A Semiautonomous Approach for Strategic Decision-Making; an Application for Digital Transformation in Finance

Abstract

This paper proposes an innovative approach to help domain knowledge experts with technology roadmapping and the strategic decision-making process. In our approach, we introduce a retrofitted parallel coordinate visualization tool, which is enhanced with a feature importance analysis algorithm. Our approach has produced four significant achievements. First, our new method reveals the shortcomings of some traditional parallel coordinate tools. Second, our method applies neutrosophic fuzzy sets in tacit knowledge analysis to foster ease with written text data; it assists with the processes in exploring possible roadmapping strategies, measuring vicinity conditions of adjacent features, and prioritizing their order based on the desired solution space of a certain attributes. The methods are applied in a case study with actual data that comes from a research project designed for financial organizations’ digitalization. Third, the application of parallel coordinates is reported for the first time for technology roadmapping in finance. Finally, proof of concept and a benchmarking practice considering generated hypotheses are provided in this paper.