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Constraint-based and dedication-based mechanisms for encouraging online self-disclosure: Is personalization the only thing that matters?

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  • Hung-pin Shih
  • Kee-hung Lai
  • T. C. E. Cheng

Abstract

Consumer-generated self-disclosure is better than firm-generated advertising and sales reports in increasing contact opportunities and also more credible for firms to foster alignment with future market expectations. Previous research mostly assesses online self-disclosure from the rational approach of anticipated benefits and privacy risks without considering the “privacy paradox” phenomenon (users behave contrarily to privacy concern) in social networking sites (SNSs). We develop a theoretical model, grounded in constraint-based (lock-in) and dedication-based (trust-building) mechanisms and social identity theory, to predict online self-disclosure. We test the proposed theoretical model by surveying 395 consumers with participation experience in an online SNS. Different from the rational approach behind personalization, we advance knowledge on how to apply social identity, as well as constraint-based and dedication-based mechanisms, to motivate online self-disclosure induced by consumers. We provide theoretical and practical insights based on our research findings for managing the motivational mechanisms of online self-disclosure.

Suggested Citation

  • Hung-pin Shih & Kee-hung Lai & T. C. E. Cheng, 2017. "Constraint-based and dedication-based mechanisms for encouraging online self-disclosure: Is personalization the only thing that matters?," European Journal of Information Systems, Taylor & Francis Journals, vol. 26(4), pages 432-450, July.
    • Handle: RePEc:taf:tjisxx:v:26:y:2017:i:4:p:432-450
    DOI: 10.1057/s41303-016-0031-0
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    Cited by:

    1. Lee, Kuo-Wei & Li, Chia-Ying, 2023. "It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    2. Li, Chia-Ying & Fang, Yu-Hui & Chiang, Yu-Hung, 2023. "Can AI chatbots help retain customers? An integrative perspective using affordance theory and service-domain logic," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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