TY - JOUR
T1 - Analyzing the co-evolution of green technology diffusion and consumers’ pro-environmental attitudes
T2 - An agent-based model
AU - Zeng, Yongchao
AU - Dong, Peiwu
AU - Shi, Yingying
AU - Wang, Lingling
AU - Li, Yang
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/5/20
Y1 - 2020/5/20
N2 - Massive diffusion of green technologies is significant for building a cleaner world. However, the process of technology diffusion is usually slow and complex. An in-depth understanding of the mechanism regarding green technology diffusion is an essential precondition for effectively stimulating this process. Green technology diffusion heavily involves both social and technological changes. Although existing studies have provided rich knowledge about identifying critical drivers and barriers affecting green technology diffusion, research that considers consumers’ pro-environmental attitudes and green technology diffusion as an evolving system is still sparse. Aiming at exploring the co-evolution of consumers’ pro-environmental attitudes and green technology diffusion, this paper builds an agent-based model that integrates the relative agreement model with technology diffusion theories to conduct a sequence of controlled numerical experiments, which progressively unveil how attitudinal and technological factors impact green technology diffusion. The main findings include that (1) improving consumers’ pro-environmental attitudes is prominently beneficial to green technology diffusion and maturation; (2) technology maturity has very limited impact on consumers’ first-time purchases but significantly affects consumers’ satisfaction, which would further impact consumers’ repeat purchases; (3) consumers that do not support green technologies frequently emerge during the evolution of attitudes (despite the high technology maturity), which corresponds to the emergence of the anti-environmental groups observed in the real world; (4) active interactions between non-adopters enable their attitudes to converge, which results in the polarization of consumers’ attitudes.
AB - Massive diffusion of green technologies is significant for building a cleaner world. However, the process of technology diffusion is usually slow and complex. An in-depth understanding of the mechanism regarding green technology diffusion is an essential precondition for effectively stimulating this process. Green technology diffusion heavily involves both social and technological changes. Although existing studies have provided rich knowledge about identifying critical drivers and barriers affecting green technology diffusion, research that considers consumers’ pro-environmental attitudes and green technology diffusion as an evolving system is still sparse. Aiming at exploring the co-evolution of consumers’ pro-environmental attitudes and green technology diffusion, this paper builds an agent-based model that integrates the relative agreement model with technology diffusion theories to conduct a sequence of controlled numerical experiments, which progressively unveil how attitudinal and technological factors impact green technology diffusion. The main findings include that (1) improving consumers’ pro-environmental attitudes is prominently beneficial to green technology diffusion and maturation; (2) technology maturity has very limited impact on consumers’ first-time purchases but significantly affects consumers’ satisfaction, which would further impact consumers’ repeat purchases; (3) consumers that do not support green technologies frequently emerge during the evolution of attitudes (despite the high technology maturity), which corresponds to the emergence of the anti-environmental groups observed in the real world; (4) active interactions between non-adopters enable their attitudes to converge, which results in the polarization of consumers’ attitudes.
KW - ABM
KW - Agent-based modeling
KW - Agent-based simulation
KW - Green technology diffusion
KW - Relative agreement model
UR - http://www.scopus.com/inward/record.url?scp=85079356458&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2020.120384
DO - 10.1016/j.jclepro.2020.120384
M3 - Article
AN - SCOPUS:85079356458
SN - 0959-6526
VL - 256
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 120384
ER -