Behavior-Based Pricing in Marketing Channels

Li, Krista J.

doi:10.1287/mksc.2017.1070

Cited by 47 publications

(26 citation statements)

References 29 publications

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“…, there is no dominant situation for two pure strategy solutions, according to oddness theorem, in this case, there is a mixed strategy Nash equilibrium (MNE), and lets assume that firm L hasp a probability to choose BBP and 1 − p a probability to choose UP; firm H has p a probability to choose BBP and 1 − p a probability to choose UP. The expected profits of Firm L and Firm H are as shown in Equations (9) and (10).…”

Section: Table 1 Revenue Matrix For Firms With Service Differentiationmentioning

confidence: 99%

“…Nowadays, with the development of mobile e-commerce and increasingly fierce market competition, firms are exploiting the opportunity of mobile e-commerce to develop the market as much as possible. Through the QR code, Wifi, APP and cookies, it is easy to track and record customer purchases to identify new customers [10]. Therefore, the aggressive strategy of preferential pricing for new customers has become more popular and has gradually become the focus of BBP theoretical research [15].…”

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confidence: 99%

“…This essentially eases the price conflict between competing firms at the expense of consumer surplus. Firms are even motivated to share consumer information with upstream manufacturers, and use BBP with manufacturers to further squeeze consumer surplus and increase their profits [10]. However, seeking short-term profits at the expense of consumers interests is bound to decrease customer loyalty [6].…”

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confidence: 99%

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Behavior-based pricing in service differentiated industries

Dong-sheng¹,

Song²

2020

Journal of Dynamics &Amp; Games

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Firms often upgrade service level to enhance their profitability, which leads to competing firms at service disadvantages using behavior-based pricing (BBP) strategy to fight back. The interaction between service differentiation and BBP affects the profits of both competitors. In order to explore the impact of BBP on the competition of firms with service differentiation, we use game theory method to construct a two-period dynamic pricing model. We explore the optimal BBP strategy by comparing and analyzing firms subgame equilibrium profits. The main conclusions are as follows: (i) the degree of service differentiation and the relative service cost interact to influence firms optimal pricing strategy. Specifically, when the degree of service differentiation is low (high) and the relative service cost is small (large), both firms do not adopt (adopt) BBP. When the degree of service differentiation is low (high) but the relative service cost is large (small), competing firms have mixed strategic Nash equilibrium, and both firms have a certain probability to adopt BBP. (ii) BBP can help low-service firms to make up for the profits loss caused by the service disadvantage under certain conditions. However, it can lead to fierce price competition, which will damage the profits of both.

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Section: Table 1 Revenue Matrix For Firms With Service Differentiationmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Behavior-based pricing in service differentiated industries

Dong-sheng¹,

Song²

2020

Journal of Dynamics &Amp; Games

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“…To avoid trivial cases, we assume that the product quality is sufficiently high such that the market is fully covered (cf. Liu and Zhang, ; Li, ). Moreover, throughout this study, we assume that the strength of the consumer's preference is nontrivial, that is,

t > \frac{γ^{2}}{4}

, to ensure the existence of the Nash equilibriums.…”

Section: Modelmentioning

confidence: 99%

For showing only, or for selling? The optimal physical store mode selection decision for e‐tailers under competition

Fan

Wang

Zhang

2019

Int Trans Operational Res

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More and more e-tailers are launching physical stores, in addition to their online presence. Whether and when it is best for the physical channel to be a pure showroom or a selling store remains unanswered. To address this issue, we develop a game-theoretical model wherein two competitive e-tailers decide to launch physical stores for showing only (as a showroom) or for actual transactions (as a selling store). By deriving the equilibrium, we obtain three major findings. First, building a pure showroom or a pure selling store is not always optimal. Interestingly, when the proportion of the store consumer segment is not too high, and the strength of the consumers' brand preference is intermediate, an asymmetric channel configuration occurs in equilibrium, that is, one e-tailer launches a showroom and the other launches the selling store. Second, if the strength of the consumers' brand preference is high relative to the proportion of the store consumer segment, a "prisoner's dilemma" emerges, that is, both e-tailers are worse off in the pure showroom channel configuration. Third, the total consumer surplus reaches the highest level if a symmetric showroom or an asymmetric channel equilibrium occurs. Otherwise, the equilibrium channel configurations are always suboptimal for consumers.

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“…Moreover, rapid advances in information technology and data science have substantially reduced the cost of implementing BBP. For example, the data storage cost for a gigabyte of a hard drive has decreased 75% from $0.11 in 2009 to $0.028 in 2017 (Klein 2017, Li 2018. Web innovators, such as Facebook, Google, and Yahoo, offer scalable storage and compute architecture to manage firms' consumer data, dramatically reducing the cost of data storage and management (Savitz 2012).…”

mentioning

confidence: 99%

Transparency of Behavior-Based Pricing

Xi¹,

Li²,

Wang³

2019

Journal of Marketing Research

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Behavior-based pricing (BBP) refers to the practice in which firms collect consumers’ purchase history data, recognize repeat and new consumers from the data, and offer them different prices. This is a prevalent practice for firms and a worldwide concern for consumers. Extant research has examined BBP under the assumption that consumers observe firms’ practice of BBP. However, consumers do not know that specific firms are doing this and are often unaware of how firms collect and use their data. In this article, the authors examine (1) how firms make BBP decisions when consumers do not observe whether firms perform BBP and (2) how the transparency of firms’ BBP practice affects firms and consumers. They find that when consumers do not observe firms’ practice of BBP and the cost of implementing BBP is low, a firm indeed practices BBP, even though BBP is a dominated strategy when consumers observe it. When the cost is moderate, the firm does not use BBP; however, it must distort its first-period price downward to signal and convince consumers of its choice. A high cost of implementing BBP serves as a commitment device that the firm will forfeit BBP, thereby improving firm profit. By comparing regimes in which consumers do and do not observe a firm’s practice of BBP, the authors find that transparency of BBP increases firm profit but decreases consumer surplus and social welfare. Therefore, requiring firms to disclose collection and usage of consumer data could hurt consumers and lead to unintended consequences.

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Behavior-Based Pricing in Marketing Channels

Cited by 47 publications

References 29 publications

Behavior-based pricing in service differentiated industries

Behavior-based pricing in service differentiated industries

For showing only, or for selling? The optimal physical store mode selection decision for e‐tailers under competition

Transparency of Behavior-Based Pricing

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