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Green Marketing: A Grey-based Rough Set Theory Analysis of Activities

1School of Management Dalian University of Technology, P.R.China
2School of Management Science and Engineering, Dongbei University of Finance & Economics, P.R.China
3School of Economics Liaoning University, P.R.China

International Journal of Innovation Science

ISSN: 1757-2223

Article publication date: 14 March 2015



As green marketing is a critical function of green supply chain management, it has generated a great deal of discussion in public discourse and academic research. Interestingly, there is a gap in the research on how a company can effectively invest and manage various green marketing activities. Thus this paper aims to introduce a grey multiple criteria decision-making methodology to investigate the relationships between green marketing activities and performance outcomes (environmental and business performance). This paper seeks to make the following contributions to the green supply chain management literature. First, review the literature to identify implementation activities for green marketing from green supply chain management literature. Second, develop a methodology to evaluate relationships of green marketing activities by integrating grey number and rough set method. Third, obtain various decision rules relating the various green marketing activities to the environmental and/or business performance outcomes through an illustrative application within an incomplete information system. Knowing those rules to help in the implementation, management, and evaluation of these green marketing activities is valuable to both researchers and practitioners. Included in the discussion are insights into how these rules for individual and aggregated performance (environmental, business, and joint performance) may be evaluated. Practical and research implications of this work are detailed in the final section of this paper.



Xu, Z., Liu, X., Bai, C. and Hu, L. (2015), "Green Marketing: A Grey-based Rough Set Theory Analysis of Activities", International Journal of Innovation Science, Vol. 7 No. 1, pp. 27-38.



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