Effects of product online reviews on product returns: a review and classification of the literature
International Transactions in Operational Research, ISSN: 1475-3995
2024
- 19Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures19
- Readers19
- 19
Article Description
Product returns pose a significant challenge for online retailers, primarily due to consumer uncertainty, both before and after the purchase. These uncertainties may stem from factors such as the absence of a “touch and feel” experience, mismatched product expectations, or post-purchase regret, where consumers change their minds. Online reviews, shared by previous consumers who have already experienced the products, can have a substantial impact not only on new consumers’ purchasing but also on return decisions. Surprisingly, there has been limited research to understand the influence of online reviews on product returns. This paper applies the input-process-output framework to conduct a comprehensive review and analysis of studies related to online reviews and product returns. Based on this review and analysis, a conceptual model is proposed, and an outline for the future research agenda is discussed.
Bibliographic Details
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