TOPSIS method for ability evaluation of industrial internet platform energizing digital transformation of manufacturing with DHHFLTSs

Abstract

China's Industrial Internet has progressed to a phase of deep implementation, finding extensive application across numerous vital sectors of the national economy. The Industrial Internet is proving to be an effective catalyst for high-quality economic and social development, increasingly serving as a pivotal force in the digital transformation of the manufacturing industry. At the heart of this transformation is the Industrial Internet platform, which acts as a transformative tool for enabling digital enhancements in manufacturing. The evaluation of the capability of these platforms to energize digital transformation is approached as a multi-attribute group decision-making (MAGDM) problem. In this context, the use of double hierarchy hesitant fuzzy linguistic term sets (DHHFLTSs) provides a precise representation of the significance in real MAGDM scenarios. Consequently, this paper introduces the double hierarchy hesitant fuzzy linguistic TOPSIS (DHHFL-TOPSIS) method, tailored specifically for MAGDM within a DHHFLTSs environment, and applies it to evaluate the capability of Industrial Internet platforms. Additionally, information entropy is utilized to determine the weights of the targets. A practical case study is also included to showcase the application of our method, and a comparative analysis is conducted to affirm its feasibility and effectiveness. The main contributions of this research are outlined as follows: (1) TOPSIS method is adapted based on DHHFLTSs; (2) PDHL-TOPSIS approach is utilized to address the MAGDM problem under DHHFLTSs; (3) A practical case study demonstrates the operational steps of our method; (4) A comparative analysis confirms the feasibility and effectiveness of the approach.