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Thursday - November 14, 2019 
Reverse Logistics Magazine - Edition 99
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Reverse Logistics Magazine - Edition 98
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A View from Academia

A View from Academia

by Mark Ferguson, Guangzhi Shang, and Michael Galbreth , , Univ of South Carolina,Florida State Univ, Univ of Tennessee

Reverse Logistics Magazine, Edition 99

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One out of three online purchases are turned. This signifies the magnitude of the consumer product returns problem for retailers working in the online space. The root cause of higher online return rates is the (relative) lack of touch and feel experience which consumers gain when they shop through a bricks-and-mortar store or a showroom. In academic terms, this is known as the product uncertainty issue and the way to solve it is to simply provide better information regarding the fit of the product to consumers. In Edition 98, we have covered a study investigating how an apparel retailer is doing this through a virtual fitting technology. Another channel of information provision, arguably much more accessible to online retailers, is the consumer generated product reviews. The value of reviews for driving sales has been demonstrated for a variety of products, such as books, movies, electronics, and apparel. In general, the conclusion is that the three Vs all matter – volume (number of reviews), valence (average rating), and variance (standard deviation of rating). However, we know much less about whether and how reviews help reduce returns. This is surprising since the fundamental goal of a review is to tell a story of “why I like/dislike the product”, which should influence subsequent consumer’s return tendency in a considerably way.

In their recently published paper in the Information System Research journal, Professors Sahoo, Dellarocas, and Srinivasan provide interesting insights into this question. Using a rich dataset from a multichannel, multibrand North America retailer, the authors show that the three Vs also matter for returns: volume and valence reduce customer’s return probability, while variation does the opposite. Moreover, the authors go on to show that not all reviews are created equal. Modern online review interface often provides with viewers an option to vote for whether a review is helpful or not (e.g., Amazon). If the fraction of helpful reviews is increased by 10%, return probability goes down by 0.44%. Who writes the review also matters. A 10% increase in the fraction of reviews written by top reviewers reduces return probability by 0.24%. Further empirical details from this study can be found below:

Sahoo, N., Dellarocas, C., & Srinivasan, S. (2018). The impact of online product reviews on product returns. Information Systems Research, 29(3), 723-738.

This recurring series provides plain-English summaries of leading academic research in the area of consumer returns. It is co-produced by Mark Ferguson (Univ. of South Carolina), Michael Galbreth (Univ. of Tennessee), and Guangzhi Shang (Florida State Univ.).
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