Selecting industrial IoT Platform for digital servitisation: a framework integrating platform leverage practices and cloud HBWM-TOPSIS approach

Abstract

Digital servitisation has emerged as an important strategy to enhance industrial companies' competitiveness. Leveraging the IIoT (industrial internet of thing) platform is considered an essential way to facilitate digital servitisation. Selecting an appropriate IIoT platform from numerous alternatives in the market is a difficult task for the firms due to lack of deep understanding of the required IIoT platform capabilities for deploying industrial service. To help firms make wise decision, we propose a feasible multi-criteria decision making framework for IIoT platform selection. Firstly, a practice-oriented technical-managerial-service criteria system is derived from typical platform leverage logics for digital servitisation. Next, an integrative approach combining cloud hierarchical BWM (best-worst method) and cloud TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is proposed for selecting the best IIoT platform. Using this approach, the criteria weights and the ranking of potential platforms can be accurately determined by considering the fuzziness and randomness of linguistic decision information. Finally, a case study of a Chinese crane manufacturer illustrates the feasibility and reliability of the proposed framework. The analysis results can help the managers find the best IIoT platform and provide them with deep insight and direction for leveraging the IIoT platform towards digital servitisation.

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