Designing a Mixed Evaluating System for Green Manufacturing of Automotive Industry

Yuhong Cao

angelcaoniuniu@sina.com
School of Management, Shanghai University, Shanghai, 200444, China (China)

Jianxin You


School of Economics &Management, Tongji University, Shanghai, 200092, China (China)

Rui Wang


School of Economics &Management, Tongji University, Shanghai, 200092, China (China)

Yongjiang Shi


Institute for Manufacturing, University of Cambridge, CB3 0FS Cambridge, UK (United Kingdom)


Abstract

The article proposed, from a sustainable development perspective, an index system based on Sustainability Balanced Scorecard (SBSC), including the main index of Financial, Internal process, Customer, Learning and growth, Social and the sub- index which comprised 28 indexes to evaluate the Green Manufacturing (GM) of automotive industry. Based on the index system, an evaluation model integrates by back-propagation artificial neural network (BPANN) and genetic algorithm (GA) was introduced. Using established model and indicators evaluated GM in four automotive companies; the key result of the evaluated show that: China’s automotive manufacturing enterprises still have big room for improvement in respect of customer satisfaction, resource consumption, community service, low-carbon activities etc., so the strategy and management activities that put much pressure on these respect are necessary.


Keywords:

SBSC, GM, index system of automotive industry, GA, BPANN

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Published
2016-01-04

Cited by

Cao, Y., You, J., Wang, R., & Shi, Y. (2016). Designing a Mixed Evaluating System for Green Manufacturing of Automotive Industry. Problemy Ekorozwoju, 11(1), 73–86. Retrieved from https://ph.pollub.pl/index.php/preko/article/view/4962

Authors

Yuhong Cao 
angelcaoniuniu@sina.com
School of Management, Shanghai University, Shanghai, 200444, China China

Authors

Jianxin You 

School of Economics &Management, Tongji University, Shanghai, 200092, China China

Authors

Rui Wang 

School of Economics &Management, Tongji University, Shanghai, 200092, China China

Authors

Yongjiang Shi 

Institute for Manufacturing, University of Cambridge, CB3 0FS Cambridge, UK United Kingdom

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