Designing a Model for Enhancing Employee Productivity in Power Companies Based on Artificial Intelligence
Keywords:
Employee performance management, organizational productivity, artificial intelligenceAbstract
This study aimed to design a model to enhance employee productivity in electric power distribution companies using artificial intelligence (AI) to improve human resource development and organizational performance. A mixed-method approach was adopted. The qualitative phase employed thematic analysis via MAXQDA and semi-structured interviews with 14 experts and senior managers from power distribution companies in western Iran. In the quantitative phase, a researcher-made questionnaire was distributed among a stratified random sample of 351 employees. Data were analyzed using SPSS and PLS software. Thematic analysis yielded 100 indicators, 24 components, and 10 core dimensions. In the quantitative analysis, the "ethical intelligence" dimension had the highest importance coefficient (0.909), while "knowledge and technology management" had the lowest (0.741). Paired t-tests confirmed significant differences between the current and ideal states across all dimensions. The final model included four core domains: philosophy and goals, theoretical foundations, evaluation system, and implementation mechanism. The proposed AI-based productivity model offers a strategic framework to optimize human resource performance in infrastructure industries. Emphasizing organizational ethics, continuous learning, digital competencies, and advanced data analytics, this model presents a forward-looking path for sustainable productivity enhancement.
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