Pricing/service strategies for a dual-channel supply chain with free riding and service-cost sharing

Motivated by the emergence of dominant physical stores utilizing a buy‐online‐and‐pickup‐in‐store (BOPS) channel, we examine the interaction of such a stronger retailer and a manufacturer's strategies on the pricing and service value. The dominant retailer provides an added service value to end consumers by the traditional channel and BOPS option, which has a positive influence on the market demand. The manufacturer makes the channel selection decision between a dual channel and an omni‐channel. We formulate a retailer Stackelberg game and characterize the equilibrium pricing and service solutions under centralized and decentralized cases. Our results indicate that the service value of a physical store strongly influences the players' pricing strategies. The sensitivity analysis reveals that the total revenue of the supply chain increases with the market scale expansion coefficient of the BOPS option. Furthermore, the result suggests that offering the BOPS channel is always an effective initiative to boost supply chain performance, especially in the centralized structure.

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“…In order to simplify the computation and make the result comparable, we assume that the price effects are same and equal to 1 (

b_{1} = b_{2} = 1

), which were ever used by many studies such as Zhou et al. (2018) and Liu et al. (2016).…”

Section: Model Descriptionmentioning

confidence: 99%

Optimal pricing decisions for an omni‐channel supply chain with retail service

Jiang

Liu

Lim

2020

Int Trans Operational Res

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“…Xu et al [17] found that a large number of consumers have heterogeneous preferences for the direct selling channel and the retail selling channel and constructed the channel conflict when the price comparison became the focus of consumers. Other scholars also conducted extensive study in price decision making [18][19][20][21][22][23][24], service decision making [25][26][27], and their coordination [28]. In the aspect of inventory decision making, the literature concerning channel conflicts studied ordering issues in dual-channel supply chain.…”

Section: Literature Reviewmentioning

confidence: 99%

Capacity Allocation and Compensation in a Dual-Channel Supply Chain under Uncertain Environment

Yang

Zhang

Huang

et al. 2019

Mathematical Problems in Engineering

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The dual-channel supply chain is widely adopted by main manufacturers, potentially incurring channel conflicts between the traditional retail channel which is owned by the independent retailer and the online channel which is directly managed by the manufacturer. The purpose of this paper is to deal with the scenario where channel conflicts may arise under production capacity uncertainty, when the manufacturer tends to privilege the direct selling channel over the retail selling channel. To achieve the goal, this paper establishes a Stackelberg game model consisting of a manufacturer and a retailer, studies the scenario where the manufacturer satisfies the direct selling channel first in the presence of capacity uncertainty, employs the decision optimization and the backward induction method to find the optimal inventory decision in the direct selling channel and the optimal order quantity decision making in the retail selling channel, and designs a compensation mechanism aiming to coordinate the channel conflict in the decentralized decision-making process. Results show that the optimal decisions aiming to maximize the expected profit of each supply chain member are not able to maximize the expected profit of entire dual-channel supply chain. However, when the manufacturer compensates the retailer’s profit loss based on the unsatisfied order and, in the meantime, adjusts the wholesale price to prevent the retailer which obtains the compensation from increasing order significantly, the compensation mechanism can coordinate the decision of each supply chain member, mitigate the channel conflict, maximize the expected profit of entire dual-channel supply chain, and achieve the Pareto improvement of supply chain members’ expected profit in the decentralized decision-making process.

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“…The supply chain is characterized by many operations that do not add value to the final product, but do add a lot costs. It is even mentioned that in some industrial sectors, up to 70% of production costs are due to logistical aspects [19]. However, that seems to be a problem of economic importance for the enterprise, since it loses competitiveness and possibly also part of the market.…”

Section: Government Supply Chain and Sustainabilitymentioning

confidence: 99%

Government Support and Market Proximity: Exploring Their Relationship with Supply Chain Agility and Financial performance

et al. 2018

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The current paper presents a structural equation model with four variables (Government, Infrastructure, Proximity to market, and supply chain Agility) affecting the Financial performance of a company. Six hypotheses or relationships among variables are proposed, supposing that Government and market Proximity are key elements to achieve a greater Agility in supply chains, considering the regional Infrastructure to determine the impact on Financial performance in manufacturing companies. The model is validated with data from a survey applied to 225 persons in 65 manufacturing companies located in Ciudad Juárez, Chihuahua, Mexico. The model is evaluated using partial least squares, and the findings indicate that there is a direct and positive effect from the Government on regional Infrastructure with a rate of 0.436. When the Government supports the availability of land, energy resources, transportation, telecommunications, mobile telephones, and other services, a positive change is achieved in the Infrastructure and supply chain Agility. Furthermore, the Government also has a direct and positive effect on the market Proximity at a rate of 0.171; consequently, the regional Infrastructure also has an effect on it. Similarly, the market Proximity directly and positively influences the supply chain Agility, as well as a company’s Financial performance at a rate of 0.506.

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Pricing/service strategies for a dual-channel supply chain with free riding and service-cost sharing

Cited by 209 publications

References 39 publications

Optimal pricing decisions for an omni‐channel supply chain with retail service

Optimal pricing decisions for an omni‐channel supply chain with retail service

Capacity Allocation and Compensation in a Dual-Channel Supply Chain under Uncertain Environment

Government Support and Market Proximity: Exploring Their Relationship with Supply Chain Agility and Financial performance

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