文献类型：期刊文献

英文题名：Technology Adoption Optimization with Heterogeneous Agents and Carbon Emission Trading Mechanism

作者：Fang, Chenhao[1]; Ma, Tieju[1,2]

机构：[1] East China University of Science and Technology, Meilong Road 130, Shanghai, 200237, China; [2] International Institute for Applied System Analysis, Schlossplatz 1, Laxenburg, 2361, Austria

年份：2018

卷号：10758 LNAI

起止页码：238

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20181204921288)

语种：英文

外文关键词：Carbon - Competition - Emission control

摘要：The adoption of new technologies with high efficiency and low emission is of great importance in achieving sustainable development. Most studies of technology adoption have been criticized of idealistically assuming only one global decision agent. In this paper, a model of optimizing technology adoption with heterogeneous agents is proposed. Each agent attempts to identify the optimal solution for a portion of the entire system. The heterogeneity in agents is the different demands they face. In order to internalize the external effects of emission, a quantity-based market incentive policy instruments - Carbon Emission Trading is implemented. With two heterogeneous agents, a bargaining process is introduced to reasonably allocate the profit to them. Computational tests are conducted with different market shares and different discounting factors. Numerical results show the impact of heterogeneity and carbon emission trading mechanism on the optimal technology adoptions. It is suggested that a smaller gap of agents’ market shares leads to earlier and more adoptions. Besides, adoptions remain no change when both agents have a same discounting factor. A big discounting factor of the seller will accelerate the adoptions in the buyer agent and the entire system if agents have different discounting factors. ? 2018, Springer International Publishing AG, part of Springer Nature.