Facilitating Review Information Disclosure in the Platform Economy: Is More Accurate Always Better?

Online consumer reviews (OCRs) publicly disclose consumer uncertainty about product valuations, enabling firms to acquire more accurate demand information. This paper develops a game-theoretic model in which a manufacturer sells products through both physical stores and a third-party online platform, which may operate in reselling or agency business modes. We investigate the interplay between OCR disclosure and business mode choices. We find that the manufacturer and the platform generally share aligned interests in OCR disclosure across business modes, with the information value of OCRs shaped by their accuracy and the uncertainty of consumers regarding product valuations. Specifically, OCR disclosure benefits both parties, yet it leads to higher gains for the manufacturer than the platform in the reselling mode, whereas their profit gains depend on the commission rate in the agency mode. When either consumer uncertainty about product valuations or the accuracy of OCRs is relatively low, both parties prefer the agency mode if the commission rate is moderate or the reselling mode if it is sufficiently high. When both consumer uncertainty about product valuations and the accuracy of OCRs are sufficiently high, both parties prefer the agency mode only if the commission rate is sufficiently high. Notably, the effects of OCR disclosure on the equilibrium business mode selection are non-monotonic: More accurate OCR disclosure facilitates the realization of an equilibrium business mode when the initial accuracy of OCRs is low and inhibits it when their accuracy is high. Last, we find that limited disclosure of OCRs and an endogenous commission rate can be employed as strategic tools to align business mode preferences. Our findings caution against the assumption that full OCR disclosure uniformly benefits platforms and manufacturers, and we offer practical insights for the design and operation of review systems.