Pricing games of mixed conventional and e-commerce distribution channels

Abstract

In this paper, a distribution system is studied, in which a supplier sells a common product through conventional (physical retailer) and e-commerce (e-tailers) channels. We examine two types of Stackelberg pricing games and one type of Nash pricing game in this dual-channel distribution system. We also analyze the effects of several key factors (i.e., the supplier’s pricing mode, game schemes, and efficiency of e-channel in relation to acceptance of channels) on the resulting prices as well as the profits for the supplier and the retailer, respectively. This paper is an effort to examine modeling competition in the multiple-channel environment from a pricing viewpoint. We find that channel acceptance plays a critical role in influencing equilibrium prices and profits in the dual-channel distribution system. When the customer acceptance of one channel exceeds a certain threshold, this channel cannibalizes all retail sales and dominates the distribution system. The supplier can make more profits by adopting a differential pricing strategy; on the contrary, the retailer prefers uniform pricing. Numerical analysis indicates that both the supplier and the retailer are worse off in the Nash game than in the Stackelberg games. The supplier prefers an e-channel with higher efficiency, whereas the physical retailer has to maintain higher channel acceptance to maintain its position in the distribution system.

Introduction

E-commerce is a concept that has been practiced for some years now. Today, selling products through Internet stores and shops has enjoyed increasing popularity all over the world. Companies can sell virtually everything over the Internet, including food, clothing, computers, household items and tickets, among other things. E-commerce businesses possess numerous advantages over offline retail locations and catalog operators (Agatza, Fleischmann, & van Nunena, 2008). As a result of the rapid development of e-commerce, many manufacturers have opted to distribute their products through physical retailers and e-tailers simultaneously. At the same time, many physical retailers have also opened their own online stores to sell their products in dual channels synchronously. These generate a pervasive multi-channel marketing system consisting of conventional and e-commerce distribution channels.

The multi-channel system enables companies to build more lasting customer relationships by simultaneously offering their customers products, information, services, and support through synchronized channels (Rangaswamy & Van Bruggen, 2005). The multi-channel system can be used as a strategic tool. When the supplier acts as a Stackelberg leader in setting the wholesale price and the direct channel price, it can use the direct channel even without sales to control the the prices of the physical retailers, thus dominating the distribution system (Chiang, Chhajed, & Hess, 2003). Moreover, the multi-channel strategy may be used as a customer segmentation method. The e-commerce channel may capture consumers who prefer to buy products from the Internet after viewing product descriptions, allowing them to save purchasing time and transportation cost. However, traditional brick-and-mortar stores still attract loyal clients who have difficulty or are simply unwilling to purchase products online (Chen, Zhang, & Sun, 2012).

Although the multi-channel distribution system promises to take over as the prevalent supply chain design for all kinds of business, it is primarily difficult to manage due to the inevitable competition between the conventional channel and the e-channel. The desire to use a multi-channel distribution system may ultimately compel a supplier to redefine its relationship with downstream retailers. Success in the age of e-commerce will be profoundly influenced by the management of channel conflict (Tsay & Agrawal, 2004). In the current paper, we study the pricing modes for a supplier selling a product through a conventional channel and an electronic channel. For example, as a manufacturer, Canon currently sells its products using both physical and e-channels, the latter through hundreds of e-tailers in China. In particular, we consider two questions: under different types of game schemes, what kind of wholesale pricing strategy should be employed by the supplier? Furthermore, how are the profits of the supplier and the physical retailer affected by pricing modes, game schemes, and efficiency of the e-channel?

Our motivation for this research comes from several different sources, including channel structures, game schemes, and pricing modes.

(1) Recently, many studies on multi-channel management have focused on the issue of pricing conflict, reporting that prices, profits, demands, and consumer welfare are influenced by channel structures, cost of participants, and customer preferences of channels (see, e.g., Cai, 2010, Fruchter and Tapiero, 2005). Among others, Jeffers and Nault (2011) have shown that, for goods that require little in-person pre- or post-sales support, a multi-channel strategy may lead to an increase in both retail prices and profits across the industry. Specifications of the good, disutility, and shipping costs versus transportation costs and competition significantly influence prices, profits, and consumer welfare as well. Yoo and Lee (2011) analyzed various alternative mixed-channel structures composed of a monopoly manufacturer and online and offline outlets. They found that the impact of the introduction of the Internet channel substantially varies across channel structures and market environments. The equilibrium solutions in various channel structures indicate that the Internet channel entry does not always lead to lower retail prices and enhanced consumer welfare.

Nowadays, e-commerce platforms have become increasingly efficient in many respects. The most notable aspect is the efficiency and accuracy of information exchange occurring through e-commerce transactions. This is a result of the adoption of popular, free instant messenger tools by e-tailers, suppliers, and customers. Moreover, customers can use third-party payment platforms, such as PayPal and Alipay, to make secure transactions online while keeping their personal information safe. All of these have dramatically reduced transaction costs between suppliers and e-tailers as well as between e-tailers and customers. Nowadays, it has become cheaper and more convenient to sell through e-tailers. Thus, many suppliers prefer selling products through various e-tailers rather than open their respective e-commerce websites.

As with online pricing, some empirical research have shown that the pricing strategy employed by e-tailers primarily focuses on elements of electronic marketing. For instance, Sotgiu and Ancarani (2005) reported that the pricing strategy used by e-tailers is highly correlated with e-tailer graphics, branding and trust, and shipping services. Thus, in the current paper, we shift the attention from the comparison between online and offline pricing to the understanding of the pricing game between the supplier and the conventional retailer. In our model, e-tailers are not strategic on the retail price and the product is sold with a fixed margin. This average profit margin level reflects the industry status of the e-commerce platform. For example, more intense competition and lower operating costs often results in a depressed price level. Thus, such pricing model in an e-channel is a reasonable hypothesis. Therefore, the supply chain structure in the current paper has an essential difference from those presented in previous models, in which the electronic channel is controlled by the supplier or the traditional retailer (Cai et al., 2009, Chen et al., 2012, Chiang et al., 2003).

(2) Several studies have indicated that the game schemes have a greater impact on competition outcomes and supply chain performance. Choi (1991), for example, discussed a supply chain with two suppliers and one common retailer. The author then analyzed the equilibrium prices for three different game cases: manufacturer-Stackelberg, vertical-Nash, and retailer-Stackelberg. Yao and Liu (2005) examined the pricing equilibria between a manufacturer with an e-tail channel and a retail channel under two types of competitive pricing schemes: the Bertrand and Stackelberg competition models. Gu, Goh, Chen, de Souza, and Tang (2011) investigated the behavior of a discrete bargaining model faced by service based organizations. Cai et al. (2009) provided a game theoretic framework from the supplier-Stackelberg, retailer-Stackelberg, and Nash game perspectives. They aimed to explore the effect of coordination in a dual-channel supply chain, which includes an online direct channel owned by the supplier and a traditional retail channel. In this work, we consider two types of game schemes, namely, the Stackelberg and Nash games. In the Stackelberg game, the supplier is the leader, and the retailer is the follower. In the Nash game, the supplier and the retailer determine the prices simultaneously, and are equally powerful in the system. On one hand, the Stackelberg game depicts a common supply-chain system in reality, in which the supplier is more powerful than the retailer. On the other hand, the Nash game allows us to deal with another supply-chain structure, in which the supplier and the retailer are equally powerful (e.g., P&G and Walmart). In the Stackelberg game, we also analyze two pricing modes for the supplier, namely, uniform price and differential price modes. Compared with previous studies, the main contribution of our research is to quantitatively evaluate the performance of a two-echelon supply chain member using a mixed-channel distribution strategy under diverse game schemes and alternative pricing modes.

Turning to related works, the current paper lies at the nexus of literature on multi-channel supply chain in e-commerce or direct sales (see, e.g., Arya et al., 2007, Chen and Liu, 2011, Rangaswamy and Van Bruggen, 2005, Yao et al., 2009). Tsay and Agrawal (2004) reviewed quantitative approaches to modeling coordination and conflict in multi-channel distribution systems, with particular emphasis on the implications of the Internet for distribution strategy. In the age of e-commerce, the management of channel conflict is a key B2B concern that can profoundly influence the supply chain success. Swaminathan and Tayur (2003), meanwhile, examined several important issues of supply chain management under the e-commerce environment, including visibility, supplier relationships, distribution and pricing, customization, and real-time decision technologies. Agatza et al. (2008) provided a systematic overview of managerial planning tasks and their corresponding quantitative models in a multi-channel environment. They pointed out that the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. Another topic, supply chain coordination in a multi-channel system, has also been extensively studied. Chen et al. (2012) examined the coordination schemes for a dual-channel supply chain and find that the contract of a supplier with wholesale price and a price for the direct channel can help coordinate the supply chain. We refer to Cattani, Gilland, and Swaminathan (2004) for surveys on channel coordination of the Internet and traditional supply chain through procurement, pricing, integration, fulfillment, and distribution.

The remainder of this paper is organized as follows. Section 2 describes the model description and assumptions. Section 3 presents the equilibrium when the supplier adopts a uniform pricing strategy and a differential strategy, respectively, for the Stackelberg game model. Analysis of the Nash game with a uniform pricing strategy is described in Section 4. In Section 5, we present managerial insights with several numerical examples. The conclusion is given in the last section. Proofs are included in the Appendix.