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Strategies for new product diffusion: Whom and how to target?

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  • Hu, Hai-hua
  • Lin, Jun
  • Qian, Yanjun
  • Sun, Jian

Abstract

This paper examines the promotional strategies for new product diffusion by leveraging peer effects among consumers. Previous studies have offered conflicting recommendations on whom to target (e.g., influentials, susceptibles, or unsusceptibles) with respect to new product promotions. Utilizing agent-based modeling and simulation (ABMS), we show that each of the proposed consumer groups can be a promising target, depending on how they are targeted, according to target size and promotion intensity. The authors further recommend the optimal combination of whom and how to target under budget constraints. Specifically, where a budget is limited, the best approach is to target as many susceptibles as possible with a weak promotion. Targeting unsusceptibles with free products should be the first choice, where the budget is large. In other cases, the best approach is to target as many influentials as possible with a moderate promotion.

Suggested Citation

  • Hu, Hai-hua & Lin, Jun & Qian, Yanjun & Sun, Jian, 2018. "Strategies for new product diffusion: Whom and how to target?," Journal of Business Research, Elsevier, vol. 83(C), pages 111-119.
    • Handle: RePEc:eee:jbrese:v:83:y:2018:i:c:p:111-119
    DOI: 10.1016/j.jbusres.2017.10.010
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    1. Mick, David Glen & Fournier, Susan, 1998. "Paradoxes of Technology: Consumer Cognizance, Emotions, and Coping Strategies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(2), pages 123-143, September.
    2. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    3. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    4. Nejad, Mohammad G. & Amini, Mehdi & Babakus, Emin, 2015. "Success Factors in Product Seeding: The Role of Homophily," Journal of Retailing, Elsevier, vol. 91(1), pages 68-88.
    5. Donald Lehmann & Mercedes Esteban-Bravo, 2006. "When giving some away makes sense to jump-start the diffusion process," Marketing Letters, Springer, vol. 17(4), pages 243-254, December.
    6. Teck-Hua Ho & Shan Li & So-Eun Park & Zuo-Jun Max Shen, 2012. "Customer Influence Value and Purchase Acceleration in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 236-256, March.
    7. Kristine de Valck & Roberts V. Kozinets & Andrea C. Wojnicki & Sarah J.S. Wilner, 2010. "Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities," Post-Print hal-00458424, HAL.
    8. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    9. Hai-hua Hu & Jun Lin & Wen-tian Cui, 2015. "Intervention Strategies and the Diffusion of Collective Behavior," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-16.
    10. Olivier Toubia & Jacob Goldenberg & Rosanna Garcia, 2014. "Improving Penetration Forecasts Using Social Interactions Data," Management Science, INFORMS, vol. 60(12), pages 3049-3066, December.
    11. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Granovetter, Mark & Soong, Roland, 1986. "Threshold models of interpersonal effects in consumer demand," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 83-99, March.
    13. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
    14. Sinan Aral, 2011. "Commentary--Identifying Social Influence: A Comment on Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 217-223, 03-04.
    15. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    16. Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
    17. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    18. Hai-hua Hu & Jun Lin & Wen-tian Cui, 2015. "Local Opinion Heterogeneity and Individual Participation in Collective Behavior: A Reconsideration," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-6.
    19. Delre, S.A. & Jager, W. & Bijmolt, T.H.A. & Janssen, M.A., 2007. "Targeting and timing promotional activities: An agent-based model for the takeoff of new products," Journal of Business Research, Elsevier, vol. 60(8), pages 826-835, August.
    20. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
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