The Influence of User Feedback on Complementary Innovation in Platform Ecosystems: NLP Evidence on the Value of Multihoming

Abstract

We study how user feedback affects innovation of multihomed applications within and across platform ecosystems. Therefore, we conduct a quantitative NLP based case study. Our sample consists of 10 multihomed applications with more than 325,000 user reviews on Apple’s iOS and Google’s Android platform between January and March 2021. We analyze how user reviews translate into functional feature releases of the selected applications within and across platforms. We report three findings. First, we find that about 61% of the functional feature improvements on both platforms were previously demanded by users in the form of user feedback. Second, we show that user feedback of iOS users is more likely to be incorporated compared to Android users’ feedback. Finally, we observe that about 10% of feature releases are inspired by cross-platform feedback, providing initial evidence that user feedback from multihoming applications might stimulate cross-platform innovation and enhance the applications’ quality and innovativeness

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