The Evolution of Compensation Systems: A Systematic Review, Bibliometric Analysis, and Structural Modelling from Reciprocal Exchange to Algorithmic Governance

M. N. Aishwarya Anandavalli, S. Antony Raj, Husna T. Lumapenet, Wong Chi-Wai, Yang Tsung-Han, Huang Shu-Fen Department of Commerce, Faculty of Science and Humanities, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India. College of Education, Cotabato Foundation College of Science and Technology, Arakan, North Cotabato, Philippines. Department of Management, Victoria Peak Exports, Tsim Sha Tsui, Kowloon, Hong Kong, China. Department of Sales, Pacific Group Exports, Chung-Cheng Road, Keelung, Taiwan, China. Department of Sales, Formosa Trading Co., Ming Harng Road, Taichung, Taiwan, China.

Abstract: This study holistically tracks the historical and technological evolution of compensation systems. It synthesises how organisational incentive mechanisms have evolved from relationship-based survival structures to data-driven, algorithmic platform revenues. The study uses a multi-method approach to synthesise qualitative evidence. A Systematic Literature Review (SLR) and PRISMA-guided screening of 5,745 initial records identified 142 key publications. Second, VOSviewer bibliometric network analysis mapped the field's intellectual structure, theme clusters, and temporal evolution. Third, Interpretive Structural Modelling (ISM) and MICMAC analysis assessed the hierarchical linkages, mutual interdependencies, driving power, and dependence power of 25 Critical Success Factors (CSFs) driving this evolution. The study divides rewards into five phases: Ancient (Barter and Survival), Traditional (Scientific Management and Commodity Labour), Pre-Digitalisation (Human Relations and Strategic Rewards), and Digitalisation (Electronic HRM and Payroll Automation), and Algorithmic. ISM and MICMAC studies show that reciprocity, redistribution, and structured pay systems underlie modern digital and algorithmic compensation methods. Technology enablers like HR Analytics and Platform Integration are crucial connection variables, but human-centric outcomes like Employee Motivation and Labour Compensation Equity depend on institutional and ethical governance frameworks. This work integrates conventional compensation theories and AI-driven management paradigms into a single evolutionary trajectory, filling a research gap. Structured mapping of the causal hierarchy of these development drivers provides HR practitioners, policymakers, and platform architects with strategic insights to balance automated algorithmic efficiency with transparency, equity, and ethical corporate governance.

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Keywords: Algorithmic Compensation; Platform Economy; Strategic Reward Management; Systematic Literature Review; Interpretive Structural Modelling (ISM); MICMAC Analysis; Compensation Systems.

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Received on: 21/06/2025Revised on: 12/08/2025Accepted on: 25/10/2025Published on: 05/03/2026

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