Mitigating Negative Side Effects of Innovation Project Terminations: The Role of Resilience and Social Support

Abstract

A substantial portion of innovation projects are terminated before their successful completion. However, how specifically innovators can be supported given the experience of a project termination is not well understood. Innovator resilience potential (IRP) has been proposed to be important for future innovative behavior and coping and is suspected to be influenced by project terminations and their characteristics. Building on these assumptions, three sources of social support are examined, as such the support from family and friends, from the leader, from the organization, and their relationship with IRP. Moreover, it is argued that IRP, in turn, is an important facilitator of the project commitment of innovators, who have experienced an innovation project termination. The authors examine these theoretical expectations based on two empirical studies. After probing the newly developed measure of IRP based on a sample of 146 software developers from a European software company, the authors test the hypotheses on a survey‐based sample of 238 innovators, of whom 180 had experienced an innovation project termination. The results indicate that IRP positively relates to innovators’ current project commitment, particularly when they had experienced an innovation project termination before. Moreover, it is found that experiencing social support from the leader and the organization in the context of the termination positively relates to IRP, while no such a relationship was found for social support from family and friends. This hints at ways as to how to support innovators during and after an innovation project termination, showing that social support from work‐related sources is most important in such situations.

Resilient employees are creative employees, when the workplace forces them to be

“…With this novel and somewhat counterintuitive insight, this study complements research about the direct impact of adverse work conditions in steering employees away from positive work behaviours (e.g., Chen et al, ; Jam et al, ). Moreover, by affirming the hypothesized invigorating effects, we extend previous research that has focused on how supportive organizational situations might spur employees' subsequent resilience levels (e.g., Kuntz et al, ; Todt et al, ), as well as their personal initiative and innovative behaviour (Hong, Liao, Raub, & Han, ; Scott & Bruce, ). We focus instead on the concurrent influence of employees' resilience levels and different sources of workplace adversity on their disruptive creative behaviour.…”

“…Moreover, by affirming the hypothesized invigorating effects, we extend previous research that has focused on how supportive organizational situations might spur employees' subsequent resilience levels (e.g., Kuntz et al, 2017;Todt et al, 2018), as well as their personal initiative and innovative behaviour (Hong, Liao, Raub, & Han, 2016;Scott & Bruce, 1994). We focus instead on the concurrent influence of employees' resilience levels and different sources of workplace adversity on their disruptive creative behaviour.…”

“…Notably, previous research also indicates that a full model, such as Model 6, in which the signs of the interaction terms match those obtained when adding the interaction terms in separate questions provides evidence for the robustness of the results (Covin et al, 2006;De Clercq, Dimov, & Thongpapanl, 2010), as in this study. 1 Finally, even if the theoretical focus of this study is on the concurrent interplay of employees' resilience and different resource-draining work conditions for explaining disruptive creative behaviour, we also performed a post hoc analysis to account for possible causal relationships among these variables, in light of findings that employees' resilience levels might depend on their surrounding organizational environment (Kuntz, Malinen, & Näswall, 2017;Todt, Weiss, & Hoegl, 2018). In particular, we ran different path models, corresponding with the regression models in Table 2, to estimate the covariances among resilience and the three adverse work conditions (work overload, organizational rigidity and organizational politics).…”

Goal Multiplicity and Innovation: How Social and Economic Goals Affect Open Innovation and Innovation Performance

“…It is similar to a bootstrapped path‐analytic model and allows for an assessment of the direct and indirect effects as well as the unique contributions of each mediator (Hayes, ; Hayes and Scharkow, ). It is widely established in psychological and organizational behavior research and has also been used in innovation management studies to test indirect effects (e.g., Lin, McDonough, Lin, and Lin, ; Todt, Weiss, and Hoegl, ). One of its advantages is that the PROCESS macro is more robust and requires fewer assumptions, such as multivariate normality, compared to covariance‐based structural equation modeling (SEM).…”

The Product Developer in the Centre of Product Development: A Systematic Literature Review on Describing Factors

“…Factors influencing the developer are: social support by executives (Todt et al 2018), conflicts of objectives between developers and management (Terho et al 2016), passing on customer feedback and new product ideas by dealers (Restuccia et al 2016), environmental turbulence (Dayan and Di Benedetto 2011) and the combination of time pressure, management support and high project experience (Zika-Viktorsson and Ingelgård 2006). The factors influenced by the developer include the size of the team, the duration of the team's existence, the strength of the relationships within the team, the degree of clustering within the team (Datta 2018), the team experience combined with intuitive cognitive decision making (Dayan and Di Benedetto 2011), the amount of reflective activities (Zika-Viktorsson and Ingelgård 2006), the personal integrity of the developer (Morton et al 2006) and the team climate in combination with financial resource bottlenecks (Weiss, M. Hoegl, M. and Gibbert 2011).…”