TY - JOUR
T1 - Determinants and associated performance improvement of green supply chain management in China
AU - Kuei, Chu Hua
AU - Madu, Christian N.
AU - CHOW, Vincent W S
AU - Chen, Yang
N1 - Funding Information:
We wish to acknowledge the helpful comments of both anonymous reviewers. These comments have helped to improve the quality of our work. This research was done while Prof. Madu was on sabbatical leave at the Shell Center for Environmental Management & Control, University of Nigeria, Enugu Campus. This research was partly funded by a grant from the National Emergency Management Agency (NEMA), Nigeria .
PY - 2015/5/15
Y1 - 2015/5/15
N2 - This study identifies the critical factors influencing the adoption of green supply chain practices in Chinese firms. The participating firms were classified into focal, downstream, and upstream firms. The data set was grouped in two namely aggregate which includes all the firms and independent data which consists of each firm's classification. Partial Least Squares (PLS) method was used to identify the determinants of green practices. The aggregate data show that external environmental factors (including customer pressures, regulatory pressures, government supports, and environmental uncertainty) were the most important in adopting green practices. For the focal firms, the independent data show that relative advantage, quality of human resources and customer pressure are positively associated with the adoption of green practice and they positively influence operations systems' performance. Conversely, the downstream firms are more efficient and effective when there are organizational and governmental supports. For upstream firms, the critical factors to organizational performance are compatibility, customer and regulatory pressures. In both the downstream and upstream firms, the factor complexity which denotes the lack of understanding and learning of green practices is the key barrier to implementing green practices. Knowledge of these critical factors for green supply chain management practice would help Chinese firms to become more environmentally responsible while simultaneously achieving their operational performance goals.
AB - This study identifies the critical factors influencing the adoption of green supply chain practices in Chinese firms. The participating firms were classified into focal, downstream, and upstream firms. The data set was grouped in two namely aggregate which includes all the firms and independent data which consists of each firm's classification. Partial Least Squares (PLS) method was used to identify the determinants of green practices. The aggregate data show that external environmental factors (including customer pressures, regulatory pressures, government supports, and environmental uncertainty) were the most important in adopting green practices. For the focal firms, the independent data show that relative advantage, quality of human resources and customer pressure are positively associated with the adoption of green practice and they positively influence operations systems' performance. Conversely, the downstream firms are more efficient and effective when there are organizational and governmental supports. For upstream firms, the critical factors to organizational performance are compatibility, customer and regulatory pressures. In both the downstream and upstream firms, the factor complexity which denotes the lack of understanding and learning of green practices is the key barrier to implementing green practices. Knowledge of these critical factors for green supply chain management practice would help Chinese firms to become more environmentally responsible while simultaneously achieving their operational performance goals.
KW - Corporate performance
KW - Determinant factors
KW - Green supply chain
UR - http://www.scopus.com/inward/record.url?scp=84927174578&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2015.02.030
DO - 10.1016/j.jclepro.2015.02.030
M3 - Journal article
AN - SCOPUS:84927174578
SN - 0959-6526
VL - 95
SP - 163
EP - 173
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
ER -