Mother logit analysis of substitution effects in consumer shopping destination choice

Abstract

The feasibility of new shopping centers is largely related to their relative location and spending power in the trade area. Commercial developers, retailers, and retail planners need information about the likely impact of new retail developments on consumer choice behavior. Several types of consumer choice models have been applied to assess the effects of retail developments.However, most of these models are based on the so-called independence of irrelevant alternatives assumption, and the variables of interest are included in the models in some indirect manner. The purpose of this article is to demonstrate how substitution effects in consumer shopping behavior can be estimated as a function of marketing strategies or planning scenarios. We focus on the universal or "mother" logit model in a decompositional framework.The mother logit model represents a generalization of conventional multinomial logit models in that the utility of alternatives depends not only on their attributes, but also upon the attributes of other alternatives in the choice set. These so-called cross-effects represent corrections on the utilities as predicted by the conventional multinomial logit model to account for substitution and other effects. The mother logit model was applied to predict the likely effects of a number of proposed actions to improve the attractiveness of some shopping centers in the Eindhoven region, The Netherlands. Rather than using attributes of shopping centers, possible planning actions were used to specify the utility function of the mother logit model. The model was estimated using choice data observed in hypothetical situations, created according to the principles of experimental design

Exposing Unobserved Spatial Similarity: Evidence from German School Choice Data

“…Many attempts in the past tried to overcome IIA weaknesses and to account for a richer pattern of substitution than that offered by the MNL (Hunt, Boots, and Kanaroglou [2004] for a more detailed overview). Unfortunately, most of these attempts were based on the logit model specified by McFadden (1975) (Timmermans and van der Waerden 1992). In general, the models used have not been consistent with random utility theory (Koppelman and Sethi 2000).…”

Modeling Consumer Perception of Public Space in Shopping Centers

“…Although few of these applications concerned retailing problems, some studies made retail applications of conjoint approaches (Ahn & Ghosh, 1989;Louviere & Gaeth, 1987;Louviere & Johnson, 1990Louviere & Meyer, 1981;Moore, 1990;Schuler, 1979;Timmermans, 1982;Timmermans, Borgers, & Van der Waerden, 1991;Timmermans, Van der Heijden, & Westerveld, 1982, 1984Verhallen & De Nooij, 1982). Moreover, almost all conjoint applications in retailing have studied preference or choice instead of perception of retail destination.…”

Random regret minimization for consumer choice modeling: Assessment of empirical evidence

“…They have been used to analyze and predict consumer choice behavior in a wide variety of contexts, such as related to shopping destination, store or channel choices and their choices between different products and product types (e.g., Timmermans et al, 1991;Volle, 2001;Kaplan et al, 2011;Oppewal et al, 2013) to name just a few of the abundant body of available examples published in this journal. Practically without exception, these choice models are rooted in the Nobel-prize winning concept of Random Utility Maximization or RUM (McFadden, 1973;Ben-Akiva & Lerman, 1985;Train, 2009).…”