This paper aims to explore what different contribution behaviors there are in online ideation. Based on a data collected from a Swedish multi-national company using an idea management system, two main factors for ideation, namely: 1) motivational proactivity and 2) cognitive specificity, were used for clustering contribution behaviors through Latent Class Analysis. The results revealed four main behavioral categories and individuals belonging to different behavioral categories contributed differently to idea generation and idea development. A logistic regression model was used to test the different behavioral categories’ impacts on ideation performance. The results showed that contribution behaviors displayed in idea development impact ideation performance more than the ones in idea generation. These results contribute to existing theory through shedding new light on innovation behaviors in different ideation processes and how these behaviors impact ideation performance. Moreover, it provides management implications for online ideation at both the individual- and the firm level.

Purpose – New opportunities to nurture good ideas for innovation arise as firms use web-based ideation platforms for collective idea generation and development. What influences creative performance in firm-internal collective idea development is however not as well researched as idea generation and thus an important area of research is the feedback and commenting on ideas. More specifically, the aim of this paper is to explore the role of feedback timeliness and knowledge overlap between feedback providers and ideas in collective firm-internal online idea development.Design/methodology/approach – An empirical study has been performed, drawing on data collected from a Swedish multi-national company using a web-based system for collective firm-internal ideation. The investigation explicitly captures the effects on ideation performance played by idea development contributions, in terms of: 1) feedback timeliness and 2) knowledge overlap between feedback providers and ideas.Findings – The empirical results show that idea development is significantly influenced by feedback timeliness as well as by the knowledge overlap between feedback providers and ideas. Specifically, it is found that longer time interval for feedback and an increased knowledge overlap result in an increased likelihood of idea acceptance. However, beyond a certain point, the positive effect of a longer feedback time interval decreases, resulting in a curvilinear relationship. Research limitations/implications – The results do not only shed new light on theory about collective idea development, but also provides management implications for collective firm-internal ideation. As the data used in the study has been collected in one single firm, care should be taken in generalizing the results to other domains.Practical implications – The results inform managers that it is not always better to involve more individuals in these emergent and distributed ideation systems, but that it might be beneficial to take measures to exercise some control in terms of when distributed and diverse employees can freely join in and out, especially considering the diversity of ideas, comments and creators. Originality/value – The results from the empirical study reveal the effects of of feedback timeliness and knowledge overlap on idea development. This provides us with new insights on the complex dynamics at place in collective firm-internal idea development, and offers implications for how we can fruitfully manage this process.

With the increased usage of internal crowdsourcing for ideas, many firms are able to receive feedback from the voluntary collective wisdom with diverse expertise instead of a limited number of specified experts, potentially resulting in a large amount of diverse and complex input to ideas. Given the so-far limited knowledge about how feedback to ideas can be managed, firms face challenges in fruitfully managing this. Two aspects playing critical roles in feedback on proposed ideas for innovation are arguably feedback sentiment and feedback providers’ expertise. This paper aims to explore the roles of feedback sentiment and expertise in internal crowdsourcing for ideas. It does so through an empirical study drawing on data collected from a Swedish multinational company using internal crowdsourcing for innovation ideas. The investigation explicitly captures the effects of feedback sentiment and expertise in terms of: 1) positive and negative feedback; 2) expertise of feedback providers; 3) interaction effect between feedback sentiment and expertise of feedback providers. The effects of these dimensions are investigated by performing a logistic regression analysis. Regression results reveal that both feedback sentiment and expertise are potentially impacting ideas in internal crowdsourcing and that the latter of these acts as a moderator on the effect of negative feedback on idea acceptance. More specifically, it is found that positive feedback outperforms negative feedback in an overall view when it comes to idea acceptance, and the expertise of negative feedback providers has an inverted U-shaped relationship with the likelihood of idea acceptance. Furthermore, more negative information provided by experts could be helpful for idea development in internal crowdsourcing. As one of the first studies to explore the feedback sentiment in conjunction with expertise, this study not only extends previous knowledge about feedback mechanisms, but also provides practical implications to manage feedback in terms of contributors as well as their contributions to internal crowdsourcing of ideas.