Are heterogeneous customers always good for iterative innovation?

Autor: Mingzhu Li, Min Gong, Xiaoxian Jiang, Ruijie Jin
Rok vydání: 2022
Předmět:
Zdroj: Journal of Business Research. 138:324-334
ISSN: 0148-2963
DOI: 10.1016/j.jbusres.2021.09.024
Popis: Are heterogeneous customers always good for iterative innovation? To address this question, building on the knowledge-based view and cognitive load theory, we investigate the impact of customer heterogeneity on software products’ iterative innovation and how such relationship changes with firms’ absorptive capacity. Using a dataset on software product iterative innovation of publicly listed firms in China from 2007 to 2019, the findings support our prediction that software products’ iterative innovation follows an inverted U-shape as customer heterogeneity increases, which indicates that a high level of customer heterogeneity impedes software products’ iterative innovation. Moreover, this nonlinear effect is moderated by a firm’s absorptive capacity such that the inflection point of the inverted U-shaped curve is shifted upward in firms with high levels of absorptive capacity, enhancing the impact of customer heterogeneity on software products’ iterative innovation.
Databáze: OpenAIRE