter, C. B. (1984). Knowledge of results and
motor learning: A review and critical reappraisal. Psychological Bulletin, 95, 355-
386.
Taylor, M. S., Fisher, C. D., & Ilgen, D. R. (1984). Individuals’ reactions to
performance feedback in organizations: A control theory perspective. In K. M.
Rowland & G. R. Ferris (Eds.), Research in personnel and human resources
management (Vol. 2, pp. 81-124). Greenwich, CT: JAI Press.
16
Thorndike, E. L. (1927). The law of effect. American Journal of Psychology, 39,
212-222.
CHAPTER 1
THE INTEGRAL ROLE OF SELF-MOTIVES
IN THE FEEDBACK-SEEKING PROCESS:
TOWARDS A MORE COMPREHENSIVE MODEL1, 2
ABSTRACT
This article reviews 49 studies that have examined feedback-seeking
behavior in organizations. The review shows that a resource-based
perspective of feedback-seeking behavior has dominated the field. However,
several mixed results about antecedents and outcomes of feedback-seeking
behavior could not be explained on the basis of the dominant resource-based
framework. Borrowing from research on self-motives in social psychology,
we offer a new theoretical perspective and more comprehensive model that
might guide future research. In particular, we propose three new directions
for future research. First, on the basis of the self-motives framework several
new antecedents of feedback-seeking behavior might be identified. Second, a
new light might be shed on unresolved issues in antecedents of feedback-
seeking behavior by considering the role of different self-motives in the
feedback-seeking process. Third, the relation between feedback-seeking
behavior and performance can be better understood by considering feedback
reactions in relation to self-motives. These new directions offer an
alternative and more theoretically-driven underpinning for studying
feedback-seeking behavior in organizations.
1 Parts of this review study were published in the Dutch blind peer-reviewed journal
“Gedrag & Organisatie”. The full reference is: Anseel, F., & Lievens, F. (2002).
Feedback-zoekend gedrag in organisaties: Literatuuroverzicht en richtingen voor
toekomstig onderzoek. Gedrag & Organisatie, 5, 294-319.
2 This paper benefited significantly from several excellent suggestions made by Paul
Levy.
18 CHAPTER 1
INTRODUCTION
In the last twenty years, an increasing number of studies has examined how
employees take on an active role in the feedback process and seek out
feedback themselves. By asking for feedback, employees can adjust their
goal-directed behavior (Morrison & Weldon, 1990), better assess their
capabilities (Ashford & Tsui, 1991; Williams & Johnson, 2000), manage
impressions about their performance potential (Ashford & Northcraft, 1992),
enhance their future effectiveness (Morrison, 1993; Renn & Fedor, 2001),
and “learn the ropes” of a new job (Morrison, 1993).
In their seminal work, Ashford and Cummings (1983) introduced feedback-
seeking behavior as “a conscious devotion of effort toward determining the
correctness and adequacy of behaviors for attaining valued end states.”
(Ashford & Cummings, 1986, p. 466). The theoretical model of Ashford and
Cummings took a “resource-based” perspective (also called a “cost-value”-
perspective). Ashford and Cummings proposed that employees make an
assessment of the costs and values that are associated with feedback-seeking
and that this cost-value analysis is the primary determinant of subsequent
feedback-seeking behavior. For instance, people will seek more feedback
from a source with a high expertise on a feedback matter because feedback
from this source is more valuable. Conversely, employees will seek less
feedback in public because of fear for face-loss in the presence of their
colleagues.
The purpose of this article is to provide a review of research on feedback-
seeking behavior and to offer a new theoretical perspective on the feedback-
seeking process in organizations. Granted, there have been other reviews of
the feedback-seeking literature (Ashford, Blatt, & VandeWalle, 2003;
Morrison, 2002). However, none of these earlier reviews have focused on
feedback-seeking from the broader social psychological literature. Yet, we
argue that theoretical perspectives in social psychology are of key relevance
SELF-MOTIVES IN FEEDBACK-SEEKING 19
to the organizational feedback-seeking literature for various reasons. First,
feedback-seeking behavior in organizations is historically grounded in social
psychology (see Ashford & Cummings, 1983). Since its origin, the literature
on organizational feedback-seeking has evolved independently from research
on self-evaluation processes in social psychology. Although several
similarities can be noted between the two domains, the social psychological
literature on self-evaluation processes has taken a broader perspective, and
now deals with how and why people select, process, and react to self-
relevant information across a variety of contexts. In social psychology,
feedback-seeking behavior is only one special case of the broad self-
evaluation framework. So far, this conceptually similar framework has
remained largely ignored in feedback-seeking research in organizations.
Second, although we believe that knowledge relevant to feedback-seeking
has advanced considerable over the last decades, in recent years several
inconsistencies and shortcomings have been noted (see Ashford et al., 2003;
Farr, 1993; VandeWalle, 2003). Furthermore, previous studies on feedback-
seeking behavior in organizations are almost entirely grounded in the
original resource-based perspective, introduced by Ashford and Cummings
(1983). A new theoretical perspective on feedback-seeking behavior might
shed additional light on these inconsistencies and shortcomings, and might
advance our understanding of the antecedents and outcomes of feedback-
seeking behavior. In short, despite the fact that seeking feedback in
organizations is essentially a self-evaluation process, the feedback-seeking
literature has not kept pace with social psychological advances in research
on self-motives. We have given special consideration, therefore, to recent
theoretical developments in social psychology as they relate to feedback-
seeking behavior in organizations.
The structure of this review is as follows. In a first section, we use
Morrison’s (2002) integrated model of information seeking as a way to
organize a systematic review of the prior empirical literature on feedback-
seeking, including both field and laboratory studies. On the one hand we
summarize the most important findings about feedback-seeking behavior in
20 CHAPTER 1
organizations. On the other hand we point out that there still are some
inconsistent findings and shortcomings in the research domain. In the second
section, we introduce various self-(evaluation) motives. On the basis of this
new perspective we propose several avenues for future research. These
recommendations are based on recent research on self-motives in social
psychology. By using this social psychological framework as a theoretical
underpinning, we aim to ground feedback-seeking behavior back to its roots
in social psychology.
METHOD
To be included in the review, we used the following criteria. First, a study
had to empirically examine a relationship between feedback-seeking
behavior (direct or indirect) and one or more antecedents or outcome
variables. Second, studies had to be conducted in a (simulated)
organizational context. We used a number of electronic databases (PsychLit,
Social Science Citation Index and Current Contents) to detect relevant
studies. Additionally, we scrutinized reference lists from obtained studies to
find other published and unpublished studies. Finally, researchers in the
feedback-seeking domain were contacted to retrieve more unpublished
papers.
Forty-nine studies, dating from 1985 to 2004 conformed to the stated
criteria. Thirty-seven studies were published, 12 studies were unpublished.
Seventeen studies used an experimental design, 26 studies used a cross-
sectional design, and 6 studies used a longitudinal design. For comparison
purposes, the results of each study are synthesized in the appendix. For each
study, we describe the objective, the sample, the design, the antecedents, and
the outcomes. In the appendix, we provide the nature of the zero-order
correlation between the feedback-seeking behavior and the antecedents and
outcomes as follows: a significant positive relationship (+), no significant
SELF-MOTIVES IN FEEDBACK-SEEKING 21
relationship (ns.), and a negative significant relationship (-). All studies
included in our review are marked by an asterisk in the Reference list.
RESULTS OF THE REVIEW
MODEL UNDERLYING PREVIOUS STUDIES
As mentioned before, almost all the studies in the appendix were guided by
perceptions of feedback costs and feedback value. In particular, 45 studies
examined antecedents that might affect cost and value perceptions and
feedback-seeking behavior. In Figure 1, a simplification of Morrison’s
(2002) integrative conceptual model is provided. We believe this model
depicts the kind of approach that has guided previous feedback-seeking
research. Basically, Morrison’s model suggests both individual and
contextual antecedents to a desire for or perceived need for feedback.
Feedback-seeking costs play an important role in this model, moderating the
relationship between one’s desire or felt need for feedback and actual
feedback-seeking intentions. Feedback-seeking research has traditionally
been built around this idea of comparing costs and values of feedback-
seeking or what Ashford and Cummings (1983) called a resource-based
approach. There has not been very much research looking at outcomes of
feedback-seeking behavior. Further, research has not been especially
effective in distinguishing among the various outcomes of feedback-seeking
behavior. Morrison breaks the outcomes up into primary and secondary
outcomes, but notes that most research has been focused on performance
improvement and, in all, the research has been inconsistent. We will use
Morrison’s integrated model as a framework for our review of the existing
literature.
22 CHAPTER 1
FIGURE 1: A SIMPLIFICATION OF MORRISON’S (2002) CONCEPTUAL MODEL OF FEEDBACK-SEEKING.
ANTECEDENTS
Individual antecedents. The study of individual antecedents that influence
feedback-seeking behavior has been mainly guided by possible value
(benefits) perceptions of feedback-seeking behavior (Ashford, 1986;
VandeWalle, Challagalla, Ganesan, & Brown, 2000; VandeWalle &
Cummings, 1997). First, feedback can be advantageous because it can help
employees to attain various valued end states and personal goals. Therefore,
it is hypothesized that antecedents, that are related to the value of a particular
goal or to the expectation of attaining a certain goal, will be significantly
related to feedback-seeking behavior. Consistent with this expectation,
several studies in the appendix showed that goal attainment (Ashford, 1986;
Morrison & Weldon, 1990), performance expectations (Ashford, 1986;
Morrison & Cummings, 1992; Northcraft & Ashford, 1990; Thomas &
Williams, 1998), need for achievement (Klich & Feldman, 1992), and job
involvement (Ashford & Cummings, 1985) were positively related to
feedback-seeking behavior.
A second benefit associated with feedback-seeking is that feedback is a
valuable source of information because feedback can be used to reduce
uncertainty (Ashford & Cummings, 1983). Some studies in the appendix
Individual
antecedents
Felt need
for
feedback
Feedback
seeking
costs
Intention to
seek
feedback
Feedback
seeking
Contextual
antecedents
Primary and
secondary
outcomes
SELF-MOTIVES IN FEEDBACK-SEEKING 23
supported this hypothesis (Ashford & Cummings, 1985; Callister, Kramer,
& Turban, 1999; Fedor et al., 1992,), but Morrison (2002) argues that it is
surprising that research has neither focused very heavily or directly on
uncertainty as a motivator of feedback-seeking nor on the role of feedback-
seeking in reducing uncertainty. From the research that does exist, one could
conclude that antecedents that are conceptually related to uncertainty (e.g.,
role ambiguity, role conflict, tolerance for ambiguity) had a positive effect
on feedback-seeking behavior (Ashford & Cummings, 1985; Fedor,
Rensvold, & Adams, 1992; Madzar, 2001). Moreover, research showed that
newcomers in organizations seek more feedback for reducing their
uncertainty (Ashford & Black, 1996; Brett, Feldman, & Weingart, 1990;
Callister et al., 1999; Morrison, 1993; Morrison, Chen, & Salgado, 2004).
However, no unequivocal conclusions about the role of uncertainty in the
feedback-seeking process can be drawn because other studies yielded
conflicting findings (Ashford, 1986; Fedor et al., 1992; Gupta,
Govindarajan, & Malhotra, 1999; Stark & Sommer, 2000). Using various
measures of uncertainty, these studies revealed that high levels of certainty
also lead to increased feedback-seeking behavior. Thus, employees who
already have high certainty about their performance continue to seek
feedback. Furthermore, several studies failed to support the hypothesis that
more tenured employees, which are supposed to suffer less from uncertainty,
seek less feedback (Brutus & Cabrera, 2004; Gupta et al., 1999; Renn &
Fedor, 2001; Roberson, Deitch, Brief, & Block, 2003; Wanberg &
Kammeyer-Mueller, 2000).
Competence creation and achieving a sense of mastery serves as a final
benefit that employees might experience by seeking feedback (Ashford &
Cummings, 1983). Along these lines, goal orientation has been found to be
an important antecedent. Two major classes of goal orientations are typically
distinguished – a learning and a performance goal orientation. Individuals
with a learning goal orientation seek to develop themselves by improving
their ability, acquiring new skills, and mastering new situations. In contrast,
people with a performance goal orientation seek to demonstrate and validate
24 CHAPTER 1
the adequacy of their ability by seeking favorable judgments and avoiding
negative judgments about their ability (Dweck & Legget, 1988; VandeWalle
& Cummings, 1997). VandeWalle and Cummings proposed that employees
with a goal orientation would seek more feedback, even in challenging
situations or when the necessary skills are not available. Individuals with a
learning goal orientation tend to view feedback in terms of its diagnosticity
and focus on how likely this feedback is to help them to improve
performance, whereas people with a performance goal orientation tend to
interpret feedback rather as an appraisal of their competency and worth.
Thus, employees with a learning goal orientation attach more value to
feedback as compared to employees with a performance goal orientation.
The appendix shows that these hypotheses have been supported by a series
of empirical studies (Farr, Ringseis & Unckless, 1999, Madzar, 2001; Moon
& Levy, 2000; Nowakowski & Kozlowski, 2004; Park, Schmidt, Scheu, &
Deshon, 2003; Stark & Sommer, 2000; Tuckey, Brewer, & Williamson,
2002; VandeWalle et al., 2000; VandeWalle & Cummings, 1997).
A number of scholars also investigated individual antecedents that influence
perceptions of feedback costs. It was hypothesized that the cost of feedback-
seeking was higher for people with low self-efficacy because of the
detrimental impact negative feedback might have on the feedback-seeker’s
self-image. However, research shows that this individual difference variable
is not directly related to feedback-seeking behavior (Brown et al., 2001;
Moon & Levy, 2000; Renn & Fedor, 2001). Instead, it seems to act as a
moderator in the feedback-seeking process. For example, Moon and Levy
(2000) demonstrated that the relation between performance goal orientation
and feedback-seeking behavior was negative for employees with a high self-
efficacy. They concluded that individuals with a low performance
orientation and a high self-efficacy, frequently seek feedback because they
have high confidence in their abilities and are more eager to use the
feedback. Employees with a low performance orientation and a low self-
efficacy exhibited lower levels of feedback-seeking behavior.
SELF-MOTIVES IN FEEDBACK-SEEKING 25
Whereas self-efficacy refers to a context-specific assessment of competence
to perform a specific task or a range of tasks in a given domain (Bandura,
1997), self-esteem refers to a global cognitive appraisal of the self-concept.
The appendix shows that the relationship between self-esteem and feedback-
seeking behavior is not very clear. For example, Ashford (1986), Morrison
(1993), and Levy, Albright, Cawley, and Williams (1995) found no
significant relationship. Northcraft and Ashford (1990) reported that self-
esteem was significantly related to feedback-seeking behavior about absolute
performance levels. Yet, it was not related to feedback-seeking about
comparative (relative to others) performance levels. Fedor et al. (1992)
found a negative relationship between self-esteem and direct feedback-
seeking (inquiry) but not between self-esteem and indirect feedback-seeking
(monitoring). Moss, Valenzi, and Taggart (2003) found that employees with
high self-esteem sought more positive feedback for reasons of impression
management. Finally, Vancouver and Morrison (1995) revealed that the
relationship between self-esteem and feedback-seeking was moderated by
the quality of the relation between the feedback source and the feedback-
seeker.
Conclusion. Our review of individual antecedents of feedback-seeking
behavior leads to three conclusions. First, it appears that individual
antecedents referring to the attainment of valued goals and competence
creation are positively related to value perceptions of feedback and
accordingly to feedback-seeking behavior. Second, the cost-value model of
feedback-seeking behavior has led to mixed findings and has only been
sporadically tested. For example, the relationship between antecedents that
are conceptually related to the uncertainty reducing function of feedback
(e.g., tenure) and feedback-seeking behavior is not clear. A third conclusion
concerns the inconsistent findings about the role of two individual difference
variables (i.e., self-esteem, and self-efficacy) in the feedback-seeking
process.
26 CHAPTER 1
It is important for future research to shed light on these inconsistent findings.
We believe that recent empirical and theoretical work in social psychology
can accomplish this, attributing a central role to the various self-motives that
guide behavior in self-evaluative situations. A limitation of previous
research examining feedback-seeking behavior in organizations is that
generally only one dominant motive underlying feedback-seeking behavior
is acknowledged, namely the uncertainty reduction motive. In other words,
although impression management and ego maintenance have been suggested
as important motives (Levy et al., 1995), it has generally been assumed that
people are more driven by feelings of uncertainty and this uncertainty drives
decisions to seek feedback, thereby reducing uncertainty and improving
performance.
Contextual antecedents. Whereas research on individual antecedents of
feedback-seeking research has primarily paid attention to the value of
feedback-seeking behavior, research on contextual antecedents has focused
on the costs associated with feedback-seeking. The perceived costs of
feedback-seeking behavior have been shown to be an important predictor of
feedback-seeking behavior (Ashford & Cummings, 1983, 1986; Fedor et al.,
1992; Thomas & Williams, 1998; Vandewalle & Cummings, 1997). When
people believe that seeking feedback will convey a negative image of
themselves (e.g., looking insecure, unconfident, incompetent) to their
supervisor and colleagues, they will refrain from seeking feedback.
The first contextual antecedent that influences the costs associated with
feedback-seeking is the presence of significant others. As can be seen in the
appendix, research has revealed that employees seek more feedback when
feedback-seeking behavior does not take place in public (Ashford &
Northcraft, 1992; Northcraft & Ashford, 1990), when the situation is
perceived as private (Levy et al., 1995; Moon & Levy, 2000; Williams,
Steelman, Miller, & Levy, 1999), when feedback can be requested and/or
provided via a computer (Ang & Cummings, 1994; Ang, Cummings, Straub,
& Early, 1993; Kluger & Adler, 1993), when stereotype threat is low
SELF-MOTIVES IN FEEDBACK-SEEKING 27
(Roberson, Deitch, Brief, & Block, 2003), and when other colleagues also
seek feedback (Ashford & Northcraft, 1992; Williams et al., 1999). These
contextual studies have typically revealed that the influence of the
environment is moderated by the presence of individual antecedents. For
example, Northcraft and Ashford (1990) found that context interacted with
performance expectations. Employees with low performance expectations
sought less feedback in a public environment, because they anticipated the
potential face-loss in presence of their colleagues and refrained from seeking
feedback. However, the anticipation of positive feedback in people with high
performance expectations yielded an appropriate opportunity to make a
positive impression to others, leading to higher levels of feedback-seeking in
public.
The costs and drawbacks associated with feedback-seeking are also be
influenced by the characteristics of the feedback-sender. Several studies in
the appendix have shown that the following characteristics of the feedback-
sender are positively related to feedback-seeking behavior: positive mood
(Ang et al., 1993), consideration and supportiveness (Brown et al., 2001;
Farr et al., 1999; Kuchinke, 2001; Levy, Cober, & Miller, 2002; Steelman,
Levy, & Snell, 2004; Thomas & Williams, 1998; Wiliams et al., 1999),
charisma (Kuchinke, 2000), accessibility, close relationship, reward power
(Thibodeaux & Kudisch, 2000; Vancouver & Morrison, 1995), and a
transformational leadership style (Levy et al., 2002; Madzar, 2001). The
credibility of the feedback-sender appears to have an influence on the value
perceptions of feedback. Employees are most likely to seek feedback from
high expertise feedback sources because their feedback is seen as more
valuable (Fedor et al., 1992; Morrison, 1993; Steelman et al., 2004;
Thibodeaux & Kudisch, 2000; Vancouver & Morrison, 1995).
Recent studies have also paid attention to cultural differences in feedback-
seeking behavior, as proposed by Sully de Luque and Sommers (2000).
Results of these studies indicated substantial variations in feedback-seeking
behavior across cultures. More specifically, individuals from the United
28 CHAPTER 1
States exhibited more direct feedback-seeking behavior (inquiry) than
individuals from Asian cultures, due to differences in self-assertiveness,
power distance, and perceived face-loss costs (Brutus & Cabrera, 2004;
Kung & Steelman, 2003; Morrison, Chen, & Salgado, 2004).
The degree of structure in an organization (e.g., in a specific team or
department) is a final contextual antecedent. This variable refers to the extent
that roles and responsibilities on the job are clearly defined and structured by
the supervisor or manager. Initially, Ashford and Cummings (1983) expected
a negative relationship with feedback-seeking behavior: when job roles are
clearly defined, employees do not suffer from uncertainty and are less
motivated to seek feedback. However, empirical research has demonstrated a
positive relationship between structure and feedback-seeking behavior
(Brown et al., 2001; VandeWalle et al., 2000). Apparently, providing a high
degree of structure involves setting clear and attainable goals (Fleishman &
Peters, 1962). Goal-setting encourages employees to seek feedback for
obtaining more clarity about the progress made toward attaining these the
goals (Morrison & Weldon, 1990).
Conclusion. Research examining situational antecedents of feedback-
seeking behavior has yielded several consistent findings. The presence of
significant others, the characteristics of the feedback source, and the degree
of job structure affect the potential costs linked to feedback-seeking and in
turn feedback-seeking behavior. Research also suggests that feedback-
seeking strategies are not universal but vary across cultures.
OUTCOMES
Only 18 of the 49 studies measured outcomes of feedback-seeking behavior.
Most studies tested whether there was a positive relationship between
feedback-seeking behavior and performance. One of the main tenets of
Ashford and Cummings’ (1983) feedback-seeking theory was that people
who actively seek feedback, would be more likely to improve performance.
SELF-MOTIVES IN FEEDBACK-SEEKING 29
A first group of studies in the appendix found empirical support for this
hypothesis (Ashford & Northcraft, 1992; Ashford & Tsui, 1991; London,
Larsen, & Thisted, 1999; Morrison & Weldon, 1990). A second group of
studies failed to find support for a positive relationship between feedback-
seeking behavior and performance (Ang et al., 1993; Ashford & Black,
1996; Klich & Feldman, 1992; Moon & Levy, 2000) or reported a negative
relationship (Brown et al., 2001; Fedor et al., 1992). Finally, a third group of
studies illustrated that the relationship between feedback-seeking behavior
and performance was more complicated than previously thought. For
example, Renn and Fedor (2001) reported that feedback-seeking behavior
did not lead to a direct improvement in the quality and quantity of
performance, but was indirectly related to work performance through
personal improvement goals established from performance feedback.
Morrison (1993) reported a positive relationship between monitoring
(indirect feedback-seeking) and performance but no significant relationship
between inquiry (direct feedback-seeking) and performance. Furthermore,
seeking social feedback ("Is my behavior acceptable ?") had no influence on
performance (Morrison, 1993).
The appendix further shows that there is a paucity of studies examining
outcomes of feedback-seeking behavior other than performance
improvement. Hence, Morrison (2002) suggested that future research should
examine other primary and secondary outcomes such as knowledge,
uncertainty reduction, and job attitudes. Only a few other outcomes have
attracted some research attention. Specifically, seeking feedback leads to a
higher congruence between self-appraisals and appraisals by others (Ashford
& Tsui, 1991; Williams & Johnson, 2000). In addition, people who
frequently seek feedback were less inclined to leave the organization and
reported more job satisfaction (Kuchinke, 2000; Morrison, 1993; Wanberg
& Kammeyer-Mueller, 2000). However, this relationship with job
satisfaction was not supported by Ashford and Black (1996). Finally, one
study found that feedback-seeking from clients yielded higher client
satisfaction (Barnard & Greguras, 2001).
30 CHAPTER 1
Conclusion. Prior research yielded mixed results concerning the relationship
between feedback-seeking behavior and performance improvement. These
inconsistent findings do not support one of the main assumptions of the
theory of Ashford and Cummings (1983). Given the importance of the
feedback-seeking – performance relationship, more research examining this
relationship is needed. Again, we hypothesize that recent research in social
psychology can shed light on these unclear findings. In particular, we
propose that many studies fail to uncover the expected relationship between
feedback-seeking behavior and performance because employees’ motives
underlying feedback and their reactions to feedback have been largely
ignored. In the remainder of this paper, we develop a conceptual argument
and model (See Figure 2) that provides a reasonable explanation for the lack
of consistent effects in the feedback-seeking literature. First, we will discuss
self-motives and the role that they play in the feedback-seeking process.
Second, we will consider other outcomes of feedback-seeking such as
employee reactions and propose where they fit into these processes.
MOTIVES OF THE SELF
BACKGROUND, ASSUMPTIONS, AND MOTIVES
Since ancient times, the importance of accurate self-knowledge has been
acknowledged. Centuries before the birth of Christ, devout pilgrims made
the arduous trek to Delphi in Greece to ask for advice from the famous
Oracle about important choices in their lives. The prophecies of the Oracle at
Delphi were given in the form of a riddle, or story, and it was left to the
person inquiring to work out the meaning for themselves. The door of
Apollo's temple at Delphi was inscribed with the famous imperative, "Know
Thy Self" (gnothi seauton). Accurate self-knowledge was believed to be the
key to gain insight in the Oracle’s advice and, consequentially in their own
lives. Throughout history, philosophers, and psychologists have not ceased
SELF-MOTIVES IN FEEDBACK-SEEKING 31
to debate whether people’s self-knowledge is accurate or biased and what the
consequences of several types of self-knowledge are for people’s social
lives. Since its origins, research on self-motives underlying information
processing has occupied a central position in social and personality
psychology. The roots of self-motives research in social psychology go back
to the early writings of Gordon Allport (1937), Charles Cooley (1902), Leon
Festinger (1957), William James (1890), and Prescott Lecky (1945). The
interest in self-motives in social psychology stems from the central
importance of the self to nearly all other phenomena studied by social and
personality psychologists. The self is the central point of reference for social
cognition, emotion, motivation, and social behavior.
Research on self-motives is based on one fundamental assumption: The way
people select, process, and remember information about themselves – their
personal attributes and behaviors – is motivated (Banaji & Prentice, 1994;
Sedikides & Strube, 1995, 1997). Motives have been proposed to color the
ways in which people seek self-relevant information, appraise its sources,
interpret its veracity, and intend to change their behavior. Traditionally, four
different theoretical models have been distinguished, each with a different
view on the dominant motive behind self-evaluation: self-verification, self-
enhancement, self-assessment, and self-improvement (see Figure 2).
According to the self-verification perspective, people are motivated to
maintain consistency between their self-conceptions and new self-relevant
information. They want others to see them as they see themselves (Lecky,
1945). Therefore, people will solicit information that confirms their existing
self-views (e.g., Swann, 1987; Swann, Rentfrow & Guinn, 2002). According
to the self-enhancement perspective, people are motivated to improve the
favorability of their self-conceptions and to protect their self-concepts from
negative information. For instance, people process positive self-relevant
information faster than negative self-relevant information and spend more
time reading favorable information (e.g., Sedikides, Gaertner & Toguchi,
2003; Sedikides, Herbst, Hardin, & Dardis, 2002). The third perspective, the
32 CHAPTER 1
self-assessment perspective proposes that people are motivated to obtain a
consensually accurate evaluation of the self. To accomplish this objective,
people are interested predominantly in the diagnosticity of self-relevant
information, that is, the extent to which the information can reduce
uncertainty about an aspect of the self. Thus, people seek diagnostic
information regardless of its positive or negative implications for the self and
regardless whether the information affirms or challenges existing self-
conceptions. For instance, people rate high diagnostic tasks as more
attractive than low diagnostic tasks (e.g., Trope, 1980; Trope & Pomeranz,
1998). According to the fourth and last perspective, self-improvement,
people are motivated to improve their traits, abilities, and skills. This motive
is conceptually different from the other three motives (Taylor, Neter, &
Wayment, 1995; Wayment & Taylor, 1995). Whereas self-enhancement is
concerned with maximizing the positivity of the self-concept, self-
improvement focuses on genuine improvement. Whereas self-verification is
concerned with maintaining consistency between old and new self-relevant
information, self-improvement focuses on self-concept change. Finally,
whereas self-assessment is concerned with increasing the accuracy of self-
knowledge, self-improvement focuses on self-concept betterment regardless
of self-concept accuracy.
Initially, a fierce debate existed between adherents of the various
perspectives. Proponents of each theoretical model questioned the existence
and dominance of the other motives and tried to persuade the opposition
through ample empirical evidence (for a review, see Shrauger, 1975).
Currently the existence and importance of each of these motives in guiding
behavior and information processing is no longer questioned. Recent studies
have started examining how the various theoretical models can be
reconciled, thus addressing broader questions as how the various self-
motives work in concert (Sedikides & Strube, 1995, 1997). A first category
of studies have looked at individual difference variables moderating the
emergence and interplay of the four motives (e.g., Dunning, 1995). For
instance, Roney and Sorrentino (1995) showed that uncertainty-oriented
SELF-MOTIVES IN FEEDBACK-SEEKING 33
persons are more likely to be guided in their self-evaluation by self-
assessment strivings, whereas certainty-oriented persons are more likely to
be guided by self-verification strivings. A second category of studies has
tried to answer the question "under which circumstances do the motives
operate ?", looking at situational moderators of the self-motives (e.g., Trope
& Gelber, 2003; Morling & Epstein, 1997). For instance, accountability has
been found to moderate the self-enhancement motive. When people expect
that they have to explain, justify, and defend their self-evaluations to another
person, self-evaluations tend to be lower (Sedikides et al., 2002). Finally, a
third category of studies shows that different motives might also be activated
simultaneously and interact with each other (Sedikides, 1993; Swann,
Pelham, & Krull, 1989). For instance, Katz and Beach (2000) found that
individuals were most attracted to romantic partners who provided both self-
verification and self-enhancement, and were less attracted to partners who
provided either self-verification alone or self-enhancement alone.
In short, self-motives research in social psychology proposes that self-
evaluation processes such as feedback-seeking are colored by four different
motives. It is assumed that these motives are dynamically interrelated; they
do not usually operate independently. The key to understanding feedback-
seeking is an enhanced understanding of the dynamic interplay among the
four motives.
IMPLICATIONS OF SELF-MOTIVES FOR ANTECEDENTS OF FEEDBACK-
SEEKING BEHAVIOR
A first implication of using a self-motives perspective for studying feedback-
seeking in organizations is that a more fine-grained view on the underlying
motives of feedback-seeking might be obtained. The common assumption in
the feedback-seeking domain was that people are predominantly motivated
to reduce uncertainty and to attain goals (e.g., Fedor et al., 1992, Gupta et
al., 1999; Renn & Fedor, 2001; VandeWalle et al., 2000). This is best
34 CHAPTER 1
reflected in the following statement of Morrison (1995, p. 352): "In fact
(various works) are best understood as reflecting the important
informational role that feedback has in reducing uncertainty and helping
people to achieve goals. This is the dominant motive behind feedback-
seeking behavior". Similarly, Ashford (1985, p.68) stated: "If one were
completely certain about all potential evaluations of those behaviors, it is
unlikely that feedback would be perceived as valuable. In such situations,
individuals would have no motive to seek feedback". However, even with
this narrow approach of uncertainty reduction, Morrison (2002) has
suggested that feedback-seeking researchers have not directly focused much
of their attention on the role of uncertainty reduction in motivating feedback-
seeking behavior. Although we learned a lot from this perspective, we
suggest that to enhance our current understanding of the feedback-seeking
process, we need to apply recent insights from the self-motives domain.
Social psychological research on self-motives, which evolved almost
independently from the study of organizational feedback-seeking, has
demonstrated that motives other than uncertainty reduction might be
activated when people evaluate themselves. In particular, social
psychological theory and empirical research has suggested that self-
assessment (e.g., uncertainty reduction), self-improvement (e.g., goal
attainment and competence creation), self-enhancement (e.g., nurturing a
more favorable identity), and self-verification (e.g., confirming one’s own
view) might play an important role in guiding self-evaluative behavior.
Although the self-enhancement motive has received some indirect attention
in previous research on feedback-seeking behavior in a public context (e.g.,
Levy et al., 1995; Williams et al., 1999), the role of the self-verification
motive has been neglected (Stark & Sommer, 2000). Furthermore, very few
studies in the feedback-seeking domain have addressed how the underlying
motives work in concert (see Morrison, 2002). Research on self-motives
offers clear guidelines how individual and contextual in variables might
regulate the interplay between the various motives. Thus, we are convinced
that self-motives offer a richer and more theoretically-driven framework for
SELF-MOTIVES IN FEEDBACK-SEEKING 35
studying feedback-seeking behavior in organizations than has typically been
provided.
A second benefit of considering the underlying motives is that we can
identify several new antecedents of feedback-seeking behavior and link them
directly to specific motives based on the self-evaluation literature. For
illustration purposes, we delineate a number of theoretically interesting
antecedents, relating them to one of the four motives. For example, evidence
suggests that people high in uncertainty orientation, people with a high
desire for self-appraisal, Type A individuals, people high in need for
cognition, people high in learning goal orientation, and individuals high in
need for closure are likely to be more prone than their counterparts to self-
assessment concerns as opposed to self-verification concerns (Sedikides &
Strubbe, 1997).
Cultural dimensions are another antecedent that deserve further attention in
relation to feedback-seeking behavior. Research indicates that the
individualism/collectivism dimension of culture instantiates the self-
enhancement versus the self-assessment motive. Apparently, people from
collectivistic cultures are less motivated by self-enhancement concerns
(Sedikides & Strubbe, 1997), whereas those from individualistic cultures are
more driven by self-enhancement concerns.
A third example of a possible antecedent is the way in which feedback is
provided. When positive feedback is given in a non-controlling manner (e.g.,
"You did well at that") self-enhancement and self-improvement concerns
might come into play. However, when feedback is given in a controlling
manner (e.g., "You did just as you should"), the two self-motives might not
become operative because perceived competence and intrinsic motivation are
undermined (Sedikides & Strubbe, 1997).
A third benefit of using self-motives is that they may help explain some of
the inconsistent findings of previous studies. For instance, our literature
36 CHAPTER 1
review showed that the relationship between tenure and feedback-seeking
behavior was unclear. In previous research, it was generally acknowledged
that tenure was an antecedent activating the self-assessment motive
(uncertainty reduction motive). Consequentially, scholars assumed that long-
tenured people do not seek feedback because they are relatively certain about
their performance. However, in social psychology several studies have
shown that certainty might activate the self-verification motive: the more
certain individuals are of a particular self-view, the more they go out of their
way to confirm and sustain this self-view (Chen, Chen, & Shaw, 2004;
Pelham & Swann, 1994; Swann & Ely, 1984; Swann, Pelham, & Chidester,
1988). Thus, highly experienced people who have acquired certainty might
also seek feedback and continue to seek feedback although they are driven
by a different motive.
Another example concerns the relationship between self-esteem and
feedback-seeking behavior. Previous studies (e.g., Ashford, 1986)
hypothesized that people with high self-esteem would seek more feedback
than people with low self-esteem. As indicated in our review, this hypothesis
was not always supported (e.g., Fedor et al., 1992). Social psychological
research offers a likely explanation for these inconsistent findings. On the
one hand, empirical research in the self-motives domain showed that people
with high self-esteem are motivated by a self-enhancement motive or self-
verification motive. People with high self-esteem generally expect to
perform well and thus expect to receive positive feedback. Consequentially,
they seek feedback in order to receive good news, to verify their abilities,
and to feel better. This also gives them an opportunity to create a favorable
impression on their colleagues (Brown & Gallagher, 1992; Brown & Smart,
1991). On the other hand, empirical research in social psychology showed
that people with low self-esteem are motivated by self-enhancement
strivings in certain situations, leading them to seek additional feedback
(Baumgardner, Kaufman, & Levy, 1989). In short, both low and high self-
esteem might lead to increased feedback-seeking behavior under different
conditions. These two examples illustrate how the previously studied
SELF-MOTIVES IN FEEDBACK-SEEKING 37
antecedents of feedback-seeking behavior can be sorted in theoretically
meaningful categories on the basis of social psychological theory and
research.
IMPLICATIONS OF SELF-MOTIVES FOR OUTCOMES OF FEEDBACK-
SEEKING BEHAVIOR
Our review of the literature pointed out that the relationship between
feedback-seeking behavior and performance improvement was often not
supported. Self-motives research in social psychology might help clarifying
the inconsistent findings regarding feedback-seeking behavior and
performance improvement. In this section we will give two possible
explanations for these inconsistent findings, both based on the self-motives
perspective.
Self-motives and locus of attention. A first explanation is based on the
nature of the four self-motives that are supposed to drive feedback-seeking.
Conceptually, these four motives fall apart in two groups. A first group
consists of the self-assessment and the self-improvement motives. These self-
motives are both geared towards obtaining accurate information about the
self and are concerned with improving, learning, bettering oneself etc. For
instance, in terms of task performance, people with a self-assessment motive
will be especially interested in their result on the task (“How am I doing?”)
and people with a self-improvement motive will be looking for strategies to
improve their task performance (“How can I do better?”).
The second conceptual group consists of the self-enhancement and the self-
verification motives. These self-motives are not so much geared towards an
accurate representation of reality, but are more concerned with protection
and ensuring that others see them in a particular way. In terms of task
performance, people with a self-enhancement motive will be especially
preoccupied with obtaining a task result that is favorable for their ego (“In
which part of the task did I do best?”) and people with a self-verification will
38 CHAPTER 1
looking for confirmation of their self-image (“I’m not the kind of person to
score high on these tasks”).
Thus, when self-assessment and self-improvement motives are activated,
attention will be directed at task performance, whereas self-enhancement and
self-verification motives will shift attention from task performance to ego-
goals. Kluger and DeNisi (1996) proposed that the effects of feedback
interventions could be explained by the locus of attention. If feedback
interventions direct attention and cognitive resources to the task,
performance will increase. However, when feedback interventions direct
attention away from the task to self-relevant goals, performance will
decrease. These hypotheses were to a large extent supported in their meta-
analysis. On the basis of these findings, we argue that self-motives might
provide more insight in the relationship between feedback-seeking and
performance. Self-motives might determine the locus of attention in
feedback interventions, leading to improved performance when attention is
shifted towards the task level (self-assessment and self-improvement
motives) and to decreased performance when attention is shifted towards the
ego level (self-enhancement and self-verification motives).
This explanation might enhance our understanding of the conditions in
which feedback is supposed to improve performance. Future research should
identify antecedents of the self-assessment and the self-improvement
motives in order to encourage feedback-seeking geared towards performance
improvement. An example of such an antecedent is the use of specific and
concrete feedback versus the use of group norms in the feedback message.
When employees are confronted with feedback comparing their performance
to the performance of others, attention is directed to ego-based goals,
resulting in decreased performance (DeNisi & Kluger, 2000; Sedikides &
Strubbe, 1997). However, the use of concrete and specific task information
in the feedback message has been related to performance improvement
(Goodman & Wood, 2004; Goodman, Wood, & Hendrickx, 2004).
SELF-MOTIVES IN FEEDBACK-SEEKING 39
Self-motives and feedback reactions. A second explanation for the troubling
relationship between feedback-seeking and performance is based on an
apparent lack of attention for feedback reactions in feedback-seeking
research. As shown in the appendix, none of the previous studies in the
feedback-seeking domain looked at the role of feedback reactions. In social
psychology, findings indicate that the same self-motives that are proposed to
guide feedback-seeking behavior, also influence how people react to
feedback. There is a relative consensus that three categories (see Figure 2) of
feedback reactions can be distinguished (Ilgen & Davis, 2000; Ilgen, Fisher,
& Taylor, 1979; Taylor, Fisher, & Ilgen, 1984). The first category concerns
how people react cognitively to the feedback provided. Feedback acceptance
(Korsgaard, Meglino, & Lester, 1997; Nease, Mudget, & Quinones, 1999)
and perception of feedback utility (Brett & Atwater, 2001; Cawley, Keeping,
& Levy, 1998) constitute two cognitive reactions referring to the extent that
people believe that the feedback accurately reflects their performance and
the extent that people intent to use the feedback for future performance. Self-
motives research suggests that these cognitive reactions to self-relevant
feedback are guided by the self-verification motive. People are more likely
to accept feedback and perceive feedback as useful when the feedback
message confirms their self-views (Shrauger, 1975; Jussim, Yen, & Aiello,
1995; Moreland & Sweeney, 1984; Swann, Griffith, Predmore, & Gaines,
1987). The second category denotes affective reactions such as satisfaction
with feedback (Brett & Atwater, 2001; Korsgaard, 1995). Affective reactions
to self-relevant feedback have been found to be in line with predictions of
self-enhancement theory. Individuals are more satisified with favorable
feedback compared to unfavorable feedback (Shrauger, 1975; Jussim et al.,
1995; Sweeney & Wells, 1990). The third category consists of behavioral or
conative reactions. Employees can change their behavior in several ways
when they receive a feedback message. They can adopt a new strategy to
achieve their goals, they can put in more or less effort, they can persevere or
quit, or they even can sabotage the organizational processes (Fedor, Davis,
Maslyn, & Mathieson, 2001; Vance & Colella, 1990). Little social
40 CHAPTER 1
psychological research has examined conative reactions to feedback,
although recent research shows that individuals reported more destructive
intentions after negative feedback, thus supporting self-enhancement theory
(Van de Vliert, Shi, Sanders, Wang, & Huang, 2004).
Although it is clear that these three categories of feedback reactions are far
from independent (Cron, Slocum, & VandeWalle, 2001; Keeping & Levy,
2000), it is generally accepted that cognitive reactions play a key role in the
feedback process. In particular, feedback acceptance serves as a central
moderator for performance improvement (Ilgen et al., 1979; Taylor et al.,
1984). Feedback only leads to performance improvement when it is
cognitively accepted (O’Reilly & Anderson, 1980, Kinicki, Prussia, Wu, &
McKee-Ryan, 2004). Thus, an examination of feedback reactions constitutes
a second possible avenue to enhance understanding of the intriguing
relationship between feedback-seeking behavior and performance. Feedback
acceptance (and other feedback reactions) have been studied in assessment
and development centers (Jones & Whitmore, 1995), 360-degree feedback
(Brett & Atwater, 2001), management development programs (Ryan, Brutus,
Greguras, & Hakel, 2000), computer testing (Tonidandel, Quinones, &
Adams, 2002), performance appraisal (Cawley, Keeping, & Levy, 1999) and
selection decisions (Bauer, Maertz, Dolen, & Campion, 1998). Given the
widespread study of feedback reactions, it is remarkable that no attention has
been paid to feedback reactions in the context of the feedback-seeking
process. As feedback reactions determine whether or not feedback leads to
performance improvement, we propose to incorporate feedback reactions
into a broader model of feedback-seeking behavior. Furthermore, on the
basis of the self-motives framework two additional moderators are included
in our model. A first moderator of feedback reactions that has been
examined is the cognitive effort that people expend when processing
feedback. It seems that people especially exhibit self-verifying feedback
reactions when they have ample time or are strongly motivated to expend
additional cognitive effort, whereas feedback reactions are driven by self-
enhancement strivings when cognitive resources for processing feedback are
SELF-MOTIVES IN FEEDBACK-SEEKING 41
lacking (Hixon & Swann, 1993; Morling & Epstein, 1997; Paulhus & Levitt,
1987; Swann & Shroeder, 1995; Swann, Hixon, Stein-Seroussi, & Gilbert,
1990). A second moderator that has been examined in relation to feedback
reactions is personal investment. Research has shown that people reacted
according to the self-verification perspective when they were highly invested
in their self-views (confidently held or personally important), whereas
feedback reactions followed predictions of self-enhancement theory when
people were not invested in their self-views (Dauenheimer, Stahlberg, &
Petersen, 1999; Markus, 1977; Seta, Donaldson, & Seta, 1999; Stahlberg,
Petersen, & Dauenheimer, 1999). As low acceptance of negative feedback
has been identified as one of the main stumbling blocks in the feedback
process (Brett & Atwater, 2001; Kinicki et al., 2004), these two moderators
might offer new strategies for enhancing feedback acceptance.
UNDERLYING MODEL FOR FUTURE RESEARCH
In Figure 2, we present a model that should guide future research on
feedback-seeking behavior. This heuristic model shows how the various new
concepts that were introduced in the previous section are theoretically
related to feedback-seeking behavior. Our model builds on Morrison’s
(2002) recent conceptual model (see Figure 1) and opens various avenues for
future research.
First, future studies should focus on the left side of the model (e.g.,
antecedents, motives and feedback-seeking behavior). For instance, scholars
might examine how previously studied antecedents (e.g., learning and
performance goal orientation) are related to various self-motives. In addition,
future studies should explore the broad range of new antecedents that might
be identified on the basis of the self-motives framework. Furthermore,
studies should examine whether self-motives act as mediators between
antecedents and feedback-seeking behavior. In particular, it is important to
42 CHAPTER 1
test whether an antecedent has a different impact on feedback-seeking
behavior depending on the motive that guides the seeking behavior.
FIGURE 2: A SELF-MOTIVE MODEL OF FEEDBACK-SEEKING
Second, other future studies should concentrate on the right side of the
model (e.g., feedback-seeking behavior, feedback reactions’ moderators and
outcomes). Here, scholars should investigate the mediating role of feedback
reactions in the relationship between feedback-seeking behavior and
outcomes such as performance improvement. Furthermore, future studies
should investigate how different feedback reactions (acceptance and
satisfaction) relate to performance improvement. In addition, potential
moderators such as cognitive effort and individual investment should be
targeted to ascertain their role in the feedback-seeking - feedback reactions
chain.
A
Individual
and
Contextual
Anteced ents
Self-
motives
Feedback
Reactions’
Moderators
Feedback
Reactions
Outcomes
A
A
A
Self-Improvement
Self-Assessment
Self-Enhancement
Self-Verification
Feedback
seeking
Cognitive
Effort
Personal
Investment
Cognitive
Affective
Conative
Performance
Job Attitudes
Self-
evaluation
Knowledge
SELF-MOTIVES IN FEEDBACK-SEEKING 43
Third, future studies might test the entire model. For instance, some
empirical findings suggest that antecedents (e.g., credibility, self-esteem,
self-efficacy, goal orientation) that affect feedback-seeking behavior also
play an important role in influencing feedback reactions (Ilgen & Davis,
2000; Steelman & Levy, 2001). Another interesting avenue would be to
investigate whether motives that have been activated at the feedback-seeking
stage continue to have an influence at the feedback reactions stage. Finally,
future research should examine whether self-motives that are geared toward
obtaining accurate, and developmental feedback (the self-assessment and
self-improvement motives) eventually lead to an increase in performance.
From a methodological perspective, two different approaches (i.e., a direct
and an indirect method) can be used. In the direct method the motives are
directly measured by surveys in a cross-sectional or longitudinal design.
This approach is typically used in field studies. Several scholars have
already employed such designs and questionnaires to study self-motives in
an organizational context (see Helgeson & Mickelson, 1995; Stark &
Sommer, 2000; Tuckey et al., 2002). However, McClelland (1980),
McClelland, Koestner, and Weinberger (1989) and Winter, John, Stewart,
Klohnen, and Duncan (1998) pointed out that there is an important
difference between explicit motives (as measured by questionnaires) and
implicit motives (as deduced from experiments) and that these different
motives might have other behavioral consequences (for a meta-analysis, see
Spangler, 1992). Along these lines, one might question whether a rather
implicit and unconscious motive as self-verification can be accurately
measured by a questionnaire (Swann, Rentfrow, & Guinn, 2002). An indirect
approach wherein the activation of several implicit motives is inferred from
experimental designs seems a valuable alternative. In social psychology,
various paradigms for assessing the role of self-motives have been
developed. For example, in a typical self-assessment experiment,
participants are presented with tasks of varying degrees of diagnosticity. The
dependent measures in these experiments focus on whether participants
prefer, choose, or are more influenced by high-diagnosticity versus low-
44 CHAPTER 1
diagnosticity tasks (e.g., Sedikides, 1993; Trope & Neter, 1994). Another
promising paradigm that can easily be transferred to an organizational
context, was developed by Swann and Read (1981). In this paradigm,
participants are presented with a choice between a variety of feedback
opportunities to find out whether they possess a particular attribute. The
typical dependent measure used deals with the degree to which a participant
demonstrates a preference for feedback that is consistent, more positive or
more negative than existing self-views.
CONCLUSIONS
Over the last two decades, research on feedback-seeking behavior has
emerged as one of the most dominant themes in the feedback domain. A
broad range of antecedents and outcomes of feedback-seeking has been
examined. Our review of 49 studies showed that a resource-based
perspective dominated prior research on antecedents of feedback-seeking
behavior. Although twenty years of research has yielded important insights,
some inconsistent findings could not be explained on the basis of the
resource-based perspective. First, it was concluded that antecedents that
were conceptually related to uncertainty did not always have a uniform
impact on feedback-seeking behavior. Second, the role played by self-
concept related variables in the feedback-seeking process was unclear. Third,
findings about the relationship between feedback-seeking behavior and
performance were mixed.
To shed light on these unresolved issues and further refine thinking in this
area, we proposed a general framework for studying feedback-seeking
behavior. By borrowing from broad models in social psychology, we
provided an alternative for the traditional resource-based perspective on
feedback-seeking behavior. The use of insights from the broader self-
motives domain might lead to a more fine-grained and theoretically-driven
picture of feedback-seeking behavior in organizations. More specifically,
SELF-MOTIVES IN FEEDBACK-SEEKING 45
three new directions for future research were presented. First, on the basis of
the self-motives framework several new antecedents of feedback-seeking
behavior might be identified. Second, self-motives research in social
psychology can provide new insights in the inconsistent results concerning
the relationship between antecedents and feedback-seeking behavior in
previous research. Third, the relationship between feedback-seeking
behavior and performance can be clarified by considering the role of various
feedback reactions in relation to self-motives. By providing this self-motives
model of feedback-seeking behavior, we not only hope to bring the study of
feedback-seeking behavior in organizations more up-to-date with recent
developments in social psychology, but also to provide a rich framework for
guiding future feedback-seeking research.
THE PRESENT DISSERTATION
In the current dissertation, I will present several studies which aim to
accomplish some of the research avenues that were suggested in the
previously described research agenda. More specifically, by using the self-
motives framework I aim to pursue three objectives. First, self-motives
should be fruitful in identifying new antecedents of feedback-seeking
behavior, which may offer new strategies to encourage feedback-seeking in
organizations. Second, a closer look will be taken at some unresolved issues
in the feedback-seeking process by considering the role of underlying self-
motives. Third, the self-motives framework will be used to shed additional
light on the troubling relationship between feedback and performance.
In Figure 3, the overarching structure of this dissertation is given. This
structure is a simplification of the self-motives model that was presented
before (Figure 2). As such, it represents a working model for this dissertation
wherein only the specific variables that are directly examined across the
empirical studies are included. As none of the four self-motives will be
directly measured in the following studies, the self-motives are not included
46 CHAPTER 1
as variables in the model. Instead, the self-motives framework acts as
theoretical underpinnings guiding the choice of antecedents and moderators
that will be studied in this dissertation, as is suggested in Figure 3. In each
empirical study, a closer look will be taken at the relationship between
specific elements of this model. Thus, the working model in Figure 3 is
meant to illustrate how the various studies in this dissertation are
interconnected. With this purpose, the model will be retaken before each
chapter, highlighting the specific elements under study.
FIGURE 3: A WORKING MODEL LINKING THE VARIABLES STUDIED IN THIS DISSERTATION.
In the first empirical study (Chapter 2), two antecedents are examined that
are believed to activate self-improvement strivings in people (Sedikides &
Strubbe, 1997), and thus are likely to influence feedback-seeking behavior,
namely people’s beliefs about the modifiability and importance of various
performance dimensions. This experimental study takes a unique perspective
Need for
Closure
Uncertainty
Feedback
seeking
Cognitive
Effort
Performance
Certainty
orientation
Modifiability
Importance
Personal
Investment
Self-motives framework
Feedback Feedback
reactions
SELF-MOTIVES IN FEEDBACK-SEEKING 47
by looking at how these two antecedents influence individuals’ feedback-
seeking decisions when they have several feedback options. Thus, the
primary focus of the first study is to identify new antecedents of feedback-
seeking behavior, targeting the first objective of the dissertation.
Consequentially, this study is situated on the left side of the overarching
structure (modifiability, importance, and feedback-seeking) in Figure 3.
The third chapter presents a laboratory and a field study that take a closer
look at the role of uncertainty in the feedback-seeking process. As discussed
earlier, some studies found that uncertainty lead to more frequent feedback-
seeking, whereas other studies failed to replicate these findings or reported
opposite relationships. The current two studies try to shed a new light on
these inconsistent findings by examining the moderating role of two
individual difference variables, need for closure and certainty orientation, as
suggested by self-motives research. Thus, on the one hand, these two studies
aim to accomplish the second objective of the dissertation, namely resolving
inconsistent findings from previous research. On the other hand, need for
closure and certainty orientation have previously not been examined as
possible antecedents of feedback-seeking behavior, thus also the first
objective is tackled in Chapter 3. As can be seen in Figure 3, these two
studies examining uncertainty, need for closure and certainty orientation
in relation to feedback-seeking are also located at the left side of the model.
Whereas Chapter 3 focused on the role of uncertainty in the feedback-
seeking stage of the feedback process, Chapter 4 mirrors this focus by
considering the role of uncertainty in the feedback reactions stage of the
feedback process. Previous research yielded different answers to the
question whether people prefer favorable or confirming feedback (Shrauger,
1975). In this chapter, I propose that individuals’ level of investment
(certainty) in their self-views might be an important factor that has been
overlooked in previous research. It is hypothesized that people’s preference
for favorable or confirming feedback is moderated by the certainty of their
self-views. Two studies, a laboratory study with a student sample, and a field
48 CHAPTER 1
study with a working sample are conducted to test this hypothesis. Similar to
the previous chapter, these two studies aim to accomplish the second
objective by gaining more insight in unresolved issues from previous
research. Together, chapter 3 and 4 also paint a more complete picture of the
role of uncertainty in the feedback process than has typically been provided.
As can be seen in Figure 3, the relationship between feedback, personal
investment and feedback reactions is situated at the center of the model.
Finally, the last empirical study (Chapter 5) tackles the third objective,
which aims to gain more knowledge concerning the effects of feedback
interventions on performance. As noted before, several theoretical models
have postulated feedback acceptance as the main determinant of performance
improvement. Therefore, low acceptance of negative feedback is identified
as one of the main stumbling blocks in the feedback process. The self-
motives framework suggests that feedback acceptance is to a large extent
determined by the cognitive effort that people put in processing feedback.
Therefore, in two different samples, I tested whether requiring individuals to
extensively elaborate on feedback messages might lead to enhanced
feedback acceptance and improved task performance. As this study looks at
the relationships between feedback, cognitive effort, feedback reactions,
and performance, this final chapter is located at the center and right part of
the model in Figure 3.
After this fourth empirical part, this dissertation finishes with Chapter 6, in
which I present the general conclusions and the theoretical, practical and
research implications which can be drawn from the previous chapters.
SELF-MOTIVES IN FEEDBACK-SEEKING 49
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60 CHAPTER 1
APPENDIX: SUMMARY OF STUDIES WHICH INVESTIGATED
FEEDBACK-SEEKING BEHAVIOR IN ORGANIZATIONS
SELF-MOTIVES IN FEEDBACK-SEEKING 61
62 CHAPTER 1
SELF-MOTIVES IN FEEDBACK-SEEKING 63
64 CHAPTER 1
SELF-MOTIVES IN FEEDBACK-SEEKING 65
66 CHAPTER 1
CHAPTER 2
AN EXAMINATION OF STRATEGIES
FOR DIRECTING FEEDBACK-SEEKING
TOWARDS SPECIFIC PERFORMANCE DIMENSIONS
Manuscript submitted for publication1
FIGURE 1: CHAPTER 2 SITUATED IN THE WORKING MODEL OF THIS DISSERTATION
1 This paper was co-authored by Filip Lievens
Need for
Closure
Uncertainty
Cognitive
Effort
Performance
Feedback
Certainty
orientation
Modifiability
Importance
Feedback
reactions
Personal
Investment
Self-motives framework
Feedback
seeking
68 CHAPTER 2
ABSTRACT
This study examines how feedback-seeking across performance dimensions
can be influenced by changing the feedback-seeker’s lay beliefs about the
importance and modifiability of the various performance dimensions. A
laboratory experiment (n = 184) showed that people sought more feedback
about important dimensions as opposed to unimportant dimensions and
sought more feedback about non-modifiable dimensions as opposed to
modifiable dimensions. These findings can assist organizations in designing
strategies that direct employee feedback-seeking towards the specific
performance dimensions that are valued in the organization.
INTRODUCTION
The last decade, the world of work experienced some dramatic changes.
Organizations compete in global markets, use state-of-the-art information
technologies, are smaller, leaner, more service-driven and do no longer have
jobs structured as a fixed bundle of tasks (Cascio, 1995). In response,
employees are confronted with multiple competing tasks and demands in
their day-to-day jobs. Additionally, managers and supervisors often demand
performance on multiple dimensions for any single task, reflecting the
heightened environmental complexity (Ashford & Northcraft, 2003). One
strategy for coping with this heightened complexity for employees is seeking
performance feedback. Research has shown that seeking feedback about
performance is an effective self-regulation strategy for employees: by asking
for performance feedback, they can better assess their capabilities (Ashford
& Tsui, 1991), adjust their goal-directed behavior (Morrison & Weldon,
1990) and "learn the ropes" of a new job (Morrison, 1993).
Given the wealth of competing tasks and demands in the current business
environments, not all feedback-seeking about performance will be directed at
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 69
improving the performance dimensions that are valued by an organization.
Similarly, people might seek feedback about performance dimensions that
are difficult to develop or improve on. As feedback-seeking behavior is often
associated with high costs for the feedback-seeker (Levy, Albright, Cawley,
& Williams, 1995), it is of key importance that these costly feedback-
seeking attempts are not in vain and are directed towards the most valued
performance dimensions in an organization. Till now, most studies have
examined how situational and individual antecedents predict the general
frequency of feedback-seeking behavior (Morrison & Vancouver, 2000;
Vandewalle, 2003). Although it is important to know how organizations can
encourage the frequency of feedback-seeking, little is known about which
performance dimensions employees seek feedback, and how these feedback-
seeking decisions might be influenced. The idea of directing feedback-
seeking towards valued KSAOs also echoes a more fundamental problem in
the strategic human resource management literature. Recent calls have been
made for mechanisms that enable a better alignment between the individual
competencies2 represented in the firm and those required by its strategic
intent (e.g., Huselid, 1995; Wright, Dunford, & Snell, 2001).
Therefore, this study addresses the following question: How can feedback-
seeking be encouraged in the direction of specific performance dimensions?
The basic assumption of this study is that employees’ feedback-seeking
decisions are made on the basis of an individual theory of performance.
Therefore, strategies for directing feedback-seeking should aim to influence
employees’ theory of performance. In a laboratory study, we will test two
2 It should be noted that the concept of competency is much debated and often
considered interchangeable with the term KSAOs (e.g., Schippmann et al., 2000).
The performance dimensions we used in this study, were derived from a recent
study by Tett et al. (2000) who developed a taxonomy of performance dimensions in
terms of managerial competencies. Thus, we further use the term competency to
refer to specific performance dimensions with the understanding that the concept is
by no means firmly established.
70 CHAPTER 2
strategies (i.e., communicating explicit importance and modifiability beliefs)
that are proposed to influence these individual performance theories and
thus, that are proposed to direct feedback-seeking towards specific
dimensions of performance. As theoretical underpinnings of these strategies,
we draw on recent developments in social psychology about the role of lay
beliefs in directing attitudes, judgment and behavior.
THEORETICAL BACKGROUND
Organizations have a general sense of the knowledge, skills, abilities and
other characteristics (KSAOs) that are deemed to lead to effective
performance as this depends on the goals and values that are emphasized in
their organizational strategy. Apart from this organizational theory of
performance, employees also hold their own beliefs about what is considered
good performance in an organization (Borman, 1987). The combined lay
beliefs of an employee form an individual theory of performance that
includes amongst others the content of the various performance dimensions,
how KSAOs are linked to performance dimensions, which KSAOs are most
instrumental for successful performance and how modifiable KSAOs are
(Maurer, Wrenn, Pierce, Tross, & Collins, 2003; Schleicher & Day, 1998).
We propose that two aspects of individual performance theories will most
likely influence the feedback-seeking decisions of employees, namely beliefs
about the importance and beliefs about the modifiability of the different
KSAOs. Therefore, in order to direct feedback-seeking of their employees,
organizations should try to influence these beliefs by communicating and
making the common theory of performance that is hold in the organization
more explicit.
IMPORTANCE BELIEFS
In a recent review of feedback-seeking behavior, Ashford, Blatt, and
VandeWalle (2003) identified the instrumental motive to achieve a goal or
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 71
perform well as one of the most dominant motives of feedback-seeking.
People seek feedback because it has informational value that can help them
to meet goals and to regulate their behavior. For instance, previous research
has shown that the higher the importance of goal-attainment, the more
frequently employees seek feedback (Ashford, 1986). On the basis of the
instrumental motive driving feedback-seeking, we expect that increasing or
decreasing the importance of specific competencies will lead to more or less
interest in feedback about these competencies. This would occur because
important traits and abilities are closely associated with people’s goals and
ambitions (Pelham, 1991). Important traits are instrumental to achieving
long-term desired outcomes and thus, diagnostic information about these
traits is highly valued (Trope, 1986).
Apart from the feedback-seeking literature, additional evidence about the
role of importance can be found in social psychological research on attitudes
and persuasion. For instance, Petty and Cacioppo (1979) examined how
people consider evidence on an issue when it is of consequence to the person
as opposed to inconsequential. Subjects more systematically processed the
arguments presented to them when the issue was important and
consequential. Furthermore, people sought out more information and were
more interested in information about important attitudes as opposed to
unimportant attitudes when they were told that they would have to use these
attitudes in subsequent judgments (Visser, Krosnick, & Simmons, 2003).
Therefore, we expect that highlighting or playing down the importance of
specific competencies will lead to the following effects:
Hypothesis 1: People will seek more feedback about competencies
they are told to be important as opposed to competencies they are
told to be unimportant.
At a practical level, it is important to note that this first mechanism for
influencing people’s feedback-seeking is relevant to many feedback
situations in organizations. For example, in recruitment and selection,
72 CHAPTER 2
organizations typically convey to applicants which KSAOs are critical so
that applicants know up front which competencies will play a central role in
the selection procedure and in successful job fulfillment. Another example is
that in the context of employee development and career management,
organizations benefit from making explicit which competencies are crucial
for the organization to sustain its competitive advantage so that people can
seek feedback about these competencies and improve on them. Despite its
practical relevance, we still do not know whether it is indeed possible to
encourage people’s feedback-seeking toward competencies that the
organization considers to be important.
MODIFIABILITY BELIEFS
Dweck (1986, see also Dweck & Leggett, 1988) found that people hold lay
beliefs about the modifiability of personal attributes and that these lay beliefs
or implicit theories have important consequences for directing attitudes,
judgments and behavior. People either believe that attributes are fixed and
not modifiable (also known as an entity theory) or that they are modifiable
and can be changed and improved upon (also known as an incremental
theory). Whereas the above mentioned findings have been found with
individuals’ generalized implicit theories, research has also shown that these
theories can be very domain-specific. For instance, people can believe that
intelligence is fixed, but that certain personality traits are highly malleable
(Dweck, Chiu, & Hong, 1995; Maurer et al., 2003). Furthermore, research
has also shown that these domain-specific lay beliefs can be manipulated by
providing individuals with an explicit incremental or entity theory (Chiu,
Hong, & Dweck, 1997; Trope, Gervey, & Bolger, 2003).
One important consequence of this theory is that people with different lay
beliefs pursue very different goals in achievement-related situations. On the
one hand, people with an incremental theory exhibit a learning goal
orientation to develop competence by acquiring new skills and mastering
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 73
new situations. On the other hand, people with an entity theory pursue a
performance goal orientation to demonstrate and validate the adequacy of
one’s competence by seeking favorable judgments and avoiding negative
judgments about one’s competency. Previous feedback-seeking research has
used this goal orientation framework and found that when people believe
traits are modifiable, they tend to seek more feedback: Learning goal
orientation has been consistently found to be related to the frequency of
feedback-seeking (Tuckey, Brewer, & Williamson, 2002; VandeWalle &
Cummings, 1997; VandeWalle, Ganesan, Challagalla, & Brown, 2000).
Taken together, this leads to a second mechanism that organizations might
use to influence the feedback-seeking of people. Specifically, organizations
can influence feedback-seeking decisions by providing employees with
explicit modifiability theories for specific competencies. Again, the practical
relevance of this mechanism should be clear as it might apply to various
assessment, training, and development interventions in organizations. We
formulate the following hypothesis.
Hypothesis 2: People will seek more feedback about competencies
they are told to be modifiable as opposed to competencies they are
told to be not modifiable.
Finally, in an exploratory sense, we examined whether importance beliefs
interacted with modifiability beliefs in predicting feedback-seeking across
performance dimensions. Dutton (1995) examined the impact of trait
importance and modifiability on students’ task preferences and did not find
an interaction effect between trait importance and modifiability. Therefore,
no a priori hypothesis was articulated regarding the direction of a possible
interaction effect.
74 CHAPTER 2
OVERVIEW OF CURRENT STUDY
Previous research has looked almost exclusively at the frequency of
feedback-seeking as a dependent variable (e.g., Ang & Cummings, 1994;
Ashford, 1986; Ashford & Cummings, 1985; Callister, Kramer, & Turban,
1999; Fedor, Rensvold, & Adams, 1992; Gupta, Govindarajan, & Malhotra,
1999; Levy, Albright, Cawley, & Williams, 1995; Levy, Cober, & Miller,
2002; Morrison, Chen, & Salgado, 2004; Morrison & Cummings, 1992;
Northcraft & Ashford, 1990; Renn & Fedor, 2001; Roberson, Deitch, Brief,
& Block, 2003; Tuckey et al., 2002; VandeWalle & Cummings, 1997;
VandeWalle et al., 2000; Williams, Steelman, Miller, & Levy, 1999). Thus,
the topic that has received most attention in the feedback-seeking domain to
date, is how employees decide whether to seek feedback or not. However,
when feedback is available about multiple tasks and dimensions, employees
have different options to seek feedback. Apart from deciding whether to seek
feedback or not, employees have to decide on which dimensions they will be
seeking feedback. To our knowledge, the current study is the first to examine
how people decide about which performance dimensions they will be
seeking feedback and how these feedback-seeking decisions can be
influenced by communicating performance theories.
As the objective of this study is investigating how feedback-seeking can be
directed across different performance dimensions, we adopted a within-
persons approach. Participants in the “experimental” condition received
information about the supposed importance and modifiability of four
different competencies. This enabled us to examine whether participants
sought more feedback about important compared to unimportant
competencies and modifiable compared to non-modifiable competencies
after receiving information about all four competencies. With few exceptions
(e.g., Vancouver & Morrison, 1995), research in the feedback-seeking area
has focused on between-persons relationships. Yet, social psychological
research on self motives and decision making research has shown that it is
appropriate that researchers also adopt within-persons designs to study this
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 75
kind of decision making (for a review, see Morrison & Vancouver, 2000;
Pelham, 1993). Thus, a within-persons examination of feedback-seeking
across the dimensionality of performance is relevant because it furthers our
understanding about how people make feedback-seeking choices.
However, as it could be argued that observed differences in feedback-
seeking across competencies are due to a priori differences in feedback-
seeking, independent of importance and modifiability manipulations, we
included a baseline condition3. In this baseline condition, we examined the
normal “base rate” feedback-seeking of people about the four competencies
(i.e., feedback-seeking rate about the four competencies without receiving
any additional information about them). Thus, a within-persons approach
was combined with a between-persons approach. To rule out the possibility
that the observed effects are caused by a priori differences and not by the
experimental manipulation, an interaction effect between the within-persons
factors and the between-persons factor should be observed, indicating that
people sought more (or less) feedback when the competencies were
manipulated compared to baseline feedback-seeking levels when these
competencies were not manipulated.
METHOD
Participants. In exchange for extra credit in a course in Human Resource
Management, 184 students from different majors (e.g., medical-social
sciences, psychology, economics) voluntarily participated in this session.
Participants had an average age of 23.1 years (SD = 1.8); 73% were female,
27% male.
3 An alternative strategy to avoid this possible confound would have been to
counterbalance or randomly assign competencies to the experimental manipulations.
However, practical constraints precluded this strategy.
76 CHAPTER 2
Design. We used a three factor experimental design containing a between-
persons factor, consisting of the experimental versus the baseline condition,
and two within-person variables that were manipulated, Importance (high vs.
low) and Modifiability (high vs. low). A covariate was also included
consisting of a measured variable (learning goal orientation).
Procedure . Participants were given the task to complete a computerized in-
basket that simulated daily work activities. We chose an in-basket as this
study’s task because it provides participants with a realistic environment that
might instigate high involvement and motivation. In addition, in-baskets are
often used in selection and development contexts (Thornton & Cleveland,
1990). The in-basket used was developed by Tett, Steele, and Beauregard
(2003). They developed this computerized in-basket to measure four
elementary managerial competencies that are included in a recently
developed competency taxonomy (Tett, Guterman, Bleier, & Murphy,
2000): Coordinating, Decisiveness, Problem Awareness and Information
Management4. Completing the computerized in-basket took participants on
average about one hour. Upon completion of the in-basket, participants were
told that there would not be time enough to receive feedback about all
competencies. Therefore, participants were asked to indicate about which
competencies they wanted to receive feedback. Finally, participants received
a feedback report with quantitative and narrative feedback about their
4 In a pilot study, 60 master students rated their standing on the four managerial
competencies relative to their fellow students on a 10-point scale ranging from 1
(bottom five percent) to 10 (top five percent). A one-way within-subjects ANOVA
revealed no significant differences between the self-ratings on the four
competencies F (3,57) = 1.77, p > .05, indicating that participants on average would
have the same performance expectations about the four competencies: Coordinating
(M = 6.10, SD = 1.28), Decisiveness (M = 5.90, SD = 1.24), Problem Awareness (M
= 5.77, SD = 1.21) and Information Management (M = 5.22, SD = 1.26). This is
important because previous research has shown that performance expectations
influence ego costs associated with feedback-seeking and thus, might prevent
people from feedback-seeking.
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 77
performance on the in-basket. At the end of the session, participants were
asked to report their general comments about the computerized in-basket in
writing.
Importance and Modifiability Manipulations. Participants were randomly
assigned to either the baseline condition or the experimental condition. In the
baseline condition, participants were introduced to the computerized in-
basket exercise and were given a short definition of the four competencies
that would be measured by the in-basket. After that, they could immediately
start working on the in-basket. In the experimental condition, participants
were also introduced to the in-basket and also received a short definition of
the four competencies. However, prior to working on the in-basket exercise,
people listened to a briefing, that was given under the pretext of better
informing participants about the background of the different competencies,
measured in this in-basket.
At this point, participants in the experimental condition were instructed
about the supposed importance and modifiability of the four competencies.
Each of the four competencies was put high or low on both the importance
and modifiability dimensions.
The importance manipulation was adapted from Butler (1993), and Dunning
(1995) and consisted of the following instruction: “Being tested on the
abilities Problem Awareness and Coordinating might be of interest to you.
Several studies have shown that these competencies determine managerial
effectiveness in professional careers. Therefore, tests that measure these two
competencies often appear on business schools entrance exams and selection
tests for junior managers. Conversely, Information Management and
Decisiveness are not that important in determining managerial effectiveness.
Although they are nice to have, they are not of overriding importance.
Therefore, these competencies are seldom tested in business schools entrance
exams and selection tests for junior managers”.
78 CHAPTER 2
FIGURE 2: MANAGERIAL COMPETENCIES DEPICTED ON THE IMPORTANCE
AND MODIFIABILITY DIMENSIONS IN THE EXPERIMENTAL CONDITION
The modifiability manipulation was adapted from Dunning (1995) and Trope
et al. (2003) and consisted of the following instruction: “Coordinating and
Information Management are two managerial competencies that are easy to
acquire. They are two of the most changeable, least stable managerial
abilities around. Research shows that these two competencies can easily be
improved by learning, experience and intensive practice. Conversely,
Decisiveness and Problem Awareness are two managerial competencies that
are hard to acquire. They are two of the most stable, least changeable
managerial abilities around. Research shows that these managerial
competencies are closely related to innate intelligence and personality.
Therefore, they are very hard to develop by practice.” As a summary of the
manipulations, participants were presented with a figure (see Figure 2)
depicting the four competencies on the importance and modifiability
dimensions. Finally, participants were told they could start working on the
in-basket exercise.
It is important to emphasize that to ensure the external validity, the
aforementioned manipulation instructions were specifically constructed to be
Importance
Modifiabilit
y
Problem Awareness Coordinating
Information
Management
Decisiveness
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 79
highly consequential to the participants. Laboratory experiments in I/O
psychology have been criticized because participants typically do not take
their role very seriously and do not perceive their actions as important since
those actions are likely to have few, if any, enduring consequences (Sackett
& Larson, 1998). For instance, suppose we had instructed participants about
the importance and modifiability beliefs of the company in the computer
simulation. As this company was entirely fictitious, participants would have
had little reason to adapt their feedback-seeking decisions. Therefore, we
used manipulations that might have important implications for the
participants in their future careers. Furthermore, previous studies have
already shown that the used manipulations were successful in changing
people’s importance and modifiability beliefs (Butler, 1993; Dunning, 1995,
Trope et al., 2003).
Measures.
Feedback-seeking. The measure of feedback-seeking was taken from
Swann, Pelham, and Krull (1989). Upon completion of the computerized in-
basket, participants were given the opportunity to seek feedback about
specific competencies. To this end, the experimenter simply suggested that
each participant ranked the four managerial competencies on the basis of
how much he/she wanted to receive feedback regarding each one (1st rank =
most preferred, 4th rank = least preferred). This way, we obtained an
indication of feedback-seeking preference for each competency. Given that
participants were told that time constraints precluded the provision of
feedback on all competencies, these measures reflect feedback-seeking in a
computerized environment. As noted above, participants also received actual
feedback about the competencies.
Given that the use of ipsative data such as rankings has been criticized (see
Vanleeuwen & Mandabach, 2002), a subsample of 41 participants in each
condition also completed another measure of feedback-seeking, taken from
Trope and Neter (1994). These participants indicated how much they wanted
80 CHAPTER 2
feedback for each of the four competencies on a 7-point scale ranging from
not at all (1) to very much (7). Results of the analyses with this measure of
feedback-seeking as dependent variable were very similar to the reported
analyses with rankings as dependent variable.
Learning goal orientation. Prior to working on the in-basket exercise,
participants filled out the academic learning goal questionnaire
(VandeWalle, Cron, & Slocum, 2000). This questionnaire included four 7-
point scale items (α = .71). People with a learning goal orientation have a
general belief that traits are modifiable and have been found to seek
feedback more frequently (Tuckey et al., 2002; VandeWalle & Cummings,
1997; VandeWalle et al., 2000). Because our manipulation was aimed at
influencing these modifiability beliefs, it was possible that this individual
difference variable would interact with the within-subjects variables.
Therefore, we included learning goal orientation as a covariate.
Analyses. Our two hypotheses were analyzed using analysis of covariance
(ANCOVA) with Importance and Modifiability as the within-persons
factors, Baseline condition as the between-persons factor and Learning Goal
Orientation as a covariate. The dependent variable consisted of the feedback-
seeking measure. Although it is generally assumed that non-parametric tests
(e.g., Kruskal-Wallis) should be substituted for the F test whenever the
initial data are ranks, research has shown that parametric significance tests
are equivalent to their non-parametric counterparts performed on ranks
(Zimmerman, 1995, see also Velleman & Wilkinson 1993). In any event,
alternative non-parametric approaches to the analysis of these data
corroborated the results of the ANCOVA. In addition, analyses with
feedback-seeking ratings as a dependent variable instead of feedback-
seeking rankings yielded the same results.
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 81
RESULTS
Check of Internal Validity of Manipulations. Participants in the
experimental condition were asked to rate the perceived importance (1 = not
important; 7 = very important) and modifiability (1 = very hard to modify; 7
= very easy to modify) of the four managerial competencies at the start and at
the end of the session (thus, before and after the manipulation). In support of
the manipulation, a repeated measures ANOVA with the importance ratings
of the competencies as dependent variables indicated that Coordinating (M =
5.76 vs. 6.32, p < .001) and Problem Awareness (M = 6.11 vs. 6.41, p < .01)
were rated as more important after the manipulation, whereas Decisiveness
(M = 6.00 vs. 4.65, p < .001) and Information Management (M = 5.87 vs.
4.22, p < .001) were rated less important after the manipulation. A repeated
measures ANOVA with the modifiability ratings as dependent variables
indicated that Coordinating (M = 5.14 vs. 6.11, p < .001) and Information
Management (M = 5.90 vs. 6.24, p < .05) were rated as more modifiable
after the manipulation, whereas Problem Awareness (M = 4.02 vs. 3.30, p <
.01) and Decisiveness (M = 3.87 vs. 3.13, p < .01) were rated less modifiable
after the manipulation, indicating that the modifiability manipulation was
also successful. No Importance and Modifiability questionnaires were
administered in the baseline condition because we did not want to influence
the feedback-seeking levels about the different competencies.
We also disposed of an indication of possible demand characteristics. When
asked about their general comments after the session, none of the
participants in the experimental condition wrote down a comment that was in
any way related to the manipulation or the nature of the competencies. All
comments concerned possible improvements in the task (e.g., less items,
different lay-out, more process feedback, items in different order…),
indicating that people had no suspicions about the objective of the study.
Check of External Validity of Experimental Task. Participants completed
an additional questionnaire measuring their involvement in the task (in-
82 CHAPTER 2
basket) on the basis of six items on a 7-point scale, with responses ranging
from 1 (strongly disagree) to 7 (strongly agree). The scale included items
such as, “The background information we received was realistic”, “I was
motivated to perform well on this exercise”, and “I received sufficient
information to perform well on this exercise”. The mean for this scale was
5.70 (SD = .63, α = .70), indicating that participants were highly involved in
the session.
Hypothesis 1. The descriptive statistics for the specific managerial
competencies across the two conditions are given in Table 1. Feedback-
seeking in the baseline condition reflects the average influence of the
participants’ various lay beliefs, whereas feedback-seeking in the
experimental condition reflects the influence of the importance and
modifiability manipulations.
Feedback-seeking (n = 184)
Baseline Condition Experimental Condition
M SD M SD
Decisiveness 2.14 1.00 2.43 .88
Information Management 2.71 1.07 3.46 1.05
Problem Awareness 2.92 1.17 2.15 1.09
Coordinating 2.22 1.06 2.11 .93
Note: Lower Ranks Represent Higher Feedback-seeking
TABLE 1: MEANS AND STANDARD DEVIATIONS OF DEPENDENT MEASURES
FOR SPECIFIC MANAGERIAL COMPETENCIES IN BASELINE AND EXPERIMENTAL GROUPS.
Hypothesis 1 posited that people would seek more feedback about
competencies they are told to be important as opposed to competencies they
are told to be unimportant. As can be seen in Table 2, we found a significant
Importance x Condition interaction effect, F (1,183) = 31.32, p < .001, η² =
.15.
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 83
Feedback-seeking (ranking)
Source df F η²
Between subjects
Learning Goal Orientation (LGO) 1 1.00 .01
Condition 1 2.32 .01
Error 183 (.11)a
Within subjects
Importance (I) 1 .16 .00
I x LGO 1 .99 .01
I x C 1 31.32*** .15
Modifiability (M) 1 2.44 .01
M x LGO 1 3.84 .02
M x C 1 11.55*** .06
I x M 1 .59 .00
I x M x LGO 1 .04 .00
I x M x C 1 .32 .00
Error 183 (1.52)a
Note: a Equals the Mean Square Error. * p < .05, ** p < .01, *** p < .001.
TABLE 2: ANALYSIS OF VARIANCE FOR THE FULL FACTORIAL MODEL
WITH FEEDBACK-SEEKING AS DEPENDENT VARIABLE.
Feedback-seeking (n = 184)
Results Baseline Condition Experimental Condition
Importance Low 2.39 2.95
High 2.55 2.13
Modifiability Low 2.51 2.29
High 2.44 2.79
Note. Lower ranks represent higher feedback-seeking
TABLE 3: MEAN FEEDBACK-SEEKING RANKINGS FOR IMPORTANCE AND MODIFIABILITY DIMENSIONS.
Table 3 presents mean feedback-seeking rankings on the basis of the
Importance dimensions for the baseline and the experimental condition. A
planned comparison indicated that people in the experimental condition
sought more feedback about the important competencies as compared to the
unimportant competencies, F (1,183) = 46.10, p < .001. Then, to examine
whether these differences were not caused by a priori differences in
feedback-seeking preferences, we compared feedback-seeking choices in the
experimental condition with feedback-seeking choices in the baseline
condition. A planned comparison indicated that people sought less feedback
about unimportant competencies in the experimental condition as compared
to the level of feedback-seeking about these competencies in the baseline
condition, F (1,183) = 37.89, p < .001, as can be seen in Figure 3.
84 CHAPTER 2
FIGURE 3: FEEDBACK-SEEKING AS A FUNCTION OF IMPORTANCE
IN THE BASELINE AND THE EXPERIMENTAL CONDITION
Conversely, people sought more feedback about the important competencies
in the experimental condition as compared to the level of feedback-seeking
about these competencies in the baseline condition, F (1,183) = 20.41, p <
.001. As shown in Figure 3, a reversal in feedback-seeking took place in the
experimental condition. The competencies that received least feedback
interest in the baseline condition, received most feedback interest in the
experimental condition. So, Hypothesis 1 was supported.
Hypothesis 2. Hypothesis 2 stated that people would seek more feedback
about competencies they were told to be modifiable as opposed to
competencies they were told to be non-modifiable. As shown in Table 2, we
found a significant Modifiability x Condition interaction effect, F (1,183) =
11.55, p < .001, η² = .06. We first looked at the within-persons effects in the
experimental condition. People in the experimental condition sought more
feedback about the competencies that were said to be non-modifiable as
Vertic al bars de note 0.95 confidence in tervals
* Lower scores represent higher feedback seeking
Baseline
Experimental
Low High
Importance
1,8
2,0
2,2
2,4
2,6
2,8
3,0
3,2
3,4
Feedback Seeking *
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 85
compared to the competencies that were said to modifiable, F (1, 183) =
18.92, p < .001. Thus, as can be seen in Figure 4, the effects of the
Modifiability manipulation were in the opposite direction as was expected.
This pattern was confirmed when we compared feedback-seeking choices in
the baseline and experimental condition. On the one hand, people sought
more feedback about those competencies that were said to be non-modifiable
as compared to the baseline condition, F (1,183) = 6.09, p < .05. On the
other hand, participants sought less feedback about those competencies that
were said to be modifiable as compared to the baseline condition, F (1,183)
= 16.05, p < .001. Again, a reversal in feedback-seeking values in the
experimental condition could be observed as compared to the baseline
condition, but not in the hypothesized direction. Thus, hypothesis 2 was not
supported. As can be seen in Table 2, the Importance and Modifiability
manipulations did not interact to predict feedback-seeking. The Importance x
Modifiability x Condition interaction effect was not statistically significant,
F (1,183) = .32, p > .05.
FIGURE 4: FEEDBACK-SEEKING AS A FUNCTION OF MODIFIABILITY
IN THE BASELINE AND THE EXPERIMENTAL CONDITION.
Vertica l bars denote 0. 95 confidence intervals
* Lower scores re
p
resent hi
g
her feedback seekin
g
Baseline
Experimental
Low High
Modifiability
2,0
2,1
2,2
2,3
2,4
2,5
2,6
2,7
2,8
2,9
3,0
3,1
Feedback Seeking *
86 CHAPTER 2
DISCUSSION
The goal of this study was to examine how people decide about which
performance dimensions they will be seeking feedback. Insight in this
decision process is important because it can assist organizations in designing
strategies that direct employee feedback-seeking towards the specific
performance dimensions that are valued in the organization. It is also crucial
for individuals because it might help them to seek feedback about those
competencies that are of key importance for advancing their careers. On the
basis of theoretical developments in social psychology, we proposed that
feedback-seeking decisions are based on an individuals’ lay theory of
performance and thus, strategies to direct feedback-seeking decisions should
be aimed at influencing these lay theories.
Our findings indicate that strategies to communicate specific aspects of a
desired theory of performance were very effective in influencing feedback-
seeking. Participants who received information about the modifiability and
importance dimensions exhibited a significantly different feedback-seeking
pattern than participants who did not receive information about the
underlying dimensions of the competencies. A reversal in feedback-seeking
values could be observed in the experimental condition as compared to the
baseline condition, illustrating the strength of these strategies. This seems to
suggest that individuals’ lay beliefs or implicit theories are indeed one of the
main factors underlying feedback-seeking decisions.
Although affecting lay beliefs was successful in influencing feedback-
seeking decisions, the direction of feedback-seeking was not always as
hypothesized. First, the effect of highlighting or downplaying the importance
of specific dimensions on feedback-seeking was in the hypothesized
direction. Individuals sought more feedback about competencies from which
the importance was highlighted as compared to competencies from which the
importance was played down, thus confirming previous social psychological
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 87
research that demonstrated how importance beliefs guide behavior in self-
evaluative situations (e.g., Pelham, 1991).
Second, emphasizing the modifiability or non-modifiability of specific
competencies resulted in a feedback-seeking pattern that was in the opposite
direction as was expected. Individuals sought more feedback about non-
modifiable competencies as opposed to modifiable competencies. This is
surprising, given that previous research indicated that people are driven by
self-improvement concerns and seek more feedback when they believe traits
are modifiable (Dweck & Legget, 1988; VandeWalle, 2003). One possible
explanation is the activation of a self-assessment motive instead of a self-
improvement motive in this specific context. In self motives research, two
different but conceptually related motives are distinguished. People who are
driven by self-assessment strivings are interested predominantly in the
diagnosticity of self-relevant information, that is, the extent to which the
information can reduce uncertainty about an aspect of the self, whereas
people who are driven by self-improvement strivings are motivated to
improve their traits, abilities, and skills (Sedikides & Strubbe, 1997; Tayler,
Neter, & Wayment, 1995). In this study, it is plausible that participants were
not highly motivated by self-improvement strivings, because they knew they
would not be assessed again on these competencies in the immediate future.
Instead, the ambition of most graduate students to obtain a management
position in the future might have instigated a self-assessment motive. The
non-modifiable competencies are more diagnostic in providing information
about their potential as future managers. That is, if feedback indicated that
they did not dispose of the non-modifiable competencies at the time of the
experiment, this meant that they probably would never obtain a management
position. In contrast, the modifiable competencies are not that diagnostic
about their management potential, because they may still acquire these
competencies in the future. When people are looking for diagnostic
information, self-assessment concerns have been found to motivate behavior
in self-evaluative situations (e.g. Trope, 1975, 1979). Thus, the higher
88 CHAPTER 2
interest in feedback about the non-modifiable competencies might be
explained by self-assessment strivings.
Finally, our results indicate that importance and modifiability beliefs
independently affect feedback-seeking across performance dimensions. No
significant interaction effect was observed, which replicates the absence of
interaction effects between trait importance and modifiability in predicting
task preference reported by Dunning (1995) .
These results have several practical implications for organizations.
Organizations are increasingly designing various HR practices (e.g.,
performance appraisal, compensation, selection, and training systems) in
order to encourage the development of the KSAOs or competencies that are
highly valued in the organizations. For instance, in the strategic management
literature it is proposed that “individual competencies” should be aligned
with the “core competences” of the organization in order to obtain a strategic
benefit (Becker, Huselid, & Ulrich, 2001; Schippmann et al., 2000). This
study demonstrates that, as an additional mechanism, organizations can also
encourage feedback-seeking to develop highly valued KSAOs or
competencies in their organization. We would recommend that organizations
take special steps to communicate which competencies are most important
for successful performance. This can be done by circulating mission
statements on a wide scale (e.g., on the intranet), by emphasizing important
competencies in recruitment advertisements, performance appraisal
approaches, and employee development plans, and by consistently and
explicitly promoting employees on the basis of important competencies.
On the other hand, the findings concerning the role of modifiability beliefs
suggest caution in emphasizing the modifiability of specific competencies in
practice (e.g., in training and development). Our results seem to indicate that
people seek less feedback about competencies that are believed to be
modifiable. The explanation we provided for this unexpected finding
suggests that this is the case when people are dealing with momentary
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 89
assessments of their abilities. For instance, the design of our task
corresponds closely to organizational practice where people are provided
with feedback about their competencies on one single occasion, for instance
in performance appraisal, developmental assessment centers, 360-degree
feedback, and after completing self-assessment tools. This study seems to
suggest that, on these occasions, organizations should emphasize that
competencies are non-modifiable to encourage feedback-seeking. However,
given that these findings were in contradiction with theoretical predictions,
these results await further confirmation in future research.
Our results also extend results from research on frame-of-reference training.
This type of rater training has been found to be quite successful in imposing
a performance theory on raters (e.g., supervisors). Specifically, frame-of-
reference training is effective in clarifying to raters what the relevant
performance dimensions and effectiveness levels for rating employees are
(Lievens, 2001; Schleicher & Day, 1998; Sulsky & Day, 1994; Woehr,
1994). Our study fits nicely in this literature because we found it is possible
to tell individuals which performance dimensions are important so that they
ask their supervisors feedback about these specific competencies.
BOUNDARY CONDITIONS AND FUTURE RESEARCH
Despite the advantages laboratory studies afford in terms of statistical
control, they are often criticized on external validity grounds. For instance,
the task and participants in this study do not completely mimic tasks and
employees in an organization. Generalizability concerns of the current
investigation were specifically focused at obtaining a high experimental
realism (Berkowitz & Donnerstein, 1982). The task was carefully designed
to be interesting, realistic, motivating and within the scope of the
participants’ abilities (see involvement ratings). Furthermore, we believe that
the most important theoretical components of situations where people can
seek feedback across performance dimensions were included in the design,
90 CHAPTER 2
which makes it possible to increase our understanding of the mechanisms
and processes involved (Dobbins, Lane, & Steiner, 1981).
Although efforts were made to create a situation that was as real as possible,
it was far less complicated than most feedback situations in organizations.
For instance, in this study we looked at feedback-seeking decisions across
performance dimensions, while keeping all other feedback-seeking decisions
constant. In an organizational environment, employees have to decide
whether they will seek feedback or not (frequency), whether they will seek
direct or indirect feedback (strategy), and from whom they will request
feedback (source). A second factor that was held constant in this study was
feedback-seeking costs. Previous research has repeatedly shown that
employees in a real feedback environment are constantly balancing the
desire for feedback against the costs associated with seeking (e.g., Ashford
& Cummings, 1986; VandeWalle & Cummings, 1997). In this study,
participants experienced very little feedback-seeking costs. First, participants
requested feedback in a private context (a computer) where face-loss costs
were minimal (Levy et al., 1995). Second, if people have low performance
expectations, this represents a high ego cost (e.g., Northcraft & Ashford,
1990). The pilot study ensured that performance expectations were on
average the same for all competencies.
The current findings present several issues for future research. One
potentially fruitful avenue focuses on feedback-seeking decisions across
performance dimensions in combination with other feedback-seeking
decisions (e.g., sources and strategy). For instance, we would expect that
employees will use different feedback sources for seeking feedback about
different performance dimensions. It is likely that employees will turn to
experts with high credibility when seeking feedback about competencies that
are deemed to be important. Furthermore, the strategy that is used might also
interact with the performance dimensions when seeking feedback. For
instance, employees will probably seek more indirect feedback (monitoring)
about competencies that are believed to be unimportant in an organization,
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 91
whereas they probably will seek more direct feedback (inquiry) about
important competencies.
A second avenue for future research is taking the influence of feedback-
seeking costs in account when studying feedback-seeking across
performance dimensions. One important variable in this context is feedback
sign. Previous research has shown that people tend to seek more feedback,
when they expect that positive feedback will be obtained (Northcraft &
Ashford, 1990). We expect that importance and modifiability beliefs will
interact with feedback sign to predict feedback-seeking. For instance, as
people typically wish to maintain a favorable image of the self, employees
will probably be more likely to seek positive feedback about non-modifiable
competencies and negative feedback about modifiable competencies (e.g.,
Dunning, 1995). A second factor that is proposed to affect feedback costs,
are feedback-seeking patterns of colleagues. Previous research has shown
that individuals seek more feedback when their peers also seek feedback
(Williams et al., 1999). What would happen if an employee believes a
specific competency is unimportant, but all his colleagues openly seek
feedback about this competency? Thus, peer feedback-seeking seems
another promising organizational strategy for directing feedback-seeking
across performance dimensions. A third factor that could influence feedback-
seeking costs is accessibility. In organizations, it is likely that feedback
about some competencies (e.g., profitability) takes more effort to acquire
than feedback about other competencies (e.g., timeliness). One question that
comes to mind is whether emphasizing the importance of these inaccessible
competencies will be sufficient to overcome the difficulties associated with
seeking feedback about these competencies.
In conclusion, although an important aspect of feedback-seeking is the
decision about which performance dimensions to ask feedback, past research
has paid little attention to the characteristics of performance dimensions that
drive seeking behavior. This study demonstrated that two aspects of
someone’s lay theory of performance affect the likelihood of seeking
92 CHAPTER 2
feedback, namely the beliefs about the importance and modifiability of the
various performance dimensions. By communicating an explicit theory of
performance, these individual beliefs and subsequent feedback-seeking
decisions can be influenced. These findings can assist organizations in
designing strategies that direct employee feedback-seeking towards the
specific performance dimensions that are valued in the organization.
FEEDBACK-SEEKING TOWARDS PERFORMANCE DIMENSIONS 93
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CHAPTER 3
A CLOSER LOOK AT THE RELATIONSHIP
BETWEEN UNCERTAINTY AND FEEDBACK-SEEKING
Manuscript submitted for publication1, 2
FIGURE 1: CHAPTER 3 SITUATED IN THE WORKING MODEL OF THIS DISSERTATION
1 This paper was co-authored by Filip Lievens
2 The authors would like to thank Eric Day for his valuable comments on an earlier
version of this manuscript.
Need for
Closure
Uncertainty
Cognitive
Effort
Performance
Feedback
Certainty
orientation
Modifiability
Importance
Feedback
reactions
Personal
Investment
Self-motives framework
Feedback
seeking
100 CHAPTER 3
ABSTRACT
The relationship between uncertainty and feedback-seeking was investigated
in two studies (a laboratory and a field study). Results showed that the
relationship between uncertainty and feedback-seeking is less simple than
previously thought. First, both studies found support for a curvilinear
relationship. People sought more indirect feedback at high and low levels of
uncertainty as opposed to moderate levels of uncertainty, indicating the
activation of both uncertainty reduction and self-verification motives in a
private context. Second, the field study indicated that Certainty orientation
moderated the uncertainty – direct feedback-seeking relationship. People
were more motivated by self-verification versus uncertainty reduction
strivings depending on their Certainty orientation. Third, this relationship
varied according to the feedback-seeking strategy (direct versus indirect)
used.
INTRODUCTION
The past two decades of research in the performance feedback domain have
demonstrated that employees in organizations are more than passive
recipients of feedback. Employees have a genuine interest in obtaining
feedback and initiate in a wide range of actions to acquire feedback about
their performance (see Ashford, Blatt, & VandeWalle, 2003, for a review).
Employees seek feedback either by directly asking their supervisors for
feedback (inquiry) or by observing their environment and others for cues
that might serve as feedback information (monitoring). By seeking feedback,
employees can better assess their capabilities (Williams & Johnson, 2000),
adjust their goal-directed behavior (Morrison & Weldon, 1990) and "learn
the ropes" of a new job (Morrison, 1993).
UNCERTAINTY AND FEEDBACK-SEEKING 101
Research has shown that employees constantly balance the costs associated
with seeking feedback (e.g., hearing negative feedback about oneself or
exposing one’s uncertainty to colleagues) against the desire for feedback.
When desire for feedback exceeds cost perceptions, people proceed to action
and actually seek feedback (Ashford & Cummings, 1986; VandeWalle &
Cummings, 1997). Scholars have proposed that employees’ feelings of
uncertainty are the primary determinant of the desire for feedback (Ashford
& Cummings, 1983; Ashford et al., 2003; Morrison, 2002; Morrison et al.,
2004). This is in line with uncertainty reduction theory which predicts that
people have an aversion to uncertainty and will gather information to reduce
uncertainty feelings. Although uncertainty reduction is generally
acknowledged as one of the main motives driving feedback-seeking
behavior, little empirical or theoretical work has directly focused on the role
of uncertainty in determining feedback-seeking (Morrison, 2002; Tuckey,
Brewer, & Williamson, 2002).
This study challenges the traditional uncertainty reduction perspective in
feedback-seeking research. Specifically, the basic premise of this study is
that the relationship between uncertainty and feedback-seeking is less simple
than previously thought. From a theoretical point of view, we draw on recent
developments in the broader domain of self motives in social psychology
(Bernichon, Cook, & Brown, 2003; Morling & Epstein, 1997; Sedikides &
Strube, 1997) to identify other theoretical perspectives about the relationship
between uncertainty and feedback-seeking. To examine these different
perspectives, two empirical studies (a laboratory experiment and a field
study) are conducted. The remainder discusses four possible theoretical
perspectives that might underpin the relationship between uncertainty and
feedback-seeking and delineates two different research approaches (within-
persons versus between-persons design) that will be used to study this
relationship.
102 CHAPTER 3
THEORETICAL BACKGROUND
UNCERTAINTY REDUCTION THEORY
Uncertainty reduction has been identified as the leading motive behind the
study of feedback-seeking in organizations (Morrison, 1995, 2002). For
instance, people with a high tolerance for ambiguity have been found to seek
less feedback because they suffer less from feelings of uncertainty (Ashford
& Cummings, 1985; Fedor, Rensvold & Adams, 1992; Gupta, Govindarajan,
& Malhotra, 1999). More indirect empirical evidence comes from research
on organizational socialization. Due to changes in expectations and needed
skills newcomers in organizations often struggle with uncertainty. Hence,
they seek more feedback for reducing these high levels of uncertainty
(Ashford & Black, 1996; Brett, Feldman, & Weingart, 1990; Morrison,
Chen, & Salgado, 2004; Wanberg & Kammeyer-Mueller, 2000). Following
the same line of thought, some studies showed that more experienced and
tenured employees suffer less from uncertainty and seek less feedback
(Ashford, 1986; Ashford & Cummings, 1985; Brown, Ganesan, &
Challagalla, 2001; VandeWalle, Ganesan, Challagalla, & Brown, 2000).
The uncertainty reduction motive in feedback-seeking is also echoed in the
self-assessment motive in the self motives domain in social psychology
(Sedikides, 1993; Sedikides & Strube, 1995). According to self-assessment
theory, people are motivated to obtain an accurate evaluation of the self.
Therefore, people are interested predominantly in the diagnosticity of self-
relevant information, that is, the extent to which information can reduce
uncertainty about an aspect of the self (see Sedikides & Strube, 1997, for a
review of empirical evidence). In sum, self-assessment theory predicts – like
uncertainty reduction theory – that people are motivated to reduce
uncertainty when they seek feedback.
Hypothesis 1a: There is a positive relationship between uncertainty
and feedback-seeking.
UNCERTAINTY AND FEEDBACK-SEEKING 103
SELF-VERIFICATION THEORY
Self-verification theory suggests that people are motivated to maintain
consistency between their self-views and new self-relevant information.
According to self-verification theory, people work to confirm their self-
conceptions because of a wish for psychological coherence and feelings of
control and stability in their social environment (Swann, Rentfrow, & Guinn,
2002; Swann, Stein-Seroussi, & Giesler, 1992). First, self-verifying
information is comforting because it convinces and reassures people that
they know themselves and their environment. Second, self-verifying
information means that individuals’ social partners perceive them "correctly"
and that these partners will treat them in familiar and understandable ways.
More specifically, this theory predicts that the more an individual is certain
of a particular self-perception, the more that individual will work at
verifying and maintaining that self-perception (Chen, Chen, & Shaw, 2004;
Pelham, 1991; Pelham & Swann, 1994; Swann & Pelham, 2002). As people
acquire more information concerning their perceptions about themselves and
the environment, they become more certain about these self-perceptions.
After time, these certain and stable self-perceptions are a prerequisite to
preserve order and stability for the self in the environment. Therefore, people
are motivated to maintain consistency between these firmly held self-
perceptions and new self-relevant information. One way of preserving this
consistency consists of soliciting self-verifying feedback (Bosson & Swann,
1999; Sanitioso & Wlodarski, 2004; Swann, Pelham, & Krull, 1989). In
sum, self-verification predicts that people will seek feedback in order to
confirm perceptions that are held with high certainty, and thus will seek
more feedback when uncertainty is low.
Although uncertainty reduction has been the main motive researched in
feedback-seeking, close inspection of the feedback-seeking literature also
reveals a couple of findings that are inconsistent with uncertainty reduction
theory and are consistent with self-verification theory. In fact, several studies
104 CHAPTER 3
reported significant negative correlations between uncertainty and inquiry
(Ashford, 1986; Fedor et al., 1992) and uncertainty and monitoring
(Ashford, 1986; Gupta et al., 1999), indicating that high levels of uncertainty
lead to less feedback-seeking.
Hypothesis 1b: There is a negative relationship between uncertainty
and feedback-seeking.
UNCERTAINTY REDUCTION AND SELF-VERIFICATION THEORY
The third theoretical perspective reconciles both previous theories. This
perspective posits that both uncertainty reduction and self-verification
motives can drive feedback-seeking. When employees are highly certain
about their perceptions about appropriate behavior in the organization, they
seek feedback to verify these perceptions. However, when employees are
highly uncertain about behavior that is deemed appropriate in the
organization, they also seek feedback to reduce uncertainty about these
views. When employees are moderately uncertain about their perceptions,
none of the two motives becomes activated so that employees seek less
feedback. So, a key conceptual point of this perspective is that people can try
to satisfy both motives when they seek feedback. This proposition is
consistent with recent research on self motives in social psychology. Several
studies have demonstrated that people often try to satisfy different and
opposite motives at the same time when seeking feedback (Bernichon et al.,
2003; Morling & Epstein, 1997; Sedikides, 1993; Swann et al., 1989).
Although conceptually meaningful, no studies in the feedback-seeking
literature have actually tested for a curvilinear relationship between
uncertainty and feedback-seeking. However, we did find evidence for a
curvilinear relationship in the information seeking literature. Boynton, Gales,
and Blackburn (1993) examined information-seeking behavior of managers
and found support for a curvilinear relationship. The highest levels of search
activity were observed when uncertainty was either high or low. At
UNCERTAINTY AND FEEDBACK-SEEKING 105
intermediate levels of uncertainty, managers engaged in less search activity.
All of this leads to the following hypothesis:
Hypothesis 1c: There is a curvilinear relationship between
uncertainty and feedback-seeking. Feedback-seeking will be higher
at low and high levels of uncertainty as opposed to intermediate
levels of uncertainty.
INTEGRATING UNCERTAINTY REDUCTION AND SELF-VERIFICATION
Recent research on self motives in social psychology has moved beyond
broad questions such as "do each of these self-evaluations motives exist?"
and "which of these motives is dominant in predicting behavior?",
acknowledging a more complicated interplay between the different motives.
This is reflected in questions such as "under what circumstances do the
motives operate?" and "who are the people in whom a given motive is more
prevalent than other motives?" (Sedikides & Strube, 1995, 1997).
Whereas situational variables have been primarily researched as possible
moderators (e.g., Dunning, 1995; Sedikides, Herbst, Hardin, & Dardis, 2002;
Tice, Butler, Muraven, & Stillwell, 1995), recent social psychological
studies have proposed that individual difference variables might moderate
the activation of the self-assessment and the self-verification motives (Roney
& Sorrentino, 1995; Sedikides & Strube, 1997). Depending on individual
differences, some people might be more motivated by uncertainty reduction
strivings, whereas other people might be more motivated by self-verification
strivings. To date, the role of these individual difference variables has
remained unexplored.
This study tests two individual difference variables as possible moderators of
the uncertainty – feedback-seeking relationship, namely Need for closure
and Certainty orientation. These specific individual difference variables were
106 CHAPTER 3
chosen because we expected them to be conceptually related to the
uncertainty reduction or self-verification motive.
Kruglanski and his colleagues (Kruglanski, 1989) introduced Need for
closure as the desire for "an answer on a given topic, any answer, as
compared to confusion and ambiguity" (p.14). Need for closure reflects the
desire for clear, definite, or unambiguous knowledge that will guide
perception and action, as opposed to the undesirable alternative of ambiguity
and confusion (for a review, see Kruglanski & Webster, 1996). Hence,
people with a high Need for closure typically show an aversion for high-
uncertainty situations and engage in various activities in order to reduce this
uncertainty. For instance, people with a high Need for closure request more
information in job interviews (Ellis, 1996) or seek more information in novel
purchase situations (Vermeir, Van Kenhove, & Hendrickx, 2002). We expect
that the same will happen in the feedback-seeking domain. Therefore, we
hypothesize the following:
Hypothesis 2a: Employees with a high Need for closure will seek
more feedback when uncertainty is high than people with a low
Need for closure.
Whereas the aforementioned individual difference variable was theoretically
linked to the uncertainty reduction motive, we related the second variable to
the self-verification motive. Certainty orientation is conceptualized as a
general orientation toward approaching and dealing with information.
Sorrentino, Short, and Raynor (1984) proposed that certainty-oriented
people are primarily motivated to avoid ambiguity by maintaining existing
beliefs. In addition, Roney and Sorrentino (1995) reviewed a number of
studies suggesting that self-verification is an important motive for certainty-
oriented people. For instance, certainty-oriented people chose more task
items that reaffirmed what they already knew with high certainty (Sorrentino
& Hewitt, 1984). If people with a high Certainty orientation are more
motivated by self-verification strivings, we expect them to seek more
UNCERTAINTY AND FEEDBACK-SEEKING 107
feedback when uncertainty is low than people with a low Certainty
orientation. Thus, we expect that Certainty orientation will interact with
uncertainty to predict feedback-seeking.
Hypothesis 2b: Employees with a high Certainty orientation will
seek more feedback when uncertainty is low than people with a low
Certainty orientation.
BETWEEN- AND WITHIN-PERSONS APPROACHES
Traditionally, studies examining feedback-seeking in organizations have
adopted a between-persons approach wherein respondents are asked to
provide self-reports of the frequency of their feedback-seeking (e.g., Ashford
& Cummings, 1985; Renn & Fedor, 2001; Roberson et al., 2003;
VandeWalle et al., 2000). Despite the usefulness of a between-persons
approach, this perspective shows only one part of the equation. First,
people’s everyday evaluations and decisions are typically made from their
own frame of reference rather than from the perspective of researchers (who
typically compare evaluations and decisions with those made by other
people). Research on self motives in social psychology and decision-making
has shown that within-person designs are well-suited to investigate this kind
of idiographic decision making (for a review, see Pelham, 1993; Morrison &
Vancouver, 2000). For example, consider a student who has an opportunity
to seek feedback after completing an in-basket exercise. Let us assume that
on a 9-point scale with a theoretical mean of 5, the average uncertainty
rating for college students is 7 for their Decisiveness and 3 for their Problem
Awareness. Now, consider Jane who rates her uncertainty about
Decisiveness as a 6 (above the scale mean but below the group average) and
Problem Awareness as a 4 (below the scale mean but above group average).
Which competency should Jane seek feedback about to reduce uncertainty?
From Jane’s perspective, she is most uncertain about Decisiveness and thus
to reduce uncertainty, she should seek feedback about this competency.
108 CHAPTER 3
However, from a between-persons perspective, Jane should seek feedback
about Problem Awareness because she is more uncertain about this
competence than the group average, whereas her uncertainty about
Decisiveness is below group average.
Second, a within-persons perspective is relevant in an organizational context
because in organizations developmental feedback is typically built around
specific performance elements (London, 1997). For instance, the context of
the present study mirrors a context in which individuals seek feedback about
specific competencies upon completion of a computerized assessment
instrument (in-basket).
Thus, between- and within-person designs represent two complementary
approaches that can paint a more complete picture about the role of
uncertainty in feedback-seeking choices in organizations. Therefore, we
tested the relationship between uncertainty and feedback-seeking in two
studies, each adopting a different approach. Study 1 was a laboratory
experiment wherein I/O psychology students could chose about which
performance elements (competencies) they wanted feedback after
completing an in-basket exercise. In this study, a within-persons approach
was adopted to study the relationship between uncertainty about
competencies and feedback-seeking. In Study 2, we used a more traditional
between-persons design to examine the relationship between general
perceptions of uncertainty and frequency of feedback-seeking in a field
setting. By conducting both a laboratory and a field study, using different
design strategies, we aimed to provide a strong test about the role of
uncertainty in the feedback-seeking process.
UNCERTAINTY AND FEEDBACK-SEEKING 109
STUDY 1
METHOD
Participants. One hundred twenty-six I/O psychology master’s students
participated in this study. They were given extra course credit for their
voluntary participation. Participants had an average age of 22.9 years (SD =
1.8); 70% were female, 30% male.
Procedure. We adapted a research paradigm for examining feedback-
seeking choices in social psychology to a work-related context (i.e., a
context in which people seek feedback about their performance on a
computerized assessment instrument). This research paradigm was created
and used by Swann and colleagues (e.g., Swann et al., 1989; Swann,
Wenzlaff, Krull, & Pelham, 1992; see also Cassidy et al., 2003). First,
participants rated themselves in a self-assessment questionnaire on eight
competencies that are included in a recently developed taxonomy of
managerial competence (Tett, Guterman, Bleier, & Murphy, 2000), namely
Coordinating, Decisiveness, Task Focus, Composure, Information
Management, Problem Awareness, Quantity Concern, and Trustworthiness.
Next, participants worked on a computerized in-basket that simulates daily
work activities. Tett, Steele, and Beauregard (2003) developed this
computerized in-basket to measure these eight competencies. Completing the
computerized in-basket took participants on average one hour. Finally,
participants were offered an opportunity to seek feedback about their
performance related to these specific competencies. Upon completion of the
in-basket, participants were told that there would not be time enough to
receive feedback about all competencies. Therefore, participants were asked
to indicate about which competencies they wanted to receive feedback.
Finally, two weeks later participants received a feedback report with
quantitative and narrative feedback about their performance on the in-basket.
110 CHAPTER 3
Measures. In the self-assessment questionnaire, students first rated their
standing relative to their colleagues on each of the eight competencies. Then,
participants reported how certain they were of their standing on each of these
competencies using scales anchored at the endpoint by 1 (not at all certain)
to 9 (extremely certain). Wording and rating format for self- and certainty
ratings were taken from the Self-Attribute Questionnaire (Pelham & Swann,
1989), which measures similar self-attributes and has shown high test-retest
reliability (.77). Mean correlation between participant’s self-assessed
standing and certainty about these self-assessed standings was moderate (M
= .40) and similar to previous research, indicating that self-assessed standing
and uncertainty ratings hold relatively well as different constructs (Krosnick
et al., 1993; Pelham & Swann, 1989).
We used an abbreviated version of the Need for closure Scale (Kossowska,
Van Hiel, Chun, & Kruglanski, 2002). The 15 items used 7-point Likert-type
response scales ranging from 1 (strongly disagree) to 7 (strongly agree).
Internal consistency equaled .81. Research showed that the Need for closure
scale possesses high test-retest reliability (r = .86) (Webster & Kruglanski,
1994).
Participants were also administrated a widely-used 11 item Certainty
orientation measure (Brouwers & Sorrentino, 1993; Roney & Sorrentino,
1995). The items used 7-point response scales ranging from 1 (strongly
disagree) to 7 (strongly agree). Internal consistency was .72. In prior
research, the scale demonstrated good test-retest reliability (r = .90) (Walker
& Sorrentino, 2000), indicating that Certainty orientation is a temporally
stable individual difference measure.
The measure of feedback-seeking was taken from Trope and Neter (1994).
Upon completion of the computerized in-basket, participants were given the
opportunity to seek feedback about specific competencies. To this end, they
indicated how much they wanted feedback for each of the eight
competencies on a 7-point scale. Given that participants were led to believe
UNCERTAINTY AND FEEDBACK-SEEKING 111
that they would not receive feedback on all competencies due to time
constraints, this measure reflects feedback-seeking in a private
(computerized) setting. As noted above, participants also received actual
feedback about the competencies.
Analyses. The hypotheses were tested with a one-way analysis of variance
(ANOVA) with Level of Uncertainty as a within-subjects factor and
feedback-seeking as a dependent variable. The procedure that was followed
to make up the within-persons factor is described in detail in the Appendix.
Planned comparisons were conducted to test for competing hypotheses.
Tests of the interactions between the individual difference measures and the
within-subjects factor were conducted using general linear model procedures
in which the individual difference measures were treated as continuous
variables.
RESULTS AND DISCUSSION
Preliminary analyses. We checked how important each of these
competencies was to the participants, with responses ranging from 1 (not
important) to 9 (very important). Participants indicated that all of these eight
competencies would be potentially important to them (M = 7.03, SD = 1.31),
illustrating that they were interested to know more about their standing on
each of these competencies. We also disposed of an indication of possible
demand characteristics. When asked about their general comments after the
session, none of the participants in the experimental condition wrote down a
comment that was in any way related to the feedback-seeking measure. All
comments concerned possible improvements in the task (e.g., less items,
different lay-out, items in different order…), indicating that people had no
suspicions about the objective of the study.
Test of Hypotheses. We found a significant effect of uncertainty on
feedback-seeking, F (2,236) = 4.34, p < .05, η² = .03. Using planned
comparisons, we tested for a linear and a curvilinear trend in the relationship
112 CHAPTER 3
between uncertainty and feedback-seeking. No support was found for a
linear relationship between uncertainty and feedback-seeking, F (1,118) =
0.00, p > .05. However, the quadratic contrast was significant, F (1,118) =
13.50, p < .001. As can be seen in Figure 2, people sought more feedback
about competencies that were held with high uncertainty (M = 5.79, SD =
1.35) and low uncertainty (M = 5.78, SD = 1.39) as opposed to competencies
that were held with moderate uncertainty (M = 5.43, SD = 1.20).
FIGURE 2: THE EFFECT OF LEVEL OF UNCERTAINTY ON FEEDBACK-SEEKING IN STUDY 1.
Although the effect sizes were small (Cohen’s d = 0.2, for feedback-seeking
about high vs. moderate uncertain competencies), paired t-tests revealed that
feedback-seeking about the moderate uncertainty level significantly differed
from feedback-seeking about both high and low uncertainty levels (p < .01),
whereas feedback-seeking about high and low uncertainty levels did not
differ (p > .05). Thus, among the three competing hypotheses, the results
from this study support hypothesis 1c : apparently, people are motivated to
Vertical bars denote 0.95 confidence intervals
Low Moderate High
Level of Uncertainty
5.1
5.2
5.3
5.4
5.5
5.6
5.7
5.8
5.9
6.0
6.1
6.2
Feedback seeking
UNCERTAINTY AND FEEDBACK-SEEKING 113
seek feedback about competencies that are held with both high and low
uncertainty3.
Concerning hypothesis 2a, no interaction effect was found between Need for
Closure and Level of Uncertainty, F (2, 232) = 0.48, p > .05. Also, no
interaction effect was found between Certainty orientation and Level of
Uncertainty, F (2, 232) = 0.88, p > .05. So, hypothesis 2a and 2b were not
supported.
Two key findings emerge from Study 1. First, the relationship between
uncertainty and feedback-seeking was best characterized by a curvilinear
relationship. Our results suggest that people seem to seek more feedback
when uncertainty is low and when uncertainty is high, reconciling the
uncertainty reduction and self-verification theories. Second, this relationship
was not moderated by individual difference variables. In contrast to recent
theoretical propositions in social psychology (Sedikides & Strubbe, 1997),
Certainty orientation and Need for closure did not interact with uncertainty
to predict feedback-seeking. Still, Study 1 seems to suggest that the
traditional positive linear relationship that has been proposed may provide a
3 As self-assessed standing on the competencies and uncertainty ratings were
moderately correlated, it could be argued that the observed curvilinear effect reflects
performance expectations instead of uncertainty. For instance, it is possible that
participants merely sought feedback about their best competencies (e.g., for
increasing self-worth) and their worst competencies (e.g., for improving
performance). Therefore, we also conducted analyses with self-assessed standing
included as a second within-persons factor (see also, Pelham, 1989). This analysis
yielded the same results for the relationship between uncertainty and feedback-
seeking. Results concerning self-assessed standing showed that people sought more
feedback about their best (M = 5.84) and moderate competencies (M = 5.66) than
about their worst competencies (M = 5.10), p < .01, indicating that there was a
positive linear relationship between self-assessed standing and feedback-seeking.
This supports previous research demonstrating that people seek more feedback
when performance expectations are high (Morrison & Weldon, 1991). In sum, the
curvilinear relationship between uncertainty and feedback-seeking seems to be
independent of the influence of self-assessed standing on the competencies.
114 CHAPTER 3
too simplistic view of the relationship between uncertainty and feedback-
seeking.
STUDY 2
One might question whether the results obtained in Study 1 will generalize
to more traditional feedback-seeking designs. We propose that if both
uncertainty reduction and self-verification motives determine feedback-
seeking choices as suggested in Study 1, this should also be reflected with
frequency of feedback-seeking as a dependent variable. Therefore, in study 2
we gathered self-reports of frequency of feedback-seeking in a field setting,
thus adopting a between-persons approach. In line with prior research, we
examined two feedback-seeking strategies, feedback inquiry and feedback
monitoring. We used a different measure of uncertainty as compared to the
first study. People were asked to give a general appraisal of perceived
uncertainty about appropriate behaviors and potential evaluations in their
environment. This was in line with prior field studies, which also employed
more global measures of uncertainty (Ashford & Cummings, 1985; Ashford,
1986; Gupta et al., 1999).
METHOD
Participants and Procedure. Data were collected in a local division of a
multinational manufacturer of agricultural machinery. Four hundred thirty-
eight employees were emailed a cover letter discussing the study and
containing a link to the actual questionnaire. Study participation was
voluntary. One hundred forty employees filled out the questionnaire (10.2%
female), yielding a response rate of 32%. Their ages ranged from 21 to 59
years (M = 42.1 years, SD = 10.1). The participants had an average tenure of
19.1 years (SD = 11.6) in the company and an average experience of 9.2
years (SD = 8.5) in their current position. In addition, 68.6% held at least an
UNCERTAINTY AND FEEDBACK-SEEKING 115
undergraduate degree and 29.2% of the participants had a supervisory or
management position.
We examined whether respondents were different from nonrespondents. To
this end, we retrieved archival data from the organization on key
demographic variables from the target population (all 438 employees who
were originally surveyed). T-tests for continuous variables and χ²-tests for
categorical variables indicated that the means of the respondents were not
significantly different from the target population on age (M = 43.7 years),
gender (9.4% female), and position (28.8% supervisory or management
position). Respondents had a significantly shorter tenure than the target
population (M = 21.6 yrs, p < .05). However, given the small difference in
tenure, the response rate did not seem to be a major threat to the
representativeness of our results.
Measures. The same measures as in Study 1 were used for Need for closure
(α = .73) and Certainty orientation (α = .81). For the other variables, we used
measures that have been used in prior field-based research about feedback-
seeking. Specifically, respondents’ perceptions of uncertainty about
appropriate behaviors and potential evaluations in their organizational
environment were assessed with a 4-item scale developed by Ashford
(1986). The items used 7-point Likert-type response scales ranging from 1
(strongly disagree) to 7 (strongly agree). The scale included items as "I
really get little useful information about performance standards within my
department." Internal consistency equaled .76.
Finally, the dependent variable (feedback-seeking) was measured with two
different scales from Roberson, Deitch, and Block (2003) (see also Ashford,
1986; Ashford & Tsui, 1991; Morrison, 1993; VandeWalle & Cummings,
1997). Respondents were asked how frequently they engaged in various
feedback-seeking strategies, using a 7-point Likert scale (1 = very
infrequently; 7 = very frequently). A 4-item scale measured direct feedback-
seeking (inquiry) and included items such as, "How frequently do you
116 CHAPTER 3
directly ask your manager for information concerning your performance?".
A 7-item scale measured indirect feedback-seeking (monitoring) and
included items such as, "How often do you observe what behaviors your
manager rewards and use this as feedback on your own performance?". As
shown in Table 1, internal consistency coefficients for these two measures
were good.
M SD 1. 2. 3. 4. 5. 6.
1. Tenure 19.14 11.58 (--)
2. Uncertainty 4.16 1.30 -.13 (.76)
3. Need for closure 4.55 .64 .23** .03 (.73)
4. Certainty orientation 4.02 .88 .23** -.31** .39** (.81)
5. Frequency of Monitoring 3.34 1.04 -.05 -.10 -.23* -.11 (.84)
6. Frequency of Inquiry 2.41 1.15 -.02 -.35** .08 .20* .38** (.84)
Note. N = 140. Cronbach’s Alphas are Reported in Parentheses on the Diagonal.
* p < .05 ** p < .01
TABLE 1: DESCRIPTIVE STATISTICS AND CORRELATION COEFFICIENTS OF STUDY 2 VARIABLES.
As mentioned before, some studies have found that organizational tenure
was negatively related to feedback-seeking (e.g., Ashford, 1986), supposedly
because experienced employees suffer less from uncertainty. However,
several studies failed to support these findings (e.g., Roberson et al., 2003).
Given these previous findings, organizational tenure was included as a
control variable in our analyses. It was assessed with a single item that asked
the participants how many years and months of tenure they had in the
organization.
RESULTS AND DISCUSSION
Descriptive statistics, correlations, and internal consistency reliabilities of
Study 2 variables are provided in Table 1. To examine our hypotheses, we
conducted a hierarchical multiple regression analysis. First, organizational
tenure was entered as a control variable. In the second step, perceived
uncertainty was entered in the equation. In the third step, we entered the
hypothesized quadratic effect of uncertainty to test for a curvilinear
UNCERTAINTY AND FEEDBACK-SEEKING 117
relationship between uncertainty and feedback-seeking. The fourth step
entered the two individual difference variables. Finally, in the fifth step we
entered the hypothesized interactions between the individual difference
variables and perceived uncertainty. To minimize collinearity between the
main effects of perceived uncertainty, Need for closure, and Certainty
orientation with the interaction terms, we mean-centered the three main
effect variables, prior to computing cross-product terms (Aiken & West,
1991). The change in R², associated with each set of terms, indicated which
of the hypotheses were supported in this study. As shown in Table 2,
different results were obtained for the two dependent variables. Therefore,
results are reported for monitoring (indirect feedback-seeking) and inquiry
(direct feedback-seeking) separately.
Frequency of Monitoring Frequency of Inquiry
ba SE
(b) t p ∆R2 ba SE
(b) t p ∆R2
Step 1
Organizational tenure .00 .01 -.53 .60 .01 -.01 .01 -1.57 .12 .00
Step 2
Uncertainty -.10 .08 -1.27 .21 .01 -.32 .07 -4.29 .00*** .14***
Step 3
Uncertainty x
Uncertainty .09 .05 1.72 .09 .04* .02 .05 .39 .70 .01
Step 4
Need for closure -.25 .17 -1.48 .14 .04 .31 .16 1.95 .05 .03
Certainty orientation -.13 .13 -1.06 .29 .06 .12 .50 .62
Step 5
Uncertainty x
Need for closure .11 .12 .93 .36 .01 .06 .11 .54 .59 .04
Uncertainty x
Certainty orientation -.07 .11 -.67 .51 -.23 .10 -2.30 .02*
Note: Parameter Estimates are for Final Step, not Entry. a In Order to Interpret The a Priori
Standardized Variables as Correctly as Possible, the B Coefficients in this Table are
Unstandardized Regression Coefficients (Aiken & West, 1991; Jaccard et al., 1990). * p <
.05, ** p < .01, *** p < .001.
TABLE 2: HIERARCHICAL REGRESSION OF FREQUENCY OF FEEDBACK-SEEKING
(INQUIRY AND MONITORING) ON UNCERTAINTY, HYPOTHESIZED QUADRATIC EFFECT,
INDIVIDUAL DIFFERENCES, AND HYPOTHESIZED INTERACTIONS.
118 CHAPTER 3
3210-1-2 -3
Feedback Monitoring
5
4
3
2
Level of Uncertainty
As shown in Table 2, uncertainty was not related to monitoring (b = -.10, p >
.05) and thus explained no significant variance (1%), F (1,107) = .90, p >
.05. Thus, neither Hypothesis 1a nor Hypothesis 1b were supported. The
quadratic term, entered in the third step, was responsible for a significant
additional variance of 4 %, F (1,106) = 4.77, p < .05. As can be seen in
Figure 3, people sought more feedback when they perceived high levels and
low levels of uncertainty in their organization. Yet, they sought less
feedback when they perceived intermediate levels of uncertainty. This
finding supports hypothesis 1c and seems to indicate that people satisfy both
self-verification and uncertainty reduction strivings when seeking feedback
through monitoring.
FIGURE 3: THE CURVILINEAR RELATIONSHIP BETWEEN UNCERTAINTY
AND INDIRECT FEEDBACK-SEEKING (MONITORING) IN STUDY 2.
UNCERTAINTY AND FEEDBACK-SEEKING 119
The individual difference variables, entered in the fourth step, did not
explain any significant additional variance (4%), F (2,104) = 2.41, p > .05.
The fifth step of the analysis revealed that adding the hypothesized
interaction terms did not explain any significant additional variance (2%), F
(3,99) = .685, p > .05. So, Hypotheses 2a, and 2b, were not supported for
indirect feedback-seeking.
As shown in table 2, a different pattern of results arose for inquiry (direct
feedback-seeking). Uncertainty explained 14% of the variance for inquiry, F
(1,125) = 19.88, p < .001. Uncertainty was negatively related to inquiry (b =
-.32, p < .001), thus disconfirming hypothesis 1a and supporting hypothesis
1b : employees who perceived higher levels of uncertainty, sought less direct
feedback. As can be seen in Table 2, entering the quadratic uncertainty term
in the equation did not explain any additional variance, F (1,124) = 1.57, p >
.05. Thus, hypothesis 1c was not supported for direct feedback-seeking. The
individual difference variables, entered in the fourth step, did not explain
any significant additional variance, F (2,122) = 1.85, p > .05.
The fifth step of the analysis revealed that adding the hypothesized
interaction terms between the individual difference variables and perceived
uncertainty increased the variance explained by 4%. This additional
explained variance of 4% was not significant, F (2,120) = 2.75, p = .07.
However, caution is needed by interpreting this non-significant finding.
Detecting reliable moderator effects in field studies is often difficult due to
low power (Aguinis, Beaty, Boik, & Pierce, in press; Aguinis & Stone-
Romero, 1997; Zedeck, 1971). Even if interactions are theoretically
defensible, large samples will be needed to detect them. Furthermore,
controlling first for quadratic effects in the moderated multiple regression
can eliminate interactions that are statistically significant (Judd &
McClelland, 1989). Indeed, if we did not first control for quadratic effects
but only for the linear effects in the hierarchical multiple regression, the
change in R² associated with the respective interaction terms was 6% and
reached significance, F (2,121) = 3.53, p < .05. Therefore, as argued by
120 CHAPTER 3
McClelland and Judd (1993), the increment in R² is not the most useful
effect size index in this context. Inspection of the regression coefficients of
Table 2 reveals that one of the two hypothesized interaction terms was
significant. Certainty orientation moderated the effect of uncertainty on
direct feedback-seeking (b = -.23, p < .05).
FIGURE 4: THE INTERACTION OF CERTAINTY ORIENTATION
AND UNCERTAINTY ON DIRECT FEEDBACK-SEEKING (INQUIRY) IN STUDY 2.
To determine if this interaction was consistent with our hypothesis, we
plotted the overall form from the full equation -/+ 1 standard deviation units
around the mean of Certainty orientation (Aiken & West, 1991). As
predicted by Hypothesis 2b, Figure 4 reveals that there is a stronger negative
relationship between perceived uncertainty and feedback-seeking for those
people with a high Certainty orientation. This seems to support the notion
that people with a high Certainty orientation are driven by a self-verification
motive and thus, are more inclined to seek feedback when they experience
low levels of uncertainty. For people with a low Certainty orientation, there
is still a small negative relationship between perceived uncertainty and
feedback-seeking.
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
-1.000 0.000 1.000
Level of Uncertainty
Feedback Inquiry
Mean
Low Certainty Orientation
High Certainty Orientation
UNCERTAINTY AND FEEDBACK-SEEKING 121
GENERAL DISCUSSION
Traditionally, uncertainty reduction has been proposed as the primary motive
behind feedback-seeking (Ashford & Cummings, 1983; Ashford et al., 2003;
Morrison, 2002; Morrison et al., 2004). Our study did not invalidate
uncertainty reduction as a possible motive behind feedback-seeking.
However, the general conclusion of our two studies is that the relationship
between uncertainty and feedback-seeking is more complicated than
previously thought. Specifically, we found evidence for (a) a curvilinear
relationship, (b) the importance of the feedback strategy (inquiry versus
monitoring) used, and (c) the moderating effect of certainty orientation. The
remainder delves deeper into these three main contributions of our studies.
CURVILINEAR RELATIONSHIP
In both the laboratory study and the feedback monitoring part of the field
study, we found support for a curvilinear relationship between uncertainty
and feedback-seeking. People sought more feedback at low and high levels
of uncertainty as compared to intermediate levels of uncertainty. Research
about self motives in social psychology offers a theoretical framework for
understanding these findings: When people find themselves in self-
evaluative situations, different motives are activated and guide the
information-processing of individuals. Our results indicate that – apart from
the uncertainty reduction motive – a self-verification motive is activated in
the feedback-seeking process. Social psychological research on self-
verification processes has repeatedly shown that the more people are certain
of specific perceptions, the more they go out of their way to obtain
confirmation of those perceptions (e.g., Pelham & Swann, 1994; Swann &
Ely, 1984; Swann, Pelham, & Chidester, 1988; Visser, Krosnick, &
Simmons, 2003). Apparently, the same mechanism is observed in the
feedback-seeking process in organizations. People try to satisfy both
122 CHAPTER 3
uncertainty reduction and self-verification needs and therefore seek feedback
when uncertainty is high and low.
This self-verification perspective on the role of uncertainty can shed a new
light on previous inconsistent findings in the feedback-seeking domain. For
instance, Fedor et al. (1992) did not find a significant correlation between
feedback uncertainty and feedback monitoring. Similarly, Gupta et al. (1999)
reported a non-significant relationship between role ambiguity and direct
feedback-seeking. These scholars tested only for linear relationships and not
for a curvilinear relationship. The simultaneous and opposite activation of
both uncertainty reduction and self-verification motives might have obscured
the relationship between uncertainty and feedback-seeking in these studies.
In any case, our study should encourage a renewed attention for the
relationship between uncertainty and feedback-seeking in future research. In
this study, uncertainty was considered to have a rather static role in
determining feedback-seeking. One particular interesting direction would be
to examine whether the role of uncertainty changes during the feedback-
seeking process. It is possible that uncertainty reduction and self-verification
motives come into play at different stages in the feedback-seeking process as
do other feedback-seeking motives (Levy, Albright, Cawley, & Williams,
1995).
FEEDBACK-SEEKING STRATEGIES
Our study revealed that the relationship between uncertainty and feedback-
seeking might be different for indirect and direct feedback-seeking
strategies. In the laboratory study as well as in the field study with feedback
monitoring as dependent variable, there was evidence for a curvilinear
relationship. However, a negative relationship between uncertainty and
feedback-seeking was found with direct inquiry as dependent variable. How
can these findings be explained? We believe that the context in which
feedback was sought might play an important role here. In the laboratory
UNCERTAINTY AND FEEDBACK-SEEKING 123
study as well as in the field study with feedback monitoring as dependent
variable, the nature of the feedback-seeking of the participants can be
characterized as an unobtrusive strategy where no interaction with other
individuals was required. When people are able to seek feedback in such a
private context (e.g., by monitoring the behavior of others as in Study 2 or
by requesting feedback from a computer as in Study 1), face-loss costs and
impression management concerns are minimal for the feedback-seeker (Levy
et al., 1995; Fedor et al., 1992; Williams, Miller, Steelman, & Levy, 1999).
Our results suggest that in this context, people feel safe to satisfy both
uncertainty reduction and self-verification needs.
Another feedback-seeking pattern appeared when people sought feedback by
direct inquiry. Direct feedback is typically sought in a public context, where
feedback-seeking costs are much higher (Fedor et al., 1992). In that case, a
negative relationship between uncertainty and feedback-seeking was found.
Other researchers have also reported negative zero-order correlations
between uncertainty and direct feedback-seeking (Ashford, 1986; Fedor et
al., 1992). Two plausible explanations for these findings can be proposed.
First, when people are highly uncertain, they may refrain from seeking
feedback through inquiry because they do not know the standards used to
judge them and so, there is a greater risk to seek feedback, as the feedback
may be negative. Thus, it is possible that for highly uncertain employees the
costs associated with overtly seeking feedback are to high. Another possible
explanation is that only a self-verification motive is activated. This would be
in line with one of the main tenets of self-verification theory. Self-
verification theory assumes that people develop self-confirmatory social
environments through social interaction in order to acquire a sense of
stability, predictability and coherence (Swann et al., 2002). For instance,
students choose to live together with room mates that have confirmed their
self-image in the past (Swann, Bosson, & Pelham, 2002). By publicly
seeking feedback about self-views that are held with high certainty,
employees can convey a clear picture of their core self-views and convince
their boss and colleagues to see them as they see themselves. As we did not
124 CHAPTER 3
dispose of direct measures of feedback-seeking costs or self-verification
motives, these two explanations that might account for the negative
relationship between uncertainty and feedback-seeking await further
research.
INDIVIDUAL DIFFERENCES AS MODERATORS
Evidence for the moderating role of individual difference variables in the
relationship between uncertainty and feedback-seeking was limited. No
moderating effects were found in Study 1. In Study 2, we found a
moderating effect of certainty orientation with direct feedback-seeking
(inquiry) as a dependent variable. This finding suggests that people with a
high certainty orientation seek more direct feedback when they are certain
than people with a low certainty orientation. Apparently, people with a high
certainty orientation are more driven by self-verification strivings than by
uncertainty reduction strivings.
Recently, several scholars have examined how various self-motives interact
to guide behavior (for a review, see Sedikides & Strube, 1997). Yet, these
studies have focused on identifying situational moderators (e.g., Dunning,
1995; Sedikides, Herbst, Hardin, & Dardis, 2002; Tice, Butler, Muraven, &
Stillwell, 1995) that might reconcile the activation of different motives in
self-evaluative situations. The current study is one of the first to examine if
the activation of the uncertainty reduction (self-assessment) and self-
verification motive is moderated by individual difference variables.
However, given the limited evidence about the moderating role of individual
difference variables in the present study, more research is needed in this
domain. We believe that the study of individual difference variables can be a
fruitful avenue for studying the interplay between various seemingly
conflicting self-evaluation motives. So far, most feedback-seeking research
has addressed how different motives might separately affect feedback-
seeking. Yet, we need more studies that investigate how those motives work
UNCERTAINTY AND FEEDBACK-SEEKING 125
in concert (see Ashford et al., 2003; Morrison, 2002). Research on self
motives in social psychology might provide a well-suited theoretical
framework for studying this interplay and outlining other individual
difference variables (e.g., self-consciousness, Sedikides & Strube, 1997).
PRACTICAL IMPLICATIONS
Our findings suggest that the widespread notion that employees seek
feedback to reduce uncertainty and improve performance is not completely
accurate. This has some practical implications for both organizations and
individuals.
From an organizational point of view, this insight is troubling. When people
seek feedback guided by a self-verification motive, the effects could be
detrimental for individual and organizational performance. According to
Kluger and DeNisi’s (1996) feedback intervention theory, the effectiveness
of any feedback depends on where the feedback intervention focuses one’s
attention. When attention is focused on the task (e.g., tasks on which the
person needs to improve) individuals focus on shrinking the gap between
their actual performance and their performance goals. Alternatively, when
feedback focuses attention on the self, (e.g., how a person views his/her self
image or concept), feedback interventions often produce strong affective
reactions that can interfere with task performance. Thus, self-verification
driven feedback-seeking can divert attention away from the task to questions
of who we really are, resulting in a decrease in performance (Kluger &
DeNisi, 1996). Organizations might consider looking for strategies to deal
with the possible negative effects of self-verification driven feedback-
seeking. For example, managers could be made aware of self-verifying
tendencies and could be trained and encouraged to provide additional
feedback about ambiguities in times of increased uncertainty (crisis, change,
mergers, and socialization periods). Furthermore, in order to promote
feedback-seeking directly aimed at uncertainty-reduction and performance
126 CHAPTER 3
improvement, organizations should try to identify factors that may influence
the feedback-seeking motives. For instance, DeNisi and Kluger (2000) have
proposed that normative feedback should be avoided, because it directs
attention to ego-motives which makes a decline in performance more likely.
Supervisors and managers could also pay more attention to the self-
verification strivings of employees in day-to-day informal conversations.
When self-verification needs are already fulfilled in these low-stake
interactions, chances are that uncertainty reduction needs gain the upper
hand when a feedback-seeking opportunity presents oneself. Finally,
employees can be trained in seeking feedback about uncertainty by
emphasizing the benefits of feedback as a tool for self-development. This
might help employees to overcome their natural proclivities toward seeking
feedback in a biased way (Larson, 1989).
From an individual point of view, our results highlight the importance of
feedback-seeking as a self-regulation strategy for employees in their
organizational environment. Whereas previous research mainly described
feedback-seeking as a means of increasing individual and organizational
performance, this study suggests that employees also use feedback-seeking
as a strategy to increase individual wellbeing. This is illustrated in recent
work by Swann et al. (2002) showing that people who acquired a sense of
coherence through self-verifying strategies demonstrated higher levels of
psychological and physical health. Thus, by seeking feedback when
experiencing low levels of uncertainty employees can increase feelings of
control and stability in their social environments. However, these self-
verifying tendencies do not have to lead to rigidity. As illustrated in these
studies, when people experience high levels of uncertainty, people will also
seek feedback to reduce this uncertainty. So, it seems that individuals use
feedback-seeking as a subtle self-regulatory strategy to find a balance
between their personal need for coherence and the need for reducing
uncertainty caused by changes in organizational environments.
UNCERTAINTY AND FEEDBACK-SEEKING 127
LIMITATIONS
One reason for conducting both a lab and a field study was to address the
weaknesses inherent in the use of any single research design. When two
designs are combined in one investigation to test the same hypotheses, the
strengths of one design can help compensate for the weaknesses of the other
(Sackett & Larson, 1990). Nevertheless, limitations to the present research
should be considered. In the lab study, participants were students, not
employees, and sought feedback from a computer. Although we ensured that
the task was realistic and important to the participants (see importance
ratings in Study 1), this study lacks contextual realism in comparison to an
organizational setting where employees can seek feedback from different
sources and feedback-seeking costs and impression management concerns
come into play. A second concern is that we did not measure actual
feedback-seeking behavior in Study 1, but rather the preference of
participants for receiving feedback about their competencies. However, as
participants were lead to believe that they only could receive feedback on a
limited number of competencies, we believe this preference measure closely
resembles actual behavior in this computerized setting. Another limitation
might be that in the field study, we collected data at a single point in time
from a single source, which introduces the possibility of common method
variance. Although common method bias is an unlikely explanation for
results that are convergent across the two studies, the effects of such bias
cannot be ruled out. A final limitation of this study is that we had no self-
report measure of the different motives driving feedback-seeking in
comparison to previous research (Tuckey et al., 2002). However, research
has shown that the use of self-report measures is not the best method for
assessing more implicit motives of behavior (McClelland, Koestner, &
Weinberger, 1989; Winter, John, Stewart, Klohnen, & Duncan, 1998).
Therefore, we inferred the activation of the uncertainty reduction and self-
verification motives from the feedback-seeking of the participants.
128 CHAPTER 3
CONCLUSION
Feedback-seeking has been identified as one of the main self-regulation
strategies of employees in organizations. This study tested various
theoretical perspectives that might explain the relationship between
uncertainty and feedback-seeking. We found that people might be motivated
by both uncertainty reduction and self-verification strivings. Future research
along these lines is needed to better understand how the various motives
work in concert in the feedback-seeking process.
UNCERTAINTY AND FEEDBACK-SEEKING 129
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UNCERTAINTY AND FEEDBACK-SEEKING 135
APPENDIX
The following question was examined in study 1: “If a participant reports to
be highly certain on one competency, moderately certain on another and
lowly certain on yet another competency, will his or her feedback-seeking
vary as a function of those competencies?” Thus, to examine feedback-
seeking decisions from the perspective of the participants, we followed a
procedure that was developed by Pelham (1989) (see also, Cassidy, Mehta,
& Feeney, 2003; Pelham & Swann, 1994; Swann et al., 1989). For each
participant, the competency that received the highest certainty rating, the
competency that corresponded with a median certainty rating and the
competency that received the lowest certainty rating was selected. For
instance, consider three participants whose highest, median, and lowest
ratings of certainty are 9-5-1, 9-8-7, and 3-2-1, respectively. The high
certainty level would have received a rating of 9, 9, and 3 from these
participants. The moderate certainty level would have received a rating of 5,
8, and 2 from these three participants, and a low certainty level would have
received a rating of 1, 7, and 1 from these participants. As can be noted in
this example, not all three participants have a low degree of certainty for
their most uncertain competency. Still, for each participant the competency
that was selected as most uncertain was the competency that received the
lowest certainty rating from their own frame of reference. Accordingly, for
each subject, we identified a "least uncertain" (M = 7.05, SD = 1.20), a
"moderate uncertain" (M = 5.78, SD = 1.29) and a “most uncertain" (M =
3.83, SD = 1.42) competency, as the three levels of the within-subjects factor
Level of Uncertainty. If more than one competency qualified as a
participant’s most, moderate or least uncertain competency, we consulted
group norms (Pelham, 1991). Note that randomly selecting one of the
competencies that qualified as a participant’s most or least uncertain
competency (see Cassidy et al., 2003), yielded the same results as consulting
group norms. Mean uncertainty ratings for the three selected competencies
136 CHAPTER 3
for each participant differed significantly from each other (p < .001),
indicating that the “uncertainty manipulation” was successful.
CHAPTER 4
CERTAINTY AS A MODERATOR
OF FEEDBACK REACTIONS:
A TEST OF THE STRENGTH
OF THE SELF-VERIFICATION MOTIVE
Manuscript submitted for publication1, 2
FIGURE 1: CHAPTER 4 SITUATED IN THE WORKING MODEL OF THIS DISSERTATION
1 This paper was co-authored by Filip Lievens
2 A previous version of Study 1 was published in the Dutch blind peer-reviewed
journal “Gedrag & Organisatie”. The full reference is: Anseel, F., & Lievens, F.
(2004). Als het bericht goed is: (On)zekerheid als determinant van feedbackreacties
in het feedbackproces. Gedrag & Organisatie, 17, 414-429.
Need for
Closure
Uncertainty
Cognitive
Effort
Performance
Feedback
Certainty
orientation
Modifiability
Importance
Feedback
reactions
Personal
Investment
Self-motives framework
Feedback
seeking
138 CHAPTER 4
ABSTRACT
The present study investigated whether employees are merely interested in
hearing good news about themselves, as predicted by self-enhancement
theory or are more interested in feedback that confirms their self-concept, as
predicted by self-verification theory. In both a lab study and a field study we
examined whether self-view certainty would serve as a moderator and would
strengthen the relationship between feedback score – self-view congruence
and feedback reactions. Results across the two studies showed that people
mainly reacted favorably to positive feedback. Prior self-views did not play a
key role in explaining feedback reactions. As feedback scores were the main
determinant of feedback reactions, it seems that feedback reactions are
dominated by self-enhancement strivings and that self-verification strivings
are less prominent. Self-view certainty moderated the self-enhancement and
self-verification motives in feedback reactions for the competency
Decisiveness.
INTRODUCTION
The finding that performance feedback does not uniformly improve
performance (Kluger & DeNisi, 1996) has led to a renewed interest in
examining feedback processes. One line of research in this area has paid
close attention to questions as “When do employees feel satisfied about the
feedback they receive?” and “When do employees perceive feedback as
accurate and intent to use the feedback obtained?” Research examining these
feedback reactions is important for numerous reasons, including (a) that
reactions represent a criterion of great interest to practitioners because
feedback reactions are vital to the acceptance and use of any feedback
system or appraisal system (Cawley, Keeping, & Levy, 1998) and (b) that
feedback reactions are included in all theoretical models of the feedback
process as the immediate predecessors of performance improvement.
CERTAINTY AND FEEDBACK REACTIONS 139
Providing feedback can lead to increased levels of individual and
organizational performance only if employees are willing to accept and
respond to feedback (Ilgen & Davis, 2000; Ilgen, Fisher, & Taylor, 1979).
Given this practical and theoretical importance, reactions to feedback have
been studied in different contexts, such as development centers (Jones &
Whitmore, 1995), 360-degree and upward feedback programs (Brett &
Atwater, 2001; Smither, Wohlers, & London, 1995), management
development (Ryan, Brutus, Greguras, & Hakel, 2000), computer-adaptive
testing (Tonidandel, Quinones, & Adams, 2002), performance appraisal
(Keeping & Levy, 2000), and selection decisions (Bauer, Maertz, Dolen, &
Campion, 1998).
One puzzling issue that has emerged across these different contexts is
whether employees are merely interested in hearing good news about
themselves or are more interested in feedback that confirms their self-
concept. Several studies could not provide an unequivocal answer to this
question. Some studies (e.g., Brett & Atwater, 2001) found that employees
reacted favorably to positive feedback, whereas other studies (e.g., Nease,
Mudgett, & Quinones, 1999) reported that employees reacted favorably to
feedback that was consistent with their self-ratings.
The current study tries to shed a new light on these mixed findings by
introducing a new moderator of feedback reactions. This moderator, self-
view certainty, is drawn from self-evaluation theory in social psychology. In
two studies, we will examine if people’s reactions to feedback are moderated
by the certainty of their self-views. Study 1 is a laboratory study wherein I/O
psychology students received feedback about their performance on a
computerized in-basket. Study 2 is a field study wherein we examined
feedback reactions in a realistic work-related context. Specifically, the
computerized in-basket was placed online on the website of a governmental
service for employment and vocational training. This website is frequently
visited by applicants and employees looking for training and coaching in job
application skills and various work-related competencies.
140 CHAPTER 4
THEORETICAL BACKGROUND
The determinant that has received most attention in feedback reactions
research is the feedback valence or feedback sign. Several studies have
found that feedback recipients are more likely to accept and use favorable
(positive) feedback than unfavorable (negative) feedback (Bannister, 1986;
Brett & Atwater, 2001; Facteau, Facteau, Schoel, Russel, & Poteet, 1998;
Halperin, Snyder, Shenkel, & Houston, 1976; Ilies, De Pater, & Judge,
submitted; Stone & Stone, 1984; Tonidandel et al., 2002). This finding
corresponds to predictions of self-enhancement theory in social psychology.
Self-enhancement theory proposes that people are motivated to view
themselves as favorably as possible. Hence, individuals are driven to elevate
the positivity of their self-concept and protect themselves from threatening
information in order to achieve a high level of personal worth (for a review,
see Sedikides & Strubbe, 1997). In the context of the feedback process, this
theoretical perspective predicts that reactions are based on a one-step
cognitive appraisal of the feedback message: “If feedback is unfavorable,
then dismiss it as inaccurate. If feedback is favorable, then accept it”.
In addition to the feedback sign, a second important determinant of feedback
reactions are people’s perceptions of themselves before they receive
feedback. These self-views might modify the general tendency to accept and
respond to favorable feedback. In particular, several studies reported that in
contrast to self-enhancement theory, feedback reactions were not determined
by the feedback sign, but by the degree of congruence between the feedback
message and the self-views individuals had before they received feedback.
Thus, people are more likely to accept feedback when the feedback message
confirms their existing self-concept (e.g., Dauenheimer, Stahlberg, &
Petersen, 1999; Jussim, Yen, & Aiello, 1995; Korsgaard, 1996; Markus,
1977; Nease et al., 1999). This finding corresponds to predictions of self-
verification theory. This social psychological motivation theory suggests that
people go out of their way to maintain consistency between their self-views
and new self-relevant information. People are motivated to confirm their
CERTAINTY AND FEEDBACK REACTIONS 141
self-views out of a desire to maximize their perceptions of prediction,
control, and stability in an often chaotic social environment (for a review,
see Swann, Rentfrow, & Guinn, 2002). In the context of the feedback
process, this theory predicts that reactions are based on a two-step cognitive
appraisal, for example: “If the feedback is favorable and the particular self-
conception is unfavorable, then dismiss feedback as inaccurate. If the
feedback is unfavorable and the particular self-conception is unfavorable,
then accept the feedback message.”
INTEGRATING SELF-VERIFICATION AND SELF-ENHANCEMENT MOTIVES
The above indicates that it remains inconclusive as to which of the two self-
evaluation theories is supported when considering feedback reactions in
organizations. These mixed findings echo a debate in social psychology
between proponents of self-enhancement and self-verification (self-
consistency) theory during the 60s. In origin, adherents of both perspectives
questioned the existence of the other motive and tried to persuade the
opposition (for a review, see Shrauger, 1975). As it could not be established
which of these self-evaluation theories was the correct one, scholars have
recently proposed that both models might be correct. That is, people might
experience a need for both self-enhancement and self-verification, but these
needs vary under different conditions. Thus, recently the research question
has shifted from "which motive is dominant?" to the search for moderators,
that is, "under which conditions do the motives operate?" (Sedikides &
Strubbe, 1995, 1997; Swann & Schroeder, 1995).
One important moderator that has been proposed is the nature of feedback
reactions. On the basis of a review of empirical findings, Shrauger (1975)
proposed that affective reactions to evaluations (e.g., satisfaction) might
follow predictions of self-enhancement theory and cognitive reactions (e.g.,
acceptance) might follow predictions of self-verification theory. Research in
the social psychological self-evaluation domain has supported this
142 CHAPTER 4
hypothesis (Dauenheimer et al., 1999; Jussim et al., 1995; Moreland &
Sweeney, 1984; Sweeney & Wells, 1990).
In the current study, we propose a new moderator of the self-enhancement
and the self-verification motive in determining feedback reactions, namely
the certainty with which self-views are held before feedback is received.
Swann and Schroeder (1995) identified self-view certainty as one of the
main moderators of the self-verification perspective. Empirical research
shows that people are most inclined to seek confirmation of their self-views
when these self-views are held with high certainty (Chen, Chen, & Shaw,
2004; Pelham, 1991; Pelham & Swann, 1994; Swann & Ely, 1984; Swann,
Pelham, & Chidester, 1988). Self-views that are held with high certainty
occupy a central position in the cognitive system of people. They are related
to a great number of other self-relevant cognitions and therefore possess a
high resistance to change (Markus, 1977). When self-concept certainty is
high, the more the feedback message is congruent with the corresponding
self-view, the more favorably people will react. Thus, higher self-view
certainty motivates people to invest time and resources in a two-step
cognitive appraisal.
However, when self-view certainty is low, people are more eager to self-
enhance (Ungar, 1980). Uncertainty about beliefs implies a low resistance to
change (Sorrentino, Bobocel, Gitta, & Olson, 1988). People can change their
low-certain self-views more easily in the direction of a more flattering self-
image. Thus, when self-view certainty is low, people will use a one-step
cognitive appraisal of the feedback. The more positive the feedback
message, the more favorably people will react, regardless of the
corresponding self-views, as predicted by self-enhancement theory. Briefly
stated, we expect a moderating effect of self-concept certainty: As self-
concept certainty increases, the relationship between feedback score - self-
view congruence and feedback reactions will become stronger.
CERTAINTY AND FEEDBACK REACTIONS 143
UNIQUE CONTRIBUTIONS OF CURRENT STUDY
There are some commonalities between the current study and previous
studies in both organizational and social psychology that need to be
addressed. Whereas our study is similar in some respects, we also believe
that several conceptual and methodological differences make the proposed
study unique and justify its importance.
First, it remains unclear whether people prefer favorable or consistent
feedback. Based on self-evaluation theory, we introduce "certainty" as a new
moderator variable of feedback reactions. In particular, we expect that self-
verifying tendencies in feedback reactions will be more pronounced as self-
concept certainty increases. However, with decreasing levels of certainty, we
expect that the self-enhancement motive will become more dominant in
determining feedback reactions. This approach is in line with recent
developments in self-evaluation theory that have called for more research
examining moderators of self-evaluation motives (Sedikides & Strubbe,
1995, 1997).
Second, examining whether people prefer favorable or consistent feedback is
a question of congruence between self-appraisals and feedback scores. In the
past, questions of feedback congruence have typically been answered using
difference scores (e.g., Ashford & Tsui, 1990; Kernan & Lord, 1990; Vance
& Collella, 1990). For instance, Sweeney and Wells (1990) examined
whether students preferred favorable or consistent feedback on their exams.
On a pre-exam questionnaire, they asked respondents to state how many
points they thought they would earn on the upcoming exam and subtracted
this value from the actual number of points they earned on the exam. Then,
this difference score was regressed on feedback acceptance and support was
found for the self-verification perspective. However, Edwards (1994, 2002)
noted a number of difficulties with the use of difference scores and
developed a regression procedure to resolve these problems. One of the main
critiques of typical difference measures is that they conceal the relative
144 CHAPTER 4
contribution of the component parts of the difference score in the effect on
the dependent variable. Conceptually, the contributions of the component
parts are of particular interest in this study because we aim to examine
whether (a) people only react to the feedback scores and thus, only one
component accounts for the variance in feedback reactions (self-
enhancement perspective) or (b) people react to the congruence between the
feedback scores and their self-ratings and thus, the two components account
for the variance in feedback reactions (self-verification perspective). The
current study is one of the first in the feedback domain to use the regression
procedures recommended by Edwards (1994, 2002), and therefore makes it
possible to accurately distinguish self-verifying from self-enhancing
feedback reactions.
Third, various studies (e.g., Jussim et al., 1995) examining self-verification
and self-enhancement motives in the feedback process have used global self-
esteem as a measure of self-concept. However, recent social psychological
research has shown that specific self-views instead of global self-esteem
predict people’s cognitive reactions to success and failure (Bernichon, Cook,
& Brown, 2003; Dutton & Brown, 1997). For instance, low self-esteem
individuals sometimes choose to self-verify (accept negative feedback) and
sometimes to self-enhance (accept positive feedback), depending upon the
area of feedback (Swann, Pelham, & Krull, 1989). Therefore, Swann et al.
(2002) recommended that the self-enhancement and self-verification motives
of individuals should be examined in light of the specific attribute upon
which feedback is given and specific self-views should be measured a priori.
Therefore, in this study we measured self-ratings for various competencies
(instead of global self-esteem) before feedback was given. Note that this
approach also parallels common organizational practices where
developmental feedback is typically provided about various performance
elements upon completion of a 360 degree feedback survey, a development
center, or an online assessment instrument and where employees can
differently respond to feedback about each of these performance elements.
CERTAINTY AND FEEDBACK REACTIONS 145
STUDY 1
METHOD
Participants. Individuals were 126 I/O psychology master’s students3. They
were given extra course credit for their voluntary participation. Participants
had an average age of 22.9 years (SD = 1.8); 70% were female, 30% male.
Procedure. First, participants rated themselves in a self-assessment
questionnaire on four managerial competencies that are included in a
recently developed taxonomy of managerial competence (Tett, Guterman,
Bleier, & Murphy, 2000), namely Problem Awareness, Coordinating,
Information Management, and Decisiveness.
Next, participants were required to work on a computerized in-basket that
simulated daily work activities and measured these four competencies. The
computerized in-basket was adapted from Tett, Steele, and Beauregard
(2003) and several efforts were taken to ensure the realism of the in-basket
(role descriptions, background information, pictures, e-mail simulation,
organizational charts, etc.).
Participants received feedback about their performance on the in-basket via
e-mail after two weeks. The feedback report consisted of their scores on each
of the 4 competencies and a brief explanatory text. The two-week time
interval was chosen to simulate common organizational practice. When
employees take part in a 360-degree feedback survey or a development
center, it usually takes a couple of weeks before all data are processed and
feedback is provided. Responses on the in-basket were scored according to
the rules developed by Tett, Menard, Guterman, and Beauregard (2001). The
feedback scores on the four competencies ranged from 1 to 10, reflecting
3 This sample consists of the same participants as in Study 1, Chapter 3.
146 CHAPTER 4
students’ performance relative to other students. A questionnaire measuring
feedback acceptance and satisfaction per competency was attached to the
feedback report. In total, 99 of these questionnaires were returned, yielding a
response rate of 77%.
Measures. In the self-assessment questionnaire, students rated their standing
relative to other students on each of the four competencies on a 10-point
scale ranging from 1 (bottom five percent) to 10 (top five percent).
Participants also reported how certain they were of their standing on each of
these competencies using scales anchored at the endpoints by 1 (not at all
certain) to 9 (extremely certain)4. Wording and rating format for the self-
and certainty ratings were taken from the Self-Attribute Questionnaire
(SAQ) (Pelham & Swann, 1989), which measures similar self-attributes and
has shown high test-retest reliability (.77).
As dependent variables, we measured both feedback satisfaction and
feedback acceptance. Feedback satisfaction was measured for each
competency with three items developed by Korsgaard (1995), and Sweeney
and Wells (1990). The items used 7-point Likert-type response scales
ranging from 1 (strongly disagree) to 7 (strongly agree). The scale included
items such as, "I am satisfied with the score I received on [name
competency]". Feedback acceptance was measured for each competency
with two items on a 7-point scale developed by Tonidandel et al. (2002). The
scale included items as "The feedback I received on [name competency] was
an accurate evaluation of my performance.”
The distinction between feedback satisfaction and feedback acceptance is
conceptually congruent with previous social psychological research
4 Mean correlation between participants’ self-ratings and certainty of these self-
ratings was moderate (Study 1, M = .40; Study 2, M = .48) and comparable to
previous research (Krosnick, Boninger, Yuang, Berent, & Carnot, 1993; Pelham &
Swann, 1989).
CERTAINTY AND FEEDBACK REACTIONS 147
examining feedback reactions (Jussim et al., 1995; Shrauger, 1975).
However, exploratory factor analyses indicated that all items loaded on one
factor. Therefore, the 5 feedback reaction items were combined in one scale
“feedback reactions”. Internal consistency for this scale varied between .91
and .95 for the different competencies5.
Involvement. We also assessed how important each of these competencies
was to the participants on a 9-point scale, with responses ranging from 1 (not
at all important) to 9 (extremely important). Participants indicated that all
the competencies were important to them (M = 7.00, SD = 1.29), illustrating
that the participants of this study cared about their performance on the in-
basket. Directly after the in-basket exercise, we also assessed interest in
feedback about each of the competencies on a 7-point scale, with responses
ranging from 1 (not at all interested) to 7 (extremely interested). Participants
indicated that they were interested to know more about their standing on
each of these competencies (M = 5.54, SD = 1.52).
Analyses. Given the limitations of traditional congruence measures we used
analytical procedures recommended by Edwards (1994, 2002). The
following quadratic regression equation was used to determine whether
predictions of self-enhancement theory or self-verification theory were
supported.
FR = b0 + b1X + b2Y + b3X² + b4XY + b5Y² + e (Equation 1)
In Equation 1, X and Y represent participants’ self-ratings and feedback
scores on the competencies, respectively, and FR represents feedback
reactions. This equation makes it possible to examine the relative
5 Reliabilities for the feedback satisfaction scale ranged from .93 to .96. Reliabilities
for the feedback acceptance scale ranged from .79 to .89. Correlations between the
two scales for each competency ranged from .63 to .83 (p < .01). All analyses were
also conducted with feedback satisfaction and feedback acceptance separately. This
yielded similar results as with the combined feedback reactions scale.
148 CHAPTER 4
contribution of the two components of interest in this study, namely the
feedback scores and the self-ratings. If results are in line with self-
verification theory, congruence between the feedback scores and the self-
ratings will lead to more favorable feedback reactions, regardless whether
the feedback scores are negative or positive. Thus, both components
(feedback scores and self-ratings) will contribute equally but in opposite
directions to feedback reactions. If results are in line with self-enhancement
theory, then higher feedback scores will result in more favorable feedback
reactions, regardless of their relationship to participants’ self-ratings. In this
case, only one component (feedback scores) will contribute to feedback
reactions. The full constraints and conditions that are statistically tested to
support each of the models can be found in Edwards (1994, 2002).
Hierarchical regression analysis was used to test the moderating effects of
self-view certainty. For each quadratic equation, the five terms were
multiplied by certainty, and the increment in R² yielded by these terms was
tested, controlling for certainty and the five original quadratic terms
(Edwards, 1994; Edwards & Rothbard, 1999). If the increment in R² was
statistically significant, coefficients from the equation were used to
determine whether certainty intensified the effects of the congruence
between self-ratings and feedback scores on feedback reactions. Prior to
quadratic regression analysis, self-ratings and feedback scores were scale
centered by subtracting the scale midpoint to reduce multicollinearity and
facilitate interpretation (Edwards, 1994).
The present sample size (N = 99) has the statistical power of .85 (α = .05) to
detect a medium effect size (f²) of .15 (which corresponds approximately to
an increase in R² of about .13) for the quadratic difference regression. In
addition, using the same alpha, we had a power of .87 to detect an increment
in R² of about .13 for the set of terms in the moderated regression equation.
The relationship between feedback – self-rating congruence and feedback
reactions and the moderating effect of certainty was tested for each of the
CERTAINTY AND FEEDBACK REACTIONS 149
four competencies separately, yielding eight regression analyses. To control
the risk of Type I error associated with these analyses, we used the
sequential Bonferroni procedure (Seaman, Levin, & Serlin, 1991). This
procedure requires the researcher to define the family of tests for which
Type I error is controlled. For our purposes, a family comprised the tests of
the R² values from the four regression equations. Tests of the four regression
equations containing certainty as a moderator were also defined as a separate
family (see Edwards & Rothbard, 1999). For each R² value that reached
significance using this procedure, coefficients from the equation were tested
using the nominal alpha level (i.e., .05). This procedure struck a balance
between Type I and Type II error by considering only those equations that
reached significance at the required familywise alpha while testing
coefficients from those equations in the usual manner.
TABLE 1: DESCRIPTIVE STATISTICS AND CORRELATION COEFFICIENTS IN STUDY 1
RESULTS
Descriptive statistics and correlations for all study variables are presented in
Table 1. As can be seen in Table 2, none of the results was in accordance
150 CHAPTER 4
with self-verification theory because none of the coefficients on self-ratings
(X or X²) was significant (p > .05). Feedback reactions were in line with
predictions of self-enhancement theory for three out of four competencies.
For Coordinating, Information Management, and Problem Awareness there
were only significant positive coefficients on feedback scores (Y or Y²). This
indicates that participants reacted favorably to positive feedback about their
competencies, regardless of their initial self-ratings.
TABLE 2: RESULTS OF QUADRATIC REGRESSIONS OF FEEDBACK REACTIONS
ON SELF-RATINGS AND FEEDBACK SCORES IN STUDY 1.
For Decisiveness, we found a significant interaction effect between self-
ratings and feedback scores (XY, p < .05), indicating that self-ratings played
a role in determining feedback reactions for this competency. Furthermore,
hierarchical regression analyses revealed that these effects of feedback
scores and self-ratings were moderated by self-view certainty for the
competency Decisiveness. As can be seen in column ∆R² in Table 2, the
additional set of moderator terms explained 5% variance above the original
quadratic terms and the moderator variable. For interpretation of this
moderation effect, we plotted estimated congruence surfaces for three levels
of self-view certainty (Edwards, 1994; Edwards & Rothbard, 1999).
As can be seen in Figure 2-A, for low self-view certainty feedback reactions
were highest when feedback scores were high and lower when feedback
scores were low. This is in line with the self-enhancement perspective.
People reacted favorably to positive feedback, regardless of self-ratings.
When feedback scores were low, a curvilinear effect of self-ratings on
feedback reactions could be observed. Apparently, people did not like to
CERTAINTY AND FEEDBACK REACTIONS 151
receive very negative feedback about moderate self-ratings when certainty
was low. The same self-enhancement pattern can be seen in Figure 2-B.
When certainty was moderate, feedback reactions were highest when
feedback scores were high and feedback reactions were lowest when
feedback scores were
lowest. However,
support for the self-
verification perspective
was found in Figure 2-
C, when certainty was
high. If we look along
the line of congruence
(X = Y) in Figure 2-C,
we see that feedback
reactions were most
favorable when self-
ratings and feedback
scores were high. The
X=Y - line also slightly
increased when both
self-ratings and
feedback scores were
very low. If we look
along the line of
incongruence (X = -Y) ,
we see that feedback
reactions were more
unfavorable when self-
ratings and feedback
scores were incongruent
than when they were
congruent. The most
152 CHAPTER 4
unfavorable feedback
reactions could be
observed when
feedback scores were
low and self-ratings
were high. This pattern
is consistent with
predictions of self-
verification theory.
Thus, the hypothesis
that feedback reactions
are moderated by self-
view certainty is
supported for
Decisiveness. For this
competency, it seems
that the self-verification
motive gets stronger as
certainty increases.
STUDY 2
METHOD
Participants. A total of 389 individuals (50% male, 50% female) completed
the web-based in-basket. Only individuals that entirely completed the in-
basket and all measures were included in the sample. Their ages ranged from
17 to 59 years (M = 31.1 yrs, SD = 10.7). The participants had an average
working experience of 8.5 years (SD = 10.7) in their company and an
average experience of 3.1 years (SD = 4.9) in their current position. 87%
Note: For Reasons of Interpretability, Scale Points on X
and Y Axis in Range from -2.5 to 2.5. 75% of
Observations Fell in this Range
FIGURE 2: ESTIMATED SURFACES RELATING FEEDBACK – SELF-
RATING CONGRUENCY TO FEEDBACK REACTIONS AT THREE
LEVELS OF CERTAINTY FOR DECISIVENESS IN STUDY 1: (A)
CERTAINTY LOW. (B) CERTAINTY MODERATE. (C) CERTAINTY HIGH
CERTAINTY AND FEEDBACK REACTIONS 153
held a bachelor’s degree and 56% had earned an advanced or professional
degree.
Procedure. The computerized in-basket exercise of Tett et al. (2003) was
slightly modified to be able to provide immediate feedback to the
participants. This was because the in-basket exercise was put on the website
of a governmental service for employment and vocational training. The in-
basket exercise was advertised as a preparation test for job applicants
providing feedback about general managerial competencies. Upon
completion of a short questionnaire measuring demographic variables,
people received a password that gave immediate access to the exercise. On
the basis of their responses to the in-basket, people received feedback about
the same four competencies (Coordinating, Decisiveness, Information
Management, and Problem Awareness) immediately after completing the in-
basket. Feedback reports were similar to the reports used in Study 1.
Measures. The self-assessment questionnaire was the same as in Study 1. As
dependent variables, we measured both feedback satisfaction and perceived
utility of feedback. Because feedback satisfaction and feedback acceptance
were highly correlated in Study 1, we used a different measure of cognitive
feedback reactions in Study 2, namely feedback utility. Previous research
has shown that affective reactions and utility judgments are independent
from each other and have different outcomes (Alliger, Tannenbaum, Bennet,
Traver, & Shotland, 1997; Keeping & Levy, 2000).
Feedback satisfaction was measured for each competency with two items
adapted from Korsgaard (1995). The items used 7-point Likert-type response
scales ranging from 1 (strongly disagree) to 7 (strongly agree). The scale
included items such as, "I am satisfied with the score I received on [name
competency]". Internal consistencies for this scale varied between .93 and
.97 for the different competencies. Feedback utility was measured for each
competency with two items on a 7-point scale adapted from Greller (1978).
The scale included items as "The feedback I received on [name competency]
154 CHAPTER 4
helped me learn how I can improve my performance.” Internal consistencies
for this scale varied between .82 and .90 for the different competencies.
Correlations between the two scales for each competency ranged from -.10
to .18. Exploratory factor analyses indicated that satisfaction and utility
items clearly loaded on two different factors.
Involvement. As in Study 1, participants indicated that all four competencies
were important to them (M = 7.25, SD = 1.16), illustrating that the
participants of this study cared about their performance on the in-basket. A
sub sample of 100 participants also completed an additional questionnaire
measuring involvement with six items on a 7-point scale, with responses
ranging from 1 (strongly disagree) to 7 (strongly agree). The scale included
items such as, “The background information we received was realistic”, “I
was motivated to perform well on this exercise”, and “I carefully followed
all instructions”. The mean for this scale was 5.80 (SD = 0.76, α = 0.78),
indicating that participants were highly involved.
Analyses. We used the same analytical approach as in Study 1. The sample
size of the present study (N = 389) had the statistical power of .80 (p = .05)
to detect a small effect size (f²) of .03 (which corresponds approximately to
R² of .03) for the quadratic difference regression. In addition, using the same
alpha, we had a power of .80 to detect an increment in R² of about .03 for the
set of terms in the moderated regression equation. Analyses of the squared
regression equations and the moderated regression equations for the two
dependent variables were treated as separate families when correcting for
Type I error (Edwards & Rothbard, 1999).
RESULTS
Descriptive statistics and correlations for all study variables are presented in
Table 3. As can be seen in Table 4, results for the competency Information
Management were in line with self-enhancement theory. Only the coefficient
on feedback scores was significant (p < .01). This indicates that people were
CERTAINTY AND FEEDBACK REACTIONS 155
satisfied with positive feedback about Information Management, regardless
of self-ratings. For the other three competencies, both coefficients on
feedback scores and self-ratings were significant and in opposite directions.
We tested if coefficients on X and Y were equal in magnitude, but opposite in
sign (see Edwards, 1994, 2002). Results showed that although coefficients
on feedback scores and self-ratings had an opposite sign, the effects of
feedback scores were greater in magnitude (p < .01).
TABLE 3: DESCRIPTIVE STATISTICS AND CORRELATION COEFFICIENTS IN STUDY 2
TABLE 4: RESULTS OF QUADRATIC REGRESSIONS OF FEEDBACK SATISFACTION
ON SELF-RATINGS AND FEEDBACK SCORES IN STUDY 2
156 CHAPTER 4
The combined effects of feedback scores and self-ratings on feedback
satisfaction for the competency Coordinating are depicted in Figure 3.
Figure 3 shows that feedback scores were more dominant in determining
feedback satisfaction than self-ratings. As can be seen in column Fm in
Table 4, self-view certainty did not moderate the relationship between
feedback – self-rating congruence and feedback satisfaction for any of the
four competencies.
Results of the analyses
with perceived utility of
feedback as a dependent
variable show that the
equation for the compe-
tency Decisiveness was in
line with predictions of
self-enhancement theory.
As can be seen in Table 5,
there was a significant
positive coefficient on
feedback scores. Howe-
ver, as hypothesized, this
main effect of feedback
scores was moderated by
self-view certainty.
TABLE 5: RESULTS OF QUADRATIC REGRESSIONS OF FEEDBACK UTILITY
ON SELF-RATINGS AND FEEDBACK SCORES IN STUDY 2.
FIGURE 3: ESTIMATED SURFACE RELATING FEEDBACK –
SELF-RATING CONGRUENCY TO FEEDBACK SATISFACTION
FOR COORDINATING IN STUDY 2
CERTAINTY AND FEEDBACK REACTIONS 157
As can be seen in column Fm in Table 5, the additional set of moderator
terms explained an additional variance of 4% (p < .05) when controlling for
the quadratic terms and certainty.
If we look along the line of congruence (X = Y) in Figure 4-A (low
certainty), we see a curvilinear relationship indicating that feedback utility
was most favorable when self-ratings and feedback scores were congruent at
their extremes. This is in line with self-verification theory. However, if we
look along the X = -Y -
line, we see that feedback
utility increased as
feedback scores got higher
and self-ratings got lower.
This is more in line with
self-enhancement theory.
If we look at Figure 4-B
(moderate certainty), we
see a curvilinear
relationship between
feedback scores and
feedback utility,
independent of self-
ratings. This indicates that
people intent to use
feedback about
Decisiveness in the future
when scores were very
high or very low,
regardless of self-ratings.
This effect was even more
pronounced when
certainty was high (Figure
4-C). Thus, although the
158 CHAPTER 4
relationship between
feedback score – self-
rating congruence and
feedback utility was
moderated by self-view
certainty, the observed
effect was not in the
hypothesized direction.
For the three other
competencies, none of the
theoretical perspectives
was supported with
feedback utility as a
dependent variable.
Although a significant
amount of variance was explained (p < .01), none of the coefficients reached
significance.
GENERAL DISCUSSION
The aim of this study was to clarify mixed results from previous research
concerning feedback reactions. Two competing perspectives in social
psychology, self-enhancement and self-verification theory, served as
conceptual underpinnings of this study. Our basic premise was that none of
them was dominant in guiding feedback reactions. Instead, we hypothesized
that self-view certainty would serve as a moderator and would strengthen the
relationship between feedback – self-rating congruence and feedback
reactions.
We tested this idea in both a lab study and a field study, using a stringent
analytical procedure recommended by Edwards (1994). This procedure was
FIGURE 4: ESTIMATED SURFACES RELATING FEEDBACK –
SELF-RATING CONGRUENCY TO FEEDBACK UTILITY AT
THREE LEVELS OF CERTAINTY FOR DECISIVENESS IN
STUDY 2: (A) CERTAINTY LOW. (B) CERTAINTY MODERATE.
(C) CERTAINTY HIGH.
CERTAINTY AND FEEDBACK REACTIONS 159
especially suited to examine our hypothesis because it enabled us to test if
feedback reactions were based on a two-step appraisal versus a one-step
appraisal of the feedback. If both components (i.e. feedback scores and self-
ratings) accounted for an equal amount of variance, feedback reactions were
characterized by a two step-appraisal and self-verification theory was
supported. When only one component (feedback scores) was significant,
feedback reactions were characterized by a one-step appraisal and self-
enhancement theory was supported.
Results of Study 1 showed strong support for self-enhancement theory, as
people reacted favorably to positive feedback, regardless of self-ratings.
Only one component (feedback scores) accounted for all variance in
feedback reactions. Self-view certainty moderated feedback reactions for the
competency Decisiveness. As hypothesized, feedback reactions where more
in line with predictions of self-enhancement theory when certainty was low
and were more in line with predictions of self-verification theory when
certainty was high.
In Study 2, we also found that people perceived greater utility of feedback
when feedback scores were high, regardless of self-ratings, for the
competency Decisiveness. This effect was also moderated by self-view
certainty, although the effect was not in the predicted direction. Different
results were observed for feedback satisfaction as a dependent variable in
study 2. For three competencies both components (feedback scores and self-
ratings) accounted for a significant amount of variance, indicating that
feedback satisfaction was determined by a two-step appraisal of feedback.
This seems to be in line with predictions of self-verification theory.
However, self-verification theory also predicts that both opposite effects are
equally strong. This was not the case. Feedback scores were stronger in
predicting feedback satisfaction, indicating that self-enhancement strivings
were also more dominant than self-verification strivings in guiding feedback
satisfaction in Study 2. The notion that both motives influence feedback
satisfaction at the same time is consistent with recent findings in social
160 CHAPTER 4
psychology that people often try to satisfy self-enhancement and self-
verification motives at the same time when processing feedback (Bernichon
et al., 2003; Sedikides, 1993; Swann et al., 1989). Certainty of self-ratings
did not moderate feedback satisfaction in Study 2.
Thus, self-enhancement strivings were dominant in both studies, although
support was found for a two-step appraisal of feedback in Study 2. One
possible explanation for the divergent findings in Study 1 and Study 2 is the
two-week time interval between the self-ratings and the feedback report in
Study 1. People are probably more likely to react to information they have
just received (the feedback report) as compared to self-ratings they have
provided two weeks ago. In study 2, people received immediate feedback
about their competencies. This suggests that when people receive instant
feedback upon their performance a two-step appraisal of feedback, with
attention for both feedback scores and self-ratings, determines feedback
satisfaction although self-enhancement strivings remain predominant.
In general, very little evidence was found for self-verification as a motive
guiding feedback reactions. Furthermore, it seems that certainty does not
play a key role as a moderator of feedback reactions and thus, does not
strengthen the self-verification motive. This is rather surprising given
previous findings in social psychological research that people tend to seek
and accept information that is consistent with central self-views across a
wide range of contexts (Dauenheimer et al., 1999; Dutton & Brown, 2003;
Markus, 1977; Stahlberg, Petersen, & Dauenheimer, 1999) and that certainty
serves as a moderator of the self-verification motive (Bui & Pelham, 2000;
Chen et al., 2004; Pelham & Swann, 1994; Seta, Donaldson, & Seta, 1999;
Swann & Pelham, 2002).
Why is there only evidence for self-enhancement in organizational
psychology? Or to put it differently, why is no support found for self-
verification in organizational psychology? Several explanations seem
plausible. First, careful inspection of the literature shows that no research
CERTAINTY AND FEEDBACK REACTIONS 161
using congruence analyses (Edwards, 1994) has examined self-verification
theory. The results of the present study illustrate the importance of using this
stringent regression procedure: If we used an algebraic difference score (e.g.,
Sweeney & Wells, 1990) as a dependent variable, results showed that the
algebraic difference was a significant predictor (p < .01) of feedback
reactions in both studies. This would have led us wrongfully to conclude that
self-verification theory was supported in all analyses. Also, more recent
research supporting self-verification theory continues to use difference
scores (e.g., Polzer, Milton, & Swann, 2002). It is possible that many alleged
self-verification effects in the literature conceal unequal effects in magnitude
of the different components.
Second, consistency effects are not easily obtained or replicated (Cialdini,
Trost, & Newsom, 1995). Therefore, researchers have often used specific
strategies to make self-verification strivings more pronounced. For instance,
self-verification effects have been observed when an oversampling strategy
was used by only selecting subjects that scored in the top and bottom
quartiles of an independent variable (e.g., Bosson & Swann, 1999; Giesler,
Josephs, & Swann, 1996) or when dependent variables were made more
extreme by multiplying self-ratings with certainty and importance ratings
(e.g., Korsgaard, 1995; Stahlberg et al., 1999)6. Although these studies
provide important insights in the underlying mechanisms and consequences
of the self-verification motive, the present study suggests that self-
verification strivings are maybe not that dominant in a natural context.
A third possible explanation is the task that is used to provide feedback to
participants. Studies in social psychology that support the self-verification
perspective on feedback reactions typically use laboratory tasks such as
6 Research has shown that extremity, certainty, and importance of self-ratings reflect
different constructs and have different cognitive and behavioral consequences
(Krosnick et al., 1993; Pelham, 1991; Visser, Krosnick, & Simmons, 2003). Thus, it
is not advisable to combine these three constructs in one measure.
162 CHAPTER 4
anagrams, block designs, and concept formation (e.g., Jussim et al., 1995;
Stahlberg et al., 1999). In organizational research which supports the self-
enhancement motive, employees received feedback about job performance
(e.g., Brett & Atwater, 2001; Illies et al., submitted). As shown by Jones
(1973), self-verification effects are less likely (as opposed to self-
enhancement effects) to occur when people are highly involved and care
about their task performance. Thus, it is possible that self-enhancement is
more dominant in guiding feedback reactions in a natural work context.
This study is not without limitations. First, both self-ratings and certainty
ratings were self-report one-item measures which possibly threatens the
reliability of these self-ratings. However, in this online setting it was
practically not feasible to use extensive questionnaires to measure self-views
because participants would not proceed with the in-basket when the
preceding questionnaire was too long. However, future research could use
other measures of self-view certainty for instance by marking uncertainty
intervals graphically (Baumgardner, 1993) or by measuring reaction times
(Molden & Higgins, 2004). Second, moderator effects in multiple regression
are often small and difficult to detect due to power problems (Aguinis,
Beaty, Boik, & Pierce, in press; McClelland & Judd, 1993; Zedeck, 1970).
In Study 1, we had adequate power to detect medium effect sizes. However,
we lacked statistical power to detect small increases in effect size. This could
explain why only one moderator effect was found. However, in Study 2 we
had statistical power to detect small effect sizes and still only one
moderating effect was observed. Third, due to the online research setting, we
had no control on self-selection and participant dropout in Study 2.
Therefore, future research should examine whether these findings generalize
to specific populations.
This study has important implications for organizations. The procedure
corresponds closely to the use of self-assessment instruments that often
precede the actual development process. For instance, as part of a
development program, employees are asked to complete self-assessment
CERTAINTY AND FEEDBACK REACTIONS 163
questionnaires or to participate in a development center or a 360-degree
feedback process. After going through the assessment process, people
receive a feedback report with narrative and quantitative feedback on several
managerial competences, as did the participants in this study. Our results
suggest that people who receive negative feedback and thus, are most in
need of improvement and development, tend to be dissatisfied and reject
feedback because it appears inaccurate. Thus, after receiving negative
feedback, chances are high that these below-average employees will be no
longer motivated to develop their competences, which is detrimental for their
future performance. Therefore, practitioners should seek for strategies to
increase acceptance of negative feedback. An example of such a strategy is
the use of feedback coaches and feedback workshops that assist people in
analyzing feedback reports and formulating development plans. Recent
research shows that managers who participated in a feedback workshop after
multi-source feedback changed their behavior accordingly, whereas
managers who only received a feedback report did not (Seifert, Yukl, &
McDonald, 2003).
In terms of future research, the problem of acceptance of negative feedback
is an important and potentially fruitful area of research. Future research
should examine specific strategies that organizations might adopt to increase
acceptance of negative feedback. Especially elaboration of feedback seems
to be a promising variable for designing specific acceptance strategies.
Social psychological research shows that self-enhancement prevails when
people lack the time and cognitive resources to analyze the obtained
feedback. However, when people are motivated or requested to actively
process and elaborate feedback, self-enhancement strivings go down,
possibly leading to higher levels of feedback acceptance (Hixon & Swann,
1993; Paulhus, Graf, & Van Selst, 1989; Swann, Hixton, Stein-Seroussi, &
Gilbert, 1990). Future research should also investigate if an emphasis on the
developmental nature of feedback leads to higher feedback acceptance. For
instance, it is possible that acceptance of negative feedback in developmental
assessment centers is higher because of the developmental nature of the
164 CHAPTER 4
feedback process. Finally, future studies should also pay attention to possible
determinants of perceived utility of feedback. The results of this study
indicate that very little variance (about 4 %) in feedback utility is explained
by feedback scores and self-ratings. As feedback utility perceptions about
the different competencies were highly correlated, it is possible that
individual difference variables (e.g., learning goal orientation, openness to
experience) underlie these utility perceptions.
In sum, our findings suggest that feedback reactions are dominated by self-
enhancement strivings and that self-verification strivings are less prominent.
Support for the role of self-view certainty as a moderator of the self-
enhancement and self-verification motives in feedback reactions was found
for the competency Decisiveness. The general finding that people seem to be
dissatisfied after receiving negative feedback and tend to reject unfavorable
feedback shows that the study of feedback reactions continues to be an
important and fruitful avenue for future research.
CERTAINTY AND FEEDBACK REACTIONS 165
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CHAPTER 5
DOES ELABORATION OF FEEDBACK ENHANCE THE
FEEDBACK – TASK PERFORMANCE RELATIONSHIP?
FIGURE 1: CHAPTER 5 SITUATED IN THE WORKING MODEL OF THIS DISSERTATION
Need for
Closure
Uncertainty
Cognitive
Effort
Performance
Feedback
Certainty
orientation
Modifiability
Importance
Feedback
reactions
Personal
Investment
Self-motives framework
Feedback
seeking
172 CHAPTER 5
ABSTRACT
The current study investigated the impact of requiring individuals to
elaborate on feedback messages on task performance. This strategy for
enhancing feedback interventions in organizations was grounded in recent
dual-process models in cognitive and social psychology, suggesting that
thoughtful information-processing leads to stronger learning effects. Results
in both a student and an employee sample showed that mean performance on
a web-based in basket improved more when participants elaborated on
feedback as compared to when feedback was not elaborated upon. These
findings point to the importance of effortful cognitive processing of
feedback and suggest several practical strategies for enhancing feedback
interventions in organizations.
INTRODUCTION
Few beliefs in organizations are so widespread as the assumption that giving
feedback to employees is beneficial for individual and organizational
performance. Feedback is believed to direct, motivate, and reward behavior
in organizations (London, 2003). Therefore, providing feedback to
employees lies at the heart of a wide range of costly performance
management tools in organizations (e.g., performance appraisal, assessment
and development centers, 360-degree feedback, computerized assessment,
coaching, and training).
Contrary to these common sense beliefs, a meta-analytic review of the
feedback literature revealed that feedback interventions do not produce
unequivocal positive effects on performance (Kluger & DeNisi, 1996).
Feedback interventions improved performance on average, but over one
third of feedback interventions decreased performance (see also Alvero,
Bucklin, & Austin, 2001; Balcazar, Hopkins, & Suarez, 1985). Furthermore,
ELABORATION OF FEEDBACK 173
results showed that there is no general principle that can predict the
effectiveness of feedback interventions (Kluger & DeNisi, 1996, 1998). One
of the main conclusions of the meta-analysis was that the major culprit of
these troubling findings was the lack of solid theoretical underpinnings to
guide feedback interventions.
So far, no research has looked at dual-process models in the broader
psychological literature to examine strategies for enhancing feedback
interventions. However, as noted by Fedor (1991), these cognitive
processing models bear specific relevance to the feedback process, as they
suggest that different modes of information-processing might determine
other cognitive, attitudinal and behavioral outcomes (e.g., Stanovich &
West, 2000; Petty & Cacioppo, 1990). Drawing on these dual-process
theories, we propose a new strategy to improve feedback interventions in
organizational settings. More specifically, the aim of this study was to
examine if requiring employees to elaborate on feedback messages might
enhance the effects of feedback on performance. In the remainder, we
discuss recent findings about the feedback - performance relationship and
introduce the theoretical and practical basis of the proposed strategy.
BACKGROUND
RECENT RESEARCH ON THE FEEDBACK-PERFORMANCE RELATIONSHIP
Since the seminal article of Kluger and DeNisi (1996), several new research
streams examining the feedback – performance relationship have emerged.
These new research perspectives have paid less attention to external factors
that might be used to enhance feedback interventions, but instead, have
attributed a more prominent role to the feedback recipient in the feedback
process.
174 CHAPTER 5
One stream of feedback research has acknowledged that employees do not
passively wait for feedback, but that feedback interventions can be initiated
by employees themselves by actively seeking performance feedback in order
to reduce uncertainty and improve performance (Ashford, Blatt, &
VandeWalle, 2003; Morrison, 2002). In this line of work, it is hypothesized
that employee feedback-seeking will lead to improved job performance.
Whereas some studies supported this hypothesis (Morrison & Weldon, 1990;
Renn & Fedor, 2001), other studies failed to support it (Ang, Cummings,
Straub, & Early, 1993; Ashford & Black, 1996) or even reported a negative
relationship between feedback-seeking and performance (Brown,
Challagalla, & Ganesan, 2001; Fedor, Rensvold, & Adams, 1992).
A second research stream did not longer look at single feedback
interventions, but started examining the feedback environment, which is
conceptualized as a continually changing dynamic system that is shaped by
the actions of the feedback recipient (Herold & Fedor, 1998; Steelman,
Levy, & Snell, 2004). Studies found that individuals’ perceptions of the
feedback environment were positively related to contextual performance
(Norris-Watts & Levy, 2004) and to job performance (Becker & Klimoski,
1989).
A third research stream paid specific attention to how employees actively
evaluate the veracity and utility of the feedback message, and decide to
respond to the feedback message (Brett & Atwater, 2001; Fedor, Davis,
Maslyn, & Mathieson, 2001; Lam, Yik, & Schaubroeck, 2002). One recent
study showed that a set of cognitive responses (e.g., perceived accuracy,
desire to respond, and intended response) completely mediated the
relationship between an employee’s receipt of feedback after a performance
appraisal and job performance one year later (Kinicki, Prussia, Wu, &
McKee-Ryan, 2004).
Whereas these three recent research streams certainly improved our
understanding of the active role of the feedback recipient throughout the
ELABORATION OF FEEDBACK 175
various stages of the feedback process, they have not provided much
information to practitioners regarding how feedback interventions might be
enhanced to improve individual and organizational performance. In this
study, a practical strategy to enhance the effects of feedback interventions on
performance in organizations is proposed. We hypothesize that requiring
people to elaborate on the feedback messages they receive, might improve
task performance. This easily applicable and cost-effective strategy was
prompted by insights from dual-process models in cognitive and social
psychology, suggesting that thoughtful information-processing might lead to
stable, and long-lasting learning effects.
THEORETICAL BASIS OF ELABORATION
When people perform tasks as diverse as solving logical problems,
evaluating persuasive arguments, and forming impressions of other persons,
they can make use of different processing strategies. People can (and in
everyday life often do so) use a sort of “quick-and-dirty” approach, arriving
at usually reasonable answers efficiently and effortlessly. People also, when
given enough time and freedom from distraction, can try hard to think
deeply about these tasks, sometimes arriving at qualitatively different
answers.
These kind of dual-process models have been developed in numerous areas
of cognitive (Sloman, 1996) and social psychology (Chaiken & Trope,
1999). An early and well-known rendition of such a model in cognitive
psychology is the levels of processing or depth of processing framework
(Craik & Lockhart, 1972; see also Craik, 2002), wherein it is proposed that
stimuli, which receive only incidental attention, are only processed to a very
“shallow” level in memory. Other stimuli are subjected to more intentional
and meaningful processing. This deeper processing elaborates the
representation of that information in memory by drawing relationships
176 CHAPTER 5
between already-known information and the information that is currently
processed, leading to better storage of the information in memory.
Dual-process models in social psychology have been especially influential in
the field of persuasion and attitude change. For instance, the Chaiken model
(Chaiken, 1980, see also the Elaboration Likelihood Model, Petty &
Cacioppo, 1986) assumes that two types of processing are possible.
Heuristic processing is said to involve the use of simple, well-learned, and
readily accessible decision rules like “experts are always right,” “the
majority is correct,” or “statistics don’t lie.” However, under certain
conditions, people go beyond heuristic processing and perform systematic
processing. This involves the active, elaborate, and effortful scrutiny of all
relevant information and therefore demands considerable cognitive capacity.
A wealth of studies has shown that attitudes formed or changed as a result of
effortful thinking are more predictive of behavioral intentions and actions
and, are more persistent over time (for reviews, see Cacioppo, Petty, &
Feinstein, 1996; Petty, Wegener, & Fabrigar, 1997).
The common thread throughout these models is that they make a distinction
between, on the one hand, cognitive processing strategies that are, automatic,
holistic, relatively undemanding of cognitive capacity, and relatively fast
and, on the other hand, cognitive processing strategies that are controlled,
analytic, demanding of cognitive capacity, and relatively time-consuming
(Evans & Over, 1996; Smith & DeCoster, 2000). A particularly striking
feature of these dual-process models is that the effortful, elaborate thinking
mode often yields different outcomes in comparison to the sparse, economic
thinking mode (e.g., other solutions to problem solving and reasoning,
deeper memory storage, more likely attitude and behavior change, less use of
stereotypes in judgments). The most significant ability of the effortful
processing mode seems to be learning a new fact or rule, and immediately
applying those facts in situations where they are relevant, suggesting that
thoughtful information-processing might be an appropriate strategy to ensure
long-lasting learning effects (Smith & DeCoster, 2000)
ELABORATION OF FEEDBACK 177
On the basis of this fine-grained look on different modes of cognitive
processing, we hypothesized that extensive elaboration of the feedback
message will lead to deeper cognitive processing of the feedback message
and consequently, will more likely lead to behavior change and performance
improvement. The specific elaboration strategy that was used in this study
was grounded in an experimental paradigm in the persuasion domain, which
has yielded particularly powerful persuasion effects and which seems
especially appropriate to apply in an organizational setting. In these studies,
the level of elaboration is directly manipulated by asking individuals to
generate a number of arguments supporting a certain point of view. By
thinking about possible arguments and examples, individuals extensively
elaborate on the persuasive message, leading to enduring changes in attitudes
and behavior in the direction of the persuasive message (e.g., Gordijn,
Postmes, & de Vries, 2001; Tormala & Petty, 2004; Tormala, Petty, &
Brinol, 2002).
We applied this same strategy to elicit elaboration of feedback in an
organizational setting. After receiving feedback about their performance on a
web-based in-basket, participants were asked to give specific examples of
behavior that was in line with the feedback message they received,
instigating a deeper processing of the feedback message. Because it still
unclear whether negatively or positively framed arguments have a stronger
persuasive effect on attitude change (e.g., Petty et al., 1997; Shiv, Britton, &
Payton, 2004), we asked participants to provide the same number of
positively framed (“What did I do correct?”) as negatively framed (“Where
did I go wrong?”) arguments.
PRACTICAL BASIS OF ELABORATION
Apart from this theoretical basis, the elaboration principle may offer
organizations a general strategy for enhancing feedback interventions.
Requiring people to elaborate on the received feedback message should be
178 CHAPTER 5
an easily applicable, inexpensive and efficient tool for more thoughtful
feedback processing and for improving performance across a wide range of
feedback situations. Especially in settings were organizations have little
control about the feedback recipient’s environment and responses (e.g., web-
based testing and on-line training programs), this strategy may offer
organizations assistance in ensuring that the provided feedback is well
received and processed. For instance, in this study, we used a web-based
assessment instrument that automatically generated feedback messages.
After participants read the feedback messages, they were instructed to give
behavioral examples in specially designed text boxes on their computer
screen. Next, their answers were submitted via the Internet to a central
server, where elaboration could be verified.
We envision that the elaboration strategy should be particularly appealing to
practitioners as it corresponds closely to current organizational practice. In
many organizations, taking part in a feedback workshop after going through
a development center, or a 360-degree feedback program, has become an
integral part of the performance management cycle (Yukl & Lepsinger,
1995; DeNisi & Kluger, 2000). Feedback workshops provide managers with
uninterrupted time to analyze and interpret their feedback and develop
improvement plans, often with the assistance of an executive coach or
feedback facilitator (Bracken, 1994). Recent research indicates that the use
of these feedback workshops is beneficial for improving performance and
changing behavior after a 360-degree feedback program (Seifert, Yukl, &
McDonald, 2003; Smither et al., 2003). The strategy for increasing feedback
elaboration that was used in the current study, might be easily included in
the design of a feedback workshop, for example by asking feedback
recipients to note down and discuss examples of correct and faulty past
behavior on the basis of the received feedback report. In this vein, the
practical application of the proposed elaboration strategy bears some
similarity to recent work on required elaboration of biodata items to reduce
faking (Schmitt et al., 2003; Schmitt & Kunce, 2002).
ELABORATION OF FEEDBACK 179
Taken together, this study seeks to extend the performance feedback domain
with a practical intervention developed to enhance the effects of feedback on
performance. On the basis of insights on dual-process models of cognitive
processing, we investigated whether eliciting individuals to extensively
elaborate feedback messages might enhance the effect of feedback
interventions on task performance. This objective was examined by using an
experimental design wherein two different samples (final-year students and
experienced employees) completed parallel versions of a web-based in-
basket exercise.
STUDY
METHOD
Participants. Two samples were used. The first sample consisted of 436
final-year students from different majors (e.g., engineering, agricultural and
plant sciences, communication, education) participating in exchange for
course credit. Participants had an average age of 22.2 years (SD = 2.0); 67%
were female, 33% male.
The second sample consisted of 517 individuals (58% male, 42% female).
Their ages ranged from 17 to 60 years (M = 36.6 yrs, SD = 10.5). The
participants had an average working experience of 13.7 years (SD = 10.5) in
their company and an average experience of 4.9 years (SD = 5.6) in their
current position. 79% held a bachelor’s degree and 45% had earned an
advanced or professional degree.
Because of problems typically associated with the use of web-based data
collection strategies, the obtained data were carefully screened. The
following precautions were taken, as recommended by Stanton and
Rogelberg (2001). First, only individuals that entirely completed the in-
basket exercise and all measures, were included in the two samples.
180 CHAPTER 5
Furthermore, responses not matching a master list with valid identifiers were
discarded. Finally, when multiple identical responses were detected in the
data, all data in the multiple-response group were dropped.
Design. We conducted a 2 (feedback vs. no feedback) x 2 (elaboration vs. no
elaboration) x 2 (trial 1 vs. trial 2) factorial design with repeated measures
on the last factor and performance on an in-basket exercise as dependent
variable. Participants were randomly assigned to one of four treatment
conditions and consecutively completed two parallel versions of the in-
basket exercise. The manipulations are described below.
Task. Participants completed a computerized in-basket exercise that was
adapted from Tett, Steele, and Beauregard (2003). The in-basket exercise
places the individual in a managerial role in responding to a set of realistic e-
mails designed to capture key work demands. Several efforts were taken to
ensure the realism of the in-basket (role descriptions, background
information, pictures, e-mail simulation, organizational charts, etc.). The
adapted exercise comprises of a set of ten e-mails, constructed to measure
four managerial competencies that are included in a recently developed
taxonomy of managerial competence (Tett, Guterman, Bleier, & Murphy,
2000), namely Problem Awareness, Coordinating, Information
Management, and Decisiveness. After each e-mail, participants received four
possible responses to the e-mail and had to rate the effectiveness of each
response. On the basis of the scoring rules developed by Tett et al. (2003),
participant’s effectiveness ratings on each e-mail response were scored on
one of the four competencies and a total score on each competency (1-20)
was computed. Correlations between total scores on the four performance
dimensions (competencies) varied between .26 (p < .01) and .47 (p < .01).
Therefore, scores on the four competencies were averaged into a global score
representing participant’s overall performance on the in-basket.
As it was our aim to examine whether performance on the task improved
after receiving performance feedback, we needed an equivalent version of
ELABORATION OF FEEDBACK 181
the in-basket exercise that could be used to assess performance at Time 2.
We used a cloning procedure, outlined by Clause, Mullins, Nee, Pulakos,
and Schmitt (1998), to construct a parallel test form of the in-basket
exercise. This cloning procedure consists of writing for each original item, a
new item measuring the same underlying skill or ability as the original item
using the same grammatical style but bearing the surface appearance of a
different question. By using this procedure, the composition of the parallel
form is identical to that of the original form, in terms of number and type of
options and response options. A sample item with its four response options
from the original exercise and the corresponding item with its four response
options from the alternate form are presented in Appendix A.
A pilot study was conducted to test if mean performance on both test forms
was comparable. Given that observed mean differences might also be due to
practice effects or fatigue effects, both test forms were presented in random
order. In this pilot study, a total of 146 employees (41% women; mean age =
37.5 yrs; organizational tenure = 14.9 yrs; job tenure = 13.0 yrs) completed
both in-basket forms in random order. Recruitment of participants in the
pilot study was the same as described below for the actual study. A 2 (Order:
normal vs. reversed) x 2 (Trial: trial 1 vs. trial 2) mixed ANOVA with
repeated measures on the last factor and performance as dependent variable
was performed. Results showed no significant main effect of trial, F(1,144)
= .10, η2 = .00, nor an interaction effect between trial and order, F(1,144) =
.00, η2 = .00, indicating that parallelism was established at the level of the
test form and that no practice or fatigue effects were present. To ensure that
none of the presumed feedback or elaboration effects were due to different
test forms or practice effects, the two alternate test forms were also presented
in random order in the actual study.
Manipulations and Measures. In this study, two different variables,
feedback and elaboration, were manipulated, creating four different
conditions. Participants were randomly assigned to each of the four
182 CHAPTER 5
conditions. The four conditions are described separately to make the
manipulations more apparent to the reader.
No Feedback – No Elaboration Condition. After completing the first
in-basket exercise, participants received a message that they were halfway
the session and that they had ten more e-mails to respond to before they
would receive feedback about their performance. After this message,
participants could start working on the parallel version of the in-basket
exercise. Thus, participants in this condition represent the control group in
the experimental design.
Feedback – No Elaboration Condition1. After completing the first
version of the in-basket exercise, participants received feedback about their
performance. A short feedback report was presented for each competency
separately, including their scores (1-20) on these specific performance
dimensions and a brief explanatory text. These texts outlined in general
terms the behavior of individuals who tend to score very high on a specific
dimension. An example of the feedback reports that were provided to the
participants can be found in Appendix B. Feedback on each performance
dimension was presented on a separate screen. After participants indicated
they had read each of the four feedback texts (by clicking the “next” button),
they were directed to a screen measuring their cognitive responses to
feedback.
Feedback – Elaboration Condition. After completing the first version
of the in-basket exercise, participants received the same kind of performance
feedback as in the previous condition. However, after having read the
feedback reports, participants were directed to a screen that was designed to
elicit elaboration of the provided feedback. Participants were asked to reflect
on their past task performance on the basis of the feedback. For each
1 Participants in the Feedback – No Elaboration condition were also part of the
sample used in Study 2, Chapter 4.
ELABORATION OF FEEDBACK 183
competency, participants had to write down one example of an item they
thought to have answered incorrect and one example of an item they thought
to have answered correct. Thus, in total, participants were asked to give eight
examples of items, four correct and four incorrect. Participants had to type
their examples in the appropriate text boxes on their screen. After
participants had given behavioral examples for each competency, they could
start working on the second version of the in-basket exercise.
No Feedback – Elaboration. In this last condition, participants did not
receive feedback after completing the first exercise, but were still asked to
give examples of items that they had presumably answered correct and
incorrect for each competency, as described above. This control condition
was included because it could be argued that performance improvement in
the Feedback – Elaboration condition might not be caused by extensive
elaboration of the feedback. Instead, the request to give examples of correct
and faulty behavior might have instigated employees to consider and adapt
their general test taking strategy, leading to improved task performance. If
this is the case, then task performance in both the Feedback – Elaboration
and the No Feedback - Elaboration should improve.
Procedure. In the student sample, sessions were conducted in groups of 45
individuals. Participants arrived in a classroom and were seated at a
computer. They received a brief description of the proceedings of the
session. To increase participants’ involvement, they were told that an in-
basket exercise as the one they were about to complete, is often used in
selection and assessment procedures for junior managers. Participants were
informed that they would receive feedback about their performance at the
end of the session and were instructed to give their best effort so they would
receive an accurate assessment of their managerial competencies. After
providing informed consent, they were given a random identifier that
provided access to the website with the computerized in-basket exercise.
184 CHAPTER 5
The sample of experienced employees was contacted via the Internet. The in-
basket exercise was put on the website of a governmental service for
employment and vocational training. This website is frequently visited by
applicants and employees looking for training and coaching in job
application skills and various work-related competencies. The in-basket
exercise was advertised as a preparation test for job applicants, providing
feedback about general managerial competencies. Upon completion of a
short questionnaire measuring demographic variables, people received a
random identifier that gave access to the website with the computerized in-
basket exercise. Before starting the exercise, participants were informed
about the study and were introduced to the exercise via their computer
screen.
RESULTS
Manipulation Checks
Feedback Manipulation. We measured satisfaction with feedback after
feedback about each competency with two items adapted from Korsgaard
(1995) (α = .80 and .79). If participants have actually read feedback
messages, then higher satisfaction should be reported when positive
feedback was received, as has repeatedly been shown in previous research
(e.g., Brett & Atwater, 2001; Korsgaard, 1995). This hypothesis was
supported. Overall Performance on Trial 1 was positively related to overall
satisfaction in the student sample (r = .24, p < .01) and the employee sample
(r = .41, p < .001), indicating that participants had read their feedback report.
Elaboration Manipulation. Recall that participants in the elaboration
condition were requested to write down examples of their behavior on the
first trial. We scrutinized their written texts to check whether feedback
elaboration had taken place. Whenever participants did not provide
behavioral examples, for instance by leaving text boxes blank, or writing
down irrelevant comments, these variables were treated as missing data and
ELABORATION OF FEEDBACK 185
corresponding cases were excluded from the analyses. This procedure
guaranteed that all participants that were included in the sample, had actually
elaborated their feedback reports.
Data from the two samples were analyzed separately to establish generality
of the results.
Student Sample
Task Performance
Source df F η²
Between subjects
Feedback 1 48.98*** .10
Elaboration 1 1.09 .00
Feedback x Elaboration 1 3.85* .01
Error 432 (1.95)a
Within subjects
Trial 1 196.73*** .31
Trial x Feedback 1 182.99*** .30
Trial x Elaboration 1 9.24** .02
Trial x Feedback x Elaboration 1 10.00** .02
Error 432 (.64)a
Note. a Equals the Mean Square Error. * p < .05, ** p < .01, *** p < .001.
TABLE 1: ANALYSIS OF VARIANCE FOR THE FULL FACTORIAL MODEL
WITH TASK PERFORMANCE AS DEPENDENT VARIABLE FOR THE STUDENT SAMPLE.
A 2 (Feedback vs. No feedback) x 2 (Elaboration vs. No elaboration) x 2
(Trial 1 vs. Trial 2) GLM analysis was conducted with repeated measures on
the last independent variable and task performance as dependent variable. As
can be seen in Table 1, we found significant effects of Trial, F(1,432) =
196.73, p < .001, η2 = .31, Trial x Feedback, F(1,432) = 182.99, p < .001, η2
= .30, and Trial x Elaboration, F(1,432) = 9.24, p < .01, η2 = .02.
Task Performance (n = 436)
Trial 1 Trial 2
Results
M SD M SD
No Feedback No Elaboration 13.21 1.15 13.24 1.18
Elaboration 13.13 1.04 13.15 1.14
Feedback No Elaboration 13.12 1.01 14.28 1.41
Elaboration 13.07 1.00 14.89 1.11
TABLE 2: MEAN TASK PERFORMANCE AND STANDARD DEVIATIONS
ACROSS EXPERIMENTAL CONDITIONS IN THE STUDENT SAMPLE
186 CHAPTER 5
However, these significant effects were qualified by a three-way Trial x
Feedback x Elaboration interaction effect, F(1,432) = 9.24, p < .01, η2 = .02 .
Table 2 presents mean task performance scores for the different
combinations of the independent variables. Mean task performance on Trial
1 (T1) did not vary across conditions, F(3,432) = .30, p = .82. Planned
comparisons indicated that Trial 2 (T2) Performance in the Feedback/ No
elaboration condition was higher than T2 Performance in the No feedback/
No elaboration condition, F(1,432)=38.96, p < .001, d = .80, and the No
feedback / Elaboration condition, F(1,432)=47.39, p < .001, d = .88.
However, T2 performance in the Feedback/ Elaboration condition was still
higher than T2 performance in the Feedback/ No Elaboration condition,
F(1,432)=14.17, p < .001, d = .49. Thus, as can be seen in Figure 2,
feedback alone significantly improved performance, but performance
improved most in the Feedback/ Elaboration condition, indicating that
elaboration enhanced the effects of feedback on performance.
FIGURE 2: EFFECTS OF FEEDBACK AND ELABORATION ON PERFORMANCE IN THE STUDENT SAMPLE.
No feedback/ No elaboration
Feedback/ No elaboration
Feedback/ Elaboration
No feedback/ Elaboration
11
12
13
14
15
16
Mean Task Performance
Trial 1
Trial 2
ELABORATION OF FEEDBACK 187
Employee Sample
As can be seen in Table 3, analyses in the employee sample yielded the same
pattern of results as in the student sample. The significant Trial, Trial x
Feedback, and Elaboration x Feedback effects were qualified by a significant
Trial x Feedback x Elaboration interaction effect, F(1, 513) = 7.54, p < .01,
η2 = .01.
Task Performance
Source df F η²
Between subjects
Feedback 1 29.53*** .05
Elaboration 1 .67 .00
Feedback x Elaboration 1 1.76 .00
Error 513 (2.58)a
Within subjects
Trial 1 120.13*** .19
Trial x Feedback 1 113.53*** .18
Trial x Elaboration 1 7.87** .02
Trial x Feedback x Elaboration 1 7.54** .01
Error (.76)a
Note: a Equals the Mean Square Error. * p < .05, ** p < .01, *** p < .001.
TABLE 3: ANALYSIS OF VARIANCE FOR THE FULL FACTORIAL MODEL
WITH TASK PERFORMANCE AS DEPENDENT VARIABLE FOR THE EMPLOYEE SAMPLE.
Task Performance (n = 517)
Trial 1 Trial 2
Results
M SD M SD
No Feedback No Elaboration 13.44 1.22 13.46 1.45
Elaboration 13.39 1.12 13.41 1.33
Feedback No Elaboration 13.42 1.22 14.30 1.50
Elaboration 13.34 1.14 14.81 1.29
TABLE 4: MEAN TASK PERFORMANCE AND STANDARD DEVIATIONS
ACROSS EXPERIMENTAL CONDITIONS IN THE EMPLOYEE SAMPLE
Mean task performance on Trial 1 (T1) did not vary across conditions,
F(3,513) = .21, p = .89. As shown in Table 4, T2 Performance in the
Feedback/ No elaboration condition was higher than T2 Performance in the
No feedback/ No elaboration condition, F(1,513) = 23.46, p < .001, d = .57,
and the No feedback / Elaboration condition, F (1,513) = 24.61, p < .001, d
=. 63. As in the student sample, T2 performance in the Feedback/
188 CHAPTER 5
Elaboration condition was higher than T2 performance in the Feedback/ No
Elaboration condition, F(1,513) = 8.78, p < .01, d = .37. As can be seen in
Figure 3, the positive effect of feedback elaboration on performance was
replicated in the working sample, although the observed effect size was
slightly smaller than in the student sample.
FIGURE 3: EFFECTS OF FEEDBACK AND ELABORATION ON PERFORMANCE IN THE EMPLOYEE SAMPLE
DISCUSSION
The results of this study support the argument that elaboration of feedback
enhances the effect of feedback interventions on task performance. We
found that when individuals were requested to elaborate the received
feedback, performance significantly improved as compared when feedback
was given without additional elaboration. Thus, predictions that were made
on the basis of dual-process models of cognitive processing were supported
No feedback/ No elaboration
Feedback/ No elaboration
Feedback/ Elaboration
No feedback/ Elaboration
11
12
13
14
15
16
Mean Task Performance
Trial 1
Trial 2
ELABORATION OF FEEDBACK 189
when students and employees were given feedback on task performance.
Furthermore, results revealed that the observed effects are caused by
elaboration of the received feedback messages and not by a general
reconsideration of test taking strategies due to elaboration, as performance
did not improve in the condition where individuals were requested to
elaborate without feedback.
The finding that effortful and elaborate cognitive processing of feedback
enhances feedback interventions, is consistent with recent theory-building in
the feedback domain. In their Feedback Intervention Theory, Kluger and
DeNisi (1996) proposed that the effectiveness of feedback interventions
depends on the allocation of available cognitive resources. When feedback
directs attention to task performance, then individuals’ cognitive resources
are allocated towards the task and performance improvement is possible, for
instance by learning new problem solving strategies. Alternatively, when
feedback directs attention away from the task, cognitive resources necessary
for task performance are depleted, which may lead to a decrease in
performance. For instance, when people receive negative or discrepant
feedback, their attention is likely to shift to ego-defensive goals instead of
task performance goals. Recent evidence seems to support this cognitive
resource conceptualization of feedback interventions (Vancouver &
Tischner, 2004). In the present study, by eliciting participants in the
elaboration condition to deeply process the feedback messages, attention was
shifted towards the task level, ensuring that cognitive resources were
available for learning new task strategies, leading to an increase in
performance. Thus, elaboration during feedback interventions might play a
role in directing cognitive resources towards the task-level resulting in
deeper processing, better retention, and hence better learning effects.
Feedback elaboration might also affect task performance through the
mediating role of cognitive responses to feedback. Dual-process research in
social psychology demonstrated that when people lack the time and
cognitive resources to “deeply” analyze information, feedback responses
190 CHAPTER 5
tend to be ego-defensive and self-enhancing (e.g., negative feedback is
poorly remembered, not satisfying and perceived as inaccurate). However,
when people are requested to introspect and elaborate on the information,
responses to feedback become less self-enhancing, leading to higher levels
of feedback acceptance (Hixon & Swann, 1993; Paulhus, Graf, & Van Selst,
1989; Swann, Hixton, Stein-Seroussi, & Gilbert, 1990; Swann & Schroeder,
1995). Thus, the observed performance improvement in the elaboration
condition may be caused by higher levels of feedback acceptance after
deeper processing of the feedback message. As we had data available on
cognitive responses (feedback acceptance and feedback utility) to feedback
before T2 performance, we conducted some additional analyses to examine
this mediation hypothesis. Results showed that feedback utility partially
mediated the elaboration – performance relationship in the employee sample.
Feedback elaboration significantly predicted feedback utility (p < .05) and
both feedback utility and feedback elaboration independently predicted T2
performance. As feedback elaboration remained a significant predictor of
performance after feedback utility had been included in the model, there was
no “perfect” mediation.
However, this finding was not confirmed in the student sample. Cognitive
responses (feedback acceptance and feedback utility) were not predicted by
feedback elaboration. Both feedback elaboration and feedback acceptance
independently predicted T2 performance (p < .05). Thus, the explanation
regarding cognitive responses as mediators of the elaboration - performance
relationship did not receive convincing support2. Our analyses seem to
2 A possible explanation for the lack of support for the mediation hypothesis is that
we had no control whether participants’ elaborated upon the feedback message
before reporting their cognitive responses. Although cognitive responses were
measured after the elaboration manipulation on each competency, this happened on
the same web page. It is possible that participants first scrolled down to complete
the cognitive responses measure and then scrolled back up again to complete the
elaboration manipulation (i.e., typing down behavioral examples in the appropriate
text boxes).
ELABORATION OF FEEDBACK 191
suggest that elaboration and cognitive responses are two independent
processes predicting performance. Clearly, more research is needed on the
relation between elaboration and cognitive responses to feedback to shed
light on these preliminary findings.
PRACTICAL IMPLICATIONS, LIMITATIONS, AND DIRECTIONS FOR
FUTURE RESEARCH
In the current study, we provided a general principle for enhancing the effect
of feedback interventions on performance in organizations. If people process
the provided feedback at a deeper cognitive level (i.e., by elaborating on past
examples of correct and faulty behavior), task performance improved
significantly. We propose that, if organizations want feedback to lead to
sustained performance improvements, they should try to guarantee this type
of effortful processing in feedback interventions. Thus, practitioners should
look for concrete strategies that might put the general elaboration principle
into practice.
As mentioned, the manipulation used in this experiment should be easily
applicable in workshops after 360-degree feedback. However, elaboration of
feedback should not only be available in feedback workshops after 360-
degree feedback programs. Practitioners should also try to ensure that
employees have ample time, and resources available for processing feedback
in career development and training programs, in performance appraisal or
after computerized assessments. The use of external coaches and mentoring
seems an advisable strategy in these settings. However, elaboration of
feedback might also be enabled through other strategies. For instance,
organizations might consider developing “feedback processing” modules on
their intranet or including feedback elaboration moments in training syllabi
or interpretive guides that often accompany a feedback report.
In this vein, it is important that future research tries to identify various
facilitating conditions concerning the effects of feedback elaboration in
192 CHAPTER 5
practice by implementing feedback elaboration in feedback workshops. Till
now, the key question “why are feedback workshops effective
developmental tools ?” has remained unanswered (Brett & Atwater, 2001;
Seifert et al., 2003; Smither et al., 2003). It is our hypothesis that feedback
workshops lead to performance improvement because they encourage deeper
feedback processing in feedback recipients, which is in line with the
proposed elaboration principle. Future research should examine this
hypothesis by experimentally combining the elaboration strategy with the
components that are typically included in a feedback workshop, namely a
group discussion, the presence of a facilitator and a goal-setting instruction.
The results of this research would be of theoretical importance as they might
assist in a better understanding of the mechanism that accounts for the
effects of feedback workshops on performance. Furthermore, such studies
would be informative to practitioners in identifying the best development
strategy in terms of costs and effectiveness to improve performance after
feedback interventions.
There are a number of limitations that should be considered when one is
interpreting the results of this study. First, we used a computerized task to
test our hypothesis. Participants completed a web-based in-basket and
received feedback from a computer. The question raises whether these
results will generalize to more natural settings, where contextual influences
(e.g., other feedback sources, behavior of colleagues, personal contact,
competing tasks) might influence feedback responses and performance.
However, the use of web-based and computerized feedback reports (e.g.,
after 360-degree feedback) and computerized tasks is becoming more and
more common in organizations. More importantly, a wealth of self-
assessment instruments are freely available on the Internet and employees
with Internet access who are looking for feedback on their managerial
competencies, can complete these self-assessment instruments on their own
pace. For instance, the past year about 12.000 people followed an online
training via the website of the governmental service for employment and
vocational training where our in-basket was put on. In the light of this
ELABORATION OF FEEDBACK 193
evolution, the design of this study actually corresponds very closely to
natural work settings and employee practices.
A second limitation that should be noted, is that due to the online research
setting, we had no control on self-selection and participant dropout in the
employee sample.
Finally, one important observation that might limit the generalizibility of the
current findings, is that in this particular setting, feedback without
elaboration also significantly improved task performance as compared to a
no-feedback control condition. With this finding, our study adds to about
two-third of the feedback intervention studies that found a positive impact of
feedback on performance (Kluger & DeNisi, 1996). The effect sizes found in
this study (d = .80 and d = .57) were comparable to the mean effect sizes that
were reported by Kluger and DeNisi in their meta-analysis (d = .41 and d =
.92, depending on the studies included). In the current study, we found that
elaboration of feedback significantly improved performance above this
feedback-alone effect. However, we don not know what the effect of
feedback elaboration would be in a setting where feedback tends to debilitate
performance, as was the case in one third of the feedback interventions
reported in Kluger and DeNisi’s (1996) meta-analysis.
In this respect, a second important avenue for future research is to examine
whether feedback elaboration can shed more light on the effects of feedback
sign on performance. Previous research yielded no clear specifications
regarding when and how favorable or unfavorable feedback increases and
decreases motivation and subsequent performance (Ilgen & Davis, 2000;
Kluger & DeNisi, 1996; Van-Dijk & Kluger, 2004). Providing favorable or
unfavorable feedback bears strong resemblance to positive or negative
framing of persuasive messages. A dual-process approach of persuasion
processes demonstrated that the level of elaboration interacts with the effects
of message framing. Negative framing of persuasive messages has generally
found to be more effective (persuasive) when the level of elaboration is high,
194 CHAPTER 5
whereas positive framing of messages seems to be more effective when the
level of elaboration is low (Levin, Schneider, & Gaeth, 1998; Rothman &
Salovey, 1997; but see also Shiv, Britton, & Payne, 2004). On the basis of
these findings, it could be expected that positive feedback should be more
likely to lead to performance improvement under low elaboration conditions
as positive feedback demands less cognitive resources, whereas negative
feedback should be more likely to lead to performance improvement under
high elaboration conditions as negative feedback demands more cognitive
resources. This would be in line with the above described Feedback
Intervention Theory, which suggests that more cognitive resources should be
allocated to the task-level when negative or discrepant feedback is provided
(Kluger & DeNisi, 1996; Vancouver & Tischner, 2004).
CONCLUSION
There is probably no unequivocal answer to the broad question whether
giving employees performance feedback enhances performance. Instead, we
believe that research should focus at a wealth of factors that might possibly
shape the impact of feedback interventions on employee attitudes, responses
and behavior in organizations. Several theoretical perspectives from different
disciplinary backgrounds might guide feedback research and seem well-
suited to shed additional light on conditions that facilitate feedback
interventions. Ultimately, the objective is to identify situations where giving
performance feedback to employees is most likely to have a positive impact
on performance versus situations where performance feedback is less likely
to lead to performance improvement. In the current study, we borrowed from
recent dual-process models in cognitive and social psychology to propose a
new condition to facilitate the impact of feedback interventions on
performance. We found that eliciting feedback elaboration seems an
effective and practical strategy for enhancing feedback interventions. On the
basis of the observed findings, we believe that general models of cognitive
processing in the broader psychological literature deserve more attention in
ELABORATION OF FEEDBACK 195
future feedback research as they might offer various strategies for enhancing
feedback interventions in organizations.
196 CHAPTER 5
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ELABORATION OF FEEDBACK 201
APPENDIX A
EXAMPLE OF AN IN-BASKET ITEM
AND THE CORRESPONDING PARALLEL ITEM
Original Item
Date : Tuesday, 06/17/02
From: Eric Danforth
Subject: Upcoming Conference
Pat,
Last week Mr. Green arranged a meeting for July 2 regarding a new line
of wind-resistant paints for use in the aviation industry. I realize my input
would be valuable at this stage, but I’ve been planning since last fall to
attend a conference in Boise, Idaho July 1-3 on new paint manufacturing
processes. Is there any way the meeting could be postponed until after the
7th? I need to know by Tuesday morning
A. It’s kind of hard to cancel this
meeting as Mr. Green is coming to
our plant to attend this meeting. Is
it possible to cancel your trip to
Boise? Please, be patient, I’ll ask
Mr. Green and let you know what
he thinks.
B. Indeed, it is probably more
important for our company that you
are present at the conference. If I
understand correctly, the theme of
the conference, “innovativeness”, is
similar to that of our meeting. So,
we can benefit from hearing the
results of the conference and
arrange the meeting afterwards.
C. I don’t think that the Boise-
conference is that important. It’s
mostly advertisements of the big
companies. I wouldn’t worry to
much about attending the
conference. I guess it’s better to
proceed as planned.
D. I can see that this conference
was planned for some time and that
it takes priority for you. I will
postpone the meeting to the 14th.
Mr. Green knows our priorities and
won’t make a problem of this.
202 CHAPTER 5
Corresponding Parallel Item
Date : Thursday, 06/19/02
From: Glen Benning
Subject: Exhibition in Chicago
Pat,
You’ll probably know we have a meeting arranged with all production
supervisors for July 15th, where you would also be present. In this
meeting, we would discuss how we might improve customized
production of industrial coatings. However, at the same day, there’s an
exhibition in Chicago on applications of coatings in the building industry,
which I like to attend. I wondered if it would be possible to schedule our
meeting at another day? I would like an answer as soon as possible.
A. It’s difficult to reschedule this
meeting because all production
supervisors have already confirmed
to be present. Have you already
made appointments with sales
people at that exhibition? I’ll first
check with all other supervisors
and then get back to you. So, we’ll
have to wait and see.
B. Customized production of
industrial coatings should become
one of our core activities in the
next years. This exhibition sounds
like a good opportunity to follow-
up recent trends. I think it’s best if
we schedule our meeting after the
exhibition. You’ll input at this
meeting is bound to be important.
C. I don’t think much of these
exhibitions. In my experience,
you’ll find mostly publicity stands
at this exhibition. You’ll probably
won’t learn anything you don’t
already know. So, I think it’s better
to let our meeting take place as was
originally scheduled.
D. I understand that this exhibition
might be very interesting to you
and you’d like to be present. I’ll
reschedule the meeting to next
week (26th). The other production
supervisors can very well judge the
importance of this exhibition and
will certainly agree with the
rescheduling.
ELABORATION OF FEEDBACK 203
APPENDIX B
EXAMPLE OF FEEDBACK REPORT
FOR COMPETENCY “COORDINATING”
Coordinating
• Definition: This competency indicates that you organize the ac-
tivities of subordinates and allocate the necessary resources for
these activities.
• Expert: People who score high on this competency typically give
specific assignments to their subordinates. They schedule ap-
pointments and meetings to promote the productive use of time.
They emphasize efficiency by establishing efficient work routines
and by integrating multiple tasks.
• Your score: 15 / 20
CHAPTER 6
GENERAL CONCLUSIONS
ABSTRACT
The objectives of the studies presented in this doctoral dissertation were
threefold. First, on the basis of the self-motives framework, we aimed to
identify new antecedents of feedback-seeking behavior. Second, we took a
closer look at unresolved issues from previous feedback research by
considering the explanatory role of self-motives. Third, we aimed to
investigate how self-motives research might contribute to understanding and
enhancing the troubling relationship between feedback and performance. In
this final chapter, the empirical findings of this dissertation are briefly
summarized. Next, the contributions, opportunities, and limitations of this
dissertation are delineated from a theoretical, methodological, and practical
perspective.
206 CHAPTER 6
RESEARCH OVERVIEW
This dissertation started with a review of 20 years of feedback-seeking
research. This review of 49 studies showed that previous feedback-seeking
studies have encountered a number of limitations. With self-motives research
in social psychology as theoretical underpinnings, an alternative model for
studying the feedback-seeking process in organizations was proposed. The
presented self-motives model outlined a roadmap with several routes for
future research. In the empirical studies in this dissertation, I aimed to
accomplish three of these research routes, namely (a) identifying new
antecedents of feedback-seeking behavior, (b) taking a closer look at
unresolved issues in previous research, and (c) understanding and enhancing
the troubling relationship between feedback and performance. The remainder
briefly recapitulates the main findings in terms of these three objectives.
OBJECTIVE 1: IDENTIFYING NEW ANTECEDENTS OF FEEDBACK-SEEKING
BEHAVIOR
The first objective was addressed in an experimental study wherein
participants could seek feedback about a number of performance dimensions
after performance on a computerized in-basket exercise (Chapter 2). In this
study, beliefs about the modifiability and importance of performance
dimensions were examined as antecedents of feedback-seeking behavior
because self-motives research has suggested that these variables are related
to the self-improvement motive. Results supported our central hypothesis.
Affecting participants’ modifiability and importance beliefs significantly
impacted their feedback-seeking decisions as compared to a baseline
condition where modifiability and importance beliefs were not affected.
Participants sought more feedback about important dimensions as opposed to
unimportant dimensions and sought more feedback about non-modifiable
dimensions as opposed to modifiable dimensions. The latter finding was
GENERAL CONCLUSIONS 207
somewhat unexpected as the observed relationship was in the opposite
direction as hypothesized. As discussed, the specific setting might have been
responsible for activating a self-assessment motive, leading to increased
interest in feedback about non-modifiable dimensions. Notwithstanding this
unexpected finding, both hypothesized antecedents were found to be
significant predictors of feedback-seeking decisions and may prove to be
useful in the future for directing employee feedback-seeking towards
specific dimensions in organizations.
A field study in Chapter 3 also identified two new antecedents of feedback-
seeking behavior. Although it was not the main focus of this study, we were
able to examine whether Need for closure and Certainty orientation were
related to feedback-seeking behavior. Self-motives research has previously
suggested that these two individual difference variables were related to the
self-assessment and self-verification motives, and thus might be related to
feedback-seeking. Results of this cross-sectional study showed that
employees with a high Need for closure sought less feedback through
monitoring, and employees with a high Certainty orientation sought more
feedback through inquiry. However, further analyses suggested that these
individual differences might only have an indirect influence on feedback-
seeking behavior as their effect on feedback-seeking behavior disappeared
when we controlled for perceived uncertainty.
Taken together, the self-motives framework showed to be successful in
identifying importance and modifiability beliefs as direct antecedents, and
Need for closure and Certainty orientation as indirect antecedents of
feedback-seeking behavior, as was put forward in the first objective.
OBJECTIVE 2: A CLOSER LOOK AT UNRESOLVED ISSUES IN THE
FEEDBACK-SEEKING PROCESS
Throughout this dissertation, I have argued that inconsistent findings in
previous research might be explained by taking the role of various self-
208 CHAPTER 6
motives into account. This hypothesis was tested in a series of empirical
studies examining two previously unresolved issues, namely (a) the
inconsistent relationship between uncertainty and feedback-seeking and (b)
the much debated question whether people prefer favorable feedback or
confirming feedback.
First, a laboratory and a field study (Chapter 3) were conducted to shed more
light on the inconsistent relationship between uncertainty and feedback-
seeking. In both studies, we found a curvilinear relationship between
uncertainty and feedback-seeking. Students and employees sought feedback
when they were highly uncertain and when they were highly certain,
suggesting that both self-assessment and self-verification strivings might
motivate feedback-seeking behavior. This finding is consistent with recent
research on self-motives showing that different and opposite motives may be
simultaneously activated (Bernichon et al., 2003; Morling & Epstein, 1997;
Sedikides, 1993; Swann, Pelham, & Krull, 1989). Our hypothesis that the
activation of these self-motives might be regulated by individual difference
variables, received partial support. Results suggested that people with a high
certainty orientation were more driven by self-verification strivings as they
sought more direct feedback when certainty was high as compared to people
with a low certainty orientation.
Second, previous research was inconclusive regarding whether people prefer
favorable feedback or confirming feedback. An in-depth look on this
unresolved issue was taken in two studies (Chapter 4) examining people’s
reactions to feedback about their performance on an in-basket exercise. On
the basis of the self-motives framework, prior certainty was proposed as a
moderator of feedback reactions. It was expected that people would prefer
self-verifying (confirming) feedback about highly certain competencies and
self-enhancing (favorable) feedback about uncertain competencies.
However, this hypothesis was not supported. Our results showed that people
were especially satisfied with favorable feedback and reported higher
acceptance and utility of favorable feedback. This means that feedback
GENERAL CONCLUSIONS 209
reactions were for the most part dominated by self-enhancement strivings,
regardless of prior certainty. Our analyses indicated that self-verification
strivings were also activated in participants’ feedback reactions, but to a
much lesser extent than self-enhancement strivings. Thus, the results of these
studies also pointed to the simultaneous activation of two different self-
motives in the feedback process. Our results further suggested that
inconsistent findings in previous research on feedback reactions might also
be due to the use of inappropriate statistical procedures and different
research paradigms.
In sum, research targeting the second objective increased understanding of
some unresolved issues in previous research by shedding additional light on
the key role of self-motives in guiding feedback preferences. The common
finding throughout the four empirical studies was that different self-motives
are simultaneously activated during the feedback process and that feedback
recipients’ behavior and responses are guided by the interplay of these self-
motives.
OBJECTIVE 3: UNDERSTANDING AND ENHANCING THE FEEDBACK -
PERFORMANCE RELATIONSHIP
Indirect Evidence
The review (Chapter 1) showed that feedback-seeking is not always
positively related to performance, in contrast to the dominant assumption
that feedback-seeking is instrumental for improving performance (Ashford &
Cummings, 1983). In the theoretical outline, we argued that one explanation
for these counterintuitive results might be that employees are not always
seeking feedback to improve themselves. That is, sometimes people seek
feedback because they want to hear good news, they want confirmation of
their self-views, or they just want to know how they are doing. When people
are looking to satisfy these self-enhancement, self-verification, or self-
assessment needs in the feedback process, it is not very likely that the
210 CHAPTER 6
obtained feedback information will be used for performance improvement.
Across the empirical studies of this dissertation, we obtained ample support
for this hypothesis. In the empirical study of Chapter 1, we found that people
sought more feedback about non-modifiable competencies than about
modifiable competencies (self-assessment). In the laboratory study in
Chapter 2, results showed that people often seek feedback about
competencies that are already held with high certainty (self-verification).
Furthermore, additional analyses revealed that people sought more feedback
about their best competencies as opposed to their worst competencies (self-
enhancement). The field study in Chapter 2 also showed that people
frequently sought feedback even when they experienced little uncertainty
about their performance in the organization (self-verification). Finally, the
studies in Chapter 3 indicated that people did not accept negative feedback
and did not intent to use it in the future (self-enhancement). Together, these
findings demonstrate that several motives other than the self-improvement
are activated during the feedback process. As a result of the activation of
these motives, employees exhibit a number of behaviors and responses
towards feedback that hold little instrumental value for performance
improvement and may even impair performance. In sum, although the
relationship with performance was not directly assessed in these studies, the
observed results offer a likely explanation for the finding that feedback does
not always lead to performance improvement.
Direct Evidence
As noted, the inconsistent relationship between feedback-seeking behavior
and performance echoes a more fundamental problem in the feedback area,
namely that there is no general principle that can predict the effectiveness of
feedback interventions (DeNisi & Kluger, 2000; Kluger & DeNisi, 1996,
1998). To increase knowledge on the relationship between feedback and
performance, a final empirical study (Chapter 5) was conducted directly
targeting performance improvement on a web-based in-basket exercise.
Participants in a feedback elaboration condition were required to elaborate
GENERAL CONCLUSIONS 211
on feedback about performance on the first trial of the exercise. We found
that performance on the second trial of the in-basket exercise improved more
when people elaborated on feedback messages as compared to a control
condition where feedback was given without requesting elaboration. Results
further showed that performance improvement was due to the elaboration of
the feedback message as performance did not improve when people were
requested to elaborate on their performance without receiving feedback.
These results indicate that elaboration of feedback may be an important
facilitating condition in the feedback process and suggest that the level of
cognitive processing of feedback may play a key role in determining the
effectiveness of feedback interventions.
As put forward in the third objective, the empirical studies of this
dissertation increased the current understanding of the relationship between
feedback and performance and point to several avenues for enhancing the
effects of feedback on performance.
CONTRIBUTIONS, LIMITATIONS, AND RESEARCH OPPORTUNITIES
FROM A THEORETICAL PERSPECTIVE
A first important theoretical contribution for the study of feedback-seeking
behavior is that this dissertation systematically listed the various antecedents
affecting feedback-seeking behavior, evaluated their effectiveness and
identified several inconsistencies concerning these antecedents. A new
theoretical model based on self-motives research in social psychology was
proposed in lieu of the traditional resource-based perspective on feedback-
seeking behavior. By framing previously studied antecedents within this
alternative framework, a plausible explanation was provided for the
observed inconsistencies. On the whole, the empirical studies of this
dissertation supported our central theoretical proposition that motives other
than uncertainty reduction are important in guiding feedback-seeking
212 CHAPTER 6
behavior and that existing inconsistencies can be better understood in light
of these motives. Hence, the insights provided by this dissertation contribute
to a better theoretical understanding of the feedback-seeking process in
organizations. Yet, results also showed that the interplay of the self-motives
is very complicated. For instance, we found that feedback reactions were in
essence guided by the self-enhancement motive, but that self-verification
strivings were simultaneously activated to a certain extent. Inferring motives
from behaviors is famously difficult (e.g., Freitas, Salovey, & Liberman,
2001; Tetlock & Levi, 1982). Accordingly, a major challenge for future
feedback-seeking research is to establish to which extent and under which
conditions each self-motive determines employee behavior and responses
towards feedback. Till now, only two studies have examined how motives
work in concert to predict feedback-seeking (Levy, Albright, Cawley, &
Williams, 1995; Tuckey, Brewer, & Williamson, 2002). Given the current
limited knowledge about the motivational basis of feedback-seeking
behavior, laboratory studies specifically designed to keep possible
confounding variables under control seem the most appropriate research
strategy to disentangle the effects of different motives on feedback-seeking.
This dissertation also contributes to broader feedback intervention theories
by uncovering the important role of different cognitive processing modes of
the feedback recipient in the feedback process. When people are required to
use a thoughtful feedback processing strategy, feedback interventions proved
to be more effective in improving performance. This finding should
encourage researchers to conduct more studies considering factors that might
stimulate elaborate cognitive processing of feedback. Dual process research
has found that people engage in thoughtful processing when they are highly
motivated to do so and when they have the appropriate cognitive capacity
(Smith & DeCoster, 2000). Hence, future research should examine variables
that might encourage the motivation to think about feedback (e.g., by
emphasizing personal relevance, desire for accuracy, social goals, scarcity of
feedback or task accountability) and variables that open up cognitive
abilities for elaborate processing (time availability, feedback format,
GENERAL CONCLUSIONS 213
elimination of distracting factors, task knowledge and experience, and
general mental ability).
A third important theoretical contribution is that we examined feedback-
seeking across different performance dimensions (competencies). As noted
before, almost all previous feedback-seeking studies have looked at
feedback-seeking behavior about general job performance. However, in
recent years, it has become apparent that the nature of job performance is
multi-dimensional (Campbell, McCloy, Oppler, & Sager, 1993; Tett,
Guterman, Bleier, & Murphy, 2000). Very different sets of behaviors might
define effective performance in the same job, depending on what goals and
values are emphasized in the organization and how the work is organized
and structured (Murphy, 1994; Murphy & Shiarella, 1997). One implication
of the multi-dimensional nature of performance for feedback research is that
more strategies should be identified to direct feedback-seeking behavior
towards performance dimensions that are valued in an organization. For
instance, one of the hallmarks of the changing nature of performance is the
increasing shift to the use of teams in organizations. An important question
is whether organizations can encourage employees to seek feedback about
team performance instead of individual performance by emphasizing the
importance of team work (e.g., by rewarding team performance). A second
implication is that feedback research should also pay attention to the multi-
dimensional nature of performance when examining the effectiveness of
feedback interventions. Till now, almost all studies have looked at the effect
of feedback interventions on task performance (Kluger & DeNisi, 1996),
including our own empirical study (Chapter 5). However, recent research
indicates that job performance can be described by three broad performance
components. These components include task performance, citizenship
performance, and counterproductive performance (Rotundo & Sackett,
2002). Future feedback research might benefit from looking at the effects of
providing feedback on citizenship performance and counterproductive
performance. The self-motives framework might also be fruitful in guiding
these studies. For example, students reported more destructive intentions
214 CHAPTER 6
after receiving negative feedback, which is in line with the self-enhancement
motive (Van de Vliert, Shi, Sanders, Wang, & Huang, 2004; for a theoretical
argument, see O’Leary-Kelly & Newman, 2003).
Fourth, the empirical study in Chapter 5 was one of the first studies to
empirically document one of the central assumptions of all theoretical
feedback process models (Ilgen, Fisher, & Taylor, 1979; Ilgen & Davis,
2000; Fedor, 1991; Taylor, Fisher, & Ilgen, 1984), namely that cognitive
responses to feedback (feedback acceptance, and feedback utility) predict
subsequent performance. Notwithstanding its key importance in the feedback
process, only one recent study has examined and supported this assumption
(Kinicki, Prussia, Wu, & McKee-Ryan, 2004). Whereas Kinicki et al. found
support for the importance of cognitive responses in predicting job
performance a year after employees’ performance appraisal, the present
study was the first to demonstrate that cognitive responses (feedback
acceptance, and feedback utility) are also predictive of short-term task
performance. However, a limitation of this dissertation concerning feedback
reactions should also be noted. In the self-motives model that was proposed
in the first chapter, we argued that feedback reactions could increase
understanding of the relationship between feedback-seeking and
performance. We found support for the role of feedback reactions in
predicting task performance, but did not closely examine the relationship
between feedback-seeking and feedback-reactions. We had data available on
both feedback-seeking about in-basket performance (first study of Chapter 3)
and feedback reactions two weeks later (first study of Chapter 4) of a sample
of 126 students. However, additional analyses revealed no relationship
between initial feedback preference and subsequent feedback reactions.
Similarly, Kluger and Adler (1993) reported no differences in task
motivation and performance if feedback was requested by participants
themselves or provided without request. Further research is needed to
examine under which conditions the proposed relationship between
feedback-seeking and feedback reactions in the self-motives model of the
feedback-seeking process receives support.
GENERAL CONCLUSIONS 215
FROM A METHODOLOGICAL PERSPECTIVE
The studies conducted in this dissertation also make a number of
contributions to a methodologically more sound study of the feedback
process. First, in contrast to traditional feedback-seeking studies which have
relied almost exclusively on between-person approaches, we adopted a
within-person design to examine feedback-seeking behavior in two studies
(Chapter 2 and 3). Whereas the traditional approach to feedback-seeking is
concerned with the question “How does feedback-seeking behavior varies
across persons”, the current approach seeks an answer to the question “How
does feedback-seeking behavior varies within persons”. The distinction
between the use of between-subjects or nomothetical approaches and within-
subjects or idiographic approaches in the study of human behavior is not
futile and has been subject to debate for decades (e.g., Allport, 1937,
Eysenck, 1954). In recent years, a general consensus has been reached that
these different levels of analysis are both legitimate avenues of study and are
in fact both necessary for developing a thorough understanding of human
behavior (Pelham, 1993; Rosenzweig & Fisher, 1997). For instance, a recent
study showed that at least half of the statistical information derived from
idiographic ratings of personal constructs was unique when compared to
ratings of the nomothetic Big Five items (Grice, 2004). Thus, as suggested
by our own empirical studies, a more complete understanding of feedback-
seeking behavior may be achieved by taking a within-subjects approach .
A second important methodology-oriented contribution of this dissertation
pertains to the statistical approach used for analyzing reactions to feedback.
Previous studies in both organizational and social psychology have used
difference scores to represent the congruence between feedback scores and
self-appraisals on feedback reactions. Typically, this difference score is then
treated as a concept in its own right and the impact of this concept on
feedback reactions is examined. Despite their widespread use, difference
scores suffer from a number of methodological problems, being one of the
most important that difference scores confound the impact of the component
216 CHAPTER 6
parts of the difference score on the dependent variable. These problems can
be avoided with polynomial regression analyses, which uses components of
difference scores supplemented by higher-order terms to represent the
hypothesized congruence effects (Edwards, 1994, 2001). The empirical
studies in Chapter 4 were the first to use polynomial regression procedures
for studying congruence in feedback research. The obtained results highlight
the importance of using the appropriate statistical procedures in feedback
research. When traditional difference scores were used, support for self-
verification theory was found, whereas polynomial regression results
indicated that actually, for the most part, self-enhancement theory was
supported. These findings offer a likely explanation for the inconsistencies
that were observed in previous research. Many of the alleged self-
verification strivings may represent concealed self-enhancement effects. In
this vein, it would be interesting to conduct an extensive re-analysis of
previous studies examining feedback reactions using polynomial regression
procedures instead of difference scores. This finding has important
methodological implications for the study of self-verification processes in
different domains of psychology. The essence of self-verification theory is
that people prefer information that is congruent with their self-conceptions.
Thus, one way or the other, analyses always come down to comparing self-
ratings with other-ratings. Recent research keeps on using difference scores
to analyze self-verification processes (Chen, Chen, & Shaw, 2004; Swann,
Kwan, Polzer, & Milton, 2003), whereas our findings indicate that the use of
difference scores may sometimes lead to erroneous conclusions.
A third methodological contribution is that we developed and used a web-
based in-basket exercise to examine feedback processes. This exercise
placed participants in a simulated organizational environment where they
were asked to take the role of an actual manager in responding to emails.
The management simulation enabled us to take an in-depth look at feedback-
seeking decisions, feedback reactions and performance improvement in the
feedback process while keeping possible confounds under control and thus,
increasing the internal validity of the results obtained (Sackett & Larson,
GENERAL CONCLUSIONS 217
1991). For instance, in field studies researchers have typically little control
about perceived feedback-seeking costs. This makes it difficult to draw
strong conclusions about motives underlying feedback-seeking as the
intention to seek feedback might have been seriously curtailed by high costs
associated with feedback-seeking. In the present management simulation,
feedback-seeking took place in a private setting where feedback-seeking
costs where minimal, which provides a clear picture of motives underlying
feedback-seeking. Furthermore, this management simulation makes it
possible to manipulate specific independent variables before the feedback
process (e.g., lay beliefs in Chapter 1) and even in the middle of the
feedback process (e.g., elaboration in Chapter 5), and draw conclusions
regarding their impact on a range of variables (feedback-seeking, feedback
reactions, task performance). Thus, the management simulation that was
developed in this dissertation should contribute to more process-oriented
research of feedback-seeking and feedback interventions, as has been
strongly called for in previous feedback research (e.g., Levy et al., 1995). Of
course, the use of laboratory simulations in organizational behavior research
also has some drawbacks as they might be criticized for their vulnerability to
external validity problems. Therefore, it is recommended that both students
and working employees participate in these studies as was the case in
Chapter 4 and 5. It is also advisable to examine whether the results obtained
in the laboratory generalize to more realistic field settings (Dobbins, Lane, &
Steiner, 1988; Sackett & Larson, 1991). For instance, this research strategy
was adopted in study 1 and 2 of Chapter 3, where the same hypotheses were
tested in a laboratory and a field setting, using different research approaches,
and generalizibility of the findings was supported.
Apart from these methodological contributions, two important limitations
should be noted. First, we did not directly measure self-motives in the
empirical studies, but instead used the self-motives framework as theoretical
underpinnings to guide the choice of relevant antecedents and moderators.
Thus, the activation of the self-motives was inferred from observed
behaviors and responses, which makes some of the conclusions about the
218 CHAPTER 6
role of self-motives in the feedback process somewhat tentative. In two
studies, not included in this dissertation (Anseel, 2004), we tried to measure
the self-motives by using an existing questionnaire (Stark & Sommer, 2000)
and by developing a new questionnaire. Although results showed that all
self-motives were significantly correlated to direct and indirect feedback-
seeking (p < .01), the scales measuring feedback-seeking motives were
highly correlated. Especially, the self-enhancement and self-verification
motives were difficult to discern (r > . 80), suggesting that these implicit
motives may be difficult to measure using questionnaires. Apart from using
experimental designs, future research may explore other research strategies
to examine the role of feedback-seeking motives, for instance by using diary
studies or think-aloud protocols.
Second, the narrative review that we conducted in the first chapter may be
criticized on subjectivity and impreciseness grounds. Although we made
efforts to prevent these threats by summarizing all reported zero-order
correlations in the appendix, a more objective and accurate strategy to
review previous feedback-seeking studies would be to conduct a meta-
analysis. A meta-analysis might shed additional light on the observed
inconsistencies by examining whether these inconsistencies stem from either
sampling (and other) artifacts or from real phenomena that require
theoretical explanations. A particularly promising route for future research
would be to test the basic hypotheses of the self-motives model we proposed
by combining the principles of psychometric meta-analysis and structural
equation modeling in a theory-driven meta-analysis (Viswesvaran & Ones,
1995).
FROM A PRACTICAL PERSPECTIVE
On the basis of the comprehensive review provided in Chapter 1, we found
that past research examining individual antecedents of feedback-seeking
behavior yielded several important insights. These insights are also valuable
GENERAL CONCLUSIONS 219
to practitioners in organizations as they suggest a number of practical
recommendations for improving feedback processes in organizations. In
addition, the empirical studies in this dissertation yielded insights which
have important practical implications concerning individual antecedents of
feedback-seeking behavior. These practical recommendations are
summarized below. We indicated the numbers of the empirical studies on
which each of these practical recommendations are based in superscript.
These studies can be retrieved in the Appendix of Chapter 1. When
recommendations were supported in our own empirical studies, the
corresponding chapter (CH) is also indicated in superscript.
1. Set specific, unambiguous and realistic goals for employees.
Design feedback systems in this way that employees can track their
progress towards their goals.4, 12, 29, 37, 45
2. In particular, encourage employees with low performance
expectations to seek feedback. Emphasize that errors and mistakes
are accepted as a normal part of the learning process and encourage
continuous development.1, 3, 4, 15, 25, 31, 33, 34, 42, 43, CH 3
3. In times of uncertainty (crisis, changes, socialization periods),
open up the feedback channels and increase the feedback flow. This
makes it possible for employees to seek feedback on one’s own
initiative. Specifically encourage feedback-seeking during
organizational newcomers’ socialization period by means of special
orientation programs, social events and mentoring.5, 6, 11, 14, 17, 32, 47, CH
3
4. Make sure to provide additional feedback to employees that (a)
are good at dealing with uncertainty, (b) are self-confident and (c)
already have extensive job experience, even when they do not seek
feedback themselves (any longer), (d) tend to seek self-verifying
feedback and have a high certainty orientation.4, 6, 10, 16, 26, 34, 39, 43, CH3
220 CHAPTER 6
5. Utilize learning goal orientation as a criterion for selecting
applicants for complicated and rapid changing jobs. Design training
programs in order to develop learning goal orientation of employees
(e.g., by changing the attributions employees make about success
and failure). Use developmental performance appraisal systems in
which behavioral feedback is provided instead of feedback relative
to others. Map goal orientations of employees individually and
customize feedback systems.15, 26, 28, 34,35, 44, 45, 47
6. Increase understanding of employees’ implicit beliefs about the
importance and modifiability of the different performance
dimensions. Communicate which performance dimensions are
valued in the organization and set out transparent management
policies on the basis of these performance dimensions (e.g.,
performance appraisal format, reward structures).CH 2
A second series of practical implications can be derived from our review
(Chapter 1) of research examining contextual antecedents of feedback-
seeking behavior. These results are particularly interesting from a practical
point of view because they stipulate strategies that organizations might adopt
to create rich feedback environments wherein employees are encouraged to
seek feedback themselves. Again, we summarized practical
recommendations on the basis of the studies included in the Appendix of
Chapter 1.
7. Use information technology and communication media in order
to encourage feedback-seeking for example by registering, tracking,
and displaying performance statistics. Develop feedback systems so
that feedback can be sought and given by face-to-face
communication. Provide alternative sources for privately seeking
feedback (for example email, memo’s, helpdesk, intranet,
handbooks, FAQ).2, 3, 7, 19, 23, 28, 34, 43
GENERAL CONCLUSIONS 221
8. Develop positive communication norms by making clear that all
employees seek feedback. Identify opinion leaders among
employees and train them to become role models in feedback-
seeking behavior. Encourage and train top-level managers to exhibit
feedback-seeking behavior in presence of their subordinates, thus
performing the behavior that will be emulated by others.7, 17, 42, 48
9. Train managers in different strategies for encouraging feedback-
seeking for example by showing consideration and supportiveness,
by concealing a bad mood, and using a transformational leadership
style. 2, 12, 15, 21, 24, 26, 29, 33, 40, 48
10. Make expatriate managers aware of cross-cultural differences in
feedback-seeking patterns. Minimize face-loss costs in collectivistic
cultures by making feedback available through informal and private
channels.13, 22, 30
11. Design organizations so as to that job roles, responsibilities and
expectations are clearly defined for the employees.11, 41
Third, in the empirical studies conducted in Chapter 4 and Chapter 5, we
highlighted the important role of feedback reactions in the feedback process.
In two studies, we found that in general people tend to embrace favorable
feedback but reject unfavorable feedback. This finding is especially
noteworthy in the light of the results in the last empirical study showing that
feedback acceptance and feedback utility predicted task performance. The
last study also identified an important facilitating condition for feedback
interventions by demonstrating that eliciting people to elaborate upon
feedback messages leads to higher performance improvement. Together,
these findings suggest some additional recommendations.
12. Consider how delivery of feedback impacts the perceived
accuracy and utility of feedback. Train managers in instrumental
leader behaviors (e.g., path-goal facilitation) that might improve
222 CHAPTER 6
perceived accuracy and desire to respond. Spend time and resources
to improve the accuracy of the appraisal system. Inform employees
on the validity and accuracy of appraisal systems.
13. Help employees interpret and react to negative feedback.
Personal coaches, feedback workshops and follow-up sessions may
be helpful in focusing on both positive and negative feedback,
motivating employees in dealing with inconsistencies, and
formulating plans for improvement.
14. Ensure that deep and thoughtful cognitive processing of
feedback messages takes place during feedback interventions. For
instance, encourage employees to process feedback by providing
ample processing time, organizing feedback workshops, or
developing “feedback modules” in the feedback report.
Although the web-based in-basket exercise was mainly developed for
research purposes, this management simulation has also shown to have great
practical value from an employee’s perspective. First, the use of web-based
assessment applications has rapidly grown in the last decade (Bartram, 2000;
Lievens & Harris, 2003). In contrast to this explosive growth, applicants are
often not yet familiar with these recent technological developments in testing
and assessment and often feel uneasy with the prospect of having to
complete web-based assessment instruments. The management simulation
that was developed in the current dissertation, should be particularly useful
in training programs that are designed to accustom and prepare applicants for
future computerized and web-based assessment procedures. Second, the last
decade there has grown a strong emphasis on employees’ responsibility in
developing and directing their own careers. In these protean careers, the
person, not the organization is, in charge. The person’s core values are
driving career decisions, and the main success criteria are subjective
psychological issues (Hall, 2004). In order to be able to take their careers in
own hands, employees have to gain knowledge on their own strengths and
GENERAL CONCLUSIONS 223
weaknesses. In this context, the web-based management simulation should
be a practical and easily accessible self-assessment instrument for assisting
people in taking important career decisions as it immediately provides
realistic and useful feedback on four basic managerial competencies
(Decisiveness, Problem Awareness, Coordinating, and Information
Management). The practical value of this instrument is probably best
reflected in the fact that the Flemish Public Employment Service (VDAB)
recently started to use the management simulation in applicant training
programs and for career assessment and career counseling purposes .
Finally, it should be noted that the practical recommendations that we
summarized are limited to organizational practices. However, the obtained
findings might also have important implications that go beyond
organizational applications. Feedback interventions are among the most used
mechanisms to enhance learning and development across a wide range of
settings. For instance, feedback processes have been found to be of key
importance in learning sport skills to athletes, cognitive skill development in
children’s education, stimulating healthy behavior in health care programs,
and for the treatment of depression in clinical settings. We envision that the
insights from this dissertation may have practical relevance for all settings
where seeking, giving, and receiving feedback are an essential part of the
development process.
224 CHAPTER 6
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