Pricing strategies of low-carbon enterprises in the Yellow River Basin considering demand information and traceability services

可追溯性 斯塔克伯格竞赛 收入 供应链 质量(理念) 环境经济学 业务 产品(数学) 收入分享 计算机科学 产业组织 微观经济学 营销 经济 财务 哲学 软件工程 认识论 数学 几何学
作者
Pan Liu,Xiaoyan Cui,Ziran Zhang,Wenwen Zhou,Yue Long
出处
期刊:Kybernetes [Emerald (MCB UP)]
卷期号:52 (1): 304-327 被引量:2
标识
DOI:10.1108/k-06-2021-0529
摘要

Purpose The purpose of this paper is to solve new pricing issues faced by low-carbon companies in the Yellow River Basin, which is caused by the change of key pricing factors in the mixed appliance background of Big Data and blockchain, such as product quality and carbon-emission reduction CER level (hereafter, CER level). Design/methodology/approach We choose a low-carbon supply chain with a low-carbon manufacturer and a retailer as our research object. Then, we propose that using the ineffective effect of the CER level and the quality and safety level to reflect the relationships among the CER level, the quality and safety level and the market demand is more suitable in the new environment. Based on these, we revise the demand equation. Afterwards, by using Stackelberg game, four cost-sharing situations and their pricing rules are analyzed. Findings Results indicated that in the four cost-sharing situations, the change trends and the magnitudes of the best retail prices were not affected by the changes of the inputs of the demand information and the traceability services costs (hereafter, DITS costs), the proportion about retailer's DITS costs undertaken by the manufacturer, the ineffective effect coefficient of the CER level and the quality and safety level and the cost optimization coefficient. However, the cost-sharing situations could affect the change magnitudes of the best revenues. Originality/value This paper has two main contributions. First, this paper proposes a demand function that is more suitable for the mixed appliance background of Big Data and blockchain. Secondly, this paper improves the cost-sharing model and finds that demand information sharing and traceability service sharing have different impacts on key pricing factors of low-carbon product. In addition, this research provides a theoretical reference for low-carbon supply chain members to formulate pricing strategies in the new background.
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