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The Relationship Between Persuasion Cues and Idea Adoption in Virtual Crowdsourcing Communities: Evidence From a Business Analytics Community

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  • Mohammad Daradkeh

    (University of Dubai, United Arab Emirates & Yarmouk University, Jordan)

Abstract

Building on the elaboration likelihood model (ELM) and absorptive capacity, this study develops a four-dimensional model of idea adoption in Virtual Crowdsourcing Communities (VCCs) and examines the influence of different persuasion cues on idea adoption. The research model was tested using hierarchical logistic regression based on a dataset from the Tableau community. The results show that both community recognition of users and community recognition of ideas are positively related to idea adoption. Proactive user engagement has a significant positive impact on idea adoption, while reactive user engagement has no significant impact. Idea content quality, represented by idea length and supporting arguments, has an inverted U-shaped relationship with idea adoption. Community absorptive capacity positively moderates the curvilinear relationship between idea content quality and idea adoption. These results contribute to a better elucidation of the persuasion mechanisms underlying idea adoption in VCCs, and thus provide important implications for open innovation research and practice.

Suggested Citation

  • Mohammad Daradkeh, 2022. "The Relationship Between Persuasion Cues and Idea Adoption in Virtual Crowdsourcing Communities: Evidence From a Business Analytics Community," International Journal of Knowledge Management (IJKM), IGI Global, vol. 18(1), pages 1-34, January.
    • Handle: RePEc:igg:jkm000:v:18:y:2022:i:1:p:1-34
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    References listed on IDEAS

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    1. Mokter Hossain & K. Islam, 2015. "Ideation through Online Open Innovation Platform: Dell IdeaStorm," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 6(3), pages 611-624, September.
    2. Elina H. Hwang & Param Vir Singh & Linda Argote, 2019. "Jack of All, Master of Some: Information Network and Innovation in Crowdsourcing Communities," Information Systems Research, INFORMS, vol. 30(2), pages 389-410, June.
    3. Barry L. Bayus, 2013. "Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community," Management Science, INFORMS, vol. 59(1), pages 226-244, June.
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    Cited by:

    1. Mohammad Daradkeh, 2022. "Lurkers versus Contributors: An Empirical Investigation of Knowledge Contribution Behavior in Open Innovation Communities," JOItmC, MDPI, vol. 8(4), pages 1-29, November.
    2. Mohammad Daradkeh, 2022. "A User Segmentation Method in Heterogeneous Open Innovation Communities Based on Multilayer Information Fusion and Attention Mechanisms," JOItmC, MDPI, vol. 8(4), pages 1-19, October.
    3. Lyu, Tu & Chen, Hao & Guo, Yulin, 2023. "Investigating innovation diffusion, social influence, and personal inner forces to understand people's participation in online e-waste recycling," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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