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How Effective Is Suggested Pricing? Experimental Evidence from an E-Commerce Platform.

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Τίτλος: How Effective Is Suggested Pricing? Experimental Evidence from an E-Commerce Platform.
Συγγραφείς: Fong, Jessica (AUTHOR) jyfong@umich.edu, Manchanda, Puneet (AUTHOR), Song, Yu (AUTHOR)
Πηγή: Journal of Marketing Research (JMR). Oct2026, Vol. 63 Issue 5, p789-810. 22p.
Θεματικοί όροι: *Digital platforms, *Pricing, *Selling, *Business revenue, *Dealers (Retail trade)
Εταιρία/Οντότητα: Mercari (Company)
Περίληψη: This research investigates how platform-suggested prices influence sellers' pricing decisions and selling outcomes. In collaboration with Mercari, a peer-to-peer e-commerce platform, the authors conduct a field experiment that varies whether a seller receives a suggested price—and, if so, the suggested price itself. They find that a 30% change in suggested prices leads to a 5% change in listing prices in the same direction. Suggested prices are more influential when pricing is more challenging, such as for new sellers and used items. Lower suggested prices improve both the likelihood of sale and the resulting seller revenue. A subsequent experiment shows that these results are likely to generalize to the full equilibrium. The findings imply that platform-suggested pricing is an effective compromise that guides seller pricing while allowing sellers to incorporate their private information. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Marketing Research (JMR) is the property of American Marketing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Business Source Index
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  Data: How Effective Is Suggested Pricing? Experimental Evidence from an E-Commerce Platform.
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  Data: *<searchLink fieldCode="DE" term="%22Digital+platforms%22">Digital platforms</searchLink><br />*<searchLink fieldCode="DE" term="%22Pricing%22">Pricing</searchLink><br />*<searchLink fieldCode="DE" term="%22Selling%22">Selling</searchLink><br />*<searchLink fieldCode="DE" term="%22Business+revenue%22">Business revenue</searchLink><br />*<searchLink fieldCode="DE" term="%22Dealers+%28Retail+trade%29%22">Dealers (Retail trade)</searchLink>
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  Data: This research investigates how platform-suggested prices influence sellers' pricing decisions and selling outcomes. In collaboration with Mercari, a peer-to-peer e-commerce platform, the authors conduct a field experiment that varies whether a seller receives a suggested price—and, if so, the suggested price itself. They find that a 30% change in suggested prices leads to a 5% change in listing prices in the same direction. Suggested prices are more influential when pricing is more challenging, such as for new sellers and used items. Lower suggested prices improve both the likelihood of sale and the resulting seller revenue. A subsequent experiment shows that these results are likely to generalize to the full equilibrium. The findings imply that platform-suggested pricing is an effective compromise that guides seller pricing while allowing sellers to incorporate their private information. [ABSTRACT FROM AUTHOR]
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  Label:
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  Data: <i>Copyright of Journal of Marketing Research (JMR) is the property of American Marketing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1177/00222437261432198
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 789
    Subjects:
      – SubjectFull: Digital platforms
        Type: general
      – SubjectFull: Pricing
        Type: general
      – SubjectFull: Selling
        Type: general
      – SubjectFull: Business revenue
        Type: general
      – SubjectFull: Dealers (Retail trade)
        Type: general
      – SubjectFull: Mercari (Company)
        Type: general
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      – TitleFull: How Effective Is Suggested Pricing? Experimental Evidence from an E-Commerce Platform.
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            NameFull: Manchanda, Puneet
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            NameFull: Song, Yu
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            – D: 01
              M: 10
              Text: Oct2026
              Type: published
              Y: 2026
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