The Signaling Effect of Sampling Size in Online Physical Goods Sampling
42 Pages Posted: 1 Sep 2016 Last revised: 20 Apr 2020
Date Written: April 18, 2020
Despite the popular use of product sampling as a promotional strategy by retailers, existing research has largely focused on offline sampling of physical goods and online sampling of information goods but overlooked online sampling of physical goods. We argue that, in the context of online sampling of physical goods, sampling size serves as a signal of product quality and can positively influence product sales. This effect would also vary across product types (i.e., search, experience, and credence products). To validate, we assemble a rich panel-level data set from Taobao.com for empirical analysis. We use a structural model to characterize the decision process of Taobao’s e-tailers on the number of free samples they should provide. We address the endogeneity of sampling size and product price using a structural model and instrumental variables. We find that sampling size has a significant and positive effect on sales and that experience products benefit the most from this effect than search and credence products. We further investigate how e-tailers’ campaign participation decision is affected by online sampling platform’s setting of sampling threshold, i.e., the minimum total value of sampling products that an e-tailer needs to provide for campaign participation. Our policy simulations find that reducing sampling threshold allows more e-tailers to participate in the campaign but lowers the average sampling size, whereas increasing it prevents many e-tailers from participation but can effectively increase sampling size. Our study fills the research gap of online physical goods sampling and provides managerial implications to practitioners.
Keywords: product sampling; product type; signaling effect; structural model
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