TY - JOUR
T1 - A sequential choice model for multiple discrete demand
AU - Lee, Sanghak
AU - Kim, Sunghoon
AU - Park, Sungho
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/6
Y1 - 2022/6
N2 - Consumer demand in a marketplace is often characterized to be multiple discrete in that discrete units of multiple products are chosen together. This paper develops a sequential choice model for such demand and its estimation technique. Given an inherently high-dimensional problem to solve, a consumer is assumed to simplify it to a sequence of one-unit choices, which eventually leads to a shopping basket of multiple discreteness. Our model and its estimation method are flexible enough to be extended to various contexts such as complementary demand, non-linear pricing, and multiple constraints. The sequential choice process generally finds an optimal solution of a convex problem (e.g., maximizing a concave utility function over a convex feasible set), while it might result in a sub-optimal solution for a non-convex problem. Therefore, in case of a convex optimization problem, the proposed model can be viewed as an econometrician’s means for establishing the optimality of observed demand, offering a practical estimation algorithm for discrete optimization models of consumer demand. We demonstrate the strengths of our model in a variety of simulation studies and an empirical application to consumer panel data of yogurt purchase.
AB - Consumer demand in a marketplace is often characterized to be multiple discrete in that discrete units of multiple products are chosen together. This paper develops a sequential choice model for such demand and its estimation technique. Given an inherently high-dimensional problem to solve, a consumer is assumed to simplify it to a sequence of one-unit choices, which eventually leads to a shopping basket of multiple discreteness. Our model and its estimation method are flexible enough to be extended to various contexts such as complementary demand, non-linear pricing, and multiple constraints. The sequential choice process generally finds an optimal solution of a convex problem (e.g., maximizing a concave utility function over a convex feasible set), while it might result in a sub-optimal solution for a non-convex problem. Therefore, in case of a convex optimization problem, the proposed model can be viewed as an econometrician’s means for establishing the optimality of observed demand, offering a practical estimation algorithm for discrete optimization models of consumer demand. We demonstrate the strengths of our model in a variety of simulation studies and an empirical application to consumer panel data of yogurt purchase.
KW - Discrete optimization
KW - Multiple discreteness
KW - Sequential choice
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U2 - 10.1007/s11129-022-09250-9
DO - 10.1007/s11129-022-09250-9
M3 - Article
AN - SCOPUS:85127719936
SN - 1570-7156
VL - 20
SP - 141
EP - 178
JO - Quantitative Marketing and Economics
JF - Quantitative Marketing and Economics
IS - 2
ER -