| Title |
Sustainable supply chain management practices and performance |
| ID_Doc |
71340 |
| Authors |
Wang, J; Dai, J |
| Title |
Sustainable supply chain management practices and performance |
| Year |
2018 |
| Published |
Industrial Management & Data Systems, 118.0, 1 |
| DOI |
10.1108/IMDS-12-2016-0540 |
| Abstract |
Purpose - The purpose of this paper is to contribute significantly to the empirical investigations related to the impact of sustainable supply chain management (SSCM) practices on performance in Chinese firms. The paper also aims to theorize and empirically assess a comprehensive SSCM practices and performance model. The model incorporates two aspects of SSCM practices: internal and external management, and analyses the impact on corporate sustainability performance from all dimensions. Design/methodology/approach - This paper develops a conceptual model to investigate the impact of SSCM practices on the firm performance. Based on the data of 172 Chinese firms, this paper analyzes the impact of SSCM practices on firm economic performance, environmental performance, and social performance for each dimension by using PLS structural equation methods. Findings - The results show that firm's internal SSCM practices have a positive impact on firm's environmental performance and social performance. Moreover, environmental performance and social performance are positively related to economic performance. Originality/value - A comprehensive SSCM practices performance model is proposed and empirically assessed for Chinese firms. The results of this investigation support the hypotheses that SSCM practices are environmentally and socially necessary and are favorable for business. A series of approach and implications of SSCM practices is recommended. |
| Author Keywords |
China; Emerging economies; Firm performance; Sustainable supply chain management; Sustainable operations |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000423366900001 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Industrial |
| Research Area |
Computer Science; Engineering |
| PDF |
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