Consumer search in the U.S. auto industry: The role of dealership visits.

IF 1.1 4区 管理学 Q3 BUSINESS Qme-Quantitative Marketing and Economics Pub Date : 2021-01-01 Epub Date: 2020-10-26 DOI:10.1007/s11129-020-09229-4
Dan Yavorsky, Elisabeth Honka, Keith Chen
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Abstract

In many markets, consumers visit stores and physically inspect products before making purchase decisions. We view the inspection of a product at a retail location as a search for product fit. We quantify the cost and benefit from searching for product fit using a discrete choice model of demand with optimal sequential search. In these models, the benefit of searching is measured by the standard deviation of the product fit and has, heretofore, been fixed to one in estimation. We show that, with an exogenous search cost shifter, both the cost and benefit of searching can be separately estimated. Our empirical setting is the U.S. automotive market. We assemble a unique data set containing individual-level smartphone geolocation data that inform us about dealership visits. We also obtain information on new vehicle purchases from proprietary DMV registration data. Our exogenous cost shifter is the distance a consumer must travel to visit a dealership. Our results show that the benefit provided by dealerships to consumers is substantial. Within our empirical context, failure to estimate the standard deviation of the product fit leads to biased search cost and consumer surplus estimates and to inaccurate predictions regarding consumers' number of searches and effects of at-home test drive programs.

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美国汽车行业的消费者搜索:经销商访问的作用
在许多市场中,消费者在做出购买决定之前,会到商店亲自检查产品。我们把在零售店检查产品看作是寻找产品是否合适。我们使用具有最优顺序搜索的离散需求选择模型来量化产品匹配搜索的成本和收益。在这些模型中,搜索的收益是通过产品拟合的标准差来衡量的,到目前为止,在估计中一直固定为1。研究表明,当存在外生搜索成本转移因子时,搜索的成本和收益都可以单独估计。我们的实证背景是美国汽车市场。我们组装了一个独特的数据集,其中包含个人层面的智能手机地理位置数据,告知我们有关经销商访问。我们还从DMV注册数据中获取新车购买信息。我们的外生成本转移因素是消费者必须前往经销商的距离。我们的研究结果表明,经销商给消费者带来的好处是巨大的。在我们的经验背景下,未能估计产品匹配的标准偏差会导致有偏见的搜索成本和消费者剩余估计,以及对消费者搜索次数和家庭试驾计划影响的不准确预测。
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来源期刊
CiteScore
2.30
自引率
10.50%
发文量
13
期刊介绍: Quantitative Marketing and Economics (QME) publishes research in the intersection of Marketing, Economics and Statistics. Our focus is on important applied problems of relevance to marketing using a quantitative approach. We define marketing broadly as the study of the interface between firms, competitors and consumers. This includes but is not limited to consumer preferences, consumer demand and decision-making, strategic interaction of firms, pricing, promotion, targeting, product design/positioning, and channel issues. We embrace a wide variety of research methods including applied economic theory, econometrics and statistical methods. Empirical research using primary, secondary or experimental data is also encouraged. Officially cited as: Quant Mark Econ
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