To tier or not to tier: An analysis of multitier loyalty programs׳ optimality conditions

We analyze the effectiveness of multitier customer loyalty programs (LPs), based on which more loyal members are rewarded with disproportionately higher benefits. We develop a theoretical model to address this essential, yet understudied, question: what are the conditions under which the multitier s...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Omega (Oxford) Jg. 74; S. 20 - 36
Hauptverfasser: Gandomi, Amir, Zolfaghari, Saeed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.01.2018
Schlagworte:
Game theory
Logit model
Markov chain
Multitier loyalty rewards
Nonlinear programming
Markov chain
Nonlinear programming
Logit model
Multitier loyalty rewards
Game theory
ISSN:0305-0483, 1873-5274
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:We analyze the effectiveness of multitier customer loyalty programs (LPs), based on which more loyal members are rewarded with disproportionately higher benefits. We develop a theoretical model to address this essential, yet understudied, question: what are the conditions under which the multitier structure is optimal? We model an asymmetric duopoly market where one firm offers a three-tier LP and the other firm offers a lower price. In a multi-period setup, heterogeneous customers strategically evaluate their utility and decide where to buy. The utility is formulated in terms of the offered prices and the LP׳s design parameters, i.e., reward values and thresholds of different tiers. The marginal effect of utility components is captured by three sensitivity coefficients, namely reward, price, and distance sensitivity. The logit model is used to formulate customers׳ choice behavior. We use Markov chain to derive the distribution of customers׳ accumulated purchases and the expected revenue functions of the firms. By conducting a rigorous numerical study, we characterize the optimality conditions of the multitier structure. Our findings show that when the distance sensitivity is higher than the reward sensitivity, the multitier structure produces suboptimal revenues. We find that the characteristics of a firm׳s customers are more important than its competitor׳s pricing in driving the optimal design of the LP. Furthermore, our model explains two other common cases in practice: offering “buy-x-get-one-free” rewards and forgoing an LP altogether. Using the model, we formulate the optimality conditions of these two cases. •A model is developed to derive the optimality conditions of a multitier LP.•We characterize the optimality conditions of buy-x-get-one-free and linear rewards.•We determine the conditions under which a firms should refrain from offering an LP.•A higher reward sensitivity than distance sensitivity makes multitier LPs suboptimal.•In determining the optimal structure, customers are more important than competitors.
ISSN:0305-0483
1873-5274
DOI:10.1016/j.omega.2017.01.003