Content uploaded by Bernd Carette
Author content
All content in this area was uploaded by Bernd Carette on Feb 23, 2016
Content may be subject to copyright.
Running head: LEARNING FROM OTHERS’ FAILURES
LEARNING FROM OTHERS’ FAILURES:
THE EFFECTIVENESS OF FAILURE-STORIES FOR MANAGERIAL LEARNING
Ronald Bledow
Singapore Management University
Bernd Carette
Ghent University
Jana Kühnel
Ulm University
Diana Pittig
Kienbaum Consulting
Manuscript accepted for publication at Academy of Management Learning & Education
Acknowledgements. We would like to thank the editor, three anonymous reviewers, and our
colleagues who provided feedback to earlier versions of the manuscript: Michael Bashshur,
Devasheesh Bhave, Kraivin Chintakananda, Roy Chua, Don Ferrin, Mengzi Jin, Jochen Reb,
Samantha Sim, and Kenneth Tai.
Abstract
We argue that failures of other people provide a neglected source of managerial learning
that is associated with enhanced learning transfer. Due to their negative valence, stories about
other peoples’ failures as compared to stories about other peoples’ successes should elicit a more
pronounced motivational response such that people elaborate the content of failure stories more
actively. As a consequence, the knowledge gained from failure stories will more likely be
applied on a transfer task. We expect this motivational response to failure stories and its benefits
for learning to be most pronounced for people who view failures as valuable learning
opportunities. We report an experimental study, in which participants were exposed to a
managerial training with stories about either managerial successes or managerial failures that
delivered the same learning content. Results showed that stories about managerial failures led to
more elaboration and learning transfer, in particular for participants who see the learning
potential of failures. We discuss how failure stories can be used to stimulate managerial learning
in educational and organizational settings.
Keywords: Vicarious Learning, Management Education, Failure, Errors, Motivation,
Transfer
LEARNING FROM OTHERS’ FAILURES 3
The wise man learns from the mistakes of others. (Otto von Bismarck)
In management education, consensus is growing regarding the critical role of experience
for learning (Klimoski & Amos, 2012). A vast body of research has reported developmental
effects of going through direct, first-hand managerial experiences (e.g., DeRue, Nahrgang,
Hollenbeck, & Workman, 2012; Eddy, Tannenbaum, & Mathieu, 2013; Erez et al., 2013; Ng,
Van Dyne, & Ang, 2009). Yet, people also go through managerial experiences indirectly by
listening to, reading about, and observing other people’s behavior and its consequences.
Vicarious learning supplements direct, personal experience and enables people to draw lessons
from a wide scope of experiences within short time frames (Hoover, Giambatista, & Belkin,
2012). Learning from others vicariously may be especially useful in the case of failures as
learners can then evade similar failures and adverse personal and organizational consequences.
Indeed, others’ failure has proven to be a fundamental source of learning for individuals and
organizations across a variety of contexts (e.g., the railroad industry, Baum & Dahlin, 2007;
firestations, Joung, Hesketh, & Neal, 2006; hospitals, KC, Staats, & Gino, 2013; the financial
industry, Kim & Miner, 2007; and the aerospace industry, Madsen & Desai, 2010).
Despite the learning potential inherent to others’ failures, vicarious learning in
management education focuses primarily on successful firms and managerial role models.
Bestselling managerial books and case studies such as Jim Collin’s (2001) “Good to Great” or
General Electric’s success story during Jack Welch’s reign are expressions of a one-sided focus
on other people’s successes. The “undersampling of failure” entails that “aspiring managers
observe the practices of top managers, but they may not observe the practices of those
individuals who fail to be promoted” (Denrell, 2003, p. 227). The prevalent focus on managerial
success stories suggests that current learning practices fall short of fully utilizing the learning
LEARNING FROM OTHERS’ FAILURES 4
potential inherent to other people’s experiences. A one-sided focus on others’ successes at the
expense of their failures may hinder the development of managerial competence not only
because of the specific lessons learners could derive from failures but also because of how
learners respond differently to success and failure. In line with fundamental psychological
research suggesting that bad events have more profound psychological consequences than good
events (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001), people may actually learn more
and retain a more elaborate memory of other people’s failures as compared to their successes.
The aim of the current paper is to compare the learning potential of other people’s failure
and success experiences in the context of management education. We argue that due to the
difference in affective valence between stories about failures and successes, people (1) elaborate
more on and therefore (2) transfer more knowledge from managerial failure stories as compared
to managerial success stories. People’s attitude towards failure is discussed as boundary
condition for how effectively people learn from failure. We test these hypotheses with an
experimental study on a managerial skill training that exposed learners either to stories about
managerial successes or managerial failures and compared consequences for learning. The article
thereby contributes to the understanding of the psychological underpinnings of learning and
informs management educators on the importance of incorporating managerial failures in the
design of courses.
THEORETICAL BACKGROUND AND DEVELOPMENT OF HYPOTHESES
Learning from others’ experiences
A fundamental form of learning occurs via the observation of others’ behavior and its
consequences (Bandura, 1977). Vicarious learning enables people to acquire complex sequences
of behavior without executing the behavior. An important component of vicarious learning is the
LEARNING FROM OTHERS’ FAILURES 5
positive or negative consequences associated with a model’s behavior (Lockwood, Jordan, &
Kunda, 2002). These consequences increase or decrease the likelihood that an observer will
replicate the model’s behavior (Manz & Sims Jr, 1981). Vicarious learning is not limited to
social learning among individuals; it also plays an important role for organizational learning. The
literature on organizational learning has focused primarily on how organizations learn
vicariously from a model’s success (Sitkin, 1992) and has shown that organizations acquire
knowledge vicariously and replicate routines, strategies, and designs of other successful
organizations (e.g., Burns & Wholey, 1993; Ingram & Baum, 1997).
Recently, scholars have paid increasing attention to learning from others’ failure. For
instance, Joung et al. (2006) showed that exposing firefighters to case studies of experienced
employees who committed errors on the fire ground yields more adequate courses of actions and
better problem identification on a post-training task, as compared to exposing firefighters to case
studies of experienced employees who did not make errors. In a sample of 71 cardiothoracic
surgeons who completed more than 6,500 cardiac procedures over the course of 10 years, KC et
al. (2013) examined how vicarious learning reduced patient mortality and found that surgeons
learn more from others’ failures than from others’ successes. Recent research on organizational
learning in the financial and aerospace industries suggests that organizations learn more
effectively from others’ failure than from others’ success and that knowledge gained from
others’ failure experiences depreciates more slowly (Baum & Dahlin, 2007; Kim & Miner, 2007;
Madsen & Desai, 2010). As noted by Kim and Miner (2007, p. 687), failure and near-failure of
firms can serve as “wake-up calls, encouraging survivors to search for new actions or to devise
new business models or routines.”
Vicarious learning in management education
LEARNING FROM OTHERS’ FAILURES 6
The widespread use of case studies, benchmarking initiatives, video vignettes, and real-
life observations in educational as well as in organizational settings shows that vicarious learning
is a corner stone of managerial learning (Christensen & Carlile, 2009; Grossman, Salas, Pavlas,
& Rosen, 2013; Hoover et al., 2012). However, as noted by Mauboussin (2012, p. 52), “the most
common method for teaching business management is to find successful businesses, identify
their common practices, and recommend that managers imitate them.” Indeed, an examination of
The Case Centre’s top 40 bestselling cases revealed that although cases typically describe a
manager whose organization is facing a challenging situation that could lead to failure, virtually
all of the cases turned into successes for the organization. Examples of these successful
organizations include McKinsey, Apple, Zara, Canon, and Virgin. This emphasis on managerial
success stories at the expense of failure stories suggests that management educators have not yet
incorporated emerging evidence on the learning potential of failure stories into their teaching
practices.
We use the terms ‘failure stories’ and ‘success stories’ to refer to narratives of specific
examples of managerial failure and success. Such stories typically describe a real or realistic
organizational setting and a chain of events from the point of view of a particular manager,
employee, or set of actors (Goodman & O’Brien, 2012). Failure stories are narratives in which a
protagonist reports an erroneous course of action that eventually led to a negative outcome. By
choosing the wrong actions or by failing to perform the right actions, the outcomes the
protagonist intended were not achieved. Conversely, success stories contain a description of a set
of actions that led to intended outcomes. In both cases the narrator establishes a causal link
between actions and their consequences. As these consequences are positive for success stories
LEARNING FROM OTHERS’ FAILURES 7
and negative for failure stories, a critical difference between success and failure stories resides in
their affective valence.
The following scenario, which we used in the experimental study reported below,
illustrates the concept of success and failure stories. The scenario tells the story of an
entrepreneur who wanted to open a coffee shop that sells novel coffee creations. In the success
story condition, the entrepreneur spent money on a market analysis to evaluate the best location
for the coffee shop. At first, the entrepreneur wanted to open the new business near a university,
but the results of the market analysis showed that students are not willing to spend a premium on
exclusive coffee creations. As a consequence, the entrepreneur opened the coffee shop in the city
center and it became a successful business. In the failure-story condition, the entrepreneur
decided not to spend money on a market analysis and opened the coffee shop near the university.
As students could not afford expensive coffee creations, the business had to close after a few
months. As this example illustrates both stories communicate the same knowledge about
effective managerial practices; they differ in whether this knowledge is embedded in a success or
failure story. We argue next that the difference in affective valence between success and failure
stories results in different motivational responses and learning outcomes.
The effectiveness of failure stories for managerial learning
The phrase “bad is stronger than good”, coined by Baumeister and colleagues (2001),
refers to a fundamental observation which forms the basis of our hypothesis regarding the
effectiveness of failure stories for managerial learning. The phrase aptly summarizes the
pervasive finding that bad events have more profound psychological consequences than good
events. People pay more attention to, engage in more thinking about, and retain a more elaborate
memory of negative as compared to positive events. Moreover, punishment has stronger effects
LEARNING FROM OTHERS’ FAILURES 8
on learning than rewards in such a way that people learn more rapidly and more easily from
punishment (e.g., Abele, 1985; Robinson-Riegler & Winton, 1996). According to Baumeister et
al. (2001), the underlying reason for the stronger reaction to adverse events is evolutionary
adaptation: The potential costs of not reacting to a single adverse event, which may threaten
survival, are higher as compared to not reacting to a single positive event such as an opportunity
to obtain a reward. Thus, the tendency to show a more pronounced motivational response to
adverse events and to process negative information more thoroughly is an adaptive characteristic
of the psychological system.
Most studies on how people respond to adversity have focused on personal rather than
vicarious experience (Seery, Leo, Lupien, Kondrak, & Almonte, 2013). For instance, Bledow,
Schmitt, Frese, and Kühnel (2011) argued that people respond to adverse work events including
failures with an affective shift and high work motivation. In an experience sampling study with
software engineers, the authors showed that participants displayed the highest level of work
engagement when they experienced adverse events such as failures and a subsequent shift to
positive mood. Further studies showed that people are often motivated to generate new ideas
after experiencing or recollecting an adverse event in an attempt to find novel solutions after
available responses have failed (Bledow, Rosing, & Frese, 2013). The common thread of these
studies is that people display a motivational response to the negative affective valence of the
adverse event.
The present study extends this line of inquiry to the situation where people are confronted
with others’ experiences and investigates the learning potential of other people’s failures on
complex managerial tasks that led to negative consequences. We hypothesize that the negative
valence of failure stories will result in a motivational response on the side of the listener to
LEARNING FROM OTHERS’ FAILURES 9
elaborate the information conveyed by the stories. Stories about other people’s experiences can
be processed on an elaboration continuum from a peripheral to a central route depending on a
person’s motivation, ability, and attitude (Petty & Wegener, 1999). We argue that failure stories
are more likely than success stories to activate the central route so that learners are motivated to
allocate cognitive resources and intensively elaborate on the content of the stories. More
specifically, failure stories should seize attention and elicit reflection so that the learner actively
decomposes the story and analyzes the critical elements that were responsible for failure. This
intensive elaboration which is induced by the negative valence of failure stories should lead to
adaptations of a person’s action-related knowledge for similar situations (Kuhl, 2000). As a
result, the newly acquired knowledge is accessible at later points in time, when a person is in a
relevant situation. By contrast, the positive valence of success stories should elicit processing via
the peripheral route so that the content is processed only superficially and has less impact on the
learner’s future actions (cf. Schwarz & Bless, 1991).
As a result of enhanced elaboration of relevant information, knowledge that is learned
from listening to failure stories should more likely be applied on a transfer task as compared to
knowledge that is learned from success stories. A protagonist’s actions that led to failure will be
associated with failure and a person should refrain from using these actions in similar situations.
Critical courses of actions that were omitted by the protagonist will be encoded as significant for
the situation and a person should be more likely to engage in them when faced with a similar
situation. Our line of argument is illustrated by one of the failure stories we used in the
experiment. In the failure story, a leader narrates about a project team she was responsible for
that developed a new product and ultimately failed. She explains that one of the reasons for
failure was that she failed to ensure heterogeneity of skills among team members. In the success-
LEARNING FROM OTHERS’ FAILURES 10
story she explained that one of the reasons for the success of the team was that she composed a
heterogeneous team. We argue that framing the story as a failure will elicit elaboration on the
importance of heterogeneity so that listeners integrate this information in their knowledge on
team effectiveness. At a later point in time, when listeners are in a similar situation that involves
composing a team, they will consider heterogeneity of team members. For the success story, we
argue that less attention is paid to heterogeneity as a distinctive cause of success. The stream of
the narrator’s story is not decomposed and analyzed for the critical elements. As a consequence,
it is less likely that the learner integrates the information and applies it on a transfer task. We
thus propose:
Hypothesis 1. Failure stories lead to more learning transfer than success stories.
We expect that people respond to failure stories with a heightened level of elaboration,
which in turn leads to enhanced learning transfer (see Figure 1). We use the concept of
elaboration to refer to the extent that people allocate cognitive resources and display self-directed
learning when processing vicarious experiences (Petty & Cacioppo, 1986). Elaboration implies
that people focus their attention on the stories and process their content via the central rather than
the peripheral route. In the case of vicariously learning from failure stories, people show
elaboration if they reflect on causes of failure, consider alternative and more successful courses
of action, and construct generalizable knowledge on effective actions in similar situations. By
elaborating on failure stories learners integrate other people’s experience in their repertoire of
experiences and derive lessons for future situations they may encounter. The integration of
learning content into one’s personal knowledge base through active elaboration is critical for
learning transfer (Frese, 1995; Kozlowski et al., 2001).
LEARNING FROM OTHERS’ FAILURES 11
Stories that describe successful vicarious experiences, by contrast, should be associated
with less elaboration and, as a consequence, lower learning transfer, even if the stories convey
the same information. The actions of the protagonist and their positive consequences will be
processed more peripherally due to the absence of negative, failure-related information. A
learner will thus show less elaboration directed at deriving lessons from the stories for effective
future actions. The downside of low elaboration associated with success stories should become
apparent when the knowledge conveyed by the story could be applied on a transfer task.
Knowledge transfer requires that people have developed flexible and generalizable knowledge
structures by means of elaboration, which allows them to not merely reproduce information but
to apply and adapt knowledge to novel tasks.
Hypothesis 2. Elaboration mediates the effect of failure stories on learning transfer.
Individual differences in learning from failure stories: the role of error orientation
According to the aptitude-treatment-interaction framework, the effectiveness of
instructional methods depends on characteristics of the learner (Snow, 1989). The framework
suggests that optimal learning results when the instruction is matched to the aptitudes of the
learner. We argue that learners’ attitude towards failure influences the motivational response
they display when exposed to failure stories and its consequence for learning transfer. The more
people are able to evaluate failure not only as something negative but also as a valuable source of
learning, the more should they elaborate failure stories and display subsequent learning transfer.
Differences in people’s attitude toward failures are captured by the concept of error orientation
(Rybowiak, Garst, Frese, & Batinic, 1999). A high error orientation indicates that people have
formed a complex attitude towards failure, which acknowledges that failures, as inherently
negative and undesirable events, are also associated with positive consequences such as learning.
LEARNING FROM OTHERS’ FAILURES 12
A high error orientation thus does not relativize and embellish failure but indicates a balanced
and adaptive evaluative tendency towards failure.
We posit that error orientation moderates the effect of failure stories on elaboration and
learning transfer. People with a high error orientation should readily pay attention to and be
motivated to learn from failures. They respond to the negative valence of failure stories by
elaborating on their content as they associate positive learning consequences with failure
experiences. People with a low error orientation, by contrast, see little value in elaborating the
information that is conveyed by failure stories. Although the negative valence of failure stories
should also seize their attention, they will engage in less elaboration, as they do not associate
positive learning consequences with failure experiences. Empirical evidence on the important
role people’s attitude plays for learning from failures is provided by the literature on error
management training (Keith & Frese, 2008). Error management training influences learner’s
attitude so that they see errors as valuable learning opportunities. Experimental studies have
shown that error management training improves learning and learning transfer as it enhances
cognitive and motivational processes when people commit errors (Keith & Frese, 2005).
Hypothesis 3a. Error orientation moderates the effect of failure stories on elaboration
such that failure stories have a stronger effect on elaboration for people with high error
orientation.
Hypothesis 3b. Error orientation moderates the mediated effect of failure stories via
elaboration on learning transfer such that failure stories have a stronger mediated effect
for people with high error orientation.
LEARNING FROM OTHERS’ FAILURES 13
METHOD
Participants and procedure
Fifty students of the social sciences participated in the study. It was announced with
notices on campus and introduced as a training on managerial skills, which was provided to
students free of charge. The sample was composed of 60% woman. Mean age was 23.62 (SD =
3.85). The study simulated a classroom setting and was administered in sessions with up to 6
participants. Participants worked on all tasks individually and did not interact during the study.
They were first asked to fill in a questionnaire and to solve a short managerial case study. The
case study was used to determine if there were baseline differences in the ability to solve case
studies between experimental conditions. Next, participants were randomly assigned to either the
failure story or the success story condition. After the training, which lasted approximately one
hour, participants solved a managerial case study to measure learning transfer.
Experimental conditions
Participants were trained on principles of effective management that were
communicated through stories told by fictional managers. Principles of effective management
referred to managerial tasks such as recognizing changes, analyzing a market, managing time
effectively, dealing with conflict, and providing leadership. These principles were based on
textbooks of organizational behavior. In order to train participants on these principles, fictional
stories were written by the authors. Five stories were constructed that described a scenario, the
actions of managers, and their consequences. Each story was then read as a first-person narrative
by a different actor, who played the role of the manager. Stories were recorded for later use in
the experiment. During the experiment, the five stories were played successively and
LEARNING FROM OTHERS’ FAILURES 14
accompanied by presentation slides that summarized the main content of the stories. After each
story participants answered a set of questions. Participants were asked to write down what the
manager had done, how they perceived the manager, and what they could learn from the case
study. The answers provided by participants were used as manipulation check and to assess
elaboration.
The experimental manipulation was achieved by embedding principles of effective
management in either success stories or failure stories. The structure of the scenarios and the
training content were the same for both conditions; they differed only in the positive or negative
valence of the outcome. In the success-story condition, managers told the listeners how they
recognized changes, analyzed the market, managed time effectively, dealt with conflict, or
provided leadership and reported that their actions led to positive outcomes. In the failure-story
condition, managers narrated how they failed to take the right actions (i.e., recognize changes,
analyze the market, etc.) and reported the detrimental consequences of these failures. Thus, in
both conditions narrators communicated the same knowledge about effective management and
established an explicit link between the actions of managers and the positive or negative
consequences. Moreover, with respect to other features of the stories such as length, level of
detail, and the speaker who narrated the story, both conditions were the same.
Measurement
Error orientation. Error orientation was measured with two subscales of the Error
Orientation Questionnaire by Rybowiak et al. (1999) which each consisted of four items. The
two subscales referred to learning from errors (e.g. “My mistakes help me to improve my work”)
and error risk taking (e.g. “If one wants to achieve at work, one has to risk making mistakes”).
Participants indicated their agreement on a scale ranging from “1= not at all” to “5= fully”. We
LEARNING FROM OTHERS’ FAILURES 15
focused on the two subscales learning from errors and error risk taking as they referred to
participants’ attitudes toward errors. Other subscales of the error orientation questionnaire refer
to people’s ability to cope with errors, which was not relevant because the study focused on
vicarious learning. The eight items of the two subscales loaded on a common factor and the two
subscales were correlated with r = .46 (p < .01). We therefore combined the two subscales.
Cronbach’s alpha of the combined scale was .85.
Baseline performance. A short case study was used to examine participants’ baseline
performance and to rule out pre-test differences between the conditions. Participants had to take
the perspective of the manager of a fashion store and make decisions drawing on the information
they were provided with. The case study did not contain any information that was related to the
content of the failure and success stories. Two independent raters rated the quality and detail of
participants’ case solution using a coding scheme. Interrater reliability of participants scores in
pre-test performance was ICC = .89.
Manipulation check. We asked participants three question after each story to examine
the effectiveness of the manipulation. The first question was an attention check and asked
participants to identify wrong actions in the failure-story condition (‘What did Mr. / Mrs. … do
wrong?’) and right actions in the success-story condition (‘What did Mr. / Mrs. … do right?’).
All participants identified at least one experimentally manipulated wrong or right action for each
story. We next asked two questions to examine whether the difference in affective valence
between success and failure stories influenced participants’ affective evaluation of the storyteller.
Participants assessed how much sympathy they had for the managers on a five point scale
between high sympathy and no sympathy at all and how easily they could put themselves in the
manager’s place on a five point-scale between very easily and not easily at all. We assumed that
LEARNING FROM OTHERS’ FAILURES 16
the negative valence of failure stories should translate to a more negative evaluation of the
protagonist so that participants report less sympathy and are less likely to identify with the
protagonist’s actions. In support of this reasoning, there were significant differences between
conditions. Across the five stories, participants in the failure-story condition reported lower
sympathy (M = 3.42 vs. M = 3.11, t [48] = 2.20, p = .031) and found it less easy to put
themselves in the manager’s place as compared to the success story condition (M = 3.69 vs. M =
3.10, t [48] = 2.71, p = .009). The difference in affective valence of the stories, which we
manipulated by framing stories as failures versus successes, thus had an impact on participants’
affective evaluation of the storyteller. This does not imply, however, that elaboration and
learning transfer are a function of participants’ affective evaluation of the storyteller, which we
view as a byproduct of the experimental manipulation. A strong negative evaluation of the
protagonist may turn participants’ attention away from the content of the stories when they see
no relevance of the protagonists’ actions for themselves. Results indeed showed that participants’
affective evaluation of the protagonists was unrelated to elaboration and learning transfer.
Elaboration. After listening to each story, participants in both conditions were asked the
open-ended question ‘What can you learn from this case study?’. The question focused
participants’ attention on the story they had just heard and elicited reflection. By answering the
question, participants elaborated on the content of the stories and connected it to existing
knowledge repertoires and personal goals. For instance, participants elaborated on how the
actions the protagonist did or did not perform could inform their own actions when in a relevant
situation, such as creating a new business. We asked participants to write down their thoughts as
a list of learning points they could derive from the case study. We used the number of distinct
learning points which were related to the content of the case studies as a quantitative measure of
LEARNING FROM OTHERS’ FAILURES 17
how intensively participants had elaborated on the stories (cf. Ellis & Davidi, 2005). A rater
examined the content of what participants’ had written down and counted the number of
distinctive learning points. Participants generated on average 3.21 (SD = .93) learning points for
each story.
Learning transfer. After listening to the stories, participants received a case study about
an advertising agency and were asked to work on the case study by answering five questions.
The five questions addressed managerial decisions the head of the agency had to make, which
were related to the topics that had been the subject of the success and failure stories. For
instance, participants had to plan a meeting with an employee in which they had to dismiss the
employee. This question was thematically related to a story regarding an interview with an
employee on frequent costumer complaints. Knowledge was transferred from the stories if
participants used elements of the stories to answer the case study. For instance, in the success-
story the manager had announced the meeting in such a way that the employee could prepare,
while the manager in the failure-story had failed to do so. If participants indicated on the transfer
task that they would prepare the employee for the meeting, they displayed learning transfer. Two
independent raters, who did not know in which condition participants had been trained, coded
participants’ responses. They used a coding scheme to determine how many elements of the
stories participants applied on the transfer task. The coding scheme defined three to five
elements for each story of the training. On average, participants applied 8.45 elements of the
training on the transfer task (SD = 2.93). The reliability of the average number of elements
counted by the two raters was ICC = .90.
Non-transferred knowledge. To further strengthen the research design, we obtained a
non-equivalent dependent variable for which we did not expect an effect of the training
LEARNING FROM OTHERS’ FAILURES 18
conditions. The two raters counted the number of actions participants suggested to solve the
transfer task that were not related to the principles of effective management communicated
through the failure or success stories. This variable reflects knowledge on managerial actions
participants had accumulated from other sources than the training. This knowledge should
therefore not be affected by the training condition. Participants named on average 7.48 additional
elements (SD = 3.60). Interrater reliability was ICC = .92.
RESULTS
Table 1 displays descriptive statistics and intercorrelations between the study variables.
Comparison of group means showed higher elaboration (t[48] = 6.22, p < 0.01) and learning
transfer (t[48] = 2.37, p = 0.02) in the failure story condition. The effect size of the manipulation
on learning transfer was d = 0.67. Table 2 displays regression models with elaboration and
learning transfer as outcomes. We included the control variables baseline performance and GPA
to examine if the manipulation and its interaction with error orientation had an effect above and
beyond these established predictors of learning. In support of Hypothesis 1, Model 1 shows that
the failure-story condition led to higher learning transfer than the success-story condition after
inclusion of the control variables (b = 1.67, p = .04). As shown in Model 5, failure stories also
led to higher elaboration than success stories (b = 1.47, p < .01). To test whether elaboration
mediated the effect of the experimental manipulation on learning transfer, we added elaboration
in Model 2 and 3 and used bootstrapping analysis. In support of Hypothesis 2, bootstrapping
analysis showed that the indirect effect of the experimental manipulation on learning transfer via
elaboration was significant (indirect effect: 1.45; 95% confidence interval: 0.39-2.73), whereas
there was no direct effect of the experimental condition on learning transfer. Elaboration thus
LEARNING FROM OTHERS’ FAILURES 19
mediated the differential effect of the experimental manipulation: Failure stories led to more
elaboration and, as a consequence, to higher learning transfer.
To test the assumption that failure stories have a specific effect on learning transfer, we
examined whether the experimental condition had an effect on the non-equivalent dependent
variable non-transferred knowledge. A comparison of group means showed that there was no
significant difference between experimental conditions on the amount of non-transferred
knowledge participants used to solve the case study (t[48] = 0.39, p = .70). Moreover, the
variable non-transferred knowledge was unrelated to the mediator elaboration (r = .15, p = .31).
These results confirm that failure stories as compared to success stories had a specific effect on
learning transfer related to the knowledge participants had acquired from the failure or success
stories.
Hypothesis 3 posited that individual differences in error orientation moderate the effect of
failure stories on elaboration and learning transfer. In support of Hypothesis 3a, the interaction
between the experimental condition and error orientation explained incremental variance in
elaboration (Model 6). The simple slope of error orientation and elaboration was significantly
positive in the failure-story condition (b = .68, p = .02) and non-significant in the success-story
condition (b = -0.18, p = .53). Thus, participants with a high error orientation elaborated more in
response to failure-stories as compared to participants with a low error orientation, while there
were no significant differences in the success-story conditions. The interaction between
experimental condition and error orientation also explained significant variance in learning
transfer (Model 4). As illustrated by Figure 2, the simple slope between error orientation and
learning transfer was significantly positive (b = 2.33, p = .01) for the failure-story condition and
significantly negative (b = -2.24, p = .01) for the success-story condition. While these results
LEARNING FROM OTHERS’ FAILURES 20
support our argument that people with a high error orientation learn more from failure stories
than people with a low error orientation, they also suggest that people with a high error
orientation learn less from success stories.
We next performed moderated mediation analyses using the procedure by Hayes (2013)
to directly test whether the indirect effect of failure stories on learning transfer, which was
mediated by elaboration, was moderated by error orientation (Hypothesis 3b). The conditional
indirect effect of the training condition was significant at p < .05 for high (1.54, confidence
interval: .03-3.77) and low (0.76, confidence interval: .09-1.92) levels of the moderator error
orientation. The index for moderated mediation was significant when a one-sided test of
significance was used (0.68, 90% confidence interval: 0.02-2.21). The indirect effect of failure
stories was stronger for people with a high error orientation. Results thus support the hypothesis
that failure stories lead to enhanced learning transfer for people with a high error orientation
because they show higher elaboration.
DISCUSSION
In support of the reasoning that failure stories stimulate deep information processing and
result in enhanced learning transfer, we found that listening to others’ managerial failures led to
more elaboration as compared to listening to other people’s managerial successes. Intensified
elaboration, in turn, yielded higher transfer of newly acquired knowledge to a subsequent task.
This effect was more pronounced for people who see failure as a valuable source of learning.
Our findings complement the literature in meaningful ways and hold important
implication for management education. Although a growing body of evidence points to the
important role of vicarious learning from others’ failures (e.g., Joung et al., 2006; KC et al.,
2013; Kim & Miner, 2007), this is to our knowledge the first study that extends this line of
LEARNING FROM OTHERS’ FAILURES 21
research to the context of management education. Moreover, the study contributes theoretically
by informing the literature on why failure can result in beneficial learning outcomes. As failure
and success stories conveyed the same learning content and differed only in the way it was
presented, framing of the learning content as a failure triggered the motivation to process the
stories more thoroughly. Learners responded to the negative valence of failure stories with
increased elaboration, which then resulted in enhanced learning. The study thus supports the
assumption that a motivational mechanism is at play and yields the learning benefits associated
with being exposed to others’ failures.
Results on the moderating role of error orientation showed that the motivational response
to failure stories is a function of people’s attitude towards failure. People with a high error
orientation, who see the learning potential of failures, showed more elaboration and learning
transfer when listening to failure stories. We would like to stress that a high error orientation
does not imply that failures are seen simply as positive events. If this were the case, there should
be no pronounced motivational response to failure in the first place, as this response is triggered
by the negative valence of failure stories. Indeed, in order to learn from failure stories people
need to be sensitive to the negative valence of failure (Baumann, Kaschel, & Kuhl, 2007). The
critical process that differentiates people on the error orientation dimension is how they respond
once a failure has been detected. Rather than showing a passive response, such as being
overwhelmed by or ignoring failure, people high in error orientation display an active and
adaptive response by elaborating on and drawing lessons from failure. Interestingly, we also
found that people with a high error orientation learned less from success stories than people with
a low error orientation. Given the small sample size and that we did not expect this result,
inferences should be drawn only tentatively. The finding could imply that a high error orientation
LEARNING FROM OTHERS’ FAILURES 22
is associated with less motivation to replicate successful experiences. Such a tendency would be
dysfunctional insofar as people acquire less successful routines by observing others; however,
there may also be benefits involved if people focus on generating their own behavioral responses
rather than relying on what is proven and tested (Kirton, 1976).
Limitations of the present study are that the affective and cognitive processes that link
failure and success stories to learning transfer could be captured only partially and that we
examined learning transfer only within the setting of our study. With respect to cognitive
processes, we measured only the overall level of elaboration participants displayed and could not
conduct a fine-grained analysis of qualitative differences in how people processed failure as
compared to success stories. Future research is needed to unpack the process of elaborating on
failure and success stories that underlies effective vicarious learning and to test our assumption
that people integrate the content of failure stories differently into their existing knowledge. With
respect to people’s affective reaction to failure stories, we showed that the manipulation led to a
more negative evaluation of the narrator. However, we did not directly measure participants’
affective response to the negative valence of failure stories, which presumably triggered greater
elaboration. Such responses typically occur fast and implicitly and cannot adequately be assessed
by self-report measures (Quirin, Kazen, & Kuhl, 2009). Regarding inferences from our study
about learning transfer, we would like to point to the uncertainty of whether the knowledge
communicated by failure stories had a lasting effect on participants’ memory and whether they
made use of it outside of our study’s setting.
In order to gain a more complete picture of managerial learning from experience, an
important avenue for future research is to compare vicarious learning from success and failure
with learning from personal success and failure. Our theoretical approach suggests that the basic
LEARNING FROM OTHERS’ FAILURES 23
motivational mechanism is the same insofar as people display a more pronounced response to
failure as compared to success. However, personal failure is more threatening for the individual
and should thus elicit stronger negative emotions and can lead to defensive reactions instead of
adaptive learning processes (Gross & John, 2003). Moreover, different cognitive processes are
likely to follow people’s initial affective reaction depending on whether failure is experienced
first-hand or vicariously. When the reason for failure is ambiguous, people will show different
attribution patterns in explaining why a failure occurred (Weiner, 1985): Personal failure will
more likely be attributed to the context, whereas failure of others will more likely be attributed to
the other person. This bias in attribution patterns should render others’ failure as compared to
personal failure particularly effective for learning, as failure is then viewed as the consequence
of an actor’s behavior, which could have been evaded by engaging in a different set of behaviors.
In their study on surgeons, KC et al. (2013) indeed showed that people effectively learned from
others’ failure but often failed to learn from their own failure.
Using failure stories to enhance managerial learning
Our theoretical rationale and the results of our study suggest that a shift towards using
failure stories more systematically can enhance managerial learning in formal as well as informal
learning settings. We contrasted learning from failure stories with learning from success stories
to highlight the specific advantage of the former; however, this should not be misunderstood as a
general recommendation to replace success stories with failure stories. Although not directly
examined in the current study, we expect that both failure stories and success stories serve
important functions for learning and that educators need to make informed decisions on when to
use and how to integrate success and failure stories.
LEARNING FROM OTHERS’ FAILURES 24
Success stories serve as inspirational examples and can teach learners effective behaviors
(Bandura, 1977). Success stories show that managerial success is attainable and can build a
learners’ confidence in their abilities, in particular when they see similarities between themselves
and a role model. Thereby approach motivation to strive towards becoming equally successful
can be stimulated. Success stories may also be particularly effective for teaching concrete
behavioral routines. For instance, Gino, Argote, Miron-Spektor, and Todorova (2010) found that
observing people who are successful at an origami exercise had a more positive impact on a
learner’s performance as compared to observing people who were unsuccessful. For the
acquisition of behavioral routines such as meticulous hand movements, paying close attention to
and imitating a role model may be more important than cognitive elaboration. Managerial tasks
are, however, typically complex and the set of behaviors that is effective depends on the specific
situation so that the mere replication of a behavior that has been successful elsewhere is not
sufficient.
Managerial learning requires more than imitating behavioral routines. Failure stories may
be particularly effective in learning contexts where learners need to intensively elaborate a topic
to develop differentiated and flexible knowledge structures that allow them to respond to unique
managerial challenges in a context sensitive manner. Examples are strategic choices managers
have to make such as whether they focus the dominant activity of an organization on refining
existing organizational products and processes or on the exploration of new opportunities
(Bledow, Frese, Anderson, Erez, & Farr, 2009; Gupta, Smith, & Shalley, 2006). For many
interpersonal situations, such as negotiations with customers or dealing with difficult employees
or co-workers, routine one-best-way solutions are equally insufficient. Failure stories that
stimulate elaboration may help learners to develop the knowledge and heuristics to deal with
LEARNING FROM OTHERS’ FAILURES 25
such managerial challenges. In contrast to the stories we used in the experiment, in which we
explicitly mentioned the cause of success and failure, real failure stories are often ambiguous
regarding the cause of failure. Generating hypotheses about the reason for failure is then a
critical part of the learning process. Indeed, a shortcoming of many success stories is that they
often readily provide a simplified interpretation of why success was achieved and do not
encourage learners to challenge this interpretation, even though the true reasons for success are
often unclear. For instance, the bestselling book ‘Good to Great’ (Collins, 2001) we mentioned
in the introduction has been criticized on the grounds that the evidence it provides for the reasons
why companies have moved from ‘good’ to ‘great’ is weak (Levitt, 2008).
Failure stories may also be particularly effective when learners lack the motivation to
elaborate on a subject because they underestimate its difficulty. Failure stories could then serve
as wake up calls and draw learners’ attention to the importance of the subject. Teachers of
organizational behavior, for instance, frequently face the problem that students view topics as
easy and intuitive and overestimate their abilities in managing others and themselves. A good
example of a failure story that can be used to address this problem is the popular Harvard
Business School case on Erik Peterson. The case tells the story of a new, conscientious and hard-
working MBA, who takes on his first job in a start-up setting and, after a series of events and
problematic decisions, ends up getting fired. Teachers using this failure story have observed that
it helps to raise students awareness of the complexities involved in leadership and management
and stimulates engaged class-discussions on what went wrong and how the protagonist could
have more effectively handled the challenges he faced.
Embedding failures in case studies or constructing entire case studies about failures
allows educators to standardize learning material and at the same time stimulate self-directed
LEARNING FROM OTHERS’ FAILURES 26
learning. By presenting a group of learners with the same managerial failures, and by letting
them explore and evaluate the reason of failure individually or in groups, the inductive learning
benefits that characterize self-directed learning approaches may be combined with the
standardization benefits that characterize guided learning methods. Depending on the learning
objective, case-writers and instructors can focus on standardization and communicate evidence-
based principles of management with failure stories that establish an explicit link between
actions and their consequences or can emphasize inductive learning. To stimulate inductive
learning, failure stories can communicate failure and its negative consequences but refrain from
stipulating only one interpretation of the causes of failure and instead present context-rich
information that lends itself to different interpretations. In classroom settings, students can then
engage in collective sense making by developing and controversially discussing alternative
views on the causes of failure. Our study suggests that the use of failure stories in classroom
settings will benefit if instructors improve students’ attitude towards failure and instigate an error
orientation by explicitly mentioning and letting students directly experience the value of learning
from others’ failure.
The content of failure stories that are gathered by case writers and educators need to be
evaluated carefully1. First, failure stories should be drawn from the most common and recurring
scenarios that trap managers and should focus on actions that consistently have detrimental
consequences (e.g. giving negative feedback in public, rewarding poor performers). A fruitful
avenue for future research is to systematically identify such scenarios and actions. Second,
failure stories need to be authentic and well-targeted for different audiences such as young
graduates or senior executive to be relatable. Third, the knowledge that is communicated by
failure stories should be backed by systematic evidence. Due to their effectiveness for learning,
LEARNING FROM OTHERS’ FAILURES 27
failure stories may also stimulate effective learning of the wrong content. When failure stories
communicate a manager’s subjective interpretation of a chain of events rather than generalizable
and evidence-based principles of management, learners may derive wrong inferences about
effective management.
A challenge for the use of failure stories for managerial learning may be their availability.
There can be costs involved for the protagonist when communicating failure stories and the
learning benefit resides with the listener. Managers who have experienced failure first-hand may
hesitate to share failure stories in order to avoid being viewed as incompetent, which is likely
one of the reason for the undersampling of failure in management education. Case writers may
thus find it difficult to gain access to failure stories and employees miss out on valuable learning
opportunities if failure stories are withheld in their organization. Although our study has shown
that the narrators of failure stories were indeed evaluated more critically, this process is arguably
more complex in real-world settings and may even be reversed. Protagonists who have a history
of successes and are generally viewed as competent may even be viewed in a more positive and
humane light if they also share their failure stories.
At a broader level, our results suggest that organizations may foster a culture in which
employees at all organizational levels are willing to share their erroneous actions that have
caused failures (van Dyck, Frese, Baer, & Sonnentag, 2005). The top-management team of an
organization can set a powerful example by openly discussing past failures. Organizations can
also institutionalize communication about failures by providing a platform for employees to
share failed experiences. For instance, After-Event Review sessions can be implemented and
their content can be documented and made publically available to other members of an
organization. After-Event Reviews are meetings of employees and their managers that are
LEARNING FROM OTHERS’ FAILURES 28
typically held after a project or task has been completed. They provide an opportunity to reflect
upon and discuss erroneous and successful courses of actions. An encouraging example of the
use of failure stories for entrepreneurial learning is the concept of ‘F***UpNights’, which has its
roots in Mexico and has quickly spread to many countries—it is thus, ironically, a success story
(http://f***upnights.com). A group of friends had spontaneously started to share their
entrepreneurial experiences, in particular their failures, and realized how fruitful this exchange
was. Today, these events are typical evening events that take place in informal locations such as
bars and give people the opportunity to go on a stage and share and discuss their failed attempts
to build businesses with the audience. Another promising example is the award winning Fail
Forward initiative (http://failforward.org), aimed at assisting organizations in embracing the
potential of sharing failure stories within and across organizations.
Conclusion
The full opening quote of this article reads ‘Only fools learn from their own mistakes.
The wise man learns from the mistakes of others’. We did not examine and would question the
validity of the first part of the quote, however, in line with a growing body of research we found
support for the quote’s second part. Drawing lessons from other people’s failures is a particularly
effective but underused form of learning. Hence, the best practice for learning from others’
experience in educational and organizational settings is to focus not only on others’ best but also
on their worst practices—and to share with others not only one’s success but also one’s failure
stories.
LEARNING FROM OTHERS’ FAILURES 29
REFERENCES
Abele, A. 1985. Thinking about thinking: Causal, evaluative and finalistic cognitions about
social situations. European Journal of Social Psychology, 15(3): 315-332.
Bandura, A. 1977. Social Learning Theory. Englewood-Cliffs, NJ: Prentice Hall.
Baum, J. A. C., & Dahlin, K. B. 2007. Aspiration performance and railroads ' patterns of learning
from train wrecks and crashes. Organization Science, 18(3): 368-385.
Baumann, N., Kaschel, R., & Kuhl, J. 2007. Affect sensitivity and affect regulation in dealing
with positive and negative affect. Journal of Research in Personality, 41(1): 239-248.
Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. 2001. Bad is stronger than
good. Review of General Psychology, 5(4): 323-370.
Bledow, R., Frese, M., Anderson, N., Erez, M., & Farr, J. 2009. A dialectic perspective on
innovation: Conflicting demands, multiple pathways, and ambidexterity. Industrial and
Organizational Psychology: Perspectives on Science and Practice, 2: 305–337.
Bledow, R., Rosing, K., & Frese, M. 2013. A dynamic perspective on affect and creativity.
Academy of Management Journal, 56(2): 432-450.
Bledow, R., Schmitt, A., Frese, M., & Kühnel, J. 2011. The affective shift model of work
engagement. Journal of Applied Psychology, 96: 1246–1257.
Burns, L. R., & Wholey, D. R. 1993. Adoption and abandonment of matrix management
programs: Effects of organizational characteristics and interorganizational networks.
Academy of Management Journal, 36: 106-138.
LEARNING FROM OTHERS’ FAILURES 30
Christensen, C. M., & Carlile, P. R. 2009. Course research: Using the case method to build and
teach management theory. Academy of Management Learning & Education, 8(2): 240-
251.
Collins, J. C. 2001. Good to great: Why some companies make the leap--and others don't:
Random House.
Denrell, J. 2003. Vicarious learning, undersampling of failure, and the myths of management.
Organization Science, 14(3): 227-243.
DeRue, D. S., Nahrgang, J. D., Hollenbeck, J. R., & Workman, K. 2012. A Quasi-Experimental
Study of After-Event Reviews and Leadership Development. Journal of Applied
Psychology, 97(5): 997-1015.
Eddy, E. R., Tannenbaum, S. I., & Mathieu, J. E. 2013. Helping teams to help themselves:
Comparing two team-led debriefing methods. Personnel Psychology, 66(4): 975-1008.
Ellis, S., & Davidi, I. 2005. After-event reviews: Drawing lessons from successful and failed
experience. Journal of Applied Psychology, 90(5): 857-871.
Erez, M., Lisak, A., Harush, R., Glikson, E., Nouri, R., & Shokef, E. 2013. Going global:
Developing management students' cultural intelligence and global identity in culturally
diverse virtual teams. Academy of Management Learning & Education, 12(3): 16-41.
Frese, M. 1995. Error management in training: Conceptual and empirical results. In C.
Zucchermaglio, S. Bagnara, & S. U. Stucky (Eds.), Organizational learning and
technological change: 112-124. Berlin: Springer.
Gino, F., Argote, L., Miron-Spektor, E., & Todorova, G. 2010. First, get your feet wet: The
effects of learning from direct and indirect experience on team creativity. Organizational
Behavior and Human Decision Processes, 111(2): 102-115.
LEARNING FROM OTHERS’ FAILURES 31
Goodman, J. S., & O’Brien, J. 2012. Teaching and learning using evidence-based principles. In
D. M. Rousseau (Ed.), The Oxford Handbook of Evidence-Based Management: 309-
337. New York: Oxford University Press.
Gross, J. J., & John, O. P. 2003. Individual Differences in Two Emotion Regulation Processes:
Implications for Affect, Relationships, and Well-Being. Journal of Personality and
Social Psychology, 85(2): 348-362.
Grossman, R., Salas, E., Pavlas, D., & Rosen, M. A. 2013. Using instructional features to
enhance demonstration-based training in management education. Academy of
Management Learning & Education, 12(2): 219-243.
Gupta, A. K., Smith, K. G., & Shalley, C. E. 2006. The interplay between exploration and
exploitation. Academy of Management Journal, 49(4): 693-706.
Hayes, A. F. 2013. Introduction to mediation, moderation, and conditional process analysis: A
regression-based approach. New York: Guilford Press.
Hoover, J. D., Giambatista, R. C., & Belkin, L. Y. 2012. Eyes On, Hands On: Vicarious
Observational Learning as an Enhancement of Direct Experience. Academy of
Management Learning & Education, 11(4): 591-608.
Ingram, P., & Baum, J. A. C. 1997. Opportunity and constraint: Organizations' learning from the
operating and competitive experience of industries. Strategic Management Journal, 18(s
1): 75-98.
Joung, W., Hesketh, B., & Neal, A. 2006. Using "war stories" to train for adaptive performance:
Is it better to learn from error or success? Applied Psychology-an International Review-
Psychologie Appliquee-Revue Internationale, 55(2): 282-302.
LEARNING FROM OTHERS’ FAILURES 32
KC, D., Staats, B. R., & Gino, F. 2013. Learning from my Success and from others' Failure:
Evidence from minimally invasive cardiac surgery. Management Science, 59(11): 2435-
2449.
Keith, N., & Frese, M. 2005. Self-Regulation in Error Management Training: Emotion Control
and Metacognition as Mediators of Performance Effects. Journal of Applied Psychology,
90(4): 677-691.
Keith, N., & Frese, M. 2008. Effectiveness of error management training: A meta-analysis.
Journal of Applied Psychology, 93(1): 59-69.
Kim, J.-Y., & Miner, A. S. 2007. Vicarious learning from the failures and near-failures of others:
Evidence from the U.S. commercial banking industry. Academy of Management
Journal, 50(3): 687-714.
Kirton, M. 1976. Adaptors and innovators: A description and measure. Journal of Applied
Psychology, 61(5): 622-629.
Klimoski, R., & Amos, B. 2012. Practicing evidence-based education in leadership development.
Academy of Management Learning & Education, 11(4): 685-702.
Kozlowski, S. W. J., Toney, R. J., Mullins, M. E., Weissbein, D. A., Brown, K. G., & Bell, B. S.
2001. Developing adaptability: A theory for the design of integrated-embedded training
systems. In E. Salas (Ed.), Human/technology interaction in complex systems, Vol. 10.
Greenwich: CT: JAI Press.
Kuhl, J. 2000. A functional-design approach to motivation and self-regulation: The dynamics of
personality systems interactions. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.),
Handbook of self-regulation: 111-169. San Diego, CA: Academic Press.
LEARNING FROM OTHERS’ FAILURES 33
Levitt, S. D. 2008. From good to great... to below average.
http://freakonomics.com/2008/07/28/from-good-to-great-to-below-average/ (accessed on
02/23/2015).
Lockwood, P., Jordan, C. H., & Kunda, Z. 2002. Motivation by positive or negative role models:
Regulatory focus determines who will best inspire us. Journal of Personality and Social
Psychology, 83(4): 854-864.
Madsen, P. M., & Desai, V. 2010. Failing to learn? The effects of failure and success on
organizational learning in the global orbital launch vehicle industry. The Academy of
Management Journal, 53(3): 451-476.
Manz, C. C., & Sims Jr, H. P. 1981. Vicarious learning: The influence of modeling on
organizational behavior. Academy of Management Review: 105-113.
Mauboussin, M. J. 2012. The True Measures of Success. Harvard Business Review, 90(10): 46-
56.
Ng, K.-Y., Van Dyne, L., & Ang, S. 2009. From experience to experiential learning: Cultural
intelligence as a learning capability for global leader development. Academy of
Management Learning & Education, 8(4): 511-526.
Petty, R. E., & Cacioppo, J. T. 1986. The Elaboration Likelihood Model of persuasion. In L.
Berkowitz (Ed.), Advances in Experimental Social Psychology Vol. 19: 123-205. New
York: Academic Press.
Petty, R. E., & Wegener, D. T. 1999. The elaboration likelihood model: Current status and
controversies. In S. Chaiken, & Y. Trope (Eds.), Dual Process Theories in Social
Psychology: 41-72. New York: Guilford Pres.
LEARNING FROM OTHERS’ FAILURES 34
Quirin, M., Kazen, M., & Kuhl, J. 2009. When nonsense sounds happy or helpless: The Implicit
Positive and Negative Affect Test (IPANAT). Journal of Personality and Social
Psychology, 97(3): 500-516.
Robinson-Riegler, G. L., & Winton, W. M. 1996. The role of conscious recollection in
recognition of affective material: Evidence for positive-negative asymmetry. The
Journal of General Psychology, 123(2): 93-104.
Rybowiak, V., Garst, H., Frese, M., & Batinic, B. 1999. Error Orientation Questionnaire (EOQ):
reliability, validity, and different language equivalence. Journal of Organizational
Behavior, 20(4): 527-547.
Schwarz, N., & Bless, H. 1991. Happy and mindless, but sad and smart? The impact of affective
states on analytic reasoning. In J. P. Forgas (Ed.), Emotion and social judgments: 55-71.
Elmsford, NY: Pergamon Press.
Seery, M. D., Leo, R. J., Lupien, S. P., Kondrak, C. L., & Almonte, J. L. 2013. An upside to
adversity?: moderate cumulative lifetime adversity is associated with resilient responses
in the face of controlled stressors. Psychological Science, 24(7): 1181-1189.
Sitkin, S. B. 1992. Learning through failure: The strategy of small losses. Research in
Organizational Behavior, 14: 231-266.
Snow, R. E. 1989. Aptitude-treatment interaction as a framework for research on individual
differences in learning. In P. L. Ackerman, R. J. Sternberg, & R. Glaser (Eds.), Learning
and individual differences: Advances in theory and research 13-58. New York
Freeman.
LEARNING FROM OTHERS’ FAILURES 35
van Dyck, C., Frese, M., Baer, M., & Sonnentag, S. 2005. Organizational error management
culture and its impact on performance: A two-study replication. Journal of Applied
Psychology, 90(6): 1228-1240.
Weiner, B. 1985. An attributional theory of achievement motivation and emotion. Psychological
Review, 92(4): 548.
LEARNING FROM OTHERS’ FAILURES 36
FOOTNOTES
1We thank an anonymous reviewer for pointing this out.
LEARNING FROM OTHERS’ FAILURES 37
TABLE 1. Descriptive statistics and correlations
1. Experimental
condition
2. Error
orientation
3. Elaboration
4. Learning
transfer
5. Non-transf.
knowledge
6. Baseline
performance
7. Age
8. Gender
9. GPA
1. Experimental condition1
-
2. Error orientation
-.02
-
3. Elaboration
.67**
.11
-
4. Learning transfer
.32*
-.01
.42**
-
5. Non-transfer. knowledge
.06
.10
.15
-.13
-
6. Baseline performance
.17
.01
.31*
.24†
.23
-
7. Age
.06
-.09
.02
.19
-.28*
-.13
-
8. Gender
-.20
.06
-.22
-.24†
.01
-.31*
.05
-
9. GPA
.06
.02
.24†
.17
.28*
.22
-.47**
-.04
-
Total sample
M
0.50
3.86
3.14
8.45
7.48
4.10
23.62
0.40
2.04
SD
0.50
0.58
1.18
2.93
3.61
1.34
3.48
0.50
0.54
Failure-Story Training
M
1.00
3.85
3.88
9.35
7.67
4.32
23.85
0.31
2.00
SD
0.00
0.56
0.98
2.82
4.00
1.22
2.82
0.47
0.57
Success-Story Training
M
0.00
3.86
2.33
7.47
7.27
3.85
23.38
0.50
2.07
SD
0.00
0.61
0.76
2.79
3.19
1.45
4.77
0.51
0.52
Note: 1 Experimental condition: 0 = success stories, 1 = failure stories; Gender: 0 = women, 1 = men; GPA: higher values indicate
better grades; N = 50; ** p < .01. * p < .05. † p < .10.
LEARNING FROM OTHERS’ FAILURES 38
TABLE 2. Hierarchical multiple regression
Dependent variables
Learning transfer
Elaboration
Independent variables
Model 1
Model 2
Model 3
Model 4
Model 5
Model 6
Constant
6.11 (1.32)**
7.45 (1.32)**
7.16 (1.45)**
6.50 (1.34)**
1.80 (0.40)**
1.79 (0.40)**
GPA
0.61 (0.75)
0.28 (0.74)
0.33 (0.76)
0.57 (0.70)
0.36 (0.23)
0.37 (0.22)
Baseline performance
0.36 (0.31)
0.24 (0.31)
0.25 (0.31)
0.33 (0.28)
0.14 (0.09)
0.14 (0.09)
Experimental condition1
1.67 (0.80)*
-
0.52 (1.05)
1.15 (0.99)
1.47 (0.24)**
1.47 (0.24)**
Elaboration
0.94 (0.35)*
0.78 (0.47)†
0.40 (0.46)
Error Orientation
-2.19 (0.86)*
-0.18 (0.28)
Error Orientation X
Experimental Condition
4.28 (1.30)**
0.86 (0.40)*
Model R²
.15
.19
.20
.36
.51
.57
F(df)
2.72 (3,46)*
3.70 (3,46)*
3.70 (4,45)*
4.07 (6,43)
15.97 (3,46)**
11.62 (5,44)**
ΔR2
.08*
.12*
.01
.16**
.38**
.06*
Note: Learning transfer is the dependent variable for Models 1 through 4; Elaboration is the dependent variable for Models 5 and 6.
Values are unstandardized parameter estimates for regression weights (standard errors in parenthesis). 1 Experimental condition: 0 =
success stories, 1 = failure stories; ΔR2 : Change in variance explained by the predictors experimental condition, elaboration, and error
orientation.
N = 50; ** p < .01. * p < .05 † p < .10
FIGURE 1
Model of the effect of failure vs. success stories on learning transfer
Failure Stories
vs.
Success Stories
Elaboration
Error Orientation
Learning Transfer
FIGURE 2
The moderating role of error orientation
