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Revenue management in a multi-level multi-channel supply chain considering pricing, greening, and advertising decisions

盈利能力指数 供应链 利润(经济学) 业务 绿化 收入 频道(广播) 收益管理 渠道协调 产业组织 供应链管理 广告 营销 微观经济学 经济 计算机科学 电信 财务 政治学 法学
作者
Behrooz Khorshidvand,Hamed Soleimani,Soheil Sibdari,Mir Mehdi Seyyed Esfahani
出处
期刊:Journal of Retailing and Consumer Services [Elsevier BV]
卷期号:59: 102425-102425 被引量:54
标识
DOI:10.1016/j.jretconser.2020.102425
摘要

This paper explores coordinated decisions regarding a multi-level multi-channel supply chain considering the price of sale channels, the advertisement level, and the green policy of the products. The main objective is to maximize the total profit of the Supply Chain (SC) by considering the profitability of entities. In this regard, two kinds of selling channels (i.e. online and in-person) are extended to enable all the entities to sell the product through their own channels. Demands in both types of channels depend on price, greenness, and advertisement. In the studied SC, the manufacturer not only produces the products and sells them to the distributor and the customer but it also decides on the greening and advertising levels. As a contribution, the demand functions simultaneously consider environmental and financial issues. Besides, since each member has its own selling channel, it should determine the price based on three criteria: advertising costs, greening costs, and other members' pricing decisions. For this purpose, three models including Centralized Supply Chain (CSC), Decentralized Supply Chain (DCSC), and Modified Centralized Supply Chain (MCSC) are developed and then solved to cope with various real-world situations. Based on the findings, although the SC gains the most profitability under the CSC model, the manufacturer faces a considerable loss. To overcome this issue, the MCSC model ensures the manufacturer's profit while keeping the price, greenness, and advertisement competitive. Also, the profitability of the MCSC model is more than that of under the DCSC model. The proposed models' performance for different situations is corroborated using several examples and various analyses, along with a real case study. The results acknowledge the applicability of the models and give practical insights for experts.

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