Enhancing Faculty Performance Measurement through HR Analytics: A Comprehensive Model of Teaching, Research, and Service Contributions

Abstract

This study intends and is designed to consider a quantitative evaluation of faculty at KPK universities, and it lists seven research objectives relating to various dimensions of performance: teaching effectiveness, research contribution, grant funding, service and leadership activities, professional development, peer evaluations, and student outcomes. At the heart of this study is the faculty performance, which is seen as a key indicator of how effective and how well contributions are made by faculty members. For achieving the objectives of the study, primary data is to be collected through a structured questionnaire that is to be administered to faculty members across KPK universities. Using a stratified random sampling method, representation would be secured from different departments and faculty ranks thus making the findings more reliable. Seven hypotheses will be tested, which explain the basic relationships between exogenous and endogenous variables of the study. This study bears a great deal of importance for the new era of human resource analytics in higher education. The aim of data-driven decision-making would improve the quality of faculty evaluations and developmental programs for better educational proficiency brought about at the end. The discovery will assist in the strategic allocation of resources and the establishment of a culture of continuous improvement among faculty members. Future research endeavors will include longitudinal studies to assess the changes in faculty performance over time and expand the sample size to include a broader array of institutions. Qualitative insights through interviews or focus groups could further inform the understanding of faculty experience. Furthermore, studying how emerging technologies might affect HR analytics, including AI and machine learning, could benefit improving methodologies for evaluating faculty performance. If these directions are taken, then future scholarship could contribute meaningfully to optimizations of faculty performance evaluation frameworks in higher education.