Search Revisits
SSRN, ISSN: 1556-5068
2020
- 1Citations
- 3,081Usage
- 5Captures
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.
Article Description
Why do consumers revisit previously searched products (“search revisits”) before making a purchase decision? Using a detailed click-stream data set from a popular hotel meta-search engine that uniquely identifies the information (photos, reviews, prices etc.) consumers obtained on every product search, we show the following. Search revisits are common, with half of all search sessions where consumers searched two or more hotels including at least one revisit. Surprisingly, most revisit behavior is not driven by consumers’ desire to look at additional information about a product, as assumed in prior work. Rather, in 70% of all revisits, consumers look at a subset of the same information that they saw on previous searches. Also, products revisited for additional information are frequently purchased. In contrast, revisits for the same information are typically short, involve more expensive and lower quality products, and are unlikely to lead to a purchase. Based on these findings, we then investigate a number of explanations for the occurrence of search revisits. Our results are consistent with consumers revisiting either to obtain more information on options they prefer or (more frequently) to eliminate inferior options from their consideration sets (thereby saving on future decision costs). We end by discussing the implications of these and other findings for modeling consumer search behavior and by deriving managerial implications of consideration set elimination for marketing mix decisions, such as ad re-targeting.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85112857907&origin=inward; http://dx.doi.org/10.2139/ssrn.3626451; https://www.ssrn.com/abstract=3626451; https://dx.doi.org/10.2139/ssrn.3626451; https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3626451; https://ssrn.com/abstract=3626451
Elsevier BV
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