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Is Negative Feedback Good or Bad for Creativity? The Role of the Direction of Feedback Flow

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Negative feedback alerts recipients to a creativity-standard gap and thus may offer an opportunity to improve creativity. However, the existing theories and empirical evidence about the relationship between negative feedback and recipient creativity are contradictory. The literature contains evidence of positive, negative, and null relationships. Our research aims to resolve this inconsistency by investigating the role of the direction of feedback flows, which include bottom-up, top-down, and lateral flows. Across two studies – one quasi-field experiment and one laboratory experiment – we found that the direction of feedback flow determined the nature of the relationship between negative feedback and recipient creativity via two distinct mechanisms: task-processes and meta-processes. Negative feedback increased recipient creativity in the bottom-up feedback flow (from followers to supervisors) because it heightened recipients’ focus on task-processes, whereby recipients focus on the generation of better task strategies to close the creativity-standard gap. In contrast, in the top-down (from supervisors to followers) or lateral (between peers) feedback flows, negative feedback heightened recipients’ focus on meta-processes – which refer to the psychological state in which recipients feel threatened by negative feedback – and thus hindered recipient creativity.
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Does Negative Feedback Benefit (or Harm) Recipient Creativity? The Role of the Direction
of Feedback Flow
Yeun Joon Kim
University of Cambridge
y.kim@jbs.cam.ac.uk
Junha Kim
The Ohio State University
kim.7333@osu.edu
Authors’ notes. We wish to thank our editor Jill Perry-Smith and three anonymous reviewers for
their insightful and constructive feedback. We also thank Angelo DeNisi, Matthew Feinberg, Soo
Min Toh, Jacob Hirsh, Geoffrey Leonardelli, Andrew Hayes, and Sojin Park for their
constructive feedback. Correspondence concerning this article should be addressed to Yeun Joon
Kim, Judge Business School, University of Cambridge. e-mail: y.kim@jbs.cam.ac.uk.
Does Negative Feedback Benefit (or Harm) Recipient Creativity? The Role of the Direction
of Feedback Flow
Abstract
Negative feedback alerts recipients to a creativity-standard gap and, thus, may offer an
opportunity to improve creativity. However, existing theories and empirical evidence are
contradictory. The literature contains evidence of positive, negative, and null relationships
between negative feedback and recipient creativity. The goal of our research is twofold: first, to
organize the contradictory theories under a comprehensive theoretical framework, and second, to
resolve the inconsistency between negative feedback and recipient creativity. Across two studies,
i.e., a quasi-field experiment and a laboratory experiment, we found that the direction of
feedback flow determined the nature of the relationship between negative feedback and recipient
creativity via two distinct mechanisms: task-processes and meta-processes. Negative feedback
increased recipient creativity in the bottom-up feedback flow (from followers to supervisors)
because it heightened the recipients’ focus on task-processes, whereby the recipients focused on
the generation of better task strategies to close the creativity-standard gap. In contrast, in the top-
down (from supervisors to followers) or lateral (between peers) feedback flows, negative
feedback heightened the recipients’ focus on meta-processes, i.e., a psychological state in which
recipients feel threatened by negative feedback, and thus, hindered recipient creativity.
KEY WORDS: Creativity, negative feedback, direction of feedback flow, feedback intervention
theory
Employee creativity – defined as the production of ideas that are both novel and useful
(Amabile, 1983; Oldham & Cummings, 1996) – is a foundation of organizational success
(Anderson, Potočnik, & Zhou, 2014). It allows organizations to continually produce innovative
products and keep them competitive in the market. Accordingly, understanding how to improve
employee creativity has been a longstanding preoccupation of management scholars (e.g.,
George, 2007; Perry-Smith, 2006). Since creativity involves a departure from the current ways of
thinking and behaving, employees often attempt to provide other organizational members with
negative feedback to create dissatisfaction with the status quo or the current levels of creativity
(Ilgen, Fisher, & Taylor, 1979). Negative feedback highlights problems with current creativity,
generating awareness of a gap between current creativity and the standards. Once the gap is
recognized, employees may be motivated to close the gap by improving their current creativity.
However, this argument has received limited empirical support. In fact, the evidence is
completely equivocal. Some scholars suggest that negative feedback has no direct effect on
recipient creativity (Fodor & Carver, 2000; George & Zhou, 2001), while others suggest that
negative feedback inhibits it (Ilies & Judge, 2005; Van Dijk & Kluger, 2011; Zhou, 1998). We
know of only three studies (Fang, Kim, & Milliken, 2014; Ford & Gioia, 2000; Vuori & Huy,
2015) that provide evidence to support that negative feedback might be positively associated
with recipient creativity. Such perplexing empirical evidence indicates that a basic question
remains unanswered, i.e., how and why does negative feedback influence creativity?
To answer this question, this research draws upon feedback intervention theory (Kluger &
DeNisi, 1996) to derive a parsimonious and coherent theoretical account of the link between
negative feedback and creativity. Feedback intervention theory argues that negative feedback
makes feedback recipients aware of the gap between their current level of creativity and the
standards (the creativity-standard gap) and that such awareness leads the recipients to engage in
one of two functionally opposite mechanisms in response to the negative feedback. The first
mechanism is task-processes, where recipients make constructive improvements by engaging in
the process of generating better task-strategies. They identify problems with their current
behavior in creativity tasks, design more useful and novel strategies for their creativity tasks and
implement the strategies. The second mechanism is meta-processes, which refer to the
psychological state in which recipients feel threatened by negative feedback. Feedback recipients
who engage in meta-processes feel that their ego, or self-concept, is threatened by the negative
feedback, deterring them from experimentations and creative attempts to improve their creativity.
Despite its usefulness in illustrating why negative feedback is inconsistently related to recipient
creativity, a notable limitation of feedback intervention theory is that it does not elaborate on
when negative feedback recipients attend to either of the two processes.
The main objectives of this paper are to organize the inconsistent theories and empirical
findings under the two mechanisms – task-processes and meta-processes – and to resolve the
inconsistency between negative feedback and recipient creativity by introducing an important,
but neglected, boundary condition – i.e., the direction of feedback flow. The direction of these
flows include bottom-up (from followers to supervisors), top-down (from supervisors to
followers), and lateral (from peers to peers). We suggest that in the bottom-up feedback flow,
negative feedback increases recipient creativity through task-processes, whereas in the top-down
and lateral feedback flows, negative feedback decreases recipient creativity through meta-
processes. In organizations, supervisors have asymmetric control over valuable organizational
resources, such as monetary rewards, promotions, training opportunities, and budgets and
materials for completing tasks. Followers do not have such control, and their supervisors
determine their access to organizational resources. This power asymmetry often causes these two
parties to have completely different psychological mindsets (Keltner, Gruenfeld, & Anderson,
2003; Magee & Galinsky, 2008). Researchers have found that power asymmetry leads the
powerful (e.g., supervisors) to be approach-oriented (versus inhibition-oriented) toward negative
evaluations by the powerless (e.g., followers), while the powerless become inhibited by negative
evaluations by the powerful (Keltner et al., 2003). In addition, the powerful tend to maintain high
levels of task-focus in the face of task-related criticisms and care less about their social
relationships with feedback senders, whereas the powerless behave in an opposite way (Galinsky,
Magee, Gruenfeld, Whitson, & Liljenquist, 2008; Smith, Jostmann, Galinsky, & Van Dijk, 2008;
Steele, Spencer, & Aronson, 2002). Based on these findings, we expect that negative feedback
increases recipient creativity via task-processes in the bottom-up feedback flow and decreases
recipient creativity via meta-processes in the top-down feedback flow.
The relationship between the feedback sender and the recipient in the lateral feedback
flow is qualitatively different from that in the bottom-up and top-down feedback flows. A peer
relationship does not involve differential social power. Instead, this relationship is characterized
by rivalry, or competition, given that organizational resources (e.g., promotions and pay
increases) are limited. Thus, employees strive to stand out among their peers and become
increasingly concerned about the possibility of lagging behind them (Bandura, 1977; DeNisi,
Randolph, & Blencoe, 1983; Festinger, 1962). Peer competition sometimes produces positive
organizational outcomes (for a review, see Birkinshaw, 2001). However, regarding negative
feedback between peers, evidence has shown that the competitive and non-hierarchical nature of
a peer relationship leads employees to interpret lateral negative feedback as an attempt to
downplay their ability and an attack on their self-esteem. For this reason, those who receive
lateral negative feedback reported that they feel threatened, distracted, and discouraged (Brett &
Atwater, 2001; DeNisi et al., 1983; Druskat & Wolff, 1999; Rogers & Feller, 2016). That is,
negative feedback from peers distracts recipients from creativity tasks – low task-processes – and
causes them to pay greater attention to meta-processes, which reduces their creativity.
The current research tests these hypotheses in two studies, i.e., a quasi-field experiment at
a Korean company and a laboratory experiment at a large North American university. By
demonstrating consistent support for our hypotheses across the two studies, our research makes
important contributions to the literature. We not only resolve the inconsistency of the relationship
between negative feedback and recipient creativity but also integrate several theoretical
arguments, variably applied in past research, under two essential mechanisms – task-processes
and meta-processes. In addition, we push the boundary of feedback intervention theory by
providing an important, albeit neglected, boundary condition, i.e., the direction of feedback flow,
which determines the mechanisms underlying the relationship between negative feedback and
creativity. Figure 1 depicts our theoretical framework.
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Insert Figure 1 about here
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THEORETICAL DEVELOPMENT
Definition of Negative Feedback
Feedback refers to information regarding whether one’s level of creativity meets the
organizational standard(s). When feedback provides information indicating a creativity-standard
gap, i.e., a discrepancy showing that the demonstrated level of creativity is below the accepted
standard, the feedback is considered negative. We investigate negative feedback in relation to
recipient creativity for two reasons. First, from a theoretical perspective, negative feedback has
strong potential to contribute to recipient creativity. If the feedback recipients are receptive,
negative feedback identifies the insufficiency in their current level of creativity and creates
dissatisfaction where none previously existed. This dissatisfaction is important because creativity
is often derived from the rejection of previous thought patterns and behavior, and negative
feedback informs feedback recipients that their current levels of creativity should be improved in
more novel and useful ways (Csikszentmihalyi, 1997; George, 2007; Zhou & George, 2001).
Second, negative feedback is prevalent in organizations and a primary means used by managers
to influence employee behavior and performance (Ilgen et al., 1979). For example, according to
Zenger and Folkman’s (2017) study of 328 managers and approximately 4,200 followers (13
followers per manager on average), the managers perceived themselves as effective leaders when
they offered criticism or negative feedback, and thus, they frequently offered negative feedback
to followers to induce meaningful changes in the followers’ behavior and performance. This led
the followers to perceive that negative feedback is pervasive in their organizations. Considering
its utility for recipient creativity and the pervasiveness in organizations, we believe that a
systematic investigation of negative feedback and its effects on recipient creativity is important.
In what follows, we review past research on the relationship between negative feedback and
recipient creativity and identify both theoretical and empirical inconsistencies in this
relationship.
Inconsistent Theories and Empirical Evidence on Negative Feedback and Creativity
Our comprehensive review of past research on the link between negative feedback and
recipient creativity revealed perplexing results; past studies have used a variety of contradicting
theories and have reported a mix of positive, negative, and null relationships. Table 1
summarizes the contexts and results of past studies.
1
Researchers who found a positive relationship between negative feedback and creativity
shared a similar perspective (Fang et al., 2014; Vuori & Huy, 2015). These authors argued that
negative feedback creates dissatisfaction with their current level of creativity. This dissatisfaction
in turn incentivizes feedback recipients to look closely at the processes involved in creativity
tasks in order to identify opportunities for improvement and fill the gap by implementing better
task strategies. In contrast, the researchers who found a negative relationship between negative
feedback and recipient creativity focused on the perceived threat resulting from negative
feedback (Van Dijk & Kluger, 2011; Zhou, 1998). This perspective suggests that negative
feedback threatens recipients’ core beliefs about themselves, their abilities, and their status in the
eyes of others and that the experience of a threatened self-concept reduces creativity because
threatened recipients disengage from any experimentation and creative attempts to improve their
creativity.
Both of these theoretical perspectives reveal fundamental aspects of the negative
feedback-creativity relationship, and therefore, we strive to integrate the two perspectives into a
broader framework. To accomplish this integration, we utilize feedback intervention theory
(Kluger & DeNisi, 1996), which parsimoniously incorporates the two theoretical perspectives.
Reconciling the Inconsistent Negative Feedback-Creativity Relationship
The primary theoretical innovation of feedback intervention theory (Kluger & DeNisi,
1996) lies in the introduction of two separate processes – task-processes and meta-processes –
that are used to explain how a feedback recipient responds to negative feedback. Task-processes
1
Two studies in this section (Fodor & Carver, 2000; Zhou, 1998) did not report the main effect of negative feedback
on creativity. Thus, we manually calculated the effect using the means, standard deviations, and degrees of freedom
reported in the paper.
refer to the mechanisms by which feedback recipients attempt to improve their current creativity
by generating better, diverse strategies for their creativity tasks. In creativity tasks, the most
common pitfall is using existing or routinized task strategies. Employees who work on creativity
tasks tend to overly rely on existing task strategies, or task routines, and they are less inclined to
experiment with new task strategies. This is because employees routinize existing task strategies
over time through repeated exposure (Kilduff, 1993; March, 1991; March & Simon, 1958).
Employees’ tendency to stick to existing task strategies could increase their routine performance
because it ensures that employees reliably perform their routine tasks without errors. However,
this tendency is detrimental to creativity because creativity often requires deviation from routines
and the status-quo (Anderson et al., 2014; Zhou & George, 2001). Indeed, the evidence has
shown that employees increased their creativity by experimenting with new ways of performing
their tasks, while sticking to existing task strategies hampered their creativity (Anderson et al.,
2014; Kim & Zhong, 2017; March, 1991). In other words, task-processes are essential
mechanisms for employee creativity. Task-processes are highly congruent with the theories used
in past research that found a positive relationship between negative feedback and creativity (e.g.,
Fang et al., 2014; Vuori & Huy, 2015).
In contrast, meta-processes refer to the mechanism whereby negative feedback threatens
recipients’ beliefs about their self-concept, their ability to perform creativity tasks, and their
social image perceived by feedback senders. Responding to negative feedback by attending to
meta-processes, recipients direct their attention toward the threatening consequences of negative
feedback. Specifically, recipients worry about how negative feedback affects the assessments of
their own ability (e.g., “Does this feedback suggest that I’m incompetent?”) or whether negative
feedback implies changes in the recipients’ important social relationships (e.g., “Does this mean
that my supervisor does not like me?”). This threatened mindset inhibits recipients from taking
risks by experimenting with creative ideas (Förster, Friedman, & Liberman, 2004; Friedman &
Förster, 2001; Kluger & DeNisi, 1996) and lowers the mental resources and cognitive capacity
that should be allocated to creative processes (see for a review, Byron, Khazanchi, & Nazarian,
2010). Thus, meta-processes prevent recipients from directly addressing the problems with their
current level of creativity and leave them in a threatened mindset, which in turn reduces their
creativity. Meta-processes are in line with the logic presented by the past research that found a
negative relationship between negative feedback and recipient creativity (e.g., Van Dijk &
Kluger, 2011; Zhou, 1998).
In summary, feedback intervention theory suggests that negative feedback has the
potential to both increase and decrease creativity via task-processes and meta-processes. Thus, it
is not surprising that past researchers reported contradictory empirical evidence on the
relationship between negative feedback and recipient creativity. Despite its usefulness in
understanding the inconsistent relationship, feedback intervention theory does not offer insight
into when negative feedback recipients adopt one of these two processes. Our research aims to
expand feedback intervention theory by investigating an important, albeit neglected, boundary
condition that channels negative feedback to creativity through task-processes and meta-
processes. We suggest that the direction of feedback flow is the sine qua non for understanding
the relationship between negative feedback and recipient creativity and resolves the
inconsistency in this relationship.
The Role of the Direction of Feedback Flow
We define the direction of feedback flow as the transfer of feedback from sender(s) to
recipient(s) where the two parties have the same or different organizational ranks. We argue that
the direction of feedback flow should not be isolated from feedback research because feedback
does not occur spontaneously in organizations. Feedback occurs within the social, organizational
contexts that create the basis of the evaluation standards. Employees try to meet the standards,
and evaluators rate employee creativity by considering the gap between demonstrated creativity
and the standards (De Stobbeleir, Ashford, & Buyens, 2011; Zhou, 2008). As a result, in a study
of feedback, it is necessary for researchers to specify the social and organizational contexts,
including the identities of the feedback sender(s) and recipient(s) (Zhou, 2008). By introducing a
novel concept – the direction of feedback flow – the current research specifies the social and
organizational context within which negative feedback flows and examines its influences on the
relationship between negative feedback and recipient creativity.
Specifically, we investigate three directions of feedback flow: bottom-up (from
followers to supervisors), top-down (from supervisors to followers), and lateral (from peers to
peers). Although the top-down feedback flow may be the most frequently observed direction,
organizations are beginning to realize the value of feedback that flows up the hierarchy and
feedback that flows laterally between employees at the same organizational rank (Antonioni,
1996; Brett & Atwater, 2001; DeNisi & Kluger, 2000). Nevertheless, a comprehensive and
systematic investigation on the roles of the direction of feedback flow is lacking in
organizational research. The majority of past research considered only top-down feedback (e.g.,
Fodor & Carver, 2000; George & Zhou, 2001; Zhou, 1998). A small minority of the research
looked at bottom-up feedback (e.g., Vuori & Huy, 2015; Ford & Gioia, 2000), and other research
did not specify the senders and recipients (e.g., Fang et al., 2014; Van Dijk & Kluger, 2011).
Interestingly, researchers who examined the top-down feedback flow generally found a negative
relationship between negative feedback and creativity, while those who investigated the bottom-
up feedback flow found a positive relationship. These results show the importance of the
direction of feedback flow as a boundary condition in the relationship between negative feedback
and creativity. We theorize that each direction of feedback flow determines a feedback recipient’s
focus – toward task-processes vs. meta-processes – and its subsequent effect on creativity.
Bottom-up and Top-down Negative Feedback Flows and Creativity
The bottom-up feedback flow. Research on social power provides a basis for
understanding how bottom-up and top-down feedback flows influence the relationship between
negative feedback and creativity. Social power refers to asymmetric control over valuable
resources, rewards, punishments, and outcomes (Keltner et al., 2003; Magee & Galinsky, 2008).
Differences in the hierarchical rank create a situation in which an employee at a higher rank
possesses social power over other employees at lower ranks; accordingly, manipulations of the
hierarchical rank have been frequently used to study social power and its effects (e.g., DeNisi et
al., 1983; Jordan, Sivanathan, & Galinsky, 2011).
Our research relies on the social power literature to suggest that the bottom-up feedback
flow enables negative feedback recipients (in this case, supervisors) to attend to task-processes
rather than to meta-processes. Regardless of their findings, the feedback researchers listed in
Table 1 acknowledged that negative feedback hurts recipients’ feelings to a certain degree, as it
criticizes some aspects of their current creativity. To utilize negative feedback constructively,
recipients should understand it strictly within the boundary of the tasks rather than expanding its
implications to personal or task-unrelated matters (e.g., concerning their image in the eyes of the
feedback sender). Research on social power has shown that supervisors may be able to do so
better than followers for several reasons. One major reason for this difference is that supervisors
tend to be more approach-oriented toward the dissenting, counter-attitudinal opinions provided
by their followers. Supervisors are aware that their followers generally cannot engender serious
social consequences (e.g., pay decreases and demotions) as followers have neither the formal
authority nor social power to do so (Bacharach & Lawler, 1980; Emerson, 1962; Pfeffer &
Salancik, 1974; Yukl, 2010). Such awareness helps supervisors better cope with the
uncomfortable feelings that negative feedback elicits and be more approach-oriented to the
potential positive outcomes that could be attained by changing their behaviors and correcting the
problems. In line with this argument, Keltner et al. (2003: 268-269) suggested that “the
experience of power involves the awareness that one can act at will without interference or
serious social consequences …[B]eing unconstrained by others’ evaluations or the consequences
of one’s actions, people with elevated power should be disposed to elevated levels of approach-
related affect, cognition, and behavior.”
In addition, social power tends to increase task-focused and goal-directed behaviors
(Karremans & Smith, 2010; Smith et al., 2008; Steele et al., 2002). As mentioned earlier, the
main purpose of providing negative feedback is to identify the creativity-standard gap to help
recipients close this gap by improving their current level of creativity. However, negative
feedback often distracts recipients’ focus from their task and directs their attention to task-
irrelevant matters, such as concern about their image in the eyes of others (Kluger & DeNisi,
1996). Therefore, as long as recipients can maintain their focus on their creativity task, they are
more likely to utilize negative feedback to improve creativity. Evidence from the social power
literature has shown that the powerful, relative to the powerless, can better plan and update task-
relevant information and suppress their attention to task-irrelevant information in order to
achieve their goals (Smith et al., 2008; Smith & Trope, 2006), even when the information
threatens their self-image (Beilock, Rydell, & McConnell, 2007; Steele et al., 2002).
Finally, social distance theory (Magee & Smith, 2013) provides a relational perspective
regarding why the bottom-up feedback flow may positively relate negative feedback to recipient
creativity. This theory suggests that high-power employees have a greater sense of social
distance, namely, “a subjective perception or experience of distance from another person or other
persons” (Magee & Smith, 2013: 2). With the heightened level of social distance, high-power
employees pay less attention to their social relationships with others; instead, they tend to
strengthen their focus on the achievement of ultimate goals and maintain high levels of self-
control in the process of goal pursuit. Furthermore, in anticipation of social disapproval, the
sense of social distance keeps high-power employees from feeling socially engaging emotions,
such as embarrassment and feeling threatened, since they value communal, intimate social
relationships less (Magee & Smith, 2013). Thus, in the bottom-up negative feedback flow from
followers to supervisors, supervisors’ sense of social distance is likely to help them maintain
their focus on creativity tasks and overcome the ego-threatening implications of negative
feedback. In summary, in the bottom-up feedback flow, supervisors likely utilize negative
feedback for their creativity by attending to task-processes rather than meta-processes.
The top-down feedback flow. In contrast to the bottom-up feedback flow, the top-down
feedback flow may lead feedback recipients (i.e., followers) to respond to negative feedback by
attending to meta-processes instead of task-processes because the asymmetrical social power in
the supervisor-follower relationship likely leads followers to be more vigilant to criticism from
their supervisor and more concerned about their image in the eyes of their supervisors. In
general, employees have a strong desire to maintain their membership in the organization and
move up the organizational hierarchy. To do so, they need favorable evaluations and support
from their supervisors as supervisors have the power to satisfy or impede their desires. In the
language of Keltner et al. (2003), “less powerful individuals have less access to material, social,
and cultural resources and are more subject to social threats and punishments. Thus, they are
more sensitive to the evaluations and potential constraints of others" (p. 269). Furthermore, as
mentioned above, people with low social power, relative to those with high social power, tend to
decrease their task-focused attention and fail to suppress their attention to task-irrelevant
information (Smith et al., 2008; Smith & Trope, 2006). This is even more pronounced when
information that threatens the recipients’ self-image (e.g., negative feedback) is present (Beilock
et al., 2007; Steele et al., 2002). Finally, low-power people tend to have a low social distance and
value social relationships with others, rendering them more vigilant to negative feedback and
criticisms from others (Magee & Smith, 2013). Taken together, we argue that the top-down
feedback flow likely directs feedback recipients’ (i.e., followers’) focus away from task-
processes to meta-processes, which is detrimental to their creativity.
Lateral Negative Feedback Flow and Creativity
While the bottom-up and the top-down feedback flows involve hierarchical relationships
in which social power is asymmetrical, the lateral feedback flow does not involve social power
differences between senders and recipients. Instead, the lateral feedback flow is often
characterized as a competitive relationship in which peers strive to attain limited organizational
resources (e.g., promotions, pay increases, or training opportunities; Magee & Galinsky, 2008).
Rarely, in organizations with a social hierarchy that does not resemble a pyramid, competition
may not be an essential feature because such organizations have several higher positions
available, allowing all employees to move up the hierarchy. “Many real-world situations, by
contrast, offer rewards that depend on an individual’s performance relative to others” (O'Keeffe,
Viscusi, & Zeckhauser, 1984: 27), and the number of people at the top is significantly smaller
than the number of people at the bottom (Magee & Galinsky, 2008). Thus, competition is an
inherent characteristic that defines employee relationships in most organizations.
However, this does not mean that the workplace is “the war of all against all.” Instead,
employees most likely compete only with their reference group, which refers to a group of
employees whose behaviors and performance are compared against each other (Bandura, 1977;
Festinger, 1962). The selection of a reference group is based on shared similarities in members’
experience and ability (Festinger, 1954; Mumford, 1983). In organizations, as peers have similar
levels of work tenure, experience, ability, and knowledge, peer groups become the reference
groups (Bandura, 1977, 1978, 2001). Most importantly, social comparisons based on appropriate
reference groups are related to employee perceptions of organizational justice. Unfair
comparisons for performance ratings (e.g., between followers and leaders) significantly
undermine employee perceptions of both distributive and procedural fairness (Bandura, 1977;
Festinger, 1962), which results in detrimental organizational outcomes, such as high levels of
turnover, low commitment, low job satisfaction, and low job performance (see for a review,
Colquitt, Conlon, Wesson, Porter, & Ng, 2001). Therefore, organizations assess employee
performance through social comparisons within a peer group and provide employees with results
in the form of performance feedback (Mumford, 1983).
Regarding the lateral negative feedback flow, the non-hierarchical and competitive
nature of peer relationships is likely to direct recipients’ focus toward meta-processes and away
from task-processes. In a peer relationship, recipients likely interpret lateral negative feedback in
an unproductive way because they are concerned about the possibility of lagging behind their
competitors and because they strive to stand out among their peers (Bendersky & Shah, 2012;
Cho, Overbeck, & Carnevale, 2011; DeNisi et al., 1983; Rogers & Feller, 2016; Tauer &
Harackiewicz, 1999). For this reason, lateral negative feedback “could be viewed as an attack on
self-esteem” and as an attempt to downplay a competitor’s abilities (DeNisi et al., 1983: 458).
Several researchers have provided empirical evidence that lateral negative feedback induces the
negative responses of feedback recipients, particularly in relation to meta-processes. DeNisi et al.
(1983) designed a longitudinal laboratory experiment to test whether lateral negative feedback
causes recipients to exhibit negative reactions. They manipulated the lateral negative feedback by
simply indicating that it came from a peer, and they found that recipients demonstrated
unproductive reactions. The lateral negative feedback decreased recipients’ satisfaction with and
trust in (or cohesiveness with) their peers; ultimately, it significantly impaired the recipients’
task-focus.
Following DeNisi et al. (1983), several other researchers have provided further evidence
that lateral negative feedback threatens recipients’ self-concept and distracts from their task-
focus. For example, Druskat and Wolff (1999) found that even though lateral negative feedback
had a developmental purpose, recipients perceived it as detrimental to peer communication,
recipient development, peer cohesion, satisfaction with peers, and the viability of their peer
group. Brett and Atwater (2001) offered more direct evidence that lateral negative feedback
threatens recipient ego and self-image. In their study, recipients of lateral negative feedback
reported that they felt discouraged, criticized, and confused by this feedback. More recently,
Rogers and Feller (2016) showed that when people identified a negative gap between their
creative performance (i.e., levels of excellence in essay writing) and a peer’s creative
performance (i.e., the reference point), they felt that their self-image and perceived abilities were
threatened. Participants reported that they felt discouraged and disappointed by the gap and that
they were not the right person for the creativity task. In addition, the recipients perceived that
their writing would not attain the same levels of excellence as their peers’ essays, and as a result,
their task-focus was significantly distracted. Relying on these findings, we suggest that the
lateral negative feedback flow likely leads negative feedback recipients to attend to meta-
processes rather than to task-processes, which will ultimately reduce their creativity.
To summarize, we suggest that the direction of feedback flow is an important boundary
condition of the negative feedback and creativity relationship. The bottom-up negative feedback
helps recipients come up with better task-strategies for their creativity tasks (task-processes),
which subsequently increases their creativity. In contrast, top-down and lateral negative feedback
directs recipients’ focus away from creativity tasks to task-irrelevant matters, such as concerns
about their ability, their social relationships with feedback senders, and their self-concept (meta-
processes), which prevents them from engaging in experimentation and creative attempts and in
turn decreases their creativity. Thus, we propose the following two hypotheses:
Hypothesis 1. The relationship between negative feedback and recipient creativity is
moderated by the direction of feedback flow; in the bottom-up feedback flow, negative
feedback is positively associated with recipient creativity, whereas in the top-down and
lateral feedback flows, negative feedback is negatively associated with recipient
creativity.
Hypothesis 2. Task-processes and meta-processes mediate the relationship between
negative feedback, the direction of feedback flow, and recipient creativity; in the bottom-
up feedback flow, task-processes mediate the positive relationship between negative
feedback and recipient creativity, whereas in the top-down and lateral feedback flows,
meta-processes mediate the negative relationship between negative feedback and
recipient creativity.
OVERVIEW OF THE STUDIES
We conducted two studies – one quasi-field experiment and one laboratory experiment –
to test our theoretical model. Both studies tested the full moderated mediation model. In Study 1,
we recruited 225 employees who were working in creative jobs – designing new products,
researching and developing new products, and developing marketing plans – in a Korean
company. Employees were quasi-randomly assigned to one of three conditions of the direction of
feedback flow: bottom-up, top-down, or lateral. The company employed bottom-up, top-down,
and lateral feedback in their quarterly evaluations. Relying on this natural organizational setting,
we measured employee perception of the extent to which their quarterly evaluation was negative.
Creativity was measured by focal employees’ superiors two months after the quarterly
evaluations. Study 2 sought to replicate the results of Study 1 with 356 undergraduate students in
a large North American university. We conducted a laboratory experiment to provide evidence of
causality by manipulating both negative feedback and the direction of feedback flow.
STUDY 1: QUASI-FIELD EXPERIMENT
Procedure
We conducted the study in the Product Development and Management department at a
health food company in Korea. The main duties of employees at the department of Product
Development and Management were (1) designing new products, (2) researching and developing
new products, and (3) developing marketing plans (e.g., promotion, advertisement) for new
products. According to our interviews with the three executives of this company, creativity is the
defining job characteristic of employees at the Product Development and Management
department, and in formal performance evaluations, employees are rated regarding how creative
they have been in their jobs. The company operates with a team-based structure, and one team
leader manages each team. Each team also has a deputy team leader, who acts as a team leader
when necessary. The team leader reports to his/her division head. In our study, we measured the
top-down, bottom-up, and lateral feedback received by focal employees in the natural context of
the company’s official quarterly evaluations. Two months later, we collected ratings of the focal
employees’ creativity from their superiors.
The company provides employees with performance feedback quarterly, in March, June,
September, and December. In alternating quarters, team members (or followers in each team)
receive lateral feedback from their peers (in March and September) and top-down feedback from
their team leader (in June and December). Team leaders also receive feedback from different
sources in alternating quarters. Since team leaders have limited contact with their peers, they
receive bottom-up feedback from their team members, instead of receiving lateral feedback in
March and September. In June and December, team leaders receive feedback from their division
heads. The feedback that employees receive (regardless of its source) includes both a numerical
evaluation and written feedback. The numerical evaluation ranges from 0% to 100%; the higher
the score, the better the employee performance. In the written feedback, a feedback sender
specifies a recipient’s strengths, weaknesses, and any other information that the sender thinks is
important for improving the recipient’s task behavior.
2
We coordinated our data collection with
an executive member of the Human Resources department, who allowed us to collect data from
one focal employee per team.
Relying on the unique, natural setting of this company, we designed a quasi-field
experiment using March and June quarterly evaluations. We created the quasi-field experimental
conditions, manipulating the direction of feedback flow by selectively inviting participants in
2
The numerical evaluations in the bottom-up and lateral feedback flows are averaged across raters as there are
multiple raters (i.e., multiple followers for the bottom-up feedback flow and multiple peers for the lateral feedback
flow), whereas in the top-down feedback flow, the score is not averaged, as there is only one rater (i.e., supervisor).
Thus, in the numerical evaluations, raters in the bottom-up and lateral feedback flows are anonymous, whereas the
top-down feedback flow reveals the identity of the feedback sender. However, the written feedback is done non-
anonymously – the company has all the feedback senders specify their names so that the feedback recipients can
receive further feedback after the quarterly evaluations. Note that it is the top-down evaluation that determines the
final grade of each employee at the end of the year; the bottom-up and lateral feedback are for informative and
developmental purposes. This setting is in line with that of the majority of organizations in which supervisors
control employee performance evaluation and other important organizational resources, as we theorized earlier.
either March or June evaluations. That is, we created three conditions, and each condition
contained about one third of the sample. The bottom-up feedback flow condition contained team
leaders who received feedback from their team members in the March evaluation. The lateral
feedback flow condition contained team members who received feedback from their peers in the
March evaluation. The top-down feedback flow condition contained team members who received
feedback from their supervisors in the June evaluation. To create the three conditions, in the
beginning of March, we sent out an invitation email to all team members and team leaders at the
Product Development and Management department. After receiving responses from employees
who were willing to take part, we selected one participant from each team and assigned them to a
condition before they received their quarterly feedback at the end of March. When multiple team
members from the same team volunteered for this study, we randomly selected one. When a team
leader and team members from the same team volunteered, we randomly chose one if possible
but were forced to preferentially choose supervisors in some cases in order to ensure equal
distribution of the number of participants across conditions (among the volunteers, there were
obviously more team members than team leaders, which gave us a larger available pool of the
former than the latter). For this reason, this study is a quasi-field experiment in which we quasi-
randomly, rather than fully randomly, invited participants to the three conditions.
After the recruitment, researchers visited the company within a week of employees
receiving their March and June quarterly evaluations to measure negative feedback, task-
processes, and meta-processes. Two months after each of our visits (i.e., in May and August,
respectively), we measured creativity from a focal employee’s superior. Thus, the data collection
occurred at four distinct time points, but the data were collapsed to create two waves of time-
lagged data. Time 1 represented the points at which negative feedback, task-processes, and meta-
processes were measured, and Time 2 (two months after Time 1) represented the point at which
superiors evaluated the focal employees’ creativity. The final data consisted of 225 employees
(response rate = 54.61%; NBottom-up negative feedback = 80, NLateral negative feedback = 73, NTop-down negative
feedback = 72). The sample contained 104 females (45.34%) and 121 males (54.66%), with an
average age of 32.38 years (SD = 4.65). The average tenure of our sample was 6.37 years (SD =
2.69). The majority of employees had completed a bachelor’s degree (87.6%) and 12.4% had
completed graduate degrees.
Manipulation and Measures
We created Korean versions of the surveys by following the survey translation
procedures recommended by Brislin (1990). All measures used a Likert scales from ‘1’ (strongly
disagree) to ‘7’ (strongly agree).
The Direction of Feedback Flow. As previously mentioned, we manipulated the
direction of feedback flow by collecting data from employees in the different positions (either
team members or team leaders) in the different quarterly evaluations (in March and June). This
allowed us to create three conditions: the top-down feedback flow condition (feedback
recipient=team members; feedback sender=team leaders; time of feedback=June), the lateral
feedback flow condition (feedback recipient=team members; feedback sender=other team
members; time of feedback=March), and the bottom-up feedback flow condition (feedback
recipient=team leaders; feedback sender=team members; time of feedback=March).
Because the conditions are categorical without any rank-order, we represented the three
conditions using two dummy variables for our analyses (Hayes, 2013). We chose the bottom-up
feedback flow condition as the reference group because it is the only condition where we
expected a positive relationship between negative feedback and recipient creativity; in the other
two conditions, we expected negative relationships between negative feedback and recipient
creativity. By choosing the bottom-up feedback flow condition as the reference group, we
investigate differences between the bottom-up feedback flow condition and the top-down
feedback flow condition using our first dummy variable (D1) and differences between the
bottom-up feedback flow condition and the lateral feedback flow condition using our second
dummy variable (D2). Specifically, we followed “indicator” dummy coding (Hayes, 2013); the
dummy coding in each condition was as follows: in the bottom-up feedback flow condition,
D1=0 and D2=0; in the top-down feedback flow condition, D1=1 and D2=0; in the lateral
feedback flow condition, D1=0 and D2=1.
Negative Feedback. Participants evaluated the extent to which their quarterly evaluation
was negative. To measure negative feedback, we modified the seven-item feedback valence scale
developed by George and Zhou (2001). The original scale captures both positive and negative
feedback on the same continuum.
3
Among the seven items in the original scale, four of them
clearly reflect negative feedback and the other three measure positive feedback. We modified the
latter three items so that they rate negative feedback. The items are reported in the Appendix.
Positive Feedback. Although the primary purposes of our research are to investigate the
relationship between negative feedback and creativity and to resolve the inconsistency in this
relationship, we also measured positive feedback for three reasons. First, we test whether
employees differentiate negative feedback from positive feedback. We tested this in our
confirmatory factor analysis. Second, we examine whether the influence of negative feedback is
3
The design of the original George and Zhou feedback scale assumes that negative and positive feedback are on the
same continuum. This assumption may be problematic because it is hard to interpret the scale midpoint. The scale
midpoint implies two different situations simultaneously: 1) a feedback source providing a high volume of both
positive and negative feedback and 2) a feedback source who provides minimal feedback of any type, positive or
negative. We discuss the theoretical and methodological aspects of this issue in the general discussion.
distinctive from that of positive feedback. Lastly, we control for it when examining the
relationship between negative feedback and creativity. The participants rated the degree to which
their quarterly evaluation was positive using another modified version of George and Zhou’s
(2001) feedback valance scale, with the items rephrased to inquire about positive feedback. We
reported all the items in the Appendix.
Task-Processes and Meta-Processes. We modified existing scales to measure task-
processes and meta-processes, based on the conceptualizations of both processes delineated in
feedback intervention theory (Kluger & DeNisi, 1996). To measure task-processes (α=.93), we
created a 4-item scale by modifying the scales for challenge construal (Elliot & Reis, 2003;
McGregor & Elliot, 2002) and primary appraisal (Tomaka, Palacios, Schneider, Colotla, Concha,
& Herrald, 1999). To measure meta-processes (α=.93), we created a 5-item scale by modifying
the scales for threat construal (Elliot & Reis, 2003; McGregor & Elliot, 2002) and secondary
appraisal (Tomaka et al., 1999). All the items are reported in the Appendix.
Creativity. Superiors rated the focal employee’s creativity using Zhou and George’s
(2001) 13-item scale of creative performance. Specifically, division heads evaluated the
creativity of team leaders in the bottom-up feedback flow condition, team leaders evaluated the
creativity of the focal team members in the lateral feedback flow condition, and deputy team
leaders evaluated the creativity of focal team members in the top-down feedback flow condition.
The reason we collected creativity evaluations from the deputy team leaders in the top-down
feedback flow condition, rather than collecting it from the primary team leaders, was to avoid
artificially inflated correlations between negative feedback and creativity. In the top-down
feedback flow, team members received feedback from their team leader. Collecting creativity
ratings from those same team leaders may introduce same-source biases into the data in this
condition. A sample item includes, “This employee is a good source of creative ideas” (α=.96).
Control Variables. We controlled for five demographic variables: age, gender, education,
tenure with the organization, and tenure with feedback sender because there could be individual
differences when recipients interpret feedback (Kluger & DeNisi, 1996). Age, tenure with
organization, and tenure with feedback sender were measured in years. Gender was measured as
a dichotomous variable: ‘0’ for female and ‘1’ for male. Education was coded in the following
manner: ‘1’ for a high school graduate, ‘2’ for a graduate from a 2-year community college
program, ‘3’ for a person with a degree from a 4-year university program, and ‘4’ for people with
a master’s degree or Ph.D. In addition, we controlled for creative role identity (α=.93) and
creative self-efficacy (α=.89). It is possible that recipients who believe that they are creative or
efficacious on creativity tasks are more likely to seek for ways of improving their creativity
(Shalley, Zhou, & Oldham, 2004), and thus they may be more receptive to negative feedback. We
also included positive feedback to investigate the unique influences of negative feedback on
creativity.
4
Confirmatory Factor Analysis
We conducted confirmatory factor analysis to examine the psychometric validity of our
measures using a variety of indicators of model fit – a chi-square statistic, Tucker-Lewis index
(TLI), the standardized root mean squared residual (SRMR), the comparative fit index (CFI), and
the root mean squared error of approximation (RMSEA). This analysis included the negative
feedback, task-processes, meta-processes, and creativity items. Furthermore, we added positive
feedback to examine if participants differentiated negative feedback from positive feedback.
According to the standards recommended by Hu and Bentler (1998), our confirmatory factor
4
Note that the results remained the same with or without the control variables.
analysis indicated a good fit for the five-factor model.
5
The chi-square value was 890.794
(df=550, p<.001), TLI was .957, SRMR was .043, CFI was .960, and the RMSEA was .050. The
average levels of the standardized loadings on the five constructs were: creativity=.83; negative
feedback=.86; meta-processes=.85; task-processes=.88; and positive feedback=.90. In addition,
we compared our five-factor model with potential alternative models. The alternative model
showing the highest fit was a four-factor model, which combines task-processes and meta-
processes (χ2(554)=1549.98, p<.001; TLI=.875; SRMR=.073; CFI=.884; RMSEA=.085).
However, a comparison analysis of our original five-factor model and the four-factor alternative
model showed that our model has a significantly better fit than the alternative model
(Δχ2(4)=659.19, p<.001). These results showed strong evidence that our variables are valid, and
that employees differentiate all of the important variables from one another. Importantly,
employees differently perceived negative and positive feedback according to the confirmatory
factor analysis, which suggests that each captures different aspect of feedback.
Results of Study 1
The means, standard deviations, and correlations for all variables in Study 1 are
presented in Table 2. To test our hypotheses, we used multiple hierarchical regression, combined
with conditional indirect effect analysis – moderated mediation analysis – using the PROCESS
macro developed by Hayes (2013).
Hypothesis 1 predicted that in the bottom-up feedback flow condition, the relationship
between negative feedback and recipient creativity is positive, whereas in the top-down and
5
Although the chi-square test showed a poor fit, all of other indicators showed good fits. Several scholars have noted
that chi-square indices may mislead the interpretation of model fit because it is too sensitive to sample size and the
violation of an assumption underlying the test (e.g., multivariate normality of variables). “Hence, using chi-square to
test the hypothesis that the population covariance matrix matches the model-implied covariance matrix is too strong
to be realistic” (Hu & Bentler, 1998: 425). Given the other indices, except for the chi-square test, were above the
traditional cut-off values, we conclude that our five-factor model has a good fit.
lateral feedback flow conditions, the relationship is negative. The results revealed that the
interactions between negative feedback and the two dummy variables were significant.
Specifically, Table 3 shows significant interactions between negative feedback and D1 (bottom-
up=0, top-down=1; b=-1.03, SE=.15, t=-6.94, p<.001), and between negative feedback and D2
(bottom-up=0, lateral=1; b=-.97, SE=.15, t=-6.61, p<.001) in predicting creativity. The result of
the former interaction indicates that there is a significant slope difference between the bottom-up
and top-down feedback flow conditions. The result of the latter interaction indicates that there is
a significant slope difference between the bottom-up and the lateral feedback flow conditions.
We further investigated these interactions by analyzing the simple slopes at each value (0 or 1) of
each moderator (D1 and D2). The results showed that in the bottom-up feedback flow condition
(from followers to supervisors; D1=0 and D2=0) the relationship between negative feedback and
recipient creativity was significantly positive (b=.48, SE=.11, t=4.34, p<.001, LLCI=.264,
ULCI=.705). In the top-down feedback flow condition (from supervisors to followers; D1=1 and
D2=0) the relationship was significantly negative (b=-.54, SE=.10, t=-5.39, p<.001; LLCI=-.739,
ULCI=-.343). In the lateral feedback flow condition (from peers to peers; D1=0 and D2=1) the
relationship was significantly negative (b=-.49, SE=.10, t=-4.94, p<.001, LLCI=-.681,
ULCI=-.293). Figure 2 depicts these relationships. Hypothesis 1 was supported.
Hypothesis 2 stated that the moderated relationships between negative feedback, the
direction of feedback flow, and recipient creativity are mediated by task-processes and meta-
processes. Before testing the moderated mediation hypothesis, we conducted two separate
analyses to examine the interaction of negative feedback and the direction of feedback flow in
predicting task-processes and meta-processes. With regard to task-processes, we found
significant interactions of negative feedback and D1 (b=-.94, SE=.18, t=-5.37, p<.001) and D2
(b=-1.26, SE=.18, t=-7.22, p<.001). Table 3 summarizes the full results. The simple slope tests
showed that the bottom-up negative feedback enabled supervisors to focus on task-processes
(b=.52, SE=.13, t=3.89, p<.001, LLCI=.255, ULCI=.778). However, the top-down negative
feedback (b=-.43, SE=.12, t=-3.58, p<.001, LLCI=-.662, ULCI=-.192) and lateral negative
feedback (b=-.74, SE=.12, t=-6.36, p<.001, LLCI=-.975, ULCI=-.513) significantly decreased
employees’ focus on task-processes. Figure 3 depicts these relationships.
Regarding meta-processes, the interactions that negative feedback had with D1 (b=.36,
SE=.17, t=2.17, p=.031) and D2 (b=.57, SE=.17, t=3.47, p=.001) were both significant (see
Table 3). The simple slope tests revealed that the relationship between negative feedback and
meta-processes was not significant in the bottom-up feedback flow condition (b=.07, SE=.13,
t=.59, p=.553, LLCI=-.173, ULCI=.322), but the relationship was significantly positive in the
top-down (b=.43, SE=.11, t=3.86, p<.001, LLCI=.212, ULCI=.657) and lateral (b=.65, SE=.11,
t=5.85, p<.001, LLCI=.429, ULCI=.865) feedback flow conditions. Figure 4 illustrates these
relationships.
Lastly, we tested the full moderated mediation model using a conditional indirect effect
analysis with 10,000 bias-corrected bootstrap resampling (Hayes, 2013). The results showed that
in the bottom-up feedback flow condition, the positive relationship between negative feedback
and creativity was mediated by task-processes (estimated size of the indirect effect=.08, SE=.04,
LLCI=.011, ULCI=.181), but not by meta-processes (estimated size of the indirect effect=-.03,
SE=.04, LLCI=-.114, ULCI=.046). In the top-down feedback flow condition, the negative
relationship between negative feedback and creativity was mediated by both task-processes
(estimated size of the indirect effect=-.07, SE=.04, LLCI=-.157, ULCI=-.010) and meta-processes
(estimated size of the indirect effect=-.15, SE=.08, LLCI=-.356, ULCI=-.037). In the lateral
feedback flow condition, the negative relationship between negative feedback and creativity was
also mediated by both task-processes (estimated size of the indirect effect=-.12, SE=.06,
LLCI=-.246, ULCI=-.021) and meta-processes (estimated size of the indirect effect=-.23, SE=.09,
LLCI=-.433, ULCI=-.082). These results supported Hypothesis 2.
------------------------------------------------------------------------
Insert Figure 2, 3, and 4 and Table 2 and 3 about here
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Discussion of Study 1
With a quasi-field experimental design, Study 1 found that the relationship between
negative feedback and creativity depends on the direction of feedback flow. Bottom-up feedback
flow was the only case in which negative feedback increased recipient creativity; top-down and
lateral feedback flows of negative feedback were detrimental to recipient creativity. The two
mechanisms – task-processes and meta-processes – accounted for these interactional
relationships. In the bottom-up feedback flow condition, negative feedback increased creativity
because recipients attempted to improve the ways of performing their creativity tasks, and they
did not feel threatened by negative feedback. However, in the top-down and lateral feedback
flow conditions, recipients failed to generate diverse strategies to perform their creativity tasks.
Instead, they felt threatened by negative feedback, which in turn decreased their creativity.
Although our primary focus was to investigate the relationship between negative feedback and
creativity, we also examined how positive feedback relates to creativity. The result shown in
Table 3 reveals that positive feedback had a nonsignificant relationship with creativity (b=-.04,
SE=.06, t=-.63, p=.528). We discuss this relationship later in the general discussion.
Although the results of Study 1 supported our hypotheses, some limitations should be
noted. First, Study 1 quasi-randomly assigned employees to the three feedback flow conditions
using the natural field setting, and we did not manipulate negative feedback. This raises a
question of potential influences that spurious third variables might have on our findings. Second,
we measured the recipients’ subjective impression of feedback. In the quarterly performance
appraisal, employees received both numerical and written feedback. Rather than using the
numerical and written feedback directly, we asked the employees to rate their subjective
evaluation of the performance appraisal with an assumption that the same feedback could be
perceived differently by employees. For example, two employees who receive 60% in the
numerical appraisal may interpret the same number differently; one may interpret it as negative
feedback, while another may perceive it as neutral feedback. In addition, methodologically
speaking, it was difficult to quantify the negativity of the written feedback objectively. Third,
there could be a confounding effect of feedback recipient positions. We collected data from
supervisors in the bottom-up feedback flow, but in the top-down and lateral feedback flows, our
data collection was done with team members. Ideally, the data should have been collected from
employees at the same position across the three conditions (e.g., middle managers who receive
feedback from their followers, supervisors, and peers). This limitation is less likely to hurt the
validity of the top-down and bottom-up feedback flows because those two flows presuppose
positional differences between feedback givers and recipients. However, there could be an
unexpected confounding effect of position in the lateral feedback flow. For example, the
underlying psychology of middle managers receiving feedback from peers could be different
from that of team members receiving feedback from peers.
To address these limitations, we conducted Study 2 in which we manipulated both
negative feedback and the direction of feedback flow and randomly assigned participants to
conditions in a well-controlled laboratory environment. This experiment directly manipulates
negative feedback rather than measuring the subjective evaluation of the feedback. Additionally,
we manipulate the lateral feedback flow without disclosing the positions of feedback giver and
recipient.
STUDY 2: LABORATORY EXPERIMENT
Participants and Procedures
Three hundred and fifty-six undergraduate students at a large North American university
(217 males, 136 females, three participants did not report their gender; MAge=19.80, SDAge=1.51,
four participants did not report their age) participated in this study for one credit point. The
sample was 57.02% East Asian, 23.31% Caucasian, 8.99% South Asian, 3.37% African/African-
Canadian, .84% Hispanic, .28% Native American/Canadian, and 7.58% other. Two independent
variables (feedback and the direction of feedback flow) were manipulated in this experiment
based on a 2 (feedback: negative vs. neutral) by 3 (the direction of feedback flow: bottom-up vs.
top-down vs. lateral) experimental design. We randomly assigned the participants to one of the
six conditions.
Upon arrival, the participants were led to a large room and completed a short survey
regarding their demographic information. After the survey, the participants were randomly
assigned to one of three roles (i.e., supervisor, follower, or peer) and led to four different rooms.
Participants playing the same role were grouped together and shared the same room, except for
those playing the peer role. The peers were divided into two groups, and each group used one
room. Then, the participants were informed that they would complete a two-round study that
involves exchanging feedback with another participant in a different room through an online
platform. Both rounds involved an in-basket task, which is an idea generation task that requires
creative solutions (Shalley, 1991). In this task, participants assume the role of an employee in a
company and are asked to generate creative ideas regarding 22 organizational issues. We used
one of the 22 issues in the first round and three issues in the second round as explained later. The
participants were informed that they would be paired with a partner in a different room. During
the first round, the participants individually generated one idea regarding an issue, and then, they
were paired with another participant. After the pairing, the two parties exchanged feedback
regarding the counterpart’s idea, including a numerical rating and written feedback in which they
could provide additional information to qualify their rating. Subsequently, the participants
responded to the measures of task-processes and meta-processes. Then, the participants
proceeded to the second round. The participants again individually generated ideas regarding
three additional issues in the in-basket tasks, which served as our dependent variable, exchanged
their ideas, and evaluated each other’s ideas. In reality, the participants did not have a real
partner, and all feedback provided was prepared by the experimenter, which allowed us to
manipulate the negative feedback.
Negative Feedback Manipulation. After the participants completed the first idea
generation task, they sent their idea to their partner and received their partner’s answer to the
same question. The idea, which was supposedly generated by their partner, was in fact prepared
by the experimenter and was identical for all participants. The participants were asked to offer
feedback regarding the level of creativity of their partner’s idea, including a percentile score and
written feedback. While the participants completed this task, they believed that their partner also
evaluated their idea and provided feedback. After completing their feedback, the participants
received their partner’s feedback regarding their own work. In reality, this feedback was prepared
by the experimenter and included the negative feedback manipulation. The participants received
feedback in the same format they had used to provide feedback to their partner: they received a
percentile score and additional written feedback. We manipulated the negative feedback using
the percentile score. In the negative feedback condition, we informed the participants that their
creativity was in the bottom 20th percentile, and in the neutral feedback condition, the
participants were informed that their creativity was average as they were in the 40th~60th
percentile. All participants received the same written feedback, which contained advice regarding
generating creative ideas. The advice included useful tips on how to increase the recipients’
cognitive flexibility and cognitive persistence in creativity tasks, which were derived from
findings reported in the creativity literature (Nijstad, De Dreu, Rietzschel, & Baas, 2010; Shalley,
1991; see Appendix). These tips likely contribute to the generation of creative ideas if the
participants are open to using them. To ensure that the manipulation worked as intended, we
asked the participants to report how they felt about the feedback they received on a scale from ‘1’
(extremely negative) to ‘7’ (extremely positive).
Direction of Feedback Flow Manipulation. The direction of feedback flow refers to the
transfer of feedback from sender(s) to recipient(s) in which the two parties have different or the
same organizational ranks. As theorized earlier, the bottom-up and top-down feedback flows are
characterized by power asymmetry between the two parties, whereas the lateral feedback flow
involves a non-hierarchical and competitive relationship between the two parties who strive to
attain limited resources. Reflecting upon these characteristics, we manipulated the direction of
feedback flow in two ways – by assigning the participants to the role of supervisor, follower, or
peer and by offering different levels of resource-controls (Anderson & Berdahl, 2002; Jordan et
al., 2011; Tost, Gino, & Larrick, 2013). The role assignment manipulation has been popular
among researchers because evidence has shown that participants primed with a certain role
possess the mindset corresponding to the role and behave accordingly (Anderson & Berdahl,
2002; Galinsky, Gruenfeld, & Magee, 2003). The role assignment was performed at the
beginning of the experiment by randomly assigning participants to the role of supervisor,
follower, or peer. In the bottom-up feedback flow condition, the participants were assigned to the
role of supervisor and paired with a follower. In the top-down feedback flow condition, the
participants were assigned to the role of follower and paired with a supervisor. In the lateral
feedback flow condition, both the participants and partners were assigned to the role of peer
without indicating any information regarding the positions of both parties.
To strengthen our manipulation, we also manipulated the different levels of resource-
controls using a lottery system. This manipulation intended to create the approximate experience
of having social power in the real world and a sense of competition to attain a limited resource
(e.g., Anderson & Berdahl, 2002; Jordan et al., 2011; Tost et al., 2013). The experimenter
provided instructions regarding a lottery as follows: the participants would be entered into a
lottery for nine $100 Amazon gift cards (three per role) at the end of the semester and compete
for the lottery only with those who played the same role. In the bottom-up feedback flow
condition, we gave the supervisors unique control over the desired reward (i.e., chance of
winning the lottery). The participants in this condition learned that their partner’s chance of
winning the lottery would depend on how they evaluated their partner’s creativity in the second
round. In other words, by considering the follower’s (or partner’s) levels of creativity in the idea
generation task, the supervisor (or the participant) could decide how many lottery tickets the
follower would receive (from 1 to 10 tickets), and each additional ticket increased the chance of
winning the lottery. Furthermore, the participants were informed that their partner’s evaluation
would not influence their chance of winning the lottery. Instead, at the end of the semester, the
researchers would evaluate the creativity of their ideas and determine the number of tickets they
would receive. In the top-down feedback flow condition, we provided the same instructions, but
this time, the participant-partner relationship was the opposite as follows: the participants played
the role of follower, and their partner played the role of supervisor. Thus, the partner could
determine the number of tickets that the participants would receive, while their evaluation of the
partner’s creativity could not influence the partner’s chance of winning the lottery. In the lateral
feedback flow condition, the instructions stated that the partners were at the same organizational
rank, indicating that they were peers. Therefore, the partner’s evaluation did not influence the
participant’s chance of winning the lottery and vice versa. The participants were also informed
that at the end of the semester, the researchers would evaluate their ideas and determine the
number of tickets they would receive for the lottery.
To ensure that the participants understood the manipulation of the direction of feedback
flow, we employed two types of manipulation checks. First, we asked the participants to report
their and their partners’ roles. Second, we checked the level of authority and social power each
participant felt over their partner by asking the following two questions: (1) “Do you have
authority and social power to control your partner’s chance of winning the lottery?” and (2) “To
what extent do you feel social power over your partner?” The participants responded on a Likert-
type scale ranging from ‘1’ (none) to ‘7’ (a lot). The scores of the two items of the second
manipulation check scale were then averaged. Finally, we used the same “indicator” coding
scheme in Study 1 to analyze the direction of feedback flow: the bottom-up feedback flow was
coded as D1=0 and D2=0; the top-down feedback flow was coded as D1=1 and D2=0; and the
lateral feedback flow was coded as D1=0 and D2=1.
Task-Processes and Meta-Processes. Task-processes (α=.96) and meta-processes
(α=.96) were measured by the same scales used in Study 1. The participants rated the two scales
between the first and second rounds of their idea generation and evaluation tasks. All items are
listed in the Appendix. The participants reported the extent to which they agreed with the items
on a 7-point scale ranging from ‘1’ (not at all) to ‘7’ (very much).
Creativity. The three ideas generated in the second round of the idea generation and
evaluation tasks served as our dependent variable, i.e., recipient creativity. Two independent
judges were trained to evaluate the extent to which the three ideas were creative using a scale
ranging from ‘1’ (not at all creative) to ‘7’ (very creative). The judges showed substantial
agreement in the evaluation of the levels of creativity of the ideas: ICC 1=.80 (p<.001) and ICC
2=.89, (p<.001). Thus, the final creativity scores were obtained by averaging the scores of the
two judges on each idea and then averaging the scores of the three ideas.
Results of Study 2
Feedback Manipulation Check. A 2 (feedback: negative vs. neutral) by 3 (direction of
feedback flow: bottom-up vs. top-down vs. lateral) ANOVA with the feedback manipulation
check item as the dependent variable showed a significant main effect of the feedback condition.
The participants who received negative feedback reported that the feedback they received was
more negative (M=3.34, SD=1.85) than those who received the neutral feedback (M=4.20,
SD=1.38), F(1, 350)=27.71, p<.001,
p2=.07. Thus, our feedback manipulation was successful.
Direction of Feedback Flow Manipulation Check. We checked this manipulation in two
ways as previously explained. First, we checked whether the participants accurately identified
their and their partners’ roles. Three hundred forty nine of the 356 participants (98.03%)
accurately identified the roles. Second, we conducted a 2 (feedback: negative vs. neutral) by 3
(direction of feedback flow: bottom-up vs. top-down vs. lateral) ANOVA with the manipulation
check scale as the dependent variable. The results showed that the participants in the bottom-up
feedback flow condition reported it higher (M=6.32, SD=1.21) than those in the lateral feedback
flow condition (M=2.01, SD=2.02) and those in the top-down feedback flow condition (M=1.88,
SD=1.55), F(2, 350)=298.93, p<.001,
p2=.63. The participants in the lateral feedback flow
condition and top-down feedback flow condition did not differ, t(231)=.54, p=.587. Thus, our
manipulation was successful.
Hypothesis Testing. The means, standard deviations, and correlations of all variables in
Study 2 are presented in Table 4. To test our first hypothesis, we created two dummy variables
for the direction of feedback flow following the same procedure used in Study 1 and performed a
regression analysis.
Hypothesis 1 predicted that in the bottom-up feedback flow condition, the effect of
negative feedback on recipient creativity is positive, whereas in the top-down and lateral
feedback flow conditions, the effect is negative. The results showed that the interaction between
the feedback condition (neutral=0; negative=1) and D1 was significant (bottom-up=0; top-
down=1; b=-1.55, SE=.30, t=-5.15, p<.001; see Table 5) as was the interaction between the
feedback condition and D2 (bottom-up=0; lateral=1; b=-2.08, SE=.32, t=-6.48, p<.001; see Table
5). The former interaction indicates that there is a significant slope difference between the
bottom-up and top-down feedback flow conditions; the latter interaction shows a significant
slope difference between the bottom-up and lateral feedback flow conditions. Furthermore, we
conducted simple slope tests at each value (0 or 1) of each moderator (D1 and D2) and found that
negative feedback (vs. neutral feedback) led to higher levels of recipient creativity in the bottom-
up feedback flow condition (MNeutral=3.56, SDNeutral=1.07; MNegative=4.52, SDNegative=1.47; b=.96,
SE=.22, t=4.45, p<.001, LLCI=.536, ULCI=1.385). However, negative feedback led to lower
levels of creativity in the top-down feedback flow condition (MNeutral=3.77, SDNeutral=1.11;
MNegative=3.19, SDNegative=1.04; b=-.59, SE=.21, t=-2.81, p=.005, LLCI=-.995, ULCI=-.176) and
lateral feedback flow condition (MNeutral=4.34, SDNeutral=1.40; MNegative=3.22, SDNegative=.94; b=-
1.12, SE=.24, t=-4.71, p<.001, LLCI=-1.589, ULCI=-.652). These relationships are depicted in
Figure 5. Thus, Hypothesis 1 is supported.
Hypothesis 2 stated that the interactional effects between negative feedback and direction
of feedback flow on recipient creativity are mediated by task-processes and meta-processes.
Before we test the full moderated mediation model, we tested the interactions between negative
feedback and direction of feedback flow in predicting task-processes and meta-processes. In
predicting task-processes, the interactions between the feedback condition and D1 (b=-1.46,
SE=.40, t=-3.64, p<.001) and between the feedback condition and D2 (b=-1.61, SE=.43, t=-3.75,
p<.001) were significant (see Table 5). Specifically, the results of the simple slope tests showed
that in the bottom-up feedback flow condition, negative feedback led to greater attention to task-
processes (MNeutral=4.79, SDNeutral=1.50; MNegative=5.61, SDNegative=1.46; b=.82, SE=.29, t=2.86,
p=.005, LLCI=.257, ULCI=1.392). However, negative feedback reduced the participants’
attention to task-processes in both the top-down feedback flow condition (MNeutral=5.08,
SDNeutral=1.27; MNegative=4.45, SDNegative=1.71; b=-.63, SE=.28, t=-2.28, p=.023, LLCI=-1.182,
ULCI=-.088) and lateral feedback flow condition (MNeutral=4.97, SDNeutral=1.89; MNegative=4.19,
SDNegative=1.79; b=-.78, SE=.32, t=-2.47, p=.014, LLCI=-1.410, ULCI=-.159). These effects are
depicted in Figure 6.
In predicting meta-processes, the interactions between the feedback condition and D1
(b=.90, SE=.45, t=2.01, p=.045) and between the feedback condition and D2 (b=1.06, SE=.48,
t=2.20, p=.029) were significant (see Table 5)
6
. The simple slope tests showed that negative
6
In the F-test of overall significance, the ΔF of these interactions was marginally significant (p=.051; see Table 5).
feedback did not influence attention to meta-processes in the bottom-up feedback flow condition
(MNeutral=3.50, SDNeutral=1.61; MNegative=3.47, SDNegative=1.53; b=-.04, SE=.32, t=-.11, p=.914,
LLCI=-.672, ULCI=.601). However, negative feedback directed the participants’ attention to
meta-processes in the top-down feedback flow condition (MNeutral=3.26, SDNeutral=1.49;
MNegative=4.12, SDNegative=1.80; b=.87, SE=.31, t=2.79, p=.006, LLCI=.255, ULCI=.1.482) and
lateral feedback flow condition (MNeutral=3.19, SDNeutral=1.77; MNegative=4.21, SDNegative=2.56;
b=1.02, SE=.36, t=2.87, p=.004, LLCI=.322, ULCI=1.725). These effects are depicted in Figure
7.
Finally, to test the full moderated mediation model, we used Hayes’s (2013) PROCESS
macro with 10,000 bias-corrected bootstrapping resamples. In the bottom-up feedback flow
condition, consistent with the results of Study 1, the positive effect of negative feedback on
recipient creativity was mediated by task-processes (estimated size of the indirect effect=.28,
SE=.10, LLCI=.093, ULCI = .484) but not by meta-processes (estimated size of the indirect
effect=.01, SE=.06, LLCI=-.104, ULCI=.128). In the top-down feedback flow condition, the
negative effect of negative feedback on creativity was mediated by both task-processes
(estimated size of the indirect effect=-.22, SE=.10, LLCI=-.421, ULCI=-.039) and meta-
processes (estimated size of the indirect effect=-.18, SE=.07, LLCI=-.336, ULCI=-.066). In the
lateral feedback flow condition, the negative effect of negative feedback on creativity was also
mediated by both task-processes (estimated size of the indirect effect=-.27, SE=.13, LLCI=-.545,
ULCI=-.026) and meta-processes (estimated size of the indirect effect=-.21, SE=.10,
LLCI=-.427, ULCI=-.040). Thus, the results supported Hypothesis 2.
Discussion of Study 2
In the laboratory experiment, we again found that the direction of feedback flow
moderates the relationship between negative feedback and recipient creativity. Specifically,
negative feedback increased recipient creativity when the feedback flows upward, but negative
feedback reduced recipient creativity when the feedback flows downward or laterally. We also
found support for the hypothesized mediating roles of task-processes and meta-processes,
replicating the findings from Study 1. Study 2 demonstrates causality by manipulating both
negative feedback and the direction of feedback flow and randomly assigning participants into
one of the six conditions in a controlled laboratory environment.
GENERAL DISCUSSION
The main objective of our research was to resolve the theoretical and empirical
inconsistency in the relationship between negative feedback and recipient creativity. The results
of our studies – one quasi-field experiment and one fully randomized laboratory experiment –
demonstrate that this inconsistency can be resolved by considering the direction of feedback
flow. We found that bottom-up negative feedback (which flows from followers to a supervisor)
enabled recipients to utilize the feedback by directing their focus to task-processes rather than to
meta-processes, and their creativity was enhanced as a result. In contrast, top-down negative
feedback (which flows from a supervisor to a follower) and lateral negative feedback (which
flows from peers to peers) directed recipients’ focus away from task-processes and toward meta-
processes, which hindered creativity. By investigating our theoretical model in the field and in
the laboratory, we were able to establish both the generalizability and causality of the
hypothesized relationships.
Theoretical and Managerial Contributions
Our research contributes to the creativity and feedback literature by integrating
contradictory findings regarding the relationship between negative feedback and creativity into a
coherent theoretical model. Through our thorough review of the literature, we were able to
categorize the past findings into two groups based on their theoretical commonalities. The first
group (e.g., Fang et al., 2014; Ford & Gioia, 2000; Vuori & Huy, 2015) relied on theories
emphasizing the fact that negative feedback identifies the creativity-standard gap, which creates
dissatisfaction with current creativity and encourages feedback recipients to close the gap by
generating better task-strategies for their creativity tasks. The second group (e.g., Van Dijk &
Kluger, 2011; Zhou, 1998) argued that negative feedback elicits feelings of insecurity or threat
and diverts attention away from creativity tasks, resulting in reduced creativity. By theorizing the
two essential mechanisms – task-processes and meta-processes – underlying the relationship
between negative feedback and recipient creativity (Kluger & DeNisi, 1996), our research
provides a comprehensive, parsimonious theoretical framework that incorporates these two
contradictory perspectives.
Our research not only develops a coherent theoretical model for organizing the
conflicting findings in the literature but also seeks to resolve the inconsistency by introducing a
novel concept – the direction of feedback flow. Past research has examined negative feedback
and recipient creativity with little understanding of how the social contexts surrounding this
relationship play a role. Zhou (2008) noted the limitation of the extant feedback research by
arguing that “how effectively we can use feedback in promoting creativity depends on the nature
and components of the feedback itself, on the characteristics of the feedback recipient, and on the
characteristics of the feedback giver” (p. 130). Addressing this limitation, our research highlights
the importance of conceptualizing feedback as a flow that occurs between two (or more) social
actors. By investigating feedback flows, we could identify the feedback senders and recipients
and examine their social hierarchical relationships, which are all essential for understanding the
effect of negative feedback on creativity. Using this novel concept, we were able to investigate
the question of how the dynamics of the hierarchical relationship between feedback senders and
recipients might resolve the inconsistent association between negative feedback and recipient
creativity. We believe that feedback researchers will benefit by considering the direction of
feedback flow in their research.
The investigation of the direction of feedback flow also extends feedback intervention
theory (Kluger & DeNisi, 1996). To the best of our knowledge, empirical studies directly testing
the two psychological processes of feedback intervention theory (i.e., task-processes and meta-
processes) are lacking in the current literature. Because the key value of this theory is that it
proposes two contradictory processes that transmit the opposite effects of negative feedback on
employee behavior and outcomes, the lack of empirical tests of the two processes could
undermine its usefulness. Our research, conducted in both a professional organization and a
laboratory setting, provides empirical evidence supporting the validity of these two
psychological processes. By doing so, we help future researchers confidently utilize feedback
intervention theory. In addition, our research adds the direction of feedback flow to feedback
intervention theory as a critical boundary condition in which the theory operates. Despite its
parsimonious theoretical framework organizing the contradicting influences of negative feedback
on organizational outcomes, this theory does not offer insights into boundary conditions in which
a recipient responds to negative feedback by attending to either task-processes or meta-
processes. Given the prevalence of negative feedback in organizations (Zenger & Folkman,
2017) and its potential for both benefiting and hampering employee outcomes, feedback
intervention theory can increase its usefulness and value by offering insights about when
organizations can reap benefits from negative feedback. Our research provides an initial
investigation into an important, albeit largely neglected, boundary condition: the direction of
feedback flow. We believe that our findings could benefit future researchers who utilize feedback
intervention theory by emphasizing the importance of considering the direction of feedback flow
in their research.
Our research also emphasizes the theoretical value of separating negative feedback from
positive feedback. Some past works have investigated both positive and negative feedback
simultaneously and treated the two as opposite ends of a single continuum. However, in real
organizations, the assumption that negative and positive feedback are on the same continuum
may be problematic. Considering that a job comprises a set of many different tasks in
organizations (Morgeson, Garza, & Campion, 2012), a feedback sender may simultaneously
provide a feedback recipient with negative feedback on some tasks and positive feedback on
other tasks. Even within one task, some behaviors may receive positive feedback, while other
behaviors may be the targets of criticism. Therefore, positive and negative feedback can be
simultaneously high and low; thus, the single-continuum assumption may not successfully reflect
the setting in real organizations. Supporting this, Table 2 shows only a weak negative correlation
between the two (r=-.26, p<.01). In addition, our confirmatory factor analysis confirmed that
these constructs differed. We hope future scholars will build separate theoretical frameworks for
negative feedback and positive feedback and measure the two independently.
Our research also has implications for practitioners. First, it is important to emphasize
that bottom-up negative feedback creates an opportunity for increasing recipient creativity. In
organizations, followers tend to have low motivation to send criticism and negative feedback to
their supervisors because such feedback may be considered a challenge against people who have
formal authority and social power over important organizational resources (Brett & Atwater,
2001; DeNisi & Kluger, 2000; London & Beatty, 1993). In contrast to such a notion, our research
revealed that supervisors tend to not take negative feedback personally. Instead, supervisors pay
heightened attention to addressing the problems indicated by the bottom-up negative feedback in
order to improve their behavior. Therefore, organizations should consider instituting formal
processes that encourage followers to provide thoughtful, critical feedback to their superiors. We
believe that the evaluation system used by the company in Study 1 can encourage bottom-up
negative feedback. This company provided formal opportunities, i.e., the quarterly evaluations,
for followers to provide negative feedback to their supervisors. Even though the quarterly
evaluations were not anonymous and the bottom-up feedback was used only for informative and
developmental purposes, the followers actively utilized such formal opportunities to offer
negative feedback to their supervisors in both numerical and written forms.
Our research also demonstrated that the top-down and lateral negative feedback flows
reduce recipient creativity because they direct recipients’ attention to meta-processes and away
from task-processes. However, this conclusion does not imply that organizations should prohibit
supervisors from giving negative feedback to their followers or that peers should avoid giving
negative feedback to one another. Instead, supervisors and peers might want to limit the flow of
negative feedback in the middle of creativity tasks, as it decreases recipient creativity. Perhaps
negative feedback can be offered after creativity tasks so that the recipients can take time to cope
with their threatened mindset and think about the ways in which they can improve their current
creativity. This suggestion is in line with the findings in the brainstorming literature that
participants should not criticize one another’s ideas during group idea generation but should
focus only on generating as many diverse ideas as possible (Esser, 1998). Another way of
increasing receptivity of feedback recipients in the top-down and lateral feedback flows could be
that organizations offer several follow-up sessions to employees. Brett and Atwater (2001)
proposed, “executive coaches or multiple follow-up sessions may help those receiving negative
or discrepant feedback to deal with negative reactions and work through them” (p. 940). Through
multiple follow-up sessions, feedback recipients may have a deeper understanding of their
current creativity and evaluation standards, which could help them focus more on ways of
addressing the creativity-standard gap instead of attending to meta-processes.
Finally, our theory suggests that competition might be the main cause of feedback
recipients attending to meta-processes when they received negative feedback from peers (i.e.,
lateral feedback flow). Competition is inevitable between peers because social hierarchies in
organizations often resemble a pyramid with peers competing for limited resources (Bandura,
1977; Festinger, 1962; O'Keeffe et al., 1984). The sense of competition makes peers negatively
react to lateral negative feedback by having them attend to meta-processes. It is then possible
that carefully crafted negative feedback that does not remind of competition between peers could
enhance peers’ receptivity to lateral negative feedback. One possible way to achieve this goal is
that peers may need to use temporal feedback instead of using social comparison feedback when
they provide negative feedback to other peers. Temporal feedback compares past performance
with current performance within one employee, whereas social comparison feedback compares
performance between employees. Feedback researchers have shown that social comparison
feedback is the most prevalent type of feedback in organizations, and it increases a sense of
competition (Brown, Cron, & Slocum Jr, 1998). Although empirical evidence concerning
temporal feedback is lacking in the literature, one group of researchers recently showed that
people tend to be more receptive to temporal feedback than social comparison feedback (Chun,
Brockner, & De Cremer, 2018) because such feedback could reduce the sense of competition.
Thus, organizations, such as the company in Study 1, may need to consider asking employees to
use temporal feedback in their quarterly performance appraisal of peers.
Limitations and Future Research
As with any research, the current research has limitations that can be fruitfully
addressed by future research. First, national cultures might have influenced our findings. Study 1
was conducted in Korea, where cultures of shame and power distance are salient (House,
Hanges, Javidan, Dorfman, & Gupta, 2004). In Korean culture, recipients of negative feedback
may feel shameful and believe that feedback senders intended to humiliate them. This cultural
background might have made the Korean employees in Study 1 more likely to attend to meta-
processes rather than to task-processes when they received negative feedback, particularly in the
top-down and lateral feedback flows. In addition, a high-power-distance might influence
supervisors’ attention to task-processes in the bottom-up feedback flow because in a high-power-
distance culture, both supervisors and followers are unlikely to believe that followers can
threaten supervisors. Thus, rather than interpreting negative feedback as a threat to themselves,
supervisors might be able to increase their focus on task-processes. Nevertheless, we believe that
such cultural influences are unlikely because Study 2 replicated the same findings in North
American culture. However, the sample of Study 2 was undergraduate students, which lowers the
external validity of our findings. Therefore, we call for future research to investigate our model
with a sample of employees in other cultural contexts.
Our findings showed that the only feedback flow that benefits recipient creativity is the
bottom-up feedback flow. However, it is possible that supervisors may also take bottom-up
negative feedback personally and be upset by it when their power is unstable or illegitimate (e.g.,
new leaders who recently joined). Research has shown that when power holders perceived that
their power is unstable, they become anxious about others’ evaluations, more vigilant to potential
threats to their power, and motivated to protect their power (Lammers, Galinsky, Gordijn, &
Otten, 2008). Thus, in situations in which supervisors perceive their power as unstable and
illegitimate, negative feedback from followers may decrease their creativity because they may
feel threatened by negative feedback (meta-processes), and their task-focus may be significantly
distracted by such feedback (task-processes). Thus, future research could explore situations
where bottom-up negative feedback hampers supervisor creativity.
Another limitation of our research is that we investigated only the effects of negative
feedback. Whether positive feedback positively or negatively influences creativity remains an
open question. Our review of past research on positive feedback and creativity revealed
inconsistencies in the literature: researchers have found positive (e.g., Hon, Chan, & Lu, 2013;
Van Dijk & Kluger, 2011) or null (e.g., Fodor & Carver, 2000) relationships between positive
feedback and creativity. This inconsistency could be explained by completely different
mechanisms from ours (task-processes and meta-processes). For example, positive feedback may
either increase or decrease task motivation, which tends to have a positive relationship with
creativity. On the one hand, positive feedback may increase task motivation because such
recognition likely encourages recipients to put more effort into their tasks (Amabile, Conti,
Coon, Lazenby, & Herron, 1996). On the other hand, as positive feedback highlights the
sufficiency of recipients’ current behavior, it may provide a sense of satisfaction with their
current behavior, which can reduce task motivation (Locke & Latham, 2002). Addressing this
inconsistency was beyond the scope of our research. It would be worthwhile for future
researchers to shed further light on the relationship between positive feedback and creativity.
The focus of this research was limited to creativity as an outcome of negative feedback.
Thus, we did not investigate another important organizational outcome, routine performance,
which refers to employee accomplishment on well-learned and frequently practiced tasks
(Kilduff, 1993; March, 1991). Researchers have suggested that routine performance (or
exploitation) and creativity (or exploration) are different, independent dimensions of job
performance (Cyert & March, 1963; March & Simon, 1958). According to our review, our
theoretical model is less likely to be applicable to routine performance. In particular, we believe
that task-processes in our model could be unrelated or even negatively related to routine
performance. By definition, task-processes refer to processes whereby employees attempt to
generate different, diverse, and novel strategies for their tasks. Such experimentation with task-
strategies could be detrimental to routine performance because routine performance requires that
employees strictly follow existing ways of doing their jobs (i.e., task routine; Cyert & March,
1963; March & Simon, 1958). Therefore, even in the case where negative feedback increases
recipient attention to task-processes (e.g., bottom-up feedback flow) we are not certain whether
negative feedback is beneficial for routine performance. As the main purpose of our research was
to resolve the inconsistency between negative feedback and creativity, the examination of routine
performance was beyond our research scope. Thus, we call for future research on this topic.
Finally, our research investigated only unsought negative feedback. It is possible that
sought negative feedback, or negative feedback that follows feedback seeking, may have
completely different effects on recipient creativity. Feedback seeking is a type of proactive
behavior that often represents the readiness to receive criticism and negative feedback and the
willingness to correct behaviors accordingly (Ashford, 1986; Ashford, Blatt, & VandeWalle,
2003; Ashford & Tsui, 1991). Therefore, negative feedback that follows feedback seeking should
be beneficial for constructive changes in task behaviors and creativity; negative feedback
indicates the shortcomings of one’s creativity, and feedback seekers are ready to admit and
correct their shortcomings. We believe this is a promising research area to which future
researchers may be able to contribute.
Notwithstanding these limitations, this paper deepens our understanding of the
relationship between negative feedback and recipient creativity. By proposing a comprehensive
theoretical framework that incorporates inconsistent theories and empirical findings in past
research, our research contributes to the creativity and feedback literature. Across two studies,
we show that the effects of negative feedback on recipient creativity depend on the direction of
feedback flow. We hope to motivate future researchers to explore the differential effects of
feedback on creativity by considering top-down, bottom-up, and lateral feedback flows.
FIGURE 1. Theoretical Framework
FIGURE 2. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Creativity (Study 1).
FIGURE 3. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Task-Processes (Study 1).
1
2
3
4
5
6
7
Low
Negative Feedback High
Negative Feedback
Employee Creativity
Bottom-up Flow
Top-down Flow
Lateral Flow
1
2
3
4
5
6
7
Low
Negative Feedback High
Negative Feedback
Task-Processes
Bottom-up Flow
Top-down Flow
Lateral Flow
FIGURE 4. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Meta-Processes (Study 1).
FIGURE 5. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Recipient Creativity (Study 2).
1
2
3
4
5
6
7
Neutral Feedback Negative Feedback
Recipient Creativity
Bottom-up Flow
Top-down Flow
Lateral Flow
FIGURE 6. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Task-Processes (Study 2).
FIGURE 7. Regression Slopes for the Interaction of Negative Feedback and the Direction
of Feedback Flow on Meta-Processes (Study 2).
1
2
3
4
5
6
7
Neutral Feedback Negative Feedback
Task-Processes
Bottom-up Flow
Top-down Flow
Lateral Flow
1
2
3
4
5
6
7
Neutral Feedback Negative Feedback
Meta-Processes
Bottom-up Flow
Top-down Flow
Lateral Flow
TABLE 1. Summary of Studies Linking Negative Feedback and Recipient Creativity
Study and Context
Feedback Directions
Findings
Laboratory experiment with
undergraduate students (Zhou, 1998)
Top-down
[Negative] Participants who received negative feedback showed
lower creativity than those who received positive feedback
Laboratory experiment with
undergraduate students (Fodor &
Carver, 2000)
Top-down
[Null] Creativity in the negative feedback condition was not
statistically different from creativity in the positive feedback
and control conditions
Interviews and survey with managers in
the eastern U.S. (Ford & Gioia, 2000)
Bottom-up
[Positive] Negative feedback was positively related to decision
creativity
Field survey with professional
employees (George & Zhou, 2001)
Top-down
[Null] There was a non-significant correlation between
feedback valence and creative behavior
Laboratory experiments with
undergraduate students (Ilies & Judge,
2005)
Top-down
[Negative] Participants who received negative feedback showed
downward goal revision in Remote Associates Test
Laboratory experiments with
undergraduate students (Van Dijk &
Kluger, 2011)
Not specified
[Negative] Negative feedback lead to a reduced number of
ideas generated compared to positive feedback.
Field survey with professional
employees (Hon et al., 2013)
Top-down
[Null] There was a non-significant correlation between negative
feedback and creativity
A simulation model study (Fang et al.,
2014)
Not specified
[Positive] Sugarcoating or distorting negative feedback reduced
organizational learning, which in turn decreased innovation
Qualitative interview study with Nokia's
managers and external experts (Vuori &
Huy, 2015)
Bottom-up
[Positive] Middle managers blocked the flow of negative
feedback to upper management, which hampered innovation.
TABLE 2. Means, Standard Deviations, and Correlations of Variables in Study 1.
Variables
M
SD
1
2
3
4
5
6
7
8
9
10
11
12
13
1. D1 (bottom-up=0; top-down=1)
.32
.47
2. D2 (bottom-up=0; lateral=1)
.32
.47
-.48**
3. Negative Feedback
3.98
1.09
-.02
-.19**
4. Task-Processes
4.86
1.35
.02
-.18**
-.12
5. Meta-Processes
3.35
1.16
.10
.09
.29**
-.44**
6. Creativity
5.14
1.07
-.12
-.05
-.17*
.37**
-.46**
7. Gender
.54
.50
-.01
-.04
-.03
.05
-.11
-.01
8. Age
32.38
4.65
-.41**
-.04
.13
.03
-.07
.02
.02
9. Education
3.08
.51
.05
-.03
-.05
.02
-.08
-.05
.12
.04
10. Tenure with Company
6.37
2.69
-.25**
.00
.02
.07
-.08
-.05
.03
.33**
-.04
11. Tenure with Team
2.15
.84
-.04
.07
-.02
-.07
.06
.00
-.20**
.08
.03
.04
12. Creative Role Identity
5.44
1.08
.02
-.14*
.07
.27**
-.10
.16*
.14*
-.01
-.01
-.09
-.14*
13. Creative Self-efficacy
5.28
1.15
-.04
-.09
.09
.37**
-.18**
.14*
.13*
.00
.03
-.05
-.19**
.71**
14. Positive Feedback
4.46
1.21
-.04
.09
-.26**
-.10
.05
-.03
-.03
-.02
.04
-.05
.07
.04
.05
Note. N=225. p<.10. *p<.05. **p<.01. All tests 2-tailed.
TABLE 3. Multiple Hierarchical Regression on Creativity, Task-Processes, and Meta-Processes in Study 1.
Variables
Creativity
Task-Processes
Meta-Processes
Model 1
Model 2
Model 1
Model 2
Model 1
Model 2
b (SE)
b (SE)
b (SE)
b (SE)
b (SE)
b (SE)
Gender
-.09 (.14)
-.08 (.13)
-.05 (.17)
-.09 (.15)
-.11 (.15)
-.09 (.15)
Age
-.01 (.02)
-.02 (.02)
.00 (.02)
-.01 (.02)
-.00 (.02)
.00 (.02)
Education
-.11 (.14)
-.10 (.12)
.01 (.16)
.04 (.15)
-.13 (.14)
-.14 (.14)
Tenure with Company
-.04 (.03)
-.02 (.02)
.04 (.03)
.06 (.03)
-.01 (.03)
-.02 (.03)
Tenure with Team
.04 (.09)
.06 (.08)
.02 (.10)
.02 (.09)
.01 (.09)
.01 (.09)
Creative Role Identity
.10 (.09)
.08 (.08)
.01 (.11)
-.02 (.10)
.08 (.09)
.10 (.09)
Creative Self-efficacy
.08 (.09)
.07 (.08)
.44 (.10)**
.41 (.09)**
-.25 (.09)**
-.24 (.09)**
Positive Feedback
-.09 (.06)
-.03 (.05)
-.18 (.07)*
-.12 (.06)
.14 (.06)*
.11 (.06)
Negative Feedback
-.24 (.07)**
.48 (.11)**
-.29 (.08)**
.52 (.13)**
.42 (.07)**
.08 (.13)
D1 (bottom-up=0; top-down=1)
-.57 (.20)**
3.66 (.63)**
-.16 (.23)
3.78 (.75)**
.50 (.20)*
-1.01 (.71)
D2 (bottom-up=0; lateral=1)
-.43 (.18)*
3.52 (.61)**
-.57 (.21)**
4.49 (.72)**
.57 (.19)**
-1.71 (.68)*
Negative Feedback×D1
-1.03 (.15)**
-.94 (.18) **
.36 (.17)*
Negative Feedback×D2
-.97 (.15)**
-1.26 (.18)**
.57 (.17)**
F
2.61**
7.41**
5.52**
10.09**
5.24**
5.58**
ΔF
2.61**
29.96**
5.52**
27.65**
5.24**
6.08**
R2
.12
.31
.22
.38
.21
.26
ΔR2
.12
.19
.22
.16
.21
.05
Note. N=225. p<.10. *p<.05. **p<.01. All tests 2-tailed.
TABLE 4. Means, Standard Deviations, and Correlations of Variables in Study 2.
Variables
M
SD
1
2
3
4
5
1. D1 (bottom-up=0; top-down=1)
.37
.48
2. D2 (bottom-up=0; lateral=1)
.28
.45
-.48**
3. Negative Feedback
.50
.50
-.03
-.28
4. Task-Processes
4.88
1.65
-.05
-.11*
-.04
5. Meta-Processes
3.61
1.82
.03
.02
.16**
-.32**
6. Creativity
3.79
1.29
-.17**
.01
-.07
.53**
-.43**
Note. N=356. *p<.05. **p<.01. All tests 2-tailed. Negative Feedback (neutral feedback=0, negative feedback=1).
TABLE 5. Multiple Hierarchical Regression on Creativity, Task-Processes, and Meta-Processes in Study 2.
Variables
Creativity
Task-Processes
Meta-Processes
Model 1
Model 2
Model 1
Model 2
Model 1
Model 2
b (SE)
b (SE)
b (SE)
b (SE)
b (SE)
b (SE)
Negative Feedback
-.20 (.14)
.96 (.22)**
-.17 (.17)
.82 (.29)**
.60 (.19)**
-.04 (.32)
D1 (bottom-up=0; top-down=1)
-.60 (.16)**
.21 (.21)
-.46 (.21)*
.29 (.29)
.22 (.23)
-.25 (.32)
D2 (bottom-up=0; lateral=1)
-.28 (.17)
.78 (.23)**
-.64 (.22)**
.18 (.30)
.23 (.24)
-.31 (.34)
Negative Feedback×D1
-1.55 (.30)**
-1.46 (.40)**
.90 (.45)*
Negative Feedback×D2
-2.08 (.32)**
-1.61 (.43)**
1.06 (.48)*
F
5.31**
13.04**
3.40*
5.82**
3.60*
3.38**
ΔF
5.31**
23.62**
3.40*
9.20**
3.60*
3.00
R2
.04
.16
.03
.08
.03
.05
ΔR2
.04
.11
.03
.05
.03
.02
Note. N=356. †p<.10. *p<.05. **p<.01. All tests 2-tailed. Negative Feedback (0=neutral feedback; 1=negative feedback).
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APPENDIX
Negative (Positive) Feedback (reference=supervisor/peers/followers)
1. In the performance appraisal, [reference] told me that I didn’t (did) do a good job.
2. In the performance appraisal, [reference] criticized (praised) my work.
3. In the performance appraisal, [reference] gave me negative (positive) feedback.
4. In the performance appraisal, [reference] told me that my performance is not (is)
up to the standard.
5. In the performance appraisal, [reference] told me that my performance is poor (excellent).
6. In the performance appraisal, [reference] indicated that [reference] is not (is) happy with
my work.
7. In the performance appraisal, [reference] gave me many criticisms (compliments).
Task-Processes
1. This feedback helped me pay more attention to how I conduct my tasks.
2. This feedback helped me think about strategies that I could use to improve my task
performance
3. This feedback made me wonder whether there were different approaches I could use to do
better on my tasks.
4. This feedback made me improve the processes involved in completing my tasks.
Meta-Processes (reference=supervisor/peers/followers)
1. This feedback made me care about how I presented myself to my [reference].
2. This feedback made me be more self-conscious about the way I look by my [reference].
3. This feedback made me worry about the impression my [reference] has to me.
4. This feedback made me think about how my [reference] might perceive me.
5. This feedback made me concern how my [reference] evaluates my abilities or weaknesses.
Feedback text used in Study 2
7
I am actually just finishing reading a book about creativity and it gave some good advice. If you
want to think "outside the box," you may want to think about broad categories first, rather than
focusing on detailed ideas. For example, on the coffee break topic you may start thinking w ideas
related to at least three broad categories (eg employees, HR system, or supervisors). Then focus
on one category & generate ideas within that category. For example: for the HR system, think
about some rules/regulations that prevent the problem. If you cannot come up with creative ideas
within the category, you can go on to the next category.
Another thing they said is that good ideas sometimes combining two or more categories. Eg:
initiate a contest where employees generate ideas about effective HR regulations to solve the
problem. This provides an opportunity that employees think about their behaviors as well as HR
policy for preventing such behaviors. (This would be related to both employee and HR system
categories.)
The book also talks about the importance of persistence I mentioned that you can jump into
other categories when you feel you cannot generate creative ideas within a certain category,
please do not give up too easily. Sometimes, you can suddenly come up with good ideas when
you put more efforts within the category
7
Note that in this text, grammatical errors were intended.
Authors’ Biographical Sketches
Yeun Joon Kim (y.kim@jbs.cam.ac.uk) is Assistant Professor of Organizational Behavior at
Judge Business School, University of Cambridge. He received his Ph.D. from the University of
Toronto, his M.S. and B.A. from Seoul National University and another B.A. from Yonsei
University. His research interests include creativity, leadership, and culture.
Junha Kim (kim.7333@osu.edu) is a doctoral student in marketing at Fisher College of
Business, Ohio State University. He received his BA and MS from KAIST. His research interests
generally focus on consumer judgment and decision making.
... First, we measured and controlled for positive feedback to disentangle the effects of negative feedback in this study. Although some studies have treated positive and negative feedback as opposite ends of a continuum, the two can occur relatively independently in organizations (Kim and Kim, 2020;Steelman et al., 2004). That is, a supervisor may simultaneously provide positive feedback on some tasks while giving negative feedback on others. ...
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