Pricing decisions of competing supply chains under power imbalance structures

Li, Tao; Zhang, Rong; Liu, Bin

doi:10.1016/j.cie.2018.02.004

Cited by 31 publications

(10 citation statements)

References 38 publications

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“…The member who makes decision first is considered to have more power over other members. To model this situation with a power retailer, Xiao et al (2014); Chen et al (2017); Li et al (2018b) etc. used Stackelberg game in which the retailer specifies the retail margin first.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative analysis of government incentives and game structures on single and two-period green supply chain

Nielsen

Majumder²,

Sana

et al. 2019

Journal of Cleaner Production

120

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Section: Literature Reviewmentioning

confidence: 99%

Comparative analysis of government incentives and game structures on single and two-period green supply chain

Nielsen

Majumder²,

Sana

et al. 2019

Journal of Cleaner Production

120

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“…Assumption 5. In order to prevent the retailers from gaining more profits for the salvage value of the returned products than selling products, 0 < s < c + c h < 1 is assumed [17,41]. Let ϕ � c h − s denote marginal additional cost for returned products; then we have 0 < ϕ < 1.…”

Section: Assumptionmentioning

confidence: 99%

“…Most consumer returns are due to misfit, as determined by the consumer after purchase [14][15][16]. Many enterprises are adopting consumer return guarantee strategy, advertising, and offline showroom service to reduce consumer returns [17]. However, consumer returns policies also increase cost and bring negative impacts on retailers' benefits [13].…”

Section: Introductionmentioning

confidence: 99%

Optimal Showroom Service Strategy and Power Structure for Retailers considering Consumer Return

Zhang

Chen

et al. 2021

Discrete Dynamics in Nature and Society

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This paper investigates the optimal showroom service strategy and power structure for online and offline retailers considering online consumer return. Combining two service strategies and three competition power structures, six models are constructed to analyze the effects of the showrooming effect and consumer return on retailers’ decisions and consumer surplus. The results show that the SS strategy is the best choice for offline retailers, and it is also an effective way to solve consumer return. Online retailers are suggested to cooperate with offline retailers to implement SS strategy and enhance the showrooming effect. Under the SS strategy, the offline-led power structure is the best choice for online retailers, but the online-led power structure is optimal for offline retailers. We also find that the supply chain and consumers are more likely to implement SS strategy and offline-led power structure. More importantly, we pinpoint that there is no incentive for retailers to implement the Nash power structure. Therefore, it is recommended to revitalize the real economy of offline retailers and implement the strategy SS effectively.

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“…This article also relates to revenue management and supply chain problems (Li et al, 2018). Taylor (2016) derives the demand rate and the number of available suppliers in equilibrium for a given price and wage and then maximizes the platform's profit by optimizing the price and wage with two-point distributions for both customers' and suppliers' valuations.…”

Section: Literature Reviewmentioning

confidence: 99%

Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning

2020

Self Cite

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The rise of the sharing economy has changed the traditional way of providing service to consumers. Airbnb is the most successful peer-to-peer model in the hospitality industry. This article investigates how to conduct strategic dynamic pricing in a competitive market by considering market conditions, quality, and risk sensitivity. Our research yields three main conclusions. First, we observe that the higher the risk level suppliers face, the more profit they will get; the lower the risk level consumers face, the more utilities they obtain. Second, we find that fixed pricing may be optimal or near-optimal for the platform when market size is small, the accommodation quality is better, and consumers’ reliability is low. Otherwise, a flexible pricing strategy is optimal. Finally, we extend the research into dynamic pricing decision in presence of Bayesian social learning and propose that the less-perfect accommodation requires social learning more urgently. In tourism peak period, social learning has less positive impact when the Airbnb accommodation is much perfect. These conclusions provide useful guidance on how the Airbnb and hotel can take advantage of the competitive market.

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Pricing decisions of competing supply chains under power imbalance structures

Cited by 31 publications

References 38 publications

Comparative analysis of government incentives and game structures on single and two-period green supply chain

Comparative analysis of government incentives and game structures on single and two-period green supply chain

Optimal Showroom Service Strategy and Power Structure for Retailers considering Consumer Return

Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning

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