IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i2d10.1007_s13198-021-01235-3.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01235-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-021-01235-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    2. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    3. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    4. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    5. Vardit Landsman & Moshe Givon, 2010. "The diffusion of a new service: Combining service consideration and brand choice," Quantitative Marketing and Economics (QME), Springer, vol. 8(1), pages 91-121, March.
    6. Yogesh V. Joshi & David J. Reibstein & Z. John Zhang, 2009. "Optimal Entry Timing in Markets with Social Influence," Management Science, INFORMS, vol. 55(6), pages 926-939, June.
    7. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    8. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.
    9. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    10. Swinerd, Chris & McNaught, Ken R., 2015. "Comparing a simulation model with various analytic models of the international diffusion of consumer technology," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 330-343.
    11. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    12. Teck-Hua Ho & Sergei Savin & Christian Terwiesch, 2002. "Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint," Management Science, INFORMS, vol. 48(2), pages 187-206, February.
    13. Rajkumar Venkatesan & Trichy V. Krishnan & V. Kumar, 2004. "Evolutionary Estimation of Macro-Level Diffusion Models Using Genetic Algorithms: An Alternative to Nonlinear Least Squares," Marketing Science, INFORMS, vol. 23(3), pages 451-464, August.
    14. Gelper, Sarah & Stremersch, Stefan, 2014. "Variable selection in international diffusion models," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 356-367.
    15. Albert C. Bemmaor & Janghyuk Lee, 2002. "The Impact of Heterogeneity and Ill-Conditioning on Diffusion Model Parameter Estimates," Marketing Science, INFORMS, vol. 21(2), pages 209-220, November.
    16. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    17. Jacob Goldenberg & Oded Lowengart & Daniel Shapira, 2009. "Zooming In: Self-Emergence of Movements in New Product Growth," Marketing Science, INFORMS, vol. 28(2), pages 274-292, 03-04.
    18. Paulo Albuquerque & Bart J. Bronnenberg & Charles J. Corbett, 2007. "A Spatiotemporal Analysis of the Global Diffusion of ISO 9000 and ISO 14000 Certification," Management Science, INFORMS, vol. 53(3), pages 451-468, March.
    19. H.P. Boswijk & D. Fok & P.-H. Franses, 2006. "A New Multivariate Product Growth Model," Tinbergen Institute Discussion Papers 06-027/4, Tinbergen Institute.
    20. Marc Vivian Lindou Tanka & Kevin Landry Lindjouom Tanka, 2024. "Estimated level of adoption of e-banking in Cameroon [Estimation du niveau d'adoption du e-banking au Cameroun]," Post-Print hal-04551120, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:13:y:2022:i:2:d:10.1007_s13198-021-01235-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.