Annals of Operations Research

, Volume 244, Issue 2, pp 647–676

Loyal customer bases as innovation disincentives for duopolistic firms using strategic signaling and Bayesian analysis

  • Madjid Tavana
  • Debora Di Caprio
  • Francisco J. Santos-Arteaga
Original Paper

DOI: 10.1007/s10479-016-2114-7

Cite this article as:
Tavana, M., Di Caprio, D. & Santos-Arteaga, F.J. Ann Oper Res (2016) 244: 647. doi:10.1007/s10479-016-2114-7


In this paper we model the strategic behavior of firms competing in duopolistic environments with a loyal customer base and formalize their decision to delay the introduction of the most technologically developed product available. The proposed model extends and complements the partial approaches studied in the economic, management and operations research literatures. The former emphasizes the role of the strategic knowledge spillovers that may take place among competing firms because of their incentives to introduce technologically superior products while assuming the acceptance of such products by customers as given. The second defines its technology acceptance model based on the demand side of the economic system without considering the resulting strategic interactions that arise among the firms. The latter addresses the effect that signals about a new technology have on the information acquisition behavior of decision makers (DMs) but does not consider the capacity of DMs to account for several product characteristics and their interaction when acquiring information. Using a duopolistic innovation game model we illustrate how the existence of loyal customer bases allows for higher expected payoffs when generating monopolized markets but decreases the incentives of firms to introduce the most technologically developed product available. The signaling equilibria of the game are determined by demand-based factors and the incentives of customers to acquire information on the existing products in the market. Among the main implications of our model is also the fact that the availability of decision support systems that can be used by DMs through their information acquisition processes would improve the quality of the technology being introduced in the market and increase the firms’ probability of success.


Multi-attribute sequential search Customer loyalty Strategic signaling Technological evolution Product introduction 

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Madjid Tavana
    • 1
    • 2
  • Debora Di Caprio
    • 3
    • 4
  • Francisco J. Santos-Arteaga
    • 5
    • 6
  1. 1.Business Systems and Analytics Department, Distinguished Chair of Business AnalyticsLa Salle UniversityPhiladelphiaUSA
  2. 2.Business Information Systems Department, Faculty of Business Administration and EconomicsUniversity of PaderbornPaderbornGermany
  3. 3.Department of Mathematics and StatisticsYork UniversityTorontoCanada
  4. 4.Polo Tecnologico IISS G. GalileiBolzanoItaly
  5. 5.School of Economics and ManagementFree University of BolzanoBolzanoItaly
  6. 6.Departamento de Economía Aplicada II Facultad de EconómicasUniversidad Complutense de MadridPozueloSpain

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