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Chinese Journal of Management Science ›› 2015, Vol. 23 ›› Issue (11): 163-170.doi: 10.16381/j.cnki.issn1003-207x.2015.11.020

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Evolution Trajectory and Intrinsic Machanism of Green Purchase Behavior

ZHAO Ai-wu1, DU Jian-guo1, GUAN Hong-jun2,3   

  1. 1. Computational Experiment Center for Social Sciencl, Jiangsu university, Zhenjiang 212013, China;
    2. School of Management Science and Engineering, Shandong University of Finance and Economic, Ji'nan 250014, China;
    3. School of Information Central University of Finance and Economic, Beijing 100081, China
  • Received:2013-08-24 Revised:2014-03-11 Online:2015-11-20 Published:2015-12-01

Abstract: Because of the premium of green products, it is more difficult for consumers to purchase green products instead of just holding green thoughts. In order to find out the real evolution trajectory and intrinsic mechanism of green purchase behavior, the effect of environmental awareness is introduced into purchase motivation function. Considering consumers' microscopic heterogeneity, limited rationality and the complexity of environment, the advantage of computational experiment method is taken to model green purchase behavior according to real-life scenario. By dynamic simulation under different scenarios, the evolution trajectory of green purchase behavior is explored from the macro aspect, and the intrinsic mechanism is analyzed from the microscopic aspect. Experimental results show, although the price sensitivity and the awareness of environment are two key factors in consumers' green purchase decision-making, "friend influence" can significantly improve the green market share when green product information is more widespread. Green consumers should actively spread green product information while they practice their own green purchase, which would prompt more consumers to turn the concept of green consumption into green purchasing action, and has important practical significance to promote the healthy development of green market.

Key words: green purchase behavior, bounded rationality, computational experiment, agent

CLC Number: