Entrepreneurial Firm’s Various Techniques and Tools to Attract and Retain Talent Management in Service Industry

Abstract

Entrepreneurial firms face challenges in talent acquisition and retention due to competition from the service industry, limited resources, high attrition, and evolving workforce demands. Addressing these challenges, firms adopt strategic compensation theories, career development systems, flexible work arrangements, and technology-based retention mechanisms. This research employs predictive analytics, clustering, and Structural Equation Modelling (SEM) to analyze the interplay of talent management strategies. Critical retention drivers such as compensation, career growth, work environment, job satisfaction, and leadership effectiveness are considered moderators of employee retention. K-means clustering is introduced to segment employees based on attrition risk, enabling firms to identify high-risk clusters and implement targeted interventions. Additionally, the Cox proportional hazards model is used to evaluate turnover rates, enhancing the understanding of resignation trends. SEM further examines the direct and indirect relationships among retention factors, assessing the alignment with theoretical constructs. The research tests four hypotheses evaluating different retention strategies’ effectiveness, offering empirical insights into talent management. By integrating predictive modelling, clustering, and statistical methodologies, the research provides a framework for developing tailored retention methods to improve staff fulfilment and commitment. The findings contribute to entrepreneurial firms by presenting evidence-based approaches to reducing attrition risk, improving workforce productivity, and ensuring business sustainability in dynamic markets. These insights enable firms to optimize talent management, fostering long-term growth and competitiveness in the service-driven economy.