Analysis of challenges of digital service enabled by big data analytics technologies using a new integrated multiple-criteria decision-making (MCDM) method

Abstract

[EN] The digitalization of services and products is an approach adopted by modern companies to produce value. The key to success is knowing what your customers are saying about your company by compiling data in many aspects and reviewing the digital content collected from digitally enabled services. On the other hand, text review is a highly subjective task. The raw data has complex features, making analyzing the data on digital services a very complex and intriguing problem. This study collects the main challenges of digitally enabled services to offer an inclusive framework and describes the framework's potential in dealing with application-specific challenges. This study aims to suggest a data-driven decision-making model using the “intuitionistic fuzzy sets (IFSs)”, “method based on the removal effects of criteria (MEREC)”, “rank sum (RS), and the “multi-attribute multi-objective optimization with ratio analysis (MULTIMOORA)” approaches. The IFMEREC-RS tool computes the weights of the digital service challenges that big data analytics technologies enable and the IF-MULTIMOORA method prioritizes the technologies to assess the challenges. Then, an integrated decision-making framework is developed to investigate these challenges' subjective and objective weights using expert opinion. Using big data analytics, the proposed model can assess the preferences of technologies over different challenges.