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Exploring the Usefulness of User-Generated Content for Business Intelligence in Innovation: Empirical Evidence From an Online Open Innovation Community

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  • Mohammad Kamel Daradkeh

    (Yarmouk University, Irbid, Jordan)

Abstract

This study presents a systematic approach that integrates the information adoption model (IAM) with topic modeling to analyze the digital voice of users in online open innovation communities (OOICs) and empirically examines the usefulness of UGC with large amounts of redundant information and varying content quality across two dimensions: information quality and information source credibility. A total of 61,227 bug comments were collected from the OOIC of Huawei EMUI and analyzed using binary logistic regression. The results show that information timeliness and completeness have a positive effect on the usefulness of UGC in OOICs; conversely, information semantics have a negative effect on the usefulness of UGC. Prior user experience has no influence on the usefulness of UGC in OOICs, while active user contribution has a positive effect on the usefulness of UGC. The results of this study offer several implications to researchers and practitioners, and thus could serve as a pivotal reference source for further investigation of potential determinants of UGC usefulness in OOICs.

Suggested Citation

  • Mohammad Kamel Daradkeh, 2021. "Exploring the Usefulness of User-Generated Content for Business Intelligence in Innovation: Empirical Evidence From an Online Open Innovation Community," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 17(2), pages 44-70, April.
    • Handle: RePEc:igg:jeis00:v:17:y:2021:i:2:p:44-70
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    Cited by:

    1. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Samad, Sarminah & Alrizq, Mesfer & Alyami, Sultan & Alghamdi, Abdullah, 2023. "Analysis of customers' satisfaction with baby products: The moderating role of brand image," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    2. Mengfan Li & Ting Wang & Wei Lu & Mengke Wang, 2022. "Optimizing the Systematic Characteristics of Online Learning Systems to Enhance the Continuance Intention of Chinese College Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    3. Saura, Jose Ramon & Palacios-Marqués, Daniel & Ribeiro-Soriano, Domingo, 2023. "Exploring the boundaries of open innovation: Evidence from social media mining," Technovation, Elsevier, vol. 119(C).

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