Interfaces with Other Disciplines
Information disclosure strategies for the intermediary and competitive sellers

https://doi.org/10.1016/j.ejor.2018.06.037Get rights and content

Highlights

  • Firms manage consumer uncertainty and returns via product information disclosure.

  • Competitive sellers always choose to disclose as much information as possible.

  • Optimal information strategy of the intermediary is provided as product-specific.

  • The modified revenue sharing fraction enables firms’ Pareto improvement.

Abstract

Product information plays an important role in consumers’ purchase decisions. In this paper, we develop an analytical model to investigate how the intermediary and sellers manage consumer uncertainty and returns/exchanges by disclosing product information. We find, given the information disclosure tools, the competitive sellers always choose to disclose as much information as possible. By analyzing the intermediary's decision on the development of information tools, our results suggest that the intermediary's optimal information strategy is determined by the disclosure cost and product characteristics (i.e., product value and return cost). The intermediary is likely to invest more to develop information tools if the cost coefficient is low or if the product has a relatively high return cost compared with its value. As a result, the information tools developed by the intermediary facilitate sellers’ information disclosure at a high level. Moreover, considering particular product characteristics and information disclosure cost, we examine the role of revenue sharing fraction between the intermediary and sellers. Our findings suggest that a modified revenue sharing fraction can facilitate firms’ Pareto improvement and lead to an information-rich platform.

Introduction

Compared with physical stores, online channels provide low prices and more product categories and attract an increasing number of consumers who shop online. Meanwhile, the online channel is limited in providing product information, especially for products with nondigital attributes. Consumers have to make purchase decisions under uncertainty regarding whether the product matches their preferences. Since consumers often do not have enough information prior to making purchase, they may return or exchange the product if their preferences are not satisfied. According to a recent study conducted by Shorr Packaging (2015), during the holiday season, the volume of product returns is estimated at $19.4 billion, approximately 30% of $64.7 billion in total sales. In addition, the retail analyst firm IHL Group (2015) reports that retailers worldwide lose approximately $642.6 billion annually due to the cost of needless returns. Approximately 35% of these returns are caused by inaccurate product portrayal online and the mismatch of consumers’ preferences (TrueShip, 2015). Prior to purchasing an item, consumers tend to consider sellers’ return policies in addition to the product's ability to match their preferences. UPS (2015) reports that more than 65% of online shoppers consider return policies when making purchase decisions. For the online market, product return/exchange is an important issue that impacts the decisions of firms and consumers.

Generally, online sellers should provide basic information about their products, such as literal descriptions, pictures, videos, consumer reviews and ratings. However, sellers are not always willing to disclose sufficient product information. In certain conditions, less information may make the product more popular among consumers. Sellers will take the opportunity to achieve higher profits despite the increased returns. In addition, the competition also plays an important role in sellers’ information disclosure decisions.

Another important factor that affects sellers’ information strategies is the information environment of the online selling platform. The online selling platform is a multi-sided market that widely exists in the industry of E-commerce, such as Amazon.com, JD.com and Tmall.com. An intermediary develops the platform and provides services for transactions between sellers and consumers, which subsequently earns profit for the intermediary. For example, an intermediary designs a framework of product webpages and introduces a module of consumer review system to facilitate sellers’ information disclosure. To build an information-rich environment for sellers and consumers, the intermediary develops information disclosure tools. The virtual dressing room is such an information tool that has been developed to provide product information to consumers. With information tools provided by the intermediary, sellers are able to choose the optimal information disclosure strategy to maximize their profits, i.e., whether to adopt the information tools and how to disclose product information to consumers. Therefore, we specifically ask the following questions.

  • (a)

    How does a firm manage consumer uncertainty and product returns/exchanges by strategically disclosing product information?

  • (b)

    What is the equilibrium of sellers’ information strategies in a competitive context?

  • (c)

    What is the optimal information strategy for the intermediary?

  • (d)

    How does the technology environment affect firms’ information strategies? How to improve the performance of firms’ information strategies in a certain technology environment?

To answer these questions, we propose a stylized model that includes two competitive sellers selling products to heterogeneous consumers in a platform that is operated by an intermediary. The disclosed product information is critical for consumers’ purchase decisions. Thus, we primarily focus on the strategic information disclosure of the intermediary and sellers.

Our results contribute to extant literature in three ways. First, developed from the research of product quality information disclosure (Grossman, 1981, Guo and Zhao, 2009, Kuksov and Lin, 2010), our study shows that sellers are willing to disclose product match information in a competitive context, which enriches the unravelling theory from the perspective of match information disclosure (Fay and Xie, 2008, Hotz and Xiao, 2013, Prasad et al., 2011). Second, we propose information strategies for the intermediary, which contributes to the emerging study of intermediaries’ operational strategy (Dukes and Liu, 2015, Renault, 2014, Zhang et al., 2017). Third, we construct a classification method based on product value and return cost to facilitate firms’ rational information disclosure, which also suggests that firms’ information strategies should be product-specific (Gu and Xie, 2013, Sun and Tyagi, 2014).

The remainder of this paper is organized as follows. The next section summarizes relevant studies. In Section 3, we describe the model. Section 4 examines sellers’ information strategies in a competitive market. Section 5 derives the optimal information strategy for the intermediary. Extensive discussions are provided in Section 6, and Section 7 provides concluding remarks.

Section snippets

Literature review

Our study focuses on product information disclosure that is made by the intermediary and competitive sellers. This topic is related to three streams of existing research.

First, we consider issues regarding information disclosure and product returns for E-commerce. When shopping online, consumers are unable to conduct physical inspection such as touching and feeling the product. Generally, consumers have limited knowledge of the product, especially when the product adopts new styles or changes

Intermediary and competitive sellers

We consider an online selling platform with an intermediary (the platform owner) and two competitive sellers. Each seller offers a product line that contains a number of sizes, colors, or designs such that consumers must figure out which product variant fits them. Specifically, when a misfit occurs, a product variant can be exchanged by another variant with different size, color or design. Without loss of generality, we assume that there are two variants of each product line (see Fig. 1), which

The subgames

Before deriving the equilibrium of sellers’ information strategies, we first come to the subgames under certain information strategies. Recall that given the intermediary's information strategy r, the sellers’ strategy set is ri ∈ {I0, IR}, i ∈ {A, B}; thus, there are four combinations of sellers’ strategies, i.e., (I0, I0), (IR, I0), (I0, IR) and (IR, IR). Since the middle two combinations are symmetric, we only analyze one of them, i.e., (IR, I0).

The optimal information strategy for the intermediary

We have demonstrated that competitive sellers will always make full use of the information tools. Taking that into account, the intermediary is able to achieve a higher profit by optimizing its information strategy. In this section, we first investigate the intermediary's information strategy in the scenarios of full coverage and partial coverage, respectively. Then, we identify the dominant information strategy for the intermediary.

Continuous information disclosure

In this study, we examine sellers’ information disclosure decisions in a competitive context. The sellers’ strategy set is considered to be discrete with two elements, I0 and IR. This consideration makes our analysis more tractable. However, online sellers actually have various options to provide consumers with product information. They may disclose less information to consumers by partially adopting the information tools offered by the intermediary. Therefore, the information strategies rA and

Conclusions

This paper examines the information strategies of the intermediary and online sellers under various situations. Based on consumer purchase behavior, we establish a model to analyze how product information influences consumer uncertainty and the return/exchange probability. Our analytical study mainly focuses on the intermediary and sellers’ information strategies.

First, we derive the equilibrium of competitive sellers’ information strategies. The results show that regardless whether the market

Acknowledgment

We thank the referees for their helpful comments on an earlier version of this paper. We are grateful for the financial support from the National Natural Science Foundation of China (grant number 71571140).

References (43)

  • ChuL. et al.

    Optimal preorder strategy with endogenous information control

    Management Science

    (2011)
  • A. Dukes et al.

    Online shopping intermediaries: the strategic design of search environments

    Management Science

    (2015)
  • FayS. et al.

    Probabilistic goods: a creative way of selling products and services

    Marketing Science

    (2008)
  • T. Fenech et al.

    Internet users’ adoption of web retailing: user and product dimensions

    Journal of Product & Brand Management

    (2001)
  • S. Gajanan et al.

    Multichannel retailing and its implications on consumer shopping behavior

    Journal of Shopping Center Research

    (2007)
  • G. Gallego et al.

    Revenue management with partially refundable fares

    Operations Research

    (2010)
  • S.J. Grossman

    The informational role of warranties and private disclosure about product quality

    Journal of Law and Economics

    (1981)
  • GuZ. et al.

    Facilitating fit revelation in the competitive market

    Management Science

    (2013)
  • GuoL.

    Quality disclosure formats in a distribution channel

    Management Science

    (2009)
  • GuoL. et al.

    Voluntary quality disclosure and market interaction

    Marketing Science

    (2009)
  • HagiuA.

    Merchant or two-sided platform

    Review of Network Economics

    (2007)
  • Cited by (31)

    • Information disclosure in a supply chain with copycat threat

      2022, European Journal of Operational Research
      Citation Excerpt :

      Grossman & Hart (1980), Grossman (1981) and Milgrom (1981) first study a monopolistic firm’s voluntary disclosure strategy, and these papers propose the classic unraveling result: a firm is unable to withhold any private product information as long as disclosure is costless and customers are rational. Since then, many scholars have examined the robustness of the classic unraveling result via different settings, such as in a competitive environment (Board, 2009; Kuksov & Lin, 2010; Zhang, Li, Lai, & Leung, 2018), in a supply chain setting (Guan & Chen, 2015; 2017; Guo, 2009), with dual-channel (Arya & Mittendorf, 2013) and in the presence of technology licensing (Hong, Zhou, & Gong, 2021; Jeon, 2019). A few papers have shown that unraveling result may break down such as Sun (2011) and Arya & Ramanan (2019).

    • Get your report a thumb-up: An empirical investigation on crowd testing

      2022, Decision Support Systems
      Citation Excerpt :

      We take the information amount, readability, perception process, and emotional expression to evaluate the information quality of the testing reports. In the e-commerce environment, consumers cannot truly see and touch the product before it is delivered, which increases quality concerns before the online purchase [42]. Consumers, trying to avoid risks, would like to wait until feedback from leading consumers is available.

    View all citing articles on Scopus
    View full text