Estimating Search Benefits from Path-Tracking Data: Measurement and Determinants
Estimating Search Benefits from Path-Tracking Data: Measurement and Determinants
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DOI：
10.1287/mksc.2017.1026
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发表时间：
2017-07-01
影响因子：
5
通讯作者：
Pinna, Fabio
中科院分区：
文献类型：
--
作者：
Seiler, Stephan;Pinna, Fabio
我们研究了实体店环境中的消费者搜索行为，使用了从超市购物车上的射频识别标签获得的独特数据集。这项技术使我们能够记录消费者的购买行为，以及他们在考虑购买哪种产品时在货架前花费的时间，从而为我们提供了搜索努力的直接衡量标准。我们估计了价格对搜索持续时间的线性回归，其中搜索持续时间是用搜索成本移位器来衡量的。我们表明，这种回归允许我们从搜索中恢复边际收益在价格方面的最佳停止点为普通消费者。我们的识别策略和系数解释对于广泛的搜索模型都是有效的，因此我们能够保持对搜索过程细节的不可知性，例如搜索顺序和搜索协议。我们估计搜索的平均回报为每分钟2.10美元，并探索了消费者类型、产品类别和商店类别位置的异质性。我们发现，不同产品类别的搜索结果差别不大，但不同消费者类型和地点的搜索结果差别很大。我们的研究结果表明，情境因素，如品类的位置或在购物过程中搜索的时间，是搜索行为的更重要的决定因素，而不是品类特征，如可用产品的数量。
We study consumer search behavior in a brick-and-mortar store environment, using a unique data set obtained from radio-frequency identification tags, which are attached to supermarket shopping carts. This technology allows us to record consumers' purchases as well as the time they spent in front of the shelf when contemplating which product to buy, giving us a direct measure of search effort. We estimate a linear regression of price paid on search duration, in which search duration is instrumented with a search-cost shifter. We show that this regression allows us to recover the marginal return from search in terms of price at the optimal stopping point for the average consumer. Our identification strategy and coefficient interpretation are valid for a broad class of search models, and we are hence able to remain agnostic about the details of the search process, such as search order and search protocol. We estimate an average return from search of $2.10 per minute and explore heterogeneity across consumer types, product categories, and category location in the store. We find little difference in the returns from search across product categories, but large differences across consumer types and locations. Our findings suggest that situational factors, such as the location of the category or the timing of the search within the shopping trip, are more important determinants of search behavior than category characteristics such as the number of available products.