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The role of cognitive complexity and risk aversion in online herd behavior

Author

Listed:
  • G. Rejikumar

    (Kochi Campus)

  • Aswathy Asokan-Ajitha

    (Indian Institute of Management Amritsar)

  • Sofi Dinesh

    (Kochi Campus)

  • Ajay Jose

    (Life Insurance Corporation of India)

Abstract

This paper investigated the role of information related, social and customer characteristics in public information adoption tendencies of online customers to result in herding in e-commerce. E-commerce platforms contains numerous online reviews about products which have the potential to influence customers. We applied structural equation modeling and a 2 × 2 scenario experiment to empirically verify the effect of a few factors in creating online herding. Two levels of cognitive complexity (simple, complex) and risk aversion (risk averse, risk taker) formed the 2 × 2 factorial design. The study's primary finding was that a person with simple cognitive structure and risk avoidance tendency may exhibit higher intention to adopt public information and engage in herding. Information specific attributes contributed maximum towards information adoption and herding. Among sociological variables, only reputation concern significantly predicted both information adoption and herding. Theoretically, the study offered a framework to explore herding intentions online and augmented the observations from the information adoption model. The quality of concise information from credible sources significantly instigates adoption of public information contained in online reviews. From the perspective of marketers, having a better understanding of herding behaviors and its mechanisms can enable the e-commerce platform to reduce herding’s erosion on the wisdom of the crowd by optimizing its information structures (i.e., public information, private information, etc.).

Suggested Citation

  • G. Rejikumar & Aswathy Asokan-Ajitha & Sofi Dinesh & Ajay Jose, 2022. "The role of cognitive complexity and risk aversion in online herd behavior," Electronic Commerce Research, Springer, vol. 22(2), pages 585-621, June.
    • Handle: RePEc:spr:elcore:v:22:y:2022:i:2:d:10.1007_s10660-020-09451-y
    DOI: 10.1007/s10660-020-09451-y
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