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Quality in Context: Experience-Relevant Consumption Context Influences Product Ratings.

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Τίτλος: Quality in Context: Experience-Relevant Consumption Context Influences Product Ratings.
Συγγραφείς: Meister, Matt (AUTHOR) mmeister@usfca.edu, Reinholtz, Nicholas (AUTHOR)
Πηγή: Journal of Marketing. Nov2026, Vol. 90 Issue 6, p69-89. 21p.
Θεματικοί όροι: *Consumption (Economics), *Product reviews, Experience, Recreational equipment, Weather
Εταιρία/Οντότητα: Recreational Equipment Inc.
Περίληψη: Experience with a product is shaped by two things: (1) aspects of the product itself and (2) aspects of the environment in which the product is consumed. This article documents evidence that when consumers translate their experiences into ratings of products, they overattribute their experience to products and underattribute experience to context (the environment in which the product is consumed). First, 218,918 ratings collected from REI demonstrate that ratings for cold-weather gear (products designed to keep people warm) are positively correlated with temperature: These products get lower ratings when the weather is cold and higher ratings when the weather is warm, controlling for climate and season. Ratings for other products (e.g., bicycles, tents, and skis) are not affected by temperature. This effect generalizes to other products and contexts both in the REI data (e.g., rain jackets and rain) and in a laboratory experiment. The article also identifies attenuating conditions for this effect. Specifically, the effect seems to be smaller when reviewers explicitly consider context, and when context information is made more accessible, while rating. These findings inform several possible interventions for platforms, which are assessed and validated. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Marketing 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: Quality in Context: Experience-Relevant Consumption Context Influences Product Ratings.
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  Data: Experience with a product is shaped by two things: (1) aspects of the product itself and (2) aspects of the environment in which the product is consumed. This article documents evidence that when consumers translate their experiences into ratings of products, they overattribute their experience to products and underattribute experience to context (the environment in which the product is consumed). First, 218,918 ratings collected from REI demonstrate that ratings for cold-weather gear (products designed to keep people warm) are positively correlated with temperature: These products get lower ratings when the weather is cold and higher ratings when the weather is warm, controlling for climate and season. Ratings for other products (e.g., bicycles, tents, and skis) are not affected by temperature. This effect generalizes to other products and contexts both in the REI data (e.g., rain jackets and rain) and in a laboratory experiment. The article also identifies attenuating conditions for this effect. Specifically, the effect seems to be smaller when reviewers explicitly consider context, and when context information is made more accessible, while rating. These findings inform several possible interventions for platforms, which are assessed and validated. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Marketing 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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      – Type: doi
        Value: 10.1177/00222429251365883
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 69
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      – SubjectFull: Consumption (Economics)
        Type: general
      – SubjectFull: Product reviews
        Type: general
      – SubjectFull: Experience
        Type: general
      – SubjectFull: Recreational equipment
        Type: general
      – SubjectFull: Weather
        Type: general
      – SubjectFull: Recreational Equipment Inc.
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              Text: Nov2026
              Type: published
              Y: 2026
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