Identifying high quality ideas in the online context: evidence from a meta-analysis

Abstract

PurposeWith the rapid development of web-based ideation platforms, firms are increasingly reaching outside their boundaries to obtain ideas, which makes idea evaluation tricky and ineffective. Numerous studies have investigated the antecedents of idea quality, but few have focused on the fragmented and contradictory conclusions these studies have drawn. Thus, the purpose of this paper is to disentangle conflicting findings regarding factors affecting idea quality.Design/methodology/approachA total of 41 independent samples from 40 articles published between 2009 and 2020 were retrieved and encoded to conduct a meta-analysis. By using Comprehensive Meta-analysis 3.0 (CMA 3.0) software, the relationship between identified influencing factors and idea quality, and the moderating effects of potential variables were investigated.FindingsFactors affecting idea quality were summarized and divided into three categories: idea-related factors, ideator-related factors and platform-related factors. The results indicated that all proposed factors (idea length, supporting evidence, past success, past submissions, past comments, votes received and comments received) had significant positive effects on idea quality. Moreover, the measurement of idea quality and idea type was the causative factor for the inconsistent findings, whereas the moderating effect of platform type was not significant.Originality/valueThis study systematically synthesized the existing research on the factors influencing idea quality and helped to reconcile the mixed results. The findings serve to enrich current knowledge of idea evaluation in the online context, which could have important implications for both scholars and practitioners.

Exploring the effects of problem- and solution-related knowledge sharing in internal crowdsourcing

“…Comment diversity : Comment diversity here represents the diversity of content in comments to ideas, measured based on Sharon entropy (Hu and Xu, 2021), something, which indicates the diversity and uncertainty degree (Jost, 2006; Masisi et al , 2008) and potentially influences the idea acceptance (Bayus, 2013). To capture the Sharon entropy of comments, the ‘topicmodels’ package in R based on word frequency is used (Hornik and Grün, 2011).…”

The social side of innovation: peer influence in online brand communities

“…Quality ideas in OBCs are those that are not developed by the organization but have sufficient value to be implemented (Bayus, 2013), and idea quality is considered a comprehensive indicator reflecting innovation requirements from different perspectives, or the potential business value that an organization might adopt (Hu and Xu, 2021). While previous research has emphasized the importance of evaluating idea quality from multiple dimensions (Dean et al, 2006), some scholars have suggested that market potential and idea adoption are the key indicators of idea quality (Li et al, 2016;Zhu et al, 2019).…”