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Bias effects, synergistic effects, and information contingency effects: Developing and testing an extended information adoption model in social Q&A

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  • Yongqiang Sun
  • Nan Wang
  • Xiao‐Liang Shen
  • Xi Zhang

Abstract

To advance the theoretical understanding on information adoption, this study tries to extend the information adoption model (IAM) in three ways. First, this study considers the relationship between source credibility and argument quality and the relationship between herding factors and information usefulness (i.e., bias effects). Second, this study proposes the interaction effects of source credibility and argument quality and the interaction effects of herding factors and information usefulness (i.e., synergistic effects). Third, this study explores the moderating role of an information characteristic – search versus experience information (i.e., information contingency effects). The proposed extended information adoption model (EIAM) is empirically tested through a 2 by 2 by 2 experiment in the social Q&A context, and the results confirm most of the hypotheses. Finally, theoretical contributions and practical implications are discussed.

Suggested Citation

  • Yongqiang Sun & Nan Wang & Xiao‐Liang Shen & Xi Zhang, 2019. "Bias effects, synergistic effects, and information contingency effects: Developing and testing an extended information adoption model in social Q&A," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(12), pages 1368-1382, December.
    • Handle: RePEc:bla:jinfst:v:70:y:2019:i:12:p:1368-1382
    DOI: 10.1002/asi.24228
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    Cited by:

    1. Juan Xie & Hongru Lu & Lele Kang & Ying Cheng, 2022. "Citing criteria and its effects on researcher's intention to cite: A mixed‐method study," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(8), pages 1079-1091, August.
    2. Qingfeng Zeng & Wei Zhuang & Qian Guo & Weiguo Fan, 2022. "What factors influence grassroots knowledge supplier performance in online knowledge platforms? Evidence from a paid Q&A service," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2507-2523, December.

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