A PCA-based method for construction of composite sustainability indicators

Sustainable manufacturing is practiced globally as a comprehensive strategy for improving the sustainability performance of the manufacturing industry. While sustainability is characterized into such three dimensions as economic, environmental, and social, currently, there is no quantitative method yet to measure the so-called "sustainability" in the manufacturing industry. The objective of this research is to develop a comprehensive and effective quantitative method to measure the overall sustainability performance of manufacturing companies. In this paper, an integrated methodology is presented for the development of composite sustainability indicators based on principal component analysis (PCA). In developing this integrated approach, both industry and academia surveys are conducted to identify what sustainability indicators are favored by the sustainable manufacturing community. A unique index is then generated to measure the overall sustainability performance of industrial practices. The methodology can be used for benchmarking the overall sustainability performance of various manufacturing companies. A case study is conducted on a total of 11 global electronic manufacturing companies. The overall sustainability performance of these companies are measured, benchmarked, and ranked. The results showed that PCA is an effective approach for constructing composite sustainability indicators across environmental, economic, and social dimensions. From this research, it is found that industry and academia have different views on the sustainability measurement, evidenced by different weights put on the same indicator in industry and academia. The case study demonstrated that the methodology presented in this paper is an effective tool for comprehensive measurement of sustainability performance of manufacturing companies. Strengths and weaknesses of each company can be identified. Then, the recommended improvements can be suggested based on the study of each of the individual indicators.