斯塔克伯格竞赛
供应链
对偶(语法数字)
业务
价值(数学)
独创性
频道(广播)
产业组织
微观经济学
营销
经济
计算机科学
机器学习
艺术
文学类
法学
政治学
创造力
计算机网络
作者
Xin Liu,Hao Gong,Chen Wei
标识
DOI:10.1108/mscra-02-2025-0010
摘要
Purpose The study aims to determine in a dual-channel low-carbon supply chain (DCSC with LC), when the adoption of Blockchain technology (BT) can maximize the profits of supply chain (SC) businesses? Design/methodology/approach To tackle the information opacity issue of low-carbon (LC) products in the dual-channel supply chain (DCSC), this paper constructs a Stackelberg model of different DCSCs with LC and explores the impact of BT on pricing decisions of DCSCs with LC. Findings The research finds: (1) Without BT, when the unit direct sales cost (UDC) is within a large threshold, the low-carbon products manufacturer’s (LCPM’s) profits under the distribution model are higher than those under the direct sales model. With BT, in both models, the profits of both LCPMs and retailers grow with the surge in the value coefficient of the shared information. (2) In the direct sales model, regardless of whether BT is adopted, the profits of LCPMs reduce with the increase in UDC; when the emission reduction cost coefficient (ECC) is within a large threshold, profits of traditional retailers (TRs) multiply with the UDC and vice versa; the profits of LCPMs after adopting BT are larger than that those without BT implementation. (3) In the distribution sales model, LCPMs and retailers that incorporate BT are more profitable than those that do not. Originality/value In the literature exploring the impact of information-sharing benefits resulting from BT on the pricing decisions of DCSCs with LC, numerous studies are conducted from the perspective that BT application can advance the consumption demand of consumers; however, only a few studies have been conducted from the perspective that the BT application can upgrade the efficiency of manufacturers and thus achieve additional information-sharing merits. Therefore, this paper investigates the pricing decisions of DCSC with LC based on BT, which further enriches the research in DCSC management.
科研通智能强力驱动
Strongly Powered by AbleSci AI