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The purpose of this paper is to study how the online temporary crowd shares knowledge in a way that fosters the integration of their diverse knowledge. Having the crowd integrate its knowledge to offer solution-ideas to ill-structured problems posed by organizations is one of the desired outcomes of crowd-based open innovation because, by integrating others’ knowledge, the ideas are more likely to consider the many divergent issues related to solving the ill-structured problem. Unfortunately, the diversity of knowledge content offered by heterogeneous specialists in the online temporary crowd makes integration difficult, and the lean social context of the crowd makes extensive dialogue to resolve integration issues impractical. The authors address this issue by exploring theoretically how the manner in which interaction is organically conducted during open innovation challenges enables the generation of integrative ideas. The authors hypothesize that, as online crowds organically share knowledge based upon successful pro-socially motivated interaction, they become more productive in generating integrative ideas.

Using a multilevel mixed-effects model, this paper analyzed 2,244 posts embedded in 747 threads with 214 integrative ideas taken from 10 open innovation challenges.

Integrative ideas were more likely to occur after pro-socially motivated interactions.

Ideas that integrate knowledge about the variety of issues that relate to solving an ill-structured problem are desired outcomes of crowd-based open innovation challenges. Given that members of the crowd in open innovation challenges rarely engage in dialogue, a new theory is needed to explain why integrative ideas emerge at all. The authors’ adaptation of pro-social motivation interaction theory helps to provide such a theoretical explanation. Practitioners of crowd-based open innovation should endeavor to implement systems that encourage the crowd members to maintain a high level of activeness in pro-socially motivated interaction to ensure that their knowledge is integrated as solutions are generated.

The present study extends the crowd-based open innovation literature by identifying new forms of social interaction that foster more integrated ideas from the crowd, suggesting the mitigating role of pro-socially motivated interaction in the negative relationship between knowledge diversity and knowledge integration. This study fills in the research gap in knowledge management research describing a need for conceptual frameworks explaining how to manage the increasing complexity of knowledge in the context of crowd-based collaboration for innovation.

This study aims to explore how and when learning from others promotes creative performance over the contributor’s tenure in the context of open innovation communities.

The authors analyze a publicly available data set that includes 25,923 innovative items developed by 2,194 contributors from an open innovation community of an online game spanning eight years. Logistic regression model is used for analyzing the data.

The results show that multicultural experiences are negatively related to contributor’s creative performance, and this negative relationship weakens as contributor’s tenure increases. While diverse skills are positively related to contributor’s creative performance, and this positive relationship strengthens as contributor’s tenure increases.

This research highlights the importance of online team collaboration in knowledge transfer through learning from others in open innovation communities. By identifying two outcomes of learning from others through online team collaboration, the authors demonstrate the double-edged role of learning from others and advance the understanding on how the effect of learning from others varies over the contributor’s tenure. These results expand the understanding of online team collaboration and provide a new perspective for research on learning from others.

Drawing from the cognitive evaluation theory, the purpose of this paper is to explore the relationship between student volunteers’ narcissism, Machiavellianism and psychopathy, and commitment to university volunteer programmes through the mediating mechanisms of self-orientation and pro-social motivation. Further, it investigates the roll of servant leadership in mitigating these personality types and encouraging student volunteers to become more pro-socially motivated.

The study uses data collected via questionnaire from 156 student volunteers across Australia. Hypothesis testing was conducted using ordinary least squares regression with the path-analytic conditional process modelling (PROCESS) macro for SPSS.

The study’s analysis indicated that self-orientated motivation mediated the relationship between narcissism and normative commitment, and pro-social motivation mediated the relationship between both Machiavellianism and psychopathy, and affective commitment. Further, servant leadership was found to moderate the relationship between both Machiavellianism and psychopathy, and pro-social motivation, such that the negative relationship became weaker under a servant leader. These findings suggest that servant leaders play a significant role in encouraging “dark” personalities to see the light.

This research is the first to examine the use of the Dark Triad in a student volunteering context. It extends the cognitive evaluation theory by revealing that extrinsic (in contrast to intrinsic) motivations are “crowded out” as intrinsic (in contrast to extrinsic) motivations develop within individuals. The study also refines the social learning theory, by examining the influences of “positive” leadership attributes (servant leadership) on “darker” (Dark Triad) personalities.

Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development.

Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis.

The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses.

This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas.

The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

The unprecedented growth in the volume, variety and velocity with which data is generated and collected over the last decade has led to the spread of big data phenomenon. Organizations have become increasingly involved in the collection and analysis of big data to improve their performance. Whereas the focus thus far has mainly been on big data collected from customers, the topic of how to collect data also from those who are not yet customers has been overlooked. A growing means of interacting with non-customers is through crowd-based phenomena, which are therefore examined in this study as a way to further collect big data. Therefore, this study aims to demonstrate the importance of jointly considering these phenomena under the proposed framework.

This study seeks to demonstrate that organizations can collect big data from a crowd of customers and non-customers through crowd-based phenomena such as crowdsourcing, citizen science and crowdfunding. The conceptual analysis conducted in this study produced an integrated framework through which companies can improve their performance.

Grounded in the resource-based view, this paper argues that non-customers can constitute a valuable resource insofar as they can be an additional source of big data when participating in crowd-based phenomena. Companies can, in this way, further improve their performance.

This study advances scientific knowledge of big data and crowd-based phenomena by providing an overview of how they can be jointly applied to further benefit organizations. Moreover, the framework posited in this study is an endeavour to stimulate further analyses of these topics and provide initial suggestions on how organizations can jointly leverage crowd-based phenomena and big data.

The adaptationist approach of evolutionary psychology provides a model of substantial scope for understanding the function of human behaviour, including harmful behaviour. The purpose of this paper is to discuss the evolutionary importance of social belonging, and also its relevance to why people deny stigmatised harmful behaviour, and the potential problems of labelling them by it.

The paper takes the form of a discussion and professional opinion.

Evolution reveals how natural selection has shaped the human nervous system for threat-detection and cooperation. It casts a light on why people convicted of harmful and stigmatised behaviour may hide, deny and lie as a means of limiting social devaluation and maintaining their fitness to belong in groups.

Amidst all our efforts as forensic practitioners to empower people to pro-socially reconnect and lead safer crime-free lives, endlessly associating them with their most unacceptable and harmful acts, might not help.

Evolutionary forensic psychology and evolutionary criminology are sub-disciplines of science that are progressively emerging. They place the adaptationist approach front and centre in the study and theory of criminal behaviour. This paper aims to offer an example of this synergy, but with a specific focus on forensic practice itself.

The purpose of this paper is to conceptualize social leader-member exchange (SLMX) and economic leader-member exchange (ELMX) as two separate dimensions of leader-member exchange, and examines how intrinsic work motivation moderates their relationship with follower work effort.

Data were obtained from 352 employee-leader dyads from the public health sector in Norway (response rate=61.9 percent). Hierarchical linear modeling was used to test the relationship between subordinate rated SLMX and ELMX relationships and leader ratings of work effort.

This study replicates prior research showing that SLMX is positively related and ELMX negatively related to followers’ work effort. A significant interaction between SLMX and intrinsic motivation is also revealed, suggesting that SLMX relationships are important with respect to work effort for followers who exhibit lower levels of intrinsic work motivation.

The data were cross-sectional, thus prohibiting causal inferences.

SLMX relationships may be particularly important for the work effort of followers low in intrinsic motivation. Leaders may draw on this finding and seek to aid the development of the relationship by means of relationship-oriented behaviors.

Given the importance of maximizing the performance of all the followers, a better understanding of the conditions under which SLMX and ELMX relationships relate to work effort is particularly important. The present study advances knowledge on SLMX and ELMX relationships by demonstrating how intrinsic motivation moderates how SLMX and ELMX relationships relate to follower work effort.

This study aims to determine how cognitive diversity at the workplace influences team creativity. In this regard, the authors examined knowledge sharing and team-focused inclusion through which team members’ cognitive diversity was expected to elevate their positive work outcomes.

A quantitative method is used to accumulate the data. The authors surveyed workers and their respective managers at a single China-based food company. The supervisors rated the outcome variables (creativity and team effectiveness) regarding their employees, whereas employees were asked to rate the cognitive diversity, inclusion and knowledge sharing within the workgroup. The final valid sample size (n = 391) consisted of 137 workgroups with an adequate response rate (62.3%).

Cognitive diversity is related to team effectiveness but not creativity. The research found that cognitive diversity can increase creativity only through enhanced inclusion and knowledge sharing. Inclusion, likewise, explained the impact of cognitive diversity on effectiveness.

The originality of the current research lies in its contemporary exploration of inclusion and cognitive diversity and their pathways to team creativity and effectiveness. The social capital theory was applied to explain the proposed relationships.