Skip to main content
SpringerLink
Log in

Assessing the impact of negative WOM on diffusion process

  • Original article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Abbreviations

IDP:

Innovation diffusion process

WOM:

Word-of-mouth

CRM:

Customer relationship management

CRA:

Customer relationship approach

PLC:

Product life cycle

References

  • Ackerberg DA (2003) Advertising, learning, and consumer choice in experience good markets: an empirical examination. Int Econ Rev 44(3):007–1040

    Article  Google Scholar 

  • Agarwal M, Aggrawal D, Anand A, Singh O (2017) Modeling multi-generation innovation adoption based on conjoint effect of awareness process. Int J Math, Eng Manag Sci 2(2):74–84

    Google Scholar 

  • Agarwal M, Anand A, Bansal G, Pathak JP (2019) Innovation diffusion process based on market coverage under dynamic environment. Nonlinear Stud 26(3):517–526

    MathSciNet  Google Scholar 

  • Aggarwal R, Singh O, Anand A, Kapur PK (2019) Modeling innovation adoption incorporating time lag between awareness and adoption process. Int J Syst Assur Eng Manag 10(1):83–90

    Article  Google Scholar 

  • Anand A, Singh O, Agarwal M, Aggarwal R (2014, October). Modeling adoption process based on awareness and motivation of consumers. In: Proceedings of 3rd international conference on reliability, infocom technologies and optimization (pp. 1–6). IEEE

  • Anand A, Aggarwal R, Singh O, Aggrawal D (2016) Understanding diffusion process in the context of product dis adoption. Hayчнo-тexничecкиe вeдoмocти Caнкт-Пeтepбypгcкoгo гocyдapcтвeннoгo пoлитexничecкoгo yнивepcитeтa. Экoнoмичecкиe нayки. 2 (240)

  • Anderson EW (1998) Customer satisfaction and word of mouth. J Serv Res 1(1):5–17

    Article  Google Scholar 

  • Arndt J (1967) Role of product-related conversations in the diffusion of a new product. J Mark Res 4:291–295

    Article  Google Scholar 

  • Bass FM (1969) A new product growth for model consumer durables. Manag Sci 15(5):215–227

    Article  Google Scholar 

  • Buttle F (1996) SERVQUAL: review, critique, research agenda. Eur J Mark 30(1):8–32

    Article  Google Scholar 

  • De Bruyn A, Lilien GL (2008) A multi-stage model of word-of-mouth influence through viral marketing. Int J Res Mark 25(3):151–163

    Article  Google Scholar 

  • Dodson JA Jr, Muller E (1978) Models of new product diffusion through advertising and word-of-mouth. Manag Sci 24(15):1568–1578

    Article  Google Scholar 

  • Easingwood CJ, Mahajan V, Muller E (1983) A nonuniform influence innovation diffusion model of new product acceptance. Mark Sci 2(3):273–295

    Article  Google Scholar 

  • Elihu K, Paul L (1955) Personal influence. The Free Press, Glencoe

    Google Scholar 

  • File KM, Judd BB, Prince RA (1992) Interactive marketing: the influence of participation on positive word-of-mouth and referrals. J Serv Mark 6(4):5–14

    Article  Google Scholar 

  • Gremler D (1994) Word-of-mouth communication: causes and consequences. Mark Rev 15(1):3

    Google Scholar 

  • Henricks M (1998) Spread the word. Entrepreneur 26(2):120–125

    Google Scholar 

  • Horsky D, Simon LS (1978, May) Advertising in a model of new product diffusion. In: TIMS/ORSA national meeting in New York City

  • Hu X (2015) Assessing source credibility on social media: an electronic word-of-mouth communication perspective (Doctoral dissertation, Bowling Green State University)

  • Huefner JC, Hunt HK (2000) Consumer retaliation as a response to dissatisfaction. J Consum Satisfaction, Dissatisfaction Complain Behav 13:61–82

    Google Scholar 

  • Jain D, Mahajan V, Muller E (1991) Innovation diffusion in the presence of supply restrictions. Mark Sci 10(1):83–90

    Article  Google Scholar 

  • Kapur PK, Bardhan AK, Jha PC (2004) An alternative formulation to innovation diffusion model and its extensions. In: Kapoor VK (ed) Mathematics and information theory. Anamaya Publication, New Delhi, pp 17–23

    Google Scholar 

  • Kapur PK, Pham H, Kumar V, Anand A (2012) Dynamic optimal control model for profit maximization of software product under the influence of promotional effort. J High Technol Managem Res 23(2):122–129

    Article  Google Scholar 

  • Kumar V, Krishnan TV (2002) Multinational diffusion models: an alternative framework. Mark Sci 21(3):318–330

    Article  Google Scholar 

  • Libai B, Muller E, Peres R (2009) The diffusion of services. J Mark Res 46(2):163–175

    Article  Google Scholar 

  • Lilien GL, Rao AG (1978) A marketing promotion model with word-of-mouth effect, Working Paper 976–78. Boston: Sloan School of Management, Massachusetts Institute of Technology

  • Mahajan V, Muller E, Wind Y (Eds.) (2000) New-product diffusion models (Vol. 11). Springer Science & Business Media

  • Mesak HI, Bari A, Babin BJ, Birou LM, Jurkus A (2011) Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers’ disadoption. Eur J Oper Res 211(3):642–649

    Article  MathSciNet  Google Scholar 

  • Parker P, Gatignon H (1994) Specifying competitive effects in diffusion models: an empirical analysis. Int J Res Mark 11(1):17–39

    Article  Google Scholar 

  • Parvin AJ, Beruvides MG (2021) Macro Patterns and trends of us consumer technological innovation diffusion rates. Systems 9(1):16

    Article  Google Scholar 

  • Putsis WP Jr, Balasubramanian S, Kaplan EH, Sen SK (1997) Mixing behavior in cross-country diffusion. Mark Sci 16(4):354–369

    Article  Google Scholar 

  • Richins ML (1987) A multivariate analysis of responses to dissatisfaction. J Acad Mark Sci 15(3):24–31

    Article  Google Scholar 

  • Roberts JH, Lattin JM (2000) Disaggregate-level diffusion models. New-product diffusion models. pp. 207–236

  • Rogers E (1962) Diffusion of Innovations. Free Press, New York

    Google Scholar 

  • Sachdeva N (2017) Influence of customer attrition on diffusion of business education services. Int J Math, Eng Manag Sci 2(2):125–134

    MathSciNet  Google Scholar 

  • SAS Institute Inc (2004) SAS/ETS User’s Guide Version 9.1, SAS Institute Inc., Cary, NC

  • Sheth JN (1971) Word-of-mouth in low-risk innovations. J Advert Res 11(3):15–18

    Google Scholar 

  • Singh O, Anand A, Kapur PK, Aggrawal D (2012) Consumer behaviour-based innovation diffusion modelling using stochastic differential equation incorporating change in adoption rate. Int J Technol Mark 7(4):346–360

    Article  Google Scholar 

  • Sundaram DS, Mitra K, Webster C (1998) Word-of-mouth communications: a motivational analysis. Adv Consum Res 25(1):527–531

    Google Scholar 

  • Swan JE, Oliver RL (1989) Post-purchase communications by consumers. J Retail 65(4):516–533

    Google Scholar 

Download references

Acknowledgements

The authors are thankful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article.

Funding

No funding.

Author information

Authors and Affiliations

  1. USME, Delhi Technological University, Delhi, 110095, India

    Deepti Aggrawal

  2. Amity School of Business, Amity University, Noida, UP, 201301, India

    Mohini Agarwal

  3. Department of Mathematics, Keshav Mahavidyalaya, University of Delhi, Delhi, 110034, India

    Rubina Mittal

  4. Department of Operational Research, University of Delhi, Delhi, 110007, India

    Adarsh Anand

Authors
  1. Deepti Aggrawal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohini Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rubina Mittal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Adarsh Anand
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohini Agarwal.

Ethics declarations

Conflicts of Interest

The authors confirm that there is no conflict of interest to declare for this publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aggrawal, D., Agarwal, M., Mittal, R. et al. Assessing the impact of negative WOM on diffusion process. Int J Syst Assur Eng Manag 13 (Suppl 2), 820–827 (2022). https://doi.org/10.1007/s13198-021-01235-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-021-01235-3

Keywords

Search

Navigation