Are heterogeneous customers always good for iterative innovation?

Xiaoxian Jiang, Ruijie Jin, Min Gong and Mingzhu Li

Journal of Business Research, 2022, vol. 138, issue C, 324-334

Abstract: 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.

Keywords: Iterative innovation; Customer heterogeneity; Absorptive capacity; Software products; Knowledge-based view; Cognitive load theory (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:138:y:2022:i:c:p:324-334

DOI: 10.1016/j.jbusres.2021.09.024

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