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Larger number of reviews or higher rating? The firm’s pricing and quality disclosure strategies on the online platform

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Abstract

Considering two common dimensions of online reviews, number of reviews and rating, this paper investigates the impacts of online reviews on the firm’s pricing and quality disclosure strategies when selling the product through an online platform’s agency or resell scheme. By setting up a two-period model, we find that the first-period retail price decreases in the presence of online reviews and the degree of the first-period retail price cut is greater when consumers assign a higher weight to the number of reviews. However, the second-period retail price does not necessarily increase in the presence of reviews, depending on realized number of reviews and rating. The firm chooses to disclose its quality when the quality is above a threshold under two selling schemes, and the quality disclosure threshold decreases with the weight that consumers assign to the rating under the resell scheme, whereas it increases with the weight to the rating under the agency scheme. The existence of online reviews may stimulate or inhibit the firm’s incentive to disclose product quality, depending on the consumer’s weight on the two dimensions and the selling scheme. Finally, the firm and the platform come to an agreement on the agency scheme when the commission rate is relatively low, leading to a win–win scenario, and the win–win scenario is more likely associated with less quality information disclosure. We also consider the endogenous correlation between the rating and true product quality in the extension to check the robustness of the results.

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Notes

  1. https://report.iresearch.cn/report/202010/3672.shtml

  2. OKEO-TEX® is the most authoritative and influential textile eco-label in the world.

  3. https://www.hbrchina.org/2015-04-07/2870.html

  4. https://www.sohu.com/a/443456019_120288442

  5. https://www.sohu.com/a/430811478_114819

  6. Empirical research [3, 4] indicates that the number of reviews and the rating are the most significant factors in the firm’s sales and consumer’s purchase decisions. Based on these empirical results, this paper considers that online review information is consisted of two dimensions of information, i.e., the number of reviews and the rating. Besides, the number of reviews is proportional to sales volume. To simplify the analysis, this paper does not distinguish between the number of reviews and sales volume.

  7. https://www.qianzhan.com/analyst/detail/329/211126-12b325a1.html

  8. This work focuses on the market that is not fully covered to guarantee higher quality leads to higher demand, given all else equal. The demand of regular consumers is \(\frac{q-ta}{2t}\). Thus, to ensure not all regular consumers will purchase the product under all possible scenarios, it needs that \(max\left\{\frac{q-ta}{2t}\right\}\le 1\), i.e., \(\frac{1}{2+a}\le t\).

  9. To focus on the impacts of online reviews on the firm’s quality disclosure strategy, we normalize the disclosure cost to \(0\) as Guan et al. [15], since the disclosure cost will not qualitatively affect our results.

  10. The “informativeness of the rating” refers to the rating that can correctly reveal the true quality of the product with a certain probability. The higher the informativeness of the rating is, the higher the probability of correctly revealing the product quality.

  11. According to Lemma 1, we have that \({\pi }_{F1}^{B*}=\frac{\left(1-\alpha \right){\left(1+2ta\right)}^{2}}{16t\left(1+bt\right)}\) and \({\pi }_{F1}^{H*}=\frac{\left(1-\alpha \right)\left[4-{m}^{2}{\left(1-\beta \right)}^{2}\right]{\left(1+2ta\right)}^{2}}{64t\left(1+bt\right)}.\)

  12. According to Lemma 1, it can be derived that \({\pi }_{F2}^{B*}=\frac{\left(1-\alpha \right)m{\left(1+2ta\right)}^{2}}{16t\left(1+bt\right)}\) and \(E\left({\pi }_{F2}^{H*}\right)=\left(1-\alpha \right)m\left[\frac{{\left(1+2ta\right)}^{2}}{16t\left(1+bt\right)}+\frac{{\beta }^{2}+4{t}^{2}{\varepsilon }^{2}{\left(1-\beta \right)}^{2}}{48t\left(1+bt\right)}\right].\)

  13. Paula’s Choice is an American skincare brand.

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Acknowledgements

He Huang was supported by the National Natural Science Foundation of China (NSFC) [Grants 72225008, 71871032] and the Fundamental Research Funds for the Central Universities, China (Projects No. 2021CDJSKZD06 and 2021CDJSKCG18). Hongyan Xu was supported by the National Natural Science Foundation of China (NSFC) [Grants 72272020, 71972019] and the Fundamental Research Funds for the Central Universities, China (Project No. 2021CDJSKCG35). The authors thank the editor and all anonymous reviewers for valuable and constructive suggestions, which have greatly improved the quality of the paper

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  1. School of Economics and Business Administration, Chongqing University, Chongqing, 400044, China

    He Huang, Yufeng Yang & Hongyan Xu

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Huang, H., Yang, Y. & Xu, H. Larger number of reviews or higher rating? The firm’s pricing and quality disclosure strategies on the online platform. Inf Technol Manag 26, 39–56 (2025). https://doi.org/10.1007/s10799-023-00397-9

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