Analysis of Compensation Theories Based on Behavioral Economics: The Application of Meta-Theory

The primary objective of this research is to identify behavioral economics theories relevant to compensation systems and, through a comprehensive metatheoretical analysis of seminal theories (focusing on structure, context, and content), to formulate foundational assumptions and guiding principles for designing behaviorally-informed compensation models. This study adopts a qualitative research design based on metatheoretical methodology. As a meta-level inquiry, metatheory enables the structural and content-based analysis of behavioral economics theories, emphasizing an interpretive approach to uncover the constitutive elements of such frameworks. Data collection was conducted via a systematic literature review, encompassing Persian and English academic sources published in reputable scientific databases without time limitations. From an initial pool of 970 studies, 12 high-quality research articles were selected for in-depth analysis. Drawing on prior studies, three analytical dimensions were defined to guide the metatheoretical examination. The findings demonstrate that behavioral economics provides a robust foundation for designing compensation systems aligned with human behavior and real-world organizational challenges. Such a model integrates the effects of loss aversion, bounded rationality, psychological preferences, and cognitive biases, thereby enabling the development of reward structures that balance internal and external motivations, enhance fairness, and increase employee engagement and productivity. The results highlight the critical role of three design elements: the type of rewards, the timing of payments, and the performance evaluation mechanism. Specifically, extrinsic rewards are more effective for simple tasks, while intrinsic and quality-based incentives are preferable for complex or creative jobs. Regular and timely payments, combined with non-monetary rewards—such as public recognition and symbolic gestures—enhance employee satisfaction and fairness perceptions. Transparent communication of reward criteria and the application of behavioral nudges (e.g., default options, framing, and feedback loops) are identified as key tools for aligning employee decisions with organizational objectives. The study further explores several core behavioral constructs influencing compensation responses: loss aversion, where the pain of losing a reward outweighs the pleasure of gaining one; mental accounting, which affects how employees value different reward formats; and motivational crowding out, where excessive financial incentives can undermine intrinsic motivation. Moreover, the findings emphasize the importance of procedural, distributive, and interactional justice in shaping perceptions of fairness and trust in the reward system. Temporal discounting and reference points are also crucial, showing that employees prefer immediate and predictable rewards relative to their prior earnings, peer salaries, or market benchmarks. The proposed behaviorally-informed compensation model includes innovative design features such as flexible reward timing (e.g., frequent micro-payments, early partial payouts), personalized non-financial incentives (e.g., experiential rewards, social recognition), stable and objective performance metrics, and employee agency through choice architecture and flexible contracts. Group-based rewards are also incorporated to foster collective responsibility, trust, and learning within teams. In sum, this model combines the theoretical insights of behavioral economics with practical strategies for compensation design. It challenges the assumptions of neoclassical models—such as perfect rationality and purely financial motivation—and offers a more nuanced, psychologically realistic framework. By accounting for cognitive and emotional factors, this model has the potential to enhance motivation, reduce perceived injustice, and improve organizational performance. This study contributes to both theory and practice by providing a conceptual foundation for future empirical research. Further studies are encouraged to test the model in real organizational settings and examine the impact of cultural and individual differences on the effectiveness of behavioral compensation mechanisms.