Innovation failure: An explorative field study about its adverse effects on employees’ innovation motivation and failure allowance climate as a buffer
Magnus J. Klages S2540746
University of Groningen July 2019
Supervisor: Suqing Wu
Abstract
While innovation has become increasingly important for organizations to guarantee
Innovation failure: An explorative field study about its adverse effects on employees’ innovation motivation and failure allowance climate as a buffer
I have not failed. I’ve just found 10,000 ways that won’t work.
—Thomas Edison, The Fabulous Drone The role of innovation, defined as the development of novel and useful ideas and their
implementation into a new and improved product, service, or process (Amabile, 1996; Baer, 2012; Van de Ven, 1986), as a source of growth and competitive advantage over other organizations, has been emphasized and confirmed by many scholars (e.g., Dess and Picken, 2000; Tellis, Prabhu, & Chandy, 2009; Tushman & O’Reilly, 1996). However, as Thomas Edison implies in his words, an inherent part of the innovation process is experimentation, where for one successful innovation there also must be developed an immense amount of useless creations first. While the world-famous inventor calculates the number to be much higher, it has been estimated by researchers that in the process of innovation out of 3000 ideas only one becomes a commercial success (Stevens and Burley, 1997). Thus, while innovation is a vital tool for a company’s survival, the nature of its process likewise implies that the majority of employees’ ideas get rejected and will never be implemented.
Furthermore, companies often have to abandon innovation projects due to strategic
management decisions (e.g., Sawang & Matthews, 2010). In the current research, I refer to innovation failure as the abandonment of an innovative initiative, such as a project or work task that has the goal of generating a creative idea and successfully developing it into a new process or product, before the final outcome is finished and introduced to the organization’s procedures or the market.
attention to the fact that innovation failure is associated with negative outcomes, such as hampered learning (Shepherd, Covin & Kuratko, 2009), negative emotions (Shepherd & Cardon, 2009) or even ‘innovation trauma’ – the inability to commit to a new innovation project (Välikangas, Hoegl & Gibbert, 2009). Accordingly, whereas unsuccessful attempts to innovate are inevitable for companies to survive in competitive markets, they can potentially affect employees in adverse ways, which can hinder subsequent innovation initiatives. Thus far, it has not been studied how innovation failures relate to employees’ innovation
motivation, here defined as the motivation to engage in innovation behaviour. Yet, it is important to investigate this relationship in order to guide organizations on how to prevent and mitigate potential negative effects of innovation failures.
Therefore, the current study sets out to explore whether innovation failure is linked to employees’ innovation motivation (Hypothesis 1). Drawing on self-efficacy theory (Bandura, 1997), I propose that employees form negative expectancies of future innovation outcomes, because they attribute innovation failures to their creative abilities, subsequently lowering their motivation to innovate (Hypothesis 2). Finally, this study explores failure allowance climate, the extent to which failure is regarded as an acceptable outcome of a project
(Mahlendorf, 2013), as a moderator in this relation. The argument for this link will be based on research that has emphasized the positive sides of ‘no blame’ approaches for organizations (Provera, Montefusco & Canato, 2010).
initiatives, and its influence on innovation motivation. The motivational perspective of this paper, therefore, offers knowledge to understand the topic more comprehensively and precisely. Meanwhile, as behaviours are driven by motivation (e.g., Gagne & Deci, 2005; Ryan & Deci, 2000), it is of vital importance to first address the relation between innovation failure and innovation motivation before one can explore how the innovative behaviours are affected. Therefore, the current study also paves the way for research of innovative
behaviours. Second, this research will test the mediating role of creative self-efficacy in the relation of innovation failure and innovation motivation, potentially uncovering employee’s belief in their creative abilities as a psychological mechanism that underlies this link. Third, this research will examine the influence of organizations’ failure allowance climate in the proposed mediated relationship and uncover whether organizations can use allowance for failures as a tool to mitigate potential adverse effects. Thus, while contributing to an extension of the innovation and failure research, this research will also be a signpost for managerial actions to tackle adverse effects of innovation failures.
Theory
Innovation failure affects creative self-efficacy
beliefs, while failure provides information that undermines it. Past theoretical papers (e.g., Newton, Khanna, and Thompson, 2008) and a considerable body of empirical studies have linked failure experiences to self-efficacy (e.g., Hackett & Campbell, 1987; Lebeau et al., 2018). Early experimental studies by Campbell and Hackett (1986; Hackett & Campbell, 1987) showed that students in the failure condition had lower self-efficacy ratings than students in the success condition subsequent to multiple trials of anagram or mathematics tasks. Studies testing individuals performing physical tasks also showed that reported self-efficacy decreased with failure and increased with success (Lebau et al., 2018; Spink, Brawley & Gyurcsik, 2016).
In this paper, I propose that innovation failure negatively relates to employees’ creative self-efficacy, referred to as the extent to which one believes that one has the ability to produce creative outcomes (Tierney & Farmer, 2002). Creative self-efficacy is an expanded, more specific concept of self-efficacy, which relates more directly to creativity and innovation. In situations described in the following employees might attribute innovation failure to a lack of creative abilities. First, in the initial stages of innovation employees generate and further develop ideas. However, they might fail to convince co-workers or managers that these ideas should be turned into a new product or process. This might either be due to a lack of good ideas, lack of persuasiveness or because their ideas are perceived as too original and “crazy” (Rietzschel, Nijstad, & Stroebe, 2010). Despite the reasons for their failure, employees might attribute the unsuccessful outcome to the quality of their ideas and, thus, a failure on their part to come up with ideas that are good enough to be implemented. Second, if innovation projects get abandoned during the implementation phase employees might feel like they were not competent enough to find solutions to finalize the project. They might rationalize a project termination based on the quality of the solutions they produced, or on their
further below, these internal attributions of failures might be especially strong, when the climate of an organization emphasizes failure as something to be avoided and something that people are blamed for (Lupton & Warren, 2018).
Innovation failure affects innovation motivation through creative self-efficacy According to Bandura (1997), self-efficacy theory has a motivational component, insofar that self-efficacy influences people’s motivation by shaping their outcome
expectancies. This is an extension of expectancy-value theories (e.g., Atkinson, 1957), which hold that people are generally motivated when they expect successful and valuable outcomes (Atkinson, 1957). Self-efficacy influences expectancies of successful and valuable outcomes by making people believe more strongly or less strongly that their actions will produce desired outcomes. On the one hand, people with low self-efficacy perceive difficult tasks as threat that they do not feel capable to overcome, have low aspirations and low commitment to their goals. On the other hand, people with high self-efficacy beliefs perceive difficult tasks as challenges that they are motivated to overcome. They expect successful outcomes due to their capabilities to achieve them and attribute failures to lack of effort instead of lack of ability. Hence, people with strong self-efficacy beliefs are more motivated to engage in goal-directed behaviours than those with weak self-efficacy beliefs.
I propose that the same relation exists between creative self-efficacy and innovation motivation, based on past research that has found a positive links between self-efficacy and innovation behaviour (e.g., Klaeijsen, Vermeulen & Martens, 2018; Hsu, Hou & Fan, 2011), which is defined as an employee’s generation and implementation of new ideas within organization (Scott & Bruce, 1994). For instance, Yu and Chen (2016) found that
Labiance, 2017) as well as creativity in the workplace (e.g., Jaussi, Randel, & Dionne, 2007; Tierney & Farmer, 2011). Researchers have argued that creative self-efficacy affects
innovative behaviour positively for two reasons. First, people with strong creative self-efficacy believes feel more confident in their abilities to produce and implement creative ideas (Jiang & Gu, 2017), which subsequently makes them more resilient towards opposition (Grosser et al., 2017). Second, they will view opposition and adversity not as threats but as challenges that they want to overcome (Bandura, 1997). Consequently, they are more
motivated to persist when defending their creative ideas and when overcoming difficulties to realize their ideas (Grosser et al., 2017).
Thus, based on self-efficacy theory I argue that employees try to seek reasons for performance outcomes in the innovation process. One reason they will likely attribute outcomes to are their own creative abilities. In the event of failure, employees then adapt their creative self-efficacy, such that they lower their beliefs. In turn, they expect that their creative efforts are less likely to lead to successful outcomes, consequently being less motivated to engage in innovative behaviours. Based on this argumentation, I propose the following hypotheses:
Hypothesis 1: Innovation failure is negatively related to employee innovation motivation.
Hypothesis 2: The negative relationship between innovation failure and innovation motivation is mediated by creative self-efficacy, such that innovation failure negatively relates to creative self-efficacy, which relates positively to innovation motivation.
The moderating role of failure allowance climate
mankind of the same by proclaiming his standpoint to others. Similarly, some organizations, such as Google, adopt strategies where failure is an active part of the process, and especially in the innovation process employees are allowed or even encouraged to fail (Mahlendorf, 2013). Thus, failure allowance climate can potentially play a positive moderating role in the proposed mediation. Accordingly, researchers have highlighted that failures should be received with tolerance (Danneels, 2008; Sullivan & Snodgrass, 1991) and dealt with in a supportive rather than a threatening manner (Senatra, 1980). Provera et al. (2010) emphasize that using a ‘no blame’ approach can shift the focus away from identifying employees as wrongdoers, thereby reducing blame and feelings of shame.
Studies have supported the positive sides of failure allowance, showing that when research scientists perceived their organization as normalizing failure they experienced fewer negative emotions (Shepherd, Patzelt & Wolfe, 2011) as well as finding that allowance for failure can reduce perceived threat in the case of project failure (Mahlendorf, 2013). Other research has confirmed that failure can lead to learning in educational contexts (Alfi, Assor & Katz, 2004; Fong et al., 2018) and organizational contexts (Lupton, & Warren, 2018), but only if the conditions foster a positive rather than negative perception of the failure experiences.
ideas are rejected or the projects they are invested in fail. In effect, they will retain their innovation motivation. However, in organizations, where scapegoats are actively looked for and the negativity towards failures gives a strong negative performance feedback, creative self-efficacy is likely to suffer when innovation initiatives fail. As a result, employees innovation motivation will likewise suffer. Thus, I predict a first-stage moderation of the previously proposed mediation:
Hypothesis 3: The relation between innovation failure and innovation motivation via creative self-efficacy is moderated by failure allowance climate. Specifically, when failure allowance climate is high compared to low, the negative association between innovation failure with innovation motivation via creative self-efficacy will be weaker.
Method
Participants and procedure
For this study, one-hundred and eighty-three (N = 183) paid participants signed up through the online platform Amazon Mechanical Turk (MTurk). In exchange for taking part in the study, which took on average 406 seconds to complete (SD = 313), respondents received $2. The participants sample had an average age of M = 39.14 (SD = 9.82), average tenure in years of M = 7.9 (SD = 5.75) and consisted of 35% women and 65% men of which 99.5% were Canadian and .5% indicated ‘other’ as their nationality. The sample consisted of 78.7% respondents with a bachelor’s degree or higher and 21.3% with a high school degree or lower education.
Measures
The battery of main measures consisted of self-created scales for innovation failure and failure allowance climate, because pre-existing measures for these constructs were not available due to the absence of prior research on this topic. However, battery included adaptations of validated scales for innovation motivation (Tierney, Farmer & Graen, 1999) and creative self-efficacy (Tierney & Farmer, 2002). After computing the reliability of items that belonged to one scale, the scores of the items for each scale were averaged to compute the final scale scores for each participant. While the main measures are briefly described in the following paragraphs, Appendix A displays the participant instructions for each scale and the specific phrasings of the items that were used.
Innovation failure. Innovation failure was assessed with a self-created four-item scale measuring the extent to which participants were involved in terminated innovation projects during the past 12 months. Participants were asked to indicate to what extent they agree with the statements (e.g. “In the past 12 months I was part of many failed innovation projects”; α = .80) on a seven-point Likert scale (1 = strongly agree, 4 = neither agree nor disagree, 7 = strongly disagree).
Creative self-efficacy. Creative self-efficacy was measured with a three-item scale developed by Tierney, and Farmer (2002) that reflects the degree to which a respondent is confident in his or her creative abilities. Participants were asked to indicate their extent of agreement with the statements (e.g. “I feel that I am good at generating novel ideas”; α= .89) on a seven-point Likert scale (1 = strongly agree, 4 = neither agree nor disagree, 7 = strongly disagree).
Participants were asked to indicate their extent of agreement with the statements (e.g. “I intend to create new procedures for work tasks.”) on a seven-point Likert scale (1 = strongly agree, 4 = neither agree nor disagree, 7 = strongly disagree; α= .90).
Failure allowance climate. To measure the extent to which innovation failures are accepted in an organization an eight-item scale was self-created. Participants were asked to indicate their extent of agreement with the statements (e.g. “Doing things wrong is viewed as a normal part of work.”) on a seven-point scale (1 = strongly agree, 4 = neither agree nor disagree, 7 = strongly disagree; α= .86).
Control variables. In order to control for potential confounding variables, participants were also asked to indicate their gender, nationality, level of education, workplace language, size of the organization, industry, tenure, job level and innovation experience, which
measured the extent of involvement and responsibility in innovation projects (e.g. “I am often involved in innovation projects of my organization.”). These control variables were included because employees of different age groups and generations within a company might display varying responses to failure experiences and subsequent innovation motivation due to their experience differences. Similarly, employees from different industries or departments might also respond differently since some might work in more inherently innovation-related positions than others.
Results
Correlations
To gain an insight into the relations of the main variables of interest I calculated their correlations (Table 1). The independent variable innovation failure was negatively correlated with the dependent variable innovation motivation (r = -.21, p < .01) but only had a
innovation motivation and creative self-efficacy were positively correlated (r = .75, p < .01). and so were failure allowance climate and creative self-efficacy. Of the control variables innovation experience had positive correlations with innovation motivation (r = .62, p < .01), creative self-efficacy (r = .62, p < .01) and failure allowance climate (r = .23, p < .01), while participant age was negatively correlated with innovation failure (r = -.22, p < .01) and positively with creative self-efficacy (r = .15, p = .04).
Main analyses
The hypothesized main effect of innovation failure on innovation motivation
(Hypothesis 1) was tested using a simple linear regression model with innovation experience, age and organizational tenure as control variables. Tests and observations of plots showed no deviations from the assumptions of normality, homoscedasticity of residuals or
multicollinearity. The model was overall significant explaining 40.7% of the variance in innovation motivation (R² = .407, F(4,178) = 18.52, p < .001; see Table 2), where innovation failure was a significant predictor (b = -.120, p = .046). Thus, the first hypothesis that
innovation failure is negatively related to innovation motivation was confirmed by the results. The hypothesized mediation of creative self-efficacy (Hypothesis 2) in the relation of innovation failure and innovation motivation was tested in SPSS using Model 4 of the
that creative self-efficacy mediates the unconditional effect of innovation failure on innovation motivation was rejected.
However, it was further hypothesized that this mediation is dependent on the failure allowance climate, such that the negative link between innovation failure and creative self-efficacy is stronger for lower than for higher levels of failure allowance climate (Hypothesis 3). This moderated mediation model was tested in SPSS using Model 7 of the PROCESS macro (Hayes, 2013) with standardized variables. The computed regression models included innovation failure as the independent variable (X), innovation motivation as the outcome variable (Y), failure allowance climate as the moderator (W); creative self-efficacy as the mediator (M) and the same control variables as the previous analyses. The results (Table 5 and 6) show that even the moderated mediation effect is not present, as the interaction effect was non-significant on creative self-efficacy (β = .007, p = .881). In line with this there was neither a conditional indirect effect mediated by creative self-efficacy at the low failure allowance climate level (b = -.010, CI .170, .065]) nor at the high level (b = -.002, CI [-.085, .086]). Furthermore, the Index of Moderated Mediation was not significant either (β = .004, SE = .036, 95% CI [-.036, .107]). The prediction that failure allowance climate
moderates a mediation by creative self-efficacy in the relation of innovation failure on innovation motivation was therefore rejected.
In sum, the analyses revealed that innovation failure had a negative association with innovation motivation (Hypothesis 1). However, neither a simple mediation by creative self-efficacy (Hypothesis 2) nor a moderated mediation dependent on failure allowance climate (Hypothesis 3) was observed.
Exploratory analyses
wanted to test in an exploratory manner whether failure allowance moderates the main effect of innovation failure on innovation motivation. In order to do this, a regression analysis was conducted with innovation failure, failure allowance climate and their interaction as
predictors and the same control variables as in the previous analyses (Table 7). Overall, the model was significant and together the predictors explained 43.7% of the variance in innovation motivation (R² = .437, F(6,176) = 22.75, p < .001). While the main effects of innovation failure (β = -.073, p = .233) and failure allowance climate (β = -.097, p = .104) turned out to be non-significant, their interaction resulted in a significant effect (β = .106, p = .021). Further testing of the interaction (Table8) showed that the simple slope at the low level (β = -.179, SE = .067, 95% CI [-.310, -.047]) of failure allowance climate was significantly different from zero, but not at the high level (β = .033, SE = .084, 95% CI [-.132, .199]). Inspection of the plotted simple slopes confirmed these results (Figure 1). The results give a more nuanced view of Hypothesis 1, providing evidence that innovation failure is only negatively related to innovation motivation, when the failure allowance climate is low.
Discussion
Innovation is an important aspect of every organization, as it is the source of sustained competitive advantage in a globalized world (Dess and Picken, 2000; Tushman & O’Reilly, 1996). However, many innovation projects are likely to fail at some point during the
Through an online survey research, I found that innovation failure is negatively related to innovation motivation (Hypothesis 1) and, contrary to expectations, that creative self-efficacy is not a mediator of this relationship (Hypotheses 2). These findings suggest that innovation failures do not affect employees’ creative self-efficacy beliefs. Alternative explanations are discussed below. Furthermore, the results disconfirmed that failure
allowance climate plays a moderating role in the mediated relationship of innovation failure and innovation motivation (Hypothesis 3). However, exploratory analyses showed that it does have a positive moderating effect on the direct link between innovation failure on innovation motivation, providing a buffer against the negative effects of innovation failure. In detail, the less the climate is accepting and allowing for innovation failures, the more failures are negatively related to employees’ motivation to engage in innovative behaviours, while at moderate or high levels of failure allowance this negative effect is eliminated.
Theoretical implications
The current study contributes to the research literature in two ways. First, it was an initial exploration of an existing gap in the literature. Only few scientific articles have addressed the potential negative outcomes of innovation failure on employees (Shepherd & Cardon, 2009; Välikangas, et al., 2009). To the best of my knowledge, this was the first study to find that failure experiences relate negatively to motivation in the innovation context specifically. Second, this research tested the validity of self-efficacy theory (Bandura, 1997) in the innovation failure context, providing evidence that creative self-efficacy is not a
mediator on motivational outcomes. However, based on this study future research can explore alternative explanations.
In line with my hypothesis, the results show that innovation failure indeed has a
employees are likely to be less motivated due to lowered commitment in subsequent projects. I propose expectancy-value theory (e.g. Atkinson, 1957) as an underlying rational for my findings. Expectancy-value theory holds that individuals are motivated by the value that successful outcomes of their actions hold as well as by the expectancy that their actions will result in these successful outcomes. In line with this, the results show that participants most likely lowered their expectancy of success due to failure rather than having it increase or left unchanged. Employees might be demotivated because they experience rejection of their ideas, their ideas do not actually get implemented and they perceive that their efforts are not valued or simply do not have the desired effect of achieving new innovations. If employees are faced with more failures compared to successes, their expectancy of unsuccessful outcomes increases, consequently lowering their motivation to engage in the same behaviours.
More specifically, I proposed that creative self-efficacy beliefs significantly affect innovation motivation by shaping outcome expectancies based on innovation failure experiences. Past research has supported failure experience as a weakening antecedent (Campbell & Hackett, 1986; Hackett & Campbell,1987; Lebeau et al., 2018; Spink et al., 2016) and motivation as a positive consequence of self-efficacy in many different contexts (Dzewaltowski, 1989; Locke, Frederick, Lee & Bobko, 1984; Wood & Bandura, 1989) as well as in the innovation context (Hsu et al., 2011; Martens, 2018). The results of my study confirmed the positive link between creative self-efficacy and innovation motivation. However, the degree of experienced innovation failures did not relate to creative self-efficacy.
when the failure signals information about one’s own abilities, such as when someone tries to master an innovation related skill (Bandura, 1997). Failures, such as the termination of an innovation project due to absence of funding possibilities, will likely be attributed to external causes rather than lack of abilities.
Second, my study employs a broad measure of innovation failure which encompasses all stages of the process. However, in which stage of the innovation process the failure occurs, likely determines which type of self-efficacy beliefs are affected. Creative self-efficacy is more related to early stages of the innovation process where ideas are generated, while stages where ideas are developed, promoted and converted into tangible outcomes might be related to other types of self-efficacy or even group efficacy (Perry-Smith & Mannucci, 2017).
Third, while on average innovation failure might not lead to lowered creative self-efficacy, some individuals might attribute failures in the innovation process more often to their own abilities. Research from the clinical field confirms this view, showing that people with depression tend to attribute negative events to internal and stable characteristics, such as their abilities (e.g., Rubenstein, Freed, Shapero, Fauber & Alloy, 2016). Thus, when
researching the effects of innovation failure on self-efficacy, future research should take into account the type of failure, the different stages in the innovation process and individual differences.
Since failure allowance climate did not moderate any mediation of the link between innovation failure and innovation motivation by creative self-efficacy, self-efficacy theory cannot be the explanatory theoretical framework in this case (Bandura, 1997). However, the observed moderation of the direct relation between innovation failure and innovation
motivation can be explained based on expectancy-value theory (e.g. Atkinson, 1957) and the ‘no blame’ approach described by Provera et al. (2010), which is characterized by ‘a
a ‘no blame’ approach the focus shifts away from identifying employees as wrongdoers, punishment, and feelings of shame.
Applied to this research, failure allowance climate might influence how much people blame each other during innovation processes. When an organization’s failure allowance climate is low, this might create a culture of blaming, where employees experience negative consequences subsequent to occurring innovation failures. Past research supports this view, since following failures, employees can experience negative emotions (Shepherd et al., 2011) and threat (Mahlendorf, 2013), when employees perceive that their organizations do not normalize failures. Subsequently, the value associated to engagement in innovation behaviour is lowered, which in turn decreases employees’ innovation motivation. On the other hand, when the climate signals allowance of failure, blaming is likely to occur less and employees are motivated to engage in innovation behaviours after failures, because the outcome value is not lowered due to employees’ expectation that they will not receive negative consequences. Future research could address this topic by researching whether fear of negative
consequences associated with blaming mediates the link between innovation failure and innovation motivation.
Practical implications
Limitations and future research
Since this research project was the first to investigate the effects of innovation failure on innovation motivation, it used a cross-sectional correlational design. Of course, this has the drawback that inferences for causality cannot be drawn and the observed effects first need to be replicated in experimental designs, as well as longitudinal studies, before any conclusive implications can be drawn. Furthermore, the current study employed self-report measures only. Future research should use more objective measures, such as actual data from companies indicating the number of failures and more objective outcome measures. For instance, to make research on innovation failure even more practical instead of using motivation as an outcome variable, individual or team performance could be used instead.
Another drawback of this study is that the data was collected from many different companies rather than many datapoints from only a few companies or from within one single company. This has the effect that there are potentially many confounding variables and it was not possible to measure failure on the team level or organizational level. Since innovation is usually a team effort, future research should also focus on this level. In this way, it could be explored how failures are perceived by the team and how team, organizational and individual factors influence subsequent innovation motivation or performance. For instance, while this study showed no mediation by creative self-efficacy on the individual level, it might be possible that it is still relevant in the innovation failure context on the team level.
Conclusion
Further research is needed in order to investigate how innovation motivation relates to diverse types of innovation failures, what difference it makes at which stage of the innovation process the failure occurs and how different individuals react to failures. However, the
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Tables Table 1
Descriptives and Correlations
Mean SD 1 2 3 4 5 6 7
1. Innovation failure 2.96 1.14 .80
2. Innovation motivation 5.65 1.05 -.21** .90
3. Creative self-efficacy 5.73 1.03 -.13† .75** .89
4. Failure allowance climate 4.39 1.04 -.16* .27** .27** .86
5. Innovation experience 5.18 1.01 -.14 .62** .62** .23** .86
6. Age 39.12 9.82 -.22** .11 .15* .08 .13 -
7. Organizational tenure 7.19 (yrs) 5.75 -.10 .05 .03 .05 .19** .47** -
8. Duration 406 (sec) 313
Table 2
Linear Regression Analysis: Innovation Motivation Regressed on Innovation Failure
Innovation motivation (Y)
Table 3
Mediation Analysis: Test of Creative Self-Efficacy (M)
Creative self-efficacy (M) Innovation motivation (Y)
β p 95% CI β p 95% CI
LLCI ULCI LLCI ULCI
Innovation failure (X) -.028 .637 -.146 .090 -.104 .035 -.200 -.007 Creative self-efficacy (M) .578 .000 .458 .699 Innovation experience .625 .000 .508 .743 .253 .001 .132 .375 Age .135 .046 .003 .266 -.020 .717 -.129 .089 Organizational tenure -.152 .023 -.283 -.022 -.018 .746 -.126 .090 Constant .000 1.000 -.114 .114 .000 1.000 -.093 .093 R2 = .40 R2 = .61 F (4, 178) = 30.25, p < .001 F (5, 177) = 54.52, p < .001
Table 4
Mediation Analysis: Direct Effects and Indirect Effects
Direct effect Indirect effect
Effect sea 95% CI Effect sea 95% CI -.104 .049 [-.200, -.007] -.016 .041 [-.108, .052] Note. CI = confidence intervals. Mediator: Creative self-efficacy. ** p < .01, * p < .05, † p < .10.
Table 5
Moderated Mediation Analysis: Test of Creative Self-Efficacy (M) and Failure Allowance Climate (W)
Creative self-efficacy (M) Innovation motivation (Y)
β p 95% CI β p 95% CI
LLCI ULCI LLCI ULCI
Innovation failure (X) -.011 .862 -.132 .111 -.104 .035 -.200 -.007
Creative self-efficacy (M) .578 .000 .458 .699
Failure allowance climate (W) .121 .046 .002 .240
M × W .007 .882 -.084 .098 Innovation experience .601 .000 .479 .723 .253 .000 .132 .375 Age .131 .050 -.000 .262 -.020 .717 -.129 .089 Organizational tenure -.150 .024 -.280 -.020 -.018 .746 -.126 .090 Constant .001 .985 -.113 .115 .000 1.000 -.093 .093 R2 = .42 R2 = .61 F (6, 176) = 21.12, p < .01 F (5, 177) = 54.52, p < .01
Table 6
Moderated Mediation Analysis: Direct Effects, Conditional Indirect Effects and Index of Moderated Mediation
Moderator
Direct effect Conditional indirect effect Index of moderated meditation
Effect sea 95% CI Effect sea 95% CI Index sea 95% CI
Model -.104* .049 [-.200, -.007] .004 .036 [-.036, .107]
Low failure allowance climate -.010 .060 [-.170, .065]
Medium failure allowance -.006 .038 [-.094, .057]
High failure allowance climate -.002 .043 [-.085, .086]
** p < .01, * p < .05, † p < .10.
Table 7
Moderation Analysis: Test of Failure Allowance Climate (W)
Innovation motivation (Y)
β p 95% CI
LLCI ULCI
Innovation failure (X) -.073 .233 -.192 .047
Failure allowance climate (W) .097 .104 -.020 .214
Table 8
Exploratory Moderation Analysis: Conditional Direct Effect of Innovation Failure (X) on Innovation Motivation (Y)
** p < .01, * p < .05, † p < .10. Note. CI = confidence intervals.
a Estimates for standard error (SE) were bootstrapped for 5000 times Moderator
Conditional effect
Effect sea 95% CI
Model 3b
Figures Figure 2
Appendices Appendix A: Measures Innovation failure. (self-created)
Before responding to the items below, please briefly think back to the innovation projects that you have been involved in during the past 12 months. If you have not been part of any innovation projects, think about innovative work tasks that you might have engaged in as part of your job (e.g. optimizing work processes, finding solutions to problems on the job, coming up with and implementing new process or product ideas, etc.).
For the following items, please indicate your dis/agreement with the statements regarding innovation projects and innovative work tasks that you were a part of during the past 12 months. I have experienced the failure of many innovation projects first-hand.
1. The innovation projects I was involved in often had to be terminated before they were finalized.
2. I was mainly involved innovation projects that were successful. 3. I was a part of many failed innovation projects.
Creative self-efficacy. (Tierney & Farmer, 2002)
Please indicate below your extent of dis/agreement with the statements regarding your general creative abilities.
1. I have confidence in my ability to solve problems creatively. 2. I feel that I am good at generating novel ideas.
3. I am good at further developing the ideas of others. Innovation motivation. (Tierney, Farmer & Graen, 1999)
3. I enjoy engaging in analytical thinking.
4. I enjoy creating new procedures for work tasks. 5. I enjoy improving existing processes or products. Innovation motivation. (self-created)
Before responding to the items on the following pages, please briefly think about the innovation projects that you are currently involved in. If you are not currently part of any innovation projects, think about innovative work tasks that you might engage in as part of your current job (e.g. optimizing work processes, finding solutions to problems on the job, coming up with and implementing new process or product ideas, etc.). Please answer the items based on these current innovation projects or innovative work tasks.
Concerning the innovation projects and innovative work tasks of your current job, to what extent do you dis/agree with the following statements?
1. I intend to create new procedures for work tasks. 2. I am likely to improve existing processes or products. 3. I am inclined to find solutions to complex problems.
4. I intend to come up with new ideas for processes or products. Failure allowance climate. (adapted from Mahlendorf, 2013).
1. It has been made clear to me that innovation projects have to be abandoned if the goals can no longer be reached.
2. I have been judged not only according to the results of innovation projects, but also for the quality of the project process.
3. It has been communicated to me that there will be no consequences if innovation projects get prematurely terminated.
Failure allowance climate. (self-created)
1. Failures in the work processes are accepted.
2. Doing things wrong is viewed as a normal part of work. 3. I get blamed when I make mistakes.
4. People support each other when things go wrong.
5. The policies and procedures of my organization take into account that projects fail. 6. The organizational climate allows employees to fail.
7. If I fail my colleagues will react negatively.
8. My supervisors/managers do not appreciate failure. Innovation experience. (self-created)
Please indicate with the items below the extent to which creativity and innovation are part of your current job.
1. I am often involved in innovation projects of my organization. 2. My job requires me to be innovative.
3. Being creative is not one of the tasks of my job. 4. I usually have a high position in innovation projects.
