Understanding Consumer Dynamic Decision Making Under Competing Loyalty Programs

60 Pages Posted: 4 Sep 2019

See all articles by Jia Liu

Jia Liu

HKUST Business School

Asim Ansari

Columbia Business School - Marketing

Date Written: May 21, 2019

Abstract

We develop an incentive-aligned experimental paradigm to study how consumer purchase dynamics are affected by the interplay between the loyalty programs and the pricing and promotional strategies of competing firms. In our experiment, subjects made sequential choices between two competing airlines in a stylized frequent traveler task for which an optimal dynamic decision policy can be numerically computed. We find that, on average, subjects are able to partially realize the long-term benefits from loyalty programs, though they are most sensitive to prices. We also find that the preferences and the levels of bounded rationality of our subjects depend on the nature of the competitive environment, the particular state of each decision scenario, and the type of optimal action. Accordingly, we use an approximate dynamic programming model to incorporate boundedly rational decision making. The model classifies subjects into five segments that exhibit variation in their performance and decision strategies. Importantly, we find that the overall market outcome and the performance of each firm are influenced by both the competitive environment and the assumption on the extent of consumer optimality.

Keywords: Loyalty Programs, Promotions, Competition, Bounded Rationality, Approximate Dynamic Programming, Experiments

JEL Classification: M31

Suggested Citation

Liu, Jia and Ansari, Asim, Understanding Consumer Dynamic Decision Making Under Competing Loyalty Programs (May 21, 2019). Columbia Business School Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=3447666 or http://dx.doi.org/10.2139/ssrn.3447666

Jia Liu (Contact Author)

HKUST Business School ( email )

Clear Water Bay
Hong Kong

Asim Ansari

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

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