Details

Autor(en) / Beteiligte

• Wang, Jiangtao
• Tsai, Sang-Bing
• Su, Jiafu
• Huang, Yating
• Zhang, Xumei
• Yang, Jiaquan
• Chang, Li-Chung
• Lolli, Francesco
• Francesco Lolli

Titel

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

Ist Teil von

• Mathematical problems in engineering, 2019, Vol.2019 (2019), p.1-12

Ort / Verlag

Cairo, Egypt: Hindawi Publishing Corporation

Erscheinungsjahr

2019

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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.