An improved TOPSIS approach for the competitiveness analysis of provincial information resource industries in China. Issue 4 (26th April 2019)

• Record Type: Journal Article
• Authors: Qian, Minghui; Wang, Yuxi; Xu, Wei; Deng, Hepu
• Other Names: Jiménez Alfredo guestEditor.; Herrero Álvaro guestEditor.
• Is Part Of: Expert systems. Volume 36:Issue 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-26
• Subjects: competitiveness analysis -- information resource industry -- multicriteria analysis -- TOPSIS; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12407
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: The development of information resources industries is becoming increasingly important for improving the competitiveness of individual economies. As a result, effectively evaluating the performance of individual information resources industries becomes a critical problem that needs to be adequately addressed. This paper presents an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) approach for evaluating the performance of provincial information resources industries in an objective manner in China. The concept of information entropy is appropriately used for determining the objective weighting of the evaluation criteria in the evaluation process. The Mahalanobis distance is adequately adopted for better reflecting the relative distance between individual alternatives and the idea solution in determining the overall performance of individual alternatives across all the evaluation criteria. This leads to the determination of consistent performance evaluation outcomes, which are better accepted by all the stakeholders in the evaluation process. An example of evaluating the competitiveness of provincial information resources industries in China is presented. The result shows that the improved TOPSIS approach is effective for evaluating the competitiveness of information resources industries in the real‐world setting.