Prioritizing the Effective Components of the Employer Branding Model Based on Artificial Intelligence Using the Fuzzy Analytic Hierarchy Process (A Case Study in the Iranian Electricity Industry)

Employer branding, as an innovative concept, bridges brand management in marketing and human resource management. It plays a critical role in offering effective branding strategies in the electric power industry. This study aims to prioritize the key components influencing AI-based employer branding in Iran's electric power industry using the Fuzzy Analytic Hierarchy Process (FAHP).

The research follows a quantitative, descriptive, and applied approach. The statistical population includes experts from the electric power industry and marketing professors from universities. Data was collected using a researcher-made questionnaire, whose validity was confirmed through the fuzzy Delphi method and expert opinions from five specialists, while reliability was assessed through inconsistency rate analysis. The data was then processed using FAHP. The quantitative section of the study was expert-driven, with 15 experts completing the FAHP pairwise comparison tables. The analyses were performed using Smart PLS software and FAHP techniques.

The results showed that the most significant components influencing AI-based employer branding in the electric power industry include employee retention, employee productivity, differentiation from competitors, job satisfaction, and efficient recruitment.

Internal marketing management for current and potential employees was found to have less impact on employer branding. These insights can assist managers in the electric power industry in designing more effective strategies to strengthen their employer brand.