Optimisation of carbon emission reduction in a competitive market with varying saturation and eco-conscious consumers

竞赛(生物学) 投资(军事) 经济 产业组织 业务 微观经济学 生态学 政治 政治学 法学 生物
作者
Baozhuang Niu,Nan Zhang,Fengfeng Xie,Hailun Zhang
出处
期刊:International Journal of Production Research [Informa]
卷期号:62 (18): 6518-6541 被引量:7
标识
DOI:10.1080/00207543.2023.2245065
摘要

AbstractNon-saturated markets such as high-tech markets are attracting more and more eco-conscious consumers. Their utility can be increased by firms' investment in carbon reduction, so the overall demand can be expanded without intensifying the market competition too much. In this paper, we build a two-stage-N-firm optimisation model by assuming firms' products are horizontally differentiated and may engage in multi-dimensional competition. We analyze three scenarios: (1) Benchmark of price-only competition, (2) Two-dimensional 'price + investment effort' competition, and (3) N-firm circular differentiated competition. We find that consumers' high eco-awareness may lead firms to lower investment levels for carbon emission reduction. When the market is sufficiently saturated, we reveal that a Prisoner's Dilemma will occur where firms are trapped in investment-effort competition, so their profits are damaged. We further investigate the environmental performance and the social welfare, finding that consumers' high eco-awareness may render the environment worse and undermine the social welfare.KEYWORDS: Market saturationMulti-dimensional competitionHorizontally differentiated productsEco-conscious consumersGreen investment AcknowledgementsThe authors are grateful to the editor and reviewers for their helpful comments. Nan Zhang is the co-first author and Fengfeng Xie is the corresponding author.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data supporting this study's findings are available from the corresponding author upon reasonable request.Additional informationFundingThis work was supported by the National Natural Science Foundation of China [grant numbers 72125006, 72293564/ 72293560]. Hailun Zhang was supported by the National Natural Science Foundation of China [grant number 72201231], Shenzhen Research Institute of Big Data [grant number T00120220004], and the Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong, Shenzhen.Notes on contributorsBaozhuang NiuBaozhuang Niu received his Ph.D. degree in Operations Management from the Hong Kong Polytechnic University in 2011. He is currently a Full Professor at the South China University of Technology, Guangzhou, China. His research interests include co-opetitive supply chain and cross-border operations. He has published more than 100 papers at peer-review flag journals including MSOM (2 papers), POM (7 papers), TRB (3 papers), and IJPR (4 papers) till now. He serves as Senior Editor of Production and Operations Management.Nan ZhangNan Zhang is currently working toward the Ph.D. degree in Management Science and Engineering with the School of Business Administration, South China University of Technology, Guangzhou, China. His research interests include sustainable supply chain, global operations, and supply chain resilience. His papers have appeared in International Journal of Production Economics, and International Journal of Production Research.Fengfeng XieFengfeng Xie received his Ph.D. degree in Management Science and Engineering from the South China University of Technology in 2023. His research interests include global operations, supply chain sustainability, and supply chain disruption. His papers have appeared in journals such as Transportation Research Part E: Logistics and Transportation Review, International Journal of Production Economics, Resources, Conservation & Recycling, and International Journal of Production Research.Hailun ZhangHailun Zhang is an assistant professor in School of Data Science (SDS), The Chinese University of Hong Kong, Shenzhen. Before joining CUHKSZ, he is a Postdoc fellow in Department of Industrial Engineering and Decision Analytics at HKUST, where he obtained a Ph.D. degree in July 2018. His research interests lie in flexibility design, queuing networks, online algorithm design and supply chain management. He received his bachelor and master's degree in Mathematics department from Peking University. He has published papers in top-tier journals like Operations Research, Management Science, Production and Operations Management, and International Journal of Production Research.
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