Platform or Wholesale? A Strategic Tool for Online Retailers to Benefit from Third-Party Information1
Abstract
Online retailing is dominated by a channel structure in which a retailer either buys products from competing manufacturers and resells to consumers (wholesale scheme) or lets manufacturers sell directly to consumers on its platform for a commission (platform scheme). Easy access to publicly available third-party information such as product reviews that facilitate consumers’ purchase decisions is another distinctive and ubiquitous characteristic of online retailing. We show that retailers can use the upstream pricing scheme, wholesale or platform, as a strategic tool to benefit from third-party information. Information on the quality dimension homogenizes consumers’ perceived utility differences between competing products and increases the upstream competition, which benefits the wholesale-based retailer but hurts the platform-based retailer. Information on the fit dimension, in constrast, heterogenizes consumers’ estimated fits to the products and softens the upstream competition, which hurts the wholesale-based retailer but benefits the platform-based retailer. Consequently, when the precision of the third-party information is high (low), a retailer can benefit from third-party information by adopting the wholesale (platform) scheme if the quality dimension plays a dominant role and by adopting the platform (wholesale) scheme if the fit dimension is dominant. Furthermore, the effect of precision improvement on the retailer’s profit depends on the pricing-scheme choice and the relative importance of quality and fit attributes in consumers’ evaluations of products. For instance, when the fit dimension is dominant, increasing the precision can hurt the wholesale-based retailer but benefit the platform-based retailer.
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Retailers can use the upstream pricing scheme as a strategic tool to benefit from online product reviews.
“Kwark et al. (2017) show that retailers can use the upstream pricing scheme as a strategic tool to benefit from online product reviews.”
From Two-Sided Adverse Selection and Bilateral Reviews in Sharing Economy (2019) · cites this paper as Kwark et al. (2017)
Cites
Bates, J. M., & Granger, C. W. J. (1969) · Journal of the Operational Research Society · doi:10.1057/jors.1969.103 · Cited by 3,201 · see citing works
Product fit uncertainty in online markets: nature, effects, and antecedents
Hong, Y. (., & Pavlou, P. A. (2014) · Information Systems Research · doi:10.1287/isre.2014.0520 · Cited by 453 · see citing works
Economics of Free Under Perpetual Licensing: Implications for the Software Industry
Niculescu, M. F., & Wu, D. J. (2014) · Information Systems Research · doi:10.1287/isre.2013.0508 · Cited by 151 · see citing works
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Desirable or Distasteful? Exploring Uncertainty in Human-Chatbot Relationships
Pan, S., Cui, J., & Mou, Y. (2024) · International Journal of Human–Computer Interaction · doi:10.1080/10447318.2023.2256554 · Cited by 44 · see citing works
Two-Sided Adverse Selection and Bilateral Reviews in Sharing Economy
Tunc, M. M., Cavusoglu, H., & Raghunathan, S. (2019) · SSRN · doi:10.2139/ssrn.3499979 · Cited by 5 · see citing works
Self-citation
- Authors
- Kwark, Y., Chen, J., & Raghunathan, S.
- Affiliations
- University of Florida (US)
- The University of Texas at Dallas (US)
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2017-09-01
- Volume
- 41
- Issue
- 3
- Pages
- 763-785
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W3123706299
- Cited by
- 350
- References
- 3
- Citations by year
- 2026: 32 · 2025: 49 · 2024: 63 · 2023: 55 · 2022: 53 · 2021: 34 · 2020: 23 · 2019: 22 · 2018: 12 · 2017: 4 · 2016: 2 · 2014: 1
- FWCI
- 28.51
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- MIS Quarterly (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Keywords
- online retail, third-party information, product reviews, information precision, upstream competition, product quality, product fit, manufacturer-retailer relationships, purchase decision
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