DOI: 10.14704/nq.2018.16.5.1393

Evolution Process of Recycling Chain of Takeout Packages Based on Behavioural Science

Huiyan Wang, Jia Li, Yong Li, Guoqing Chen


With the rapid development of the takeout food industry in recent years, the amount of non-degradable wastes such as packing boxes and plastic bags are increasing day by day, which leads to severe waste of resources and pollution of environment. How to deal with the takeout packaging wastes have become a new problem of online ordering and also an important subject of social sustainable development. The construction of a recycling industry chain is an important measure to achieve the recycling of takeout packaging wastes. But this process involves many stakeholders, such as the government, takeout enterprises, package manufacturers and consumers. The cognition and decision of these stakeholders play a decisive role in the construction of the recycling industry chain. An evolutionary game model was established to analyze the effects of different decision behaviours of stakeholders on the construction of the recycling industry chain. And then the MATLAB software was used to dynamically simulate the game system. The results show that in the absence of government intervention, the proportion of the initial decision of consumers and enterprises determines whether the evolutionary game system can converge to the ideal state or not, meanwhile the consumers and enterprises have benign interaction effect in the process of constructing the recycling industry chain; in the case of government intervention, the evolution results of the game system will always reach to the ideal state, and the evolution speed is greatly increased. In the end, the countermeasures and suggestions to optimize the decision behaviours of various stakeholders were provided from the perspective of the government behaviour.


Behaviour Science, Takeout Packages, Evolutionary Game, Recycling Industry Chain, MATLAB Simulation

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Araujo, De, MVF, Oliveira, De, UR, Marins, & Fernando, AS, Muniz JJ. Cost assessment and benefits of using RFID in reverse logistics of waste electrical & electronic equipment (WEEE). Procedia Computer Science 2015; 55: 688-97.

Ayvaz B, Bolat B, Aydın N. Stochastic reverse logistics network design for waste of electrical and electronic equipment. Resources Conservation & Recycling 2015; 104: 391-404.

Chen BS, Bo SH. Recovery prediction on waste plastic based on reverse logistics system. China Plastics Industry 2016; 44(12): 142-44.

Dat LQ, Linh DT, Chou SY, Vincent FY. Optimizing reverse logistic costs for recycling end-of-life electrical and electronic products. Expert Systems with Applications 2012; 39(7):6380-87.

Dwivedy M, Mittal RK. Willingness of residents to participate in e-waste recycling in India. Environmental Development 2013; 6(1): 48-68.

Friedman JH. Multivariate adaptive regression splines. Annals of Statistics 1991; 19(1): 1-67.

Gu XF. Research on collaborative governance mechanism of electronic waste recycling industry chain. Nanjing: Nanjing University of Information Science & Technology, 2016.

Liu GQ, Huang XY, Jia YL. Research on reverse logistics recovery model of packaging materials under cyclic symbiosis economy. Enterprise Economy 2014; 4: 23-27.

Liu JQ, Liu Y. Research on construction of express packaging waste recycling industry in China and its impact on environment. Environmental Science and Management 2017; 42(5): 18-21.

Peng BH, Gu XF, Wu BY. Co-evolutionary simulation analysis of multiple stakeholders in the E-waste recycling industry chain. Journal of Beijing Institute of Technology (Social Sciences Edition) 2016; 18(2): 53-63.

Ramezani M, Bashiri M, Tavakkoli-Moghaddam R. A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Applied Mathematical Modelling 2013; 37(1-2): 328-44.

Saphores JDM, Ogunseitan OA, Shapiro AA. Willingness to engage in a pro-environmental behavior: An analysis of e-waste recycling based on a national survey of U.S. households. Resources Conservation & Recycling 2012; 60(3): 49-63.

Satapathy S. An analysis of barriers for plastic recycling in the Indian plastic industry. Benchmarking: An International Journal 2017; 27(2): 415-30.

Starr J, Nicolson C. Patterns in trash: Factors driving municipal recycling in Massachusetts. Resources Conservation & Recycling 2015; 99: 7-18.

Tansel B. From electronic consumer products to e-wastes: Global outlook, waste quantities, recycling challenges. Environment International 2016; 98: 35-45.

Tian LP, Zeng J, Jia PF. Research on the recycling pricing model of electronic waste recycling by retailers. Mathematics in Practice and Theory 2017; 47(3): 9-16.

Xiang N, Mei FQ, Ye WH. Collection and treatment management of WEEE in Germany. China Population Resources and Environment 2014; 24(2): 111-18.

Yu FM, Zhong YG, Shen ZZ. Decision model on E-waste collecting and recycling considering the leading of government’s premium mechanisms. Chinese Journal of Management Science 2014; 22(5): 131-37.

Zeng ZW, Hu MZ, Long JL. Study on recycling and reusing countermeasures of electronic waste in Liupanshui. Journal of Liupanshui Normal University 2016; 28(3): 16-19.

Zhang HY. Recovery and utilization of municipal solid waste in United States. Environmental Science and Management 2017; 42(5): 74-78.

Zhang WM, Chen M, Geng WL, Yang M, Zeng YT, Lu HX. Research on recycling and reuse of express packages based on the concept of sustainable development. E-Business Journal 2017; 4: 36-37.

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