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Assessing the impact of negative WOM on diffusion process

Author

Listed:
  • Deepti Aggrawal

    (USME, Delhi Technological University)

  • Mohini Agarwal

    (Amity University)

  • Rubina Mittal

    (University of Delhi)

  • Adarsh Anand

    (University of Delhi)

Abstract

The diffusion process has been considered as the propagation of messages associated with new ideas that lead to innovations; be it products, processes, or technology. With the anticipation of the change in receptor behavior, this diffusion process tends to bring out the adoption of the innovation. Most of the literature on innovation diffusion modeling is based on market growth however, very less work is available that focuses on how a new product penetrates a market under the effect of attrition on its growth. The intended purpose here is to study the dynamic behind the growth of an innovative product. The impact that past adopters of an innovation exercise on potential adopters by convincing them to imitate them in their choice to accept/reject the advancement (communication impact, impersonation impact), assists in explaining the acceleration of the diffusion process. With this objective, we have formulated and investigated an innovation diffusion model to include both adoption and disadoption behavior. The proposed framework has been validated and empirically analyzed on three real sales data sets.

Suggested Citation

  • Deepti Aggrawal & Mohini Agarwal & Rubina Mittal & Adarsh Anand, 2022. "Assessing the impact of negative WOM on diffusion process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 820-827, June.
  • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:2:d:10.1007_s13198-021-01235-3
    DOI: 10.1007/s13198-021-01235-3
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    References listed on IDEAS

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    1. V. Kumar & Trichy V. Krishnan, 2002. "Multinational Diffusion Models: An Alternative Framework," Marketing Science, INFORMS, vol. 21(3), pages 318-330, July.
    2. Richie Aggarwal & Ompal Singh & Adarsh Anand & P. K. Kapur, 2019. "Modeling innovation adoption incorporating time lag between awareness and adoption process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 83-90, February.
    3. De Bruyn, Arnaud & Lilien, Gary L., 2008. "A multi-stage model of word-of-mouth influence through viral marketing," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 151-163.
    4. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    5. Mesak, Hani I. & Bari, Abdullahel & Babin, Barry J. & Birou, Laura M. & Jurkus, Anthony, 2011. "Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers' disadoption," European Journal of Operational Research, Elsevier, vol. 211(3), pages 642-649, June.
    6. Dipak Jain & Vijay Mahajan & Eitan Muller, 1991. "Innovation Diffusion in the Presence of Supply Restrictions," Marketing Science, INFORMS, vol. 10(1), pages 83-90.
    7. Joe A. Dodson, Jr. & Eitan Muller, 1978. "Models of New Product Diffusion Through Advertising and Word-of-Mouth," Management Science, INFORMS, vol. 24(15), pages 1568-1578, November.
    8. Christopher J. Easingwood & Vijay Mahajan & Eitan Muller, 1983. "A Nonuniform Influence Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 2(3), pages 273-295.
    9. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, August.
    10. William P. Putsis, Jr. & Sridhar Balasubramanian & Edward W. Kaplan & Subrata K. Sen, 1997. "Mixing Behavior in Cross-Country Diffusion," Marketing Science, INFORMS, vol. 16(4), pages 354-369.
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