The Effect of Rating Scale Design on Extreme Response Tendency in Consumer Product Ratings
| Autor: | Dimitrios Tsekouras |
|---|---|
| Přispěvatelé: | Department of Technology and Operations Management |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Economics and Econometrics
05 social sciences Word of mouth 050109 social psychology Response bias Extreme Response Rating scale 0502 economics and business Econometrics 050211 marketing 0501 psychology and cognitive sciences Product (category theory) Business and International Management Extreme point Marketing Marketing research Robustness (economics) Psychology |
| Zdroj: | International Journal of Electronic Commerce, 21(2), 270-296. M.E. Sharpe Inc. |
| ISSN: | 1557-9301 1086-4415 |
| Popis: | Consumer-generated product ratings have become a fundamental component of online businesses, yet seem to be susceptible to biases that shift the distribution toward the extreme points of the rating scales. Response biases (such as extreme response style) due to intrinsic traits are widely investigated in survey design and marketing research, yet little is known about how rating scale variations in consumer-generated product evaluation systems influence the generated ratings. In two experiments across two product categories, the findings suggest that explicitly labeling the midpoint of the rating scale reduces extreme responses, though this effect is attenuated when emotional labels are used at the endpoints. Furthermore, the use of emotional labels deters users from giving extreme ratings when the size of the rating scale is large. The effects remain consistent across different model specifications and robustness checks. The study extends the theoretical implications regarding extreme response bias in the context of consumer product ratings and enriches the understanding of response behavior beyond self-selection reasons, and across various rating scale elements, product contexts, and sample traits. The broad use of product ratings in generating recommendations and estimating future product performance and investments necessitates a focus on how to better account for such potential distortions in these ratings due to the implemented rating scales. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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