Evaluation of the provincial competitiveness of the Chinese high-tech industry using an improved TOPSIS method

• Published in: Expert systems with applications 2014-05, Vol.41 (6), p.2824-2831
• Main Authors: Wang, Zheng-Xin, Wang, Yan-Yu
• Format: Article
• Language: English
• Subjects: Applied sciences; Competitiveness evaluation; Computer science; control theory; systems; Correlation; Criteria; Data processing. List processing. Character string processing; Decision theory. Utility theory; Exact sciences and technology; Expert systems; Firm modelling; High-tech industry; Indicators; Information overlap; Invariants; Linear transformations; Linkages; Mahalanobis distance; Memory organisation. Data processing; Operational research and scientific management; Operational research. Management science; Similarity; Software; TOPSIS
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2013.10.015

•The Mahalanobis distance is employed to improve the traditional TOPSIS method.•The new properties of the improved TOPSIS method are proven.•Chinese high-tech industry data is used to validate advantages of the new method. Evaluation of the competitiveness of high-tech industry is a technical decision-making issue involving multiple criteria. It is also a practical path to promote a country’s competitiveness. However, the competitiveness indicators in high-tech industry often act and react upon one another. Moreover, different dimensions and indicator weights also affect the evaluation results. In this paper, the Mahalanobis distance is used to improve the traditional technique for order preference by similarity to ideal solution (TOPSIS). The improved TOPSIS method has the following properties: (1) an improved relative closeness which is invariant after non-singular linear transformation, and (2) the weighted Mahalanobis distance is the same as the weighted Euclidean distance when the indicators are uncorrelated. The new method is applied to evaluate the competitiveness of the Chinese high-tech industry using data from 2011. Consideration of the correlation between indicators improves the evaluation results (in terms of sorting and closeness) to a certain extent compared to the traditional TOPSIS method. The top five provinces are: Guangdong, Jiangsu, Shanghai, Beijing, and Shandong. This finding reflects the practical linkage among provinces and softens the closeness value, consistent with reality.