Sparking innovation: exploring the dual-engine effect of idea generation and conversion enabled by open innovation communities
Ying Chu, Guijie Qi, Kaiping Wang, Huiying Wang · Technology Analysis and Strategic Management · 2024
Open innovation communities (OICs) help firms gather ideas and access external resources for innovation, but the mechanisms and quantitative impacts of OICs on product innovation are underexplored. This study examines how OIC-driven innovation affects market performance, specifically word-of-mouth, for new products. Using the innovation value chain framework, this paper conceptualises two OIC-enabled innovation phases: idea generation (gathering ideas) and idea conversion (applying ideas to product development). Based on dynamic capability theory, we hypothesise that idea generation outputs enhance enterprise sensing capability, and idea conversion outputs enhance enterprise seising capability, contributing to competitive advantage through improved product word-of-mouth. Focusing on Xiaomi's MIUI system, we quantify each phase's impact on feature word-of-mouth post-launch using text mining techniques such as LDA topic clustering and sentiment analysis on community ideas and XiaomiStore reviews. Employing econometric methods, we empirically examine how outputs from idea generation and conversion stages affect feature word-of-mouth. Our findings highlight significant effects from both stages, with idea conversion serving as a partial mediator between idea generation and subsequent word-of-mouth. Pre-conversion ‘likes’ enhance the impact of both stages, while ‘comments’ show diminishing returns. This research provides insights into optimising OIC management and contributes to the existing literature.