Dissertation

Essays on product trade-ins: Implications for consumer demand and retailer behavior

Kwon, Ohjin

2010

Overview

My dissertation research examines implications of product trade-ins for consumer demand and retailer pricing behavior. Although product trade-ins are very prevalent in many durable goods markets, such as golf clubs, home appliances, and automobiles, there has been relatively little academic research examining this phenomenon. I examine how information provided by consumers' previous purchases can be leveraged to predict their future choices and its implications for retailer pricing decisions. In the first chapter, I propose a spatial autoregressive multinomial probit model in which the preferences and marketing mix responsiveness of different consumers depend upon their relative proximity to each other. Unlike previous applications of spatial models in marketing that have focused on the impact of geographical proximity between consumers, I develop a contiguity metric which accounts for the similarity between consumer's previous purchases. I demonstrate that information about a consumer's previous purchase can be harnessed to predict the choices of other consumers for other products as well as simply to improve choice predictions of the same consumer for the same product, known in the marketing literature as structural state dependence. I estimate the proposed model using transaction data for new car purchases in the midsize sedan market. The proposed model outperforms the commonly used random coefficient probit model as well as other spatial models that are based solely on the geographic closeness between consumers or that only incorporate preference or response correlation individually, but not together. I show the spatial correlations in one market may be used to yield more accurate predictions of consumer demand in other markets. I also show that ignoring spatial correlation based on previous vehicle similarity is found to underestimate the elasticity differences between brand-loyal consumers and switchers. Building on this idea, in the second chapter, I investigate how retailers incorporate consumer trade-in information in their pricing of new products, and test it in a field setting. First, I develop an analytical model of the phenomenon, and use it to derive the optimal new car prices with and without trade-in information. Second, I test the predictions of my theoretical model by estimating a hedonic regression model of new car prices obtained from transaction data in the midsize sedan market. Finally, I develop and estimate a structural choice model and conduct a series of counterfactual analysis to quantify the benefit of trade-in information to the dealer. The unique equilibrium solution of my theoretical model suggests that retailers charge a premium on new car when consumers trade in their used cars and that the premiums are even higher if the traded in vehicle is more similar to the new one. My empirical analysis supports my theory by showing that consumers who traded-in a used vehicle paid a higher price for the same new car than those who did not. Further, those consumers who traded in used cars that were of the same make and model of the new vehicle paid an even higher premium on their new car purchase. The structural model estimation results and counterfactual analysis show that price discrimination based on consumer trade-in information reduces market share but increases retailer profits because retailers end up leaving less money on the table. This demonstrates that the better information about consumer preferences provided by trade-ins substantially impacts dealer profits.

• Publisher: ProQuest Dissertations & Theses
• Subject: Business administration / Economic models / Marketing / Retailing industry / Studies
• ISBN: 9781109774504, 1109774508