Green Supply Chain Management in Chinese Electronic Manufacturing Organisations: An Analysis of Senior Managements' Perceptions

Eoin Plant, Yusen Xu and Gareth R.T. White
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Eoin Plant: Business School, University of South Wales, Treforest, UK
Yusen Xu: Business School, University of South Wales, Treforest, UK
Gareth R.T. White: Business School, University of South Wales, Treforest, UK

International Journal of Social Ecology and Sustainable Development (IJSESD), 2015, vol. 6, issue 3, 21-30

Abstract: Green supply chain management and reverse logistics has emerged as a key area of research interest. Recent environmental regulations have also stimulated interest in this field. However, information sharing is a prerequisite to efficient and effective logistics utilisation. Manufacturing organisations in China were argued to be 10-20 years behind their Western counterparts in relation to information sharing in their supply chains (). This barrier needs to be addressed if China is going to maintain and grow its manufacturing position in the world, attempt to address green supply chain issues and their negative externalities. A systematic literature review was undertaken and green supply chain management theoretical framework adopted. The paper explores the perceptions of senior management toward green logistics and information sharing in Chinese electronic manufacturers. Previous research has concentrated on the focal companies (brand owners). This research concentrated on SME organisations further up the supply chain. Semi-structured interviews of eighteen senior managers of electronic manufactures in Jiangsu province China were conducted in 2012. Thematic analysis is applied and the findings contrasted to other research. The paper provides insight to the current status of managers' views on information sharing and green supply chain initiatives. Information platform, skills, investment, and trust emerged as key influences on their willing to engage in information sharing in relation to green supply chains. This research, among others, assists to inform policy for optimal evidence based intervention. Future research directions are also considered.

Date: 2015
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