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The Influence of Sentiment Orientation in Open Innovation Communities: Empirical Evidence from a Business Analytics Community

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  • Mohammad Daradkeh

    (Department of Information Technology, Faculty of Information Technology and Computer Sciences, Yarmouk University, 566, Irbid 21163, Jordan)

Abstract

This study aims to investigate the influence of presentation and sentiment orientation of user-generated ideas and reviews on idea adoption in open innovation communities (OICs). Drawing on the social influence theory, this study develops a research model that divides idea components into informational and normative determinants. The sentiment orientation of the idea title, description, and associated reviews is determined using a lexicon-based sentiment analysis approach. The research model is empirically tested using logistic regression analysis based on a dataset from the Microsoft community for business analytics products. The results reveal that the sentiment orientation of idea title has a negative influence on idea adoption, whilst the sentiment orientation of description has no influence on idea adoption. The sentiment orientation of the associated reviews has a positive influence on idea adoption, and this influence is moderated by the number of reviews. In addition, both idea title length and description length have a positive influence on idea adoption. These results offer several theoretical and practical implications and should therefore contribute to a better understanding of how user-generated ideas can be leveraged to drive innovation development and sustainability in OICs.

Suggested Citation

  • Mohammad Daradkeh, 2021. "The Influence of Sentiment Orientation in Open Innovation Communities: Empirical Evidence from a Business Analytics Community," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-36, September.
    • Handle: RePEc:wsi:jikmxx:v:20:y:2021:i:03:n:s0219649221500313
    DOI: 10.1142/S0219649221500313
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