Evaluate and identify the competencies of the future workforce for digital technologies implementation in higher education

In recent years, both information technology (IT) labor demand and IT job characteristics have been significantly influenced by the advent of Industry 4.0 (I4.0) and the digital age. The higher education sector is expected to upgrade itself with such progress and train graduates capable of meeting the new industry requirements. However, due to the present demand gap, universities are seeking to identify the skills new digital workers are expected to have. As we live in the digital age, the literature has failed to address the questions of the consequences for individual workers adequately. Considerable scientific efforts should be made to design certain curricula and training programs that could nurture digital competencies (DC). There is a need to construct an inclusive framework of the term. In addition, different options exist for studying the DC of the workforce in relation to human resources management (HRM). The current paper attempts to fill the gap by developing an integrated decision-making framework. The paper aims to introduce an innovative discrimination measure and discuss its elegant properties. A Measurement of Alternatives and Ranking according to the COmpromise Solution (MARCOS) framework for evaluating the MCDM problem on a fuzzy set has been developed based on it. On the other hand, the new methodology of the PF-entropy-RS weight technique is used to compute the criteria weights or significance degrees of criteria. Then, the MARCOS method is a new elegant approach to handle the MCDM problems. Thus, in this study, we have developed a new approach to the multi-criteria decision-making (MCDM) method using the PF-entropy-RS and PF-MARCOS methods and further implemented for the evaluation of the competencies of the future workforce for digital technologies implementation in higher education. It helps to calculate the objective/subjective weights of criteria to evaluate the competencies of the future workforce for digital technologies implementation in higher education; then, the approach is used to assess the preferences of higher education institutes over different competencies of the future workforce for digital technologies implementation in higher education. An empirical case study is carried out in this paper for the evaluation of the most important competencies of the future workforce for digital technologies implementation in higher education. In addition, to evaluate the performance quality of the proposed framework, this study also involves some comparison and sensitivity analyses. This study found that data and information processing has emerged as the most important competencies of the future workforce for digital technologies implementation in higher education. The ability to interact with modern interfaces is the second most important competency of the future workforce for digital technologies implementation in higher education. In conclusion, the workforce responsible for implementing digital technologies in higher education will significantly impact students' learning experiences. As technological advancements continue, higher education institutions will require skilled professionals with diverse digital expertise to manage and integrate these technologies successfully.