Empirical Validation and Testing of the Human Performance Evaluation Model in the Context of Implementing the New Tax Law

Abstract

Fundamental changes in the tax system and the imperative to transition from traditional paradigms to data-driven management require a high degree of adaptability in human capital. Nevertheless, the evident gap between auditors’ individual competencies and the structural inertia of the organization impedes the effective implementation of new policies. The present study aimed to validate and empirically test a human performance evaluation model in the context of implementing modern tax laws. In terms of purpose, this study was applied, and in terms of methodological approach, it employed a quantitative, descriptive-survey, correlational design. The statistical population consisted of employees and managers of the Tax Administration, from whom a sample of 170 participants was selected using convenience sampling. Data were collected using a standardized questionnaire based on a five-point Likert scale. Data analysis and hypothesis testing were conducted through partial least squares structural equation modeling (PLS-SEM) using SmartPLS, supplemented by one-sample t-tests and the Friedman test. Evaluation of the measurement model confirmed convergent validity, with average variance extracted (AVE) values ranging from 0.52 to 0.57, as well as composite reliability (CR), with values ranging from 0.79 to 0.90. The structural model also demonstrated satisfactory goodness-of-fit indices (SRMR = 0.075; NFI = 0.90) and explained 50% of the variance in the outcome variable (R² = 0.50). Path analysis indicated that contextual conditions, with an effect coefficient of β = 0.36 and the highest ranking in the Friedman test (mean rank = 4.39), constituted the most influential moderating determinant within the system. Moreover, the strongest direct effect was observed for the path from strategies to outcomes (β = 0.71). Descriptive statistical analysis further revealed that auditors’ digital skills (μ = 4.10) represented an organizational strength, whereas the transition toward data-driven analytical practices (μ = 3.58) constituted the organization’s principal weakness. Based on the empirical findings, the successful implementation of tax laws depends on reengineering contextual and organizational structures and overcoming organizational inertia so that existing human-capital capabilities can be aligned with data-driven requirements and translated into desirable performance outcomes.