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Designing competitive loyalty programs: a stochastic game-theoretic model to guide the choice of reward structure

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Abstract

We develop a game-theoretic model to guide the choice of the reward structure in customer loyalty programs. We model a duopoly market in which one firm adopts a loyalty program. Firms independently and simultaneously set the prices and rewards. Heterogeneous customers buy homogeneous products in a multi-period setting. Customers are segmented into three groups based on their level of strategic behavior, which is expressed in terms of their degree of forward-lookingness. We use two exogenous parameters to represent the size of each segment. A third parameter captures the point pressure effect, which refers to the increase in customer spending as they approach a reward threshold. In each period, customers choose the firm that maximizes their utility, which is a function of offered prices, rewards, and the distance to the next reward. We use the logit model to model the customer choice behavior. Customers’ accumulated purchases evolve as a Markov chain. We derive the limiting distribution of accumulated purchases, which is subsequently used to formulate the firm’s expected revenue functions. We develop two algorithms to find the Nash equilibrium for both the linear and nonlinear rewards in term of the three parameters. Using a thorough numerical analysis, we show that the choice of the structure becomes more critical as the size of the strategic segment increases. The nonlinear scheme is superior when the size of the highly-strategic segment is very small. The linear rewards is superior in markets where the size of the highly-strategic segment and the sensitivity to distance are simultaneously not small.

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References

  • Bazargan, A., Karray, S., & Zolfaghari, S. (2017). Modeling reward expiry for loyalty programs in a competitive market. International Journal of Production Economics, 193, 352–364.

    Article  Google Scholar 

  • Bazargan, A., Karray, S., & Zolfaghari, S. (2018). ‘Buy n times, get one free’ loyalty cards: Are they profitable for competing firms? A game theoretic analysis. European Journal of Operational Research, 265(2), 621–630.

    Article  Google Scholar 

  • Ben-Akiva, M., & Lerman, S. R. (1985). Discrete choice analysis: Theory and application to travel demand (1st ed.). Cambridge, MA: The MIT Press.

    Google Scholar 

  • Berry, J. (2015). The 2015 COLLOQUY loyalty census: Big numbers, big hurdles. Technical report, COLLOQUY, Cincinnati, OH.

  • Boulogne, T., Altman, E., & Pourtallier, O. (2002). On the convergence to Nash equilibrium in problems of distributed computing. Annals of Operations Research, 109(1–4), 279–291.

    Article  Google Scholar 

  • Breugelmans, E., Bijmolt, T. H. A., Zhang, J., Basso, L. J., Dorotic, M., Kopalle, P., et al. (2014). Advancing research on loyalty programs: A future research agenda. Marketing Letters, 26(2), 127–139.

    Article  Google Scholar 

  • Byrd, R. H., Gilbert, J. C., & Nocedal, J. (2000). A trust region method based on interior point techniques for nonlinear programming. Mathematical Programming, 89(1), 149–185.

    Article  Google Scholar 

  • Cachon, G. P., & Swinney, R. (2009). The impact of strategic consumer behavior on the value of operational flexibility. In C. S. Tang & S. Netessine (Eds.), Consumer-driven demand and operations management models’, number 131 in ‘International series in operations research & management science’ (pp. 371–395). New York: Springer.

    Google Scholar 

  • Cao, Y., Nsakanda, A. L., & Diaby, M. (2015). Planning the supply of rewards with cooperative promotion considerations in coalition loyalty programmes management. Journal of the Operational Research Society, 66(7), 1140–1154.

    Article  Google Scholar 

  • Dai, Y., Chao, X., Fang, S.-C., & Nuttle, H. L. W. (2005). Game theoretic analysis of a distribution system with customer market search. Annals of Operations Research, 135(1), 223–228.

    Article  Google Scholar 

  • Dasu, S., & Tong, C. (2010). Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes. European Journal of Operational Research, 204(3), 662–671.

    Article  Google Scholar 

  • Dowling, G. R., & Uncles, M. (1997). Do customer loyalty programs really work? MIT Sloan Management Review, 38(4), 71–82.

    Google Scholar 

  • Drèze, X., & Nunes, J. (2009). Feeling superior: The impact of loyalty program structure on consumers perceptions of status. Journal of Consumer Research, 35(6), 890–905.

    Article  Google Scholar 

  • Eggert, A., Steinhoff, L., & Garnefeld, I. (2015). Managing the bright and dark sides of status endowment in hierarchical loyalty programs. Journal of Service Research, 18(2), 210–228.

    Article  Google Scholar 

  • Facchinei, F., & Kanzow, C. (2010). Generalized Nash equilibrium problems. Annals of Operations Research, 175(1), 177–211.

    Article  Google Scholar 

  • Gandomi, A., & Zolfaghari, S. (2011). A stochastic model on the profitability of loyalty programs. Computers & Industrial Engineering, 61(3), 482–488.

    Article  Google Scholar 

  • Gandomi, A., & Zolfaghari, S. (2013). Profitability of loyalty reward programs: An analytical investigation. OMEGA-International Journal of Management Science, 41(4), 797–807.

    Article  Google Scholar 

  • Gandomi, A., & Zolfaghari, S. (2018). To tier or not to tier: An analysis of multitier loyalty programs optimality conditions. OMEGA-International Journal of Management Science, 74, 20–36.

    Article  Google Scholar 

  • Jongen, H. T., & Weber, G.-W. (1990). On parametric nonlinear programming. Annals of Operations Research, 27(1), 253–283.

    Article  Google Scholar 

  • Kang, J., Alejandro, T. B., & Groza, M. D. (2015). Customer company identification and the effectiveness of loyalty programs. Journal of Business Research, 68(2), 464–471.

    Article  Google Scholar 

  • Keh, H. T., & Lee, Y. H. (2006). Do reward programs build loyalty for services? The moderating effect of satisfaction on type and timing of rewards. Journal of Retailing, 82(2), 127–136.

    Article  Google Scholar 

  • Kim, B.-D., Shi, M., & Srinivasan, K. (2001). Reward programs and tacit collusion. Marketing Science, 20(2), 99–120.

    Article  Google Scholar 

  • Kivetz, R. (2003). The effects of effort and intrinsic motivation on risky choice. Marketing Science, 22(4), 477–502.

    Article  Google Scholar 

  • Kivetz, R. (2005). Promotion reactance: The role of effortreward congruity. Journal of Consumer Research, 31(4), 725–736.

    Article  Google Scholar 

  • Kivetz, R., & Simonson, I. (2002). Earning the right to indulge: Effort as a determinant of customer preferences toward frequency program rewards. Journal of Marketing Research, 39(2), 155–170.

    Article  Google Scholar 

  • Kivetz, R., Urminsky, O., & Zheng, Y. (2006). The goal-gradient hypothesis resurrected: Purchase acceleration, illusionary goal progress, and customer retention. Journal of Marketing Research, 43(1), 39–58.

    Article  Google Scholar 

  • Kopalle, P. K., Sun, Y., Neslin, S. A., Sun, B., & Swaminathan, V. (2012). The joint sales impact of frequency reward and customer tier components of loyalty programs. Marketing Science, 31(2), 216–235.

    Article  Google Scholar 

  • Lacey, R., Suh, J., & Morgan, R. M. (2007). Differential effects of preferential treatment levels on relational outcomes. Journal of Service Research, 9(3), 241–256.

    Article  Google Scholar 

  • Lederman, M. (2007). Do enhancements to loyalty programs affect demand? The impact of international frequent flyer partnerships on domestic airline demand. The RAND Journal of Economics, 38(4), 1134–1158.

    Article  Google Scholar 

  • Lewis, M. (2004). The influence of loyalty programs and short-term promotions on customer retention. Journal of Marketing Research, 41(3), 281–292.

    Article  Google Scholar 

  • Lim, S., & Lee, B. (2015). Loyalty programs and dynamic consumer preference in online markets. Decision Support Systems, 78, 104–112.

    Article  Google Scholar 

  • Liu, Y. (2007). The long-term impact of loyalty programs on consumer purchase behavior and loyalty. Journal of Marketing, 71(4), 19–35.

    Article  Google Scholar 

  • Liu, Y., & Yang, R. (2009). Competing loyalty programs: Impact of market saturation, market share, and category expandability. Journal of Marketing, 73(1), 93–108.

    Article  Google Scholar 

  • Mägi, A. W. (2003). Share of wallet in retailing: The effects of customer satisfaction, loyalty cards and shopper characteristics. Journal of Retailing, 79(2), 97–106.

    Article  Google Scholar 

  • Marianov, V., & Eiselt, H. A. (2016). On agglomeration in competitive location models. Annals of Operations Research, 246(1–2), 31–55.

    Article  Google Scholar 

  • McCall, M., & Voorhees, C. (2010). The drivers of loyalty program success: An organizing framework and research agenda. Cornell Hospitality Quarterly, 51(1), 35–52.

    Article  Google Scholar 

  • Meyer-Waarden, L. (2008). The influence of loyalty programme membership on customer purchase behaviour. European Journal of Marketing, 42(1/2), 87–114.

    Article  Google Scholar 

  • Morè, J. J., Garbow, B. S., & Hillstrom, K. E. (1980). User guide for MINPACK-1. Technical report, Argonne National Laboratory, Argonne, IL.

  • Nako, S. M. (1992). Frequent flyer programs and business travellers: An empirical investigation. Logistics and Transportation Review, 28(4), 395–414.

    Google Scholar 

  • Nunes, J., & Drèze, X. (2006). The endowed progress effect: How artificial advancement increases effort. Journal of Consumer Research, 32(4), 504–512.

    Article  Google Scholar 

  • Ott, B. (2011). Making loyalty programs work. Viewed May 26, 2016. http://www.gallup.com/businessjournal/149570/Making-Loyalty-Programs-Work.aspx.

  • Passingham, J. (1998). Grocery retailing and the loyalty card. Journal of the Market Research Society, 40(1), 55–64.

    Article  Google Scholar 

  • Roehm, M. L., Pullins, E. B., & Roehm, H. A, Jr. (2002). Designing loyalty-building programs for packaged goods brands. Journal of Marketing Research, 39(2), 202–213.

    Article  Google Scholar 

  • Roehm, M. L., & Roehm, H. A, Jr. (2010). The influence of redemption time frame on responses to incentives. Journal of the Academy of Marketing Science, 39(3), 363–375.

    Article  Google Scholar 

  • Ross, S. M. (1995). Stochastic processes (2nd ed.). New York: Wiley.

    Google Scholar 

  • Sharp, B., & Sharp, A. (1997). Loyalty programs and their impact on repeat-purchase loyalty patterns. International Journal of Research in Marketing, 14(5), 473–486.

    Article  Google Scholar 

  • Shugan, S. M. (2005). Brand loyalty programs: Are they shams? Marketing Science, 24(2), 185–193.

    Article  Google Scholar 

  • Singh, S. S., Jain, D. C., & Krishnan, T. V. (2008). Customer loyalty programs: Are they profitable? Management Science, 54(6), 1205–1211.

    Article  Google Scholar 

  • Smith, A., Sparks, L., Hart, S., & Tzokas, N. (2003). Retail loyalty schemes: Results from a consumer diary study. Journal of Retailing and Consumer Services, 10(2), 109–119.

    Article  Google Scholar 

  • Talluri, K. T., & Van Ryzin, G. (2004). The theory and practice of revenue management, number 68 in ‘International series in operations research & management science’. Boston, MA: Kluwer.

    Google Scholar 

  • Tanford, S. (2013). The impact of tier level on attitudinal and behavioral loyalty of hotel reward program members. International Journal of Hospitality Management, 34, 285–294.

    Article  Google Scholar 

  • Taylor, G. A., & Neslin, S. A. (2005). The current and future sales impact of a retail frequency reward program. Journal of Retailing, 81(4), 293–305.

    Article  Google Scholar 

  • Van den Poel, D., & Lariviere, B. (2004). Customer attrition analysis for financial services using proportional hazard models. European Journal of Operational Research, 157(1), 196–217.

    Article  Google Scholar 

  • Von Weizsacker, C. (1984). The costs of substitution. Econometrica, 52(5), 1085–1116.

    Article  Google Scholar 

  • Wagner, T., Hennig-Thurau, T., & Rudolph, T. (2009). Does customer demotion jeopardize loyalty? Journal of Marketing, 73(3), 69–85.

    Article  Google Scholar 

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Correspondence to Amir Gandomi.

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List of symbols

See Table 3.

Table 3 List of symbols

The effect of parameters on the equilibrium values of decision variables

See Figs. 14 and 15.

Fig. 14
figure 14

The effect of parameters on equilibrium prices and rewards in the nonlinear rewards case

Fig. 15
figure 15

The effect of parameters on equilibrium prices and rewards in the linear rewards case

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Gandomi, A., Bazargan, A. & Zolfaghari, S. Designing competitive loyalty programs: a stochastic game-theoretic model to guide the choice of reward structure. Ann Oper Res 280, 267–298 (2019). https://doi.org/10.1007/s10479-019-03179-1

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