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.

近年来，信息技术（IT）劳动力需求和IT岗位特征都受到工业4.0（I4.0）和数字时代的显着影响。高等教育部门有望通过这样的进步进行自我升级，并培养能够满足新行业要求的毕业生。然而，由于目前的需求差距，大学正在寻求确定新的数字工作者应具备的技能。由于我们生活在数字时代，文献未能充分解决对个体工人造成的后果问题。应做出大量科学努力来设计某些可以培养数字能力（DC）的课程和培训计划。有必要构建一个包容性的术语框架。此外，研究与人力资源管理 (HRM) 相关的劳动力 DC 存在不同的选择。本文试图通过开发综合决策框架来填补这一空白。本文旨在介绍一种创新的歧视措施并讨论其优雅的特性。在此基础上开发了一种根据 COmpromise Solution (MARCOS) 框架的替代方案测量和排名，用于评估模糊集上的 MCDM 问题。另一方面，采用PF-熵-RS权重技术的新方法来计算准则权重或准则的显着性程度。那么，MARCOS方法是处理MCDM问题的一种新的优雅方法。因此，在本研究中，我们使用 PF-entropy-RS 和 PF-MARCOS 方法开发了一种新的多标准决策 (MCDM) 方法，并进一步用于评估未来劳动力的能力数字技术在高等教育中的实施。它有助于计算标准的客观/主观权重，以评估未来劳动力在高等教育中实施数字技术的能力；然后，该方法用于评估高等教育机构对未来劳动力在高等教育中实施数字技术的不同能力的偏好。本文进行了实证案例研究，以评估未来劳动力在高等教育中实施数字技术的最重要能力。此外，为了评估所提出框架的性能质量，本研究还涉及一些比较和敏感性分析。这项研究发现，数据和信息处理已成为未来劳动力在高等教育中实施数字技术的最重要能力。与现代界面交互的能力是未来劳动力在高等教育中实施数字技术的第二重要能力。综上所述，负责在高等教育中实施数字技术的劳动力将极大地影响学生的学习体验。随着技术的不断进步，高等教育机构将需要具有不同数字专业知识的熟练专业人员来成功管理和集成这些技术。