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Recommendation technologies and consumption diversity: An experimental study on product recommendations, consumer search, and sales diversity

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  • Yi, Sangyoon
  • Kim, Dongyeon
  • Ju, Jaehyeon

Abstract

Research has found two contrasting effects of recommendations on sales diversity: the long-tail effect (enabling niche products to be discovered and purchased) and the rich-get-richer effect (making popular products more popular). Given the mixed empirical findings, however, the literature lacks scholarly efforts to systematically examine when and why recommendations result in certain consequences. To fill this gap, we design a laboratory experiment where participants, divided into two groups with and without product recommendations, engage in online shopping for two types of products, search and experience goods. We find that with recommendations, more diverse products are attended, but less diverse ones are purchased. The sales diversity-reducing (rich-get-richer) effect of recommendations is more pronounced when shopping for the search goods, whereas the search scope-broadening (long-tail) effect of recommendations is more pronounced for the experience goods. We theorize that recommendations not only generate a popularity bias, but also serve a preference-matching role, and the former is more pronounced when shopping for the search goods while the later for the experience goods. Consequently, recommendations result in shorter search for the search goods, but longer search for the experience goods. Our analysis suggests recommendation scope and intensity as useful measures to understand the underlying mechanism. We conclude with discussions on the implications of our results, including potential social costs of recommendation technologies such as distortions or biases in market demand.

Suggested Citation

  • Yi, Sangyoon & Kim, Dongyeon & Ju, Jaehyeon, 2022. "Recommendation technologies and consumption diversity: An experimental study on product recommendations, consumer search, and sales diversity," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
  • Handle: RePEc:eee:tefoso:v:178:y:2022:i:c:s004016252200018x
    DOI: 10.1016/j.techfore.2022.121486
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    References listed on IDEAS

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