Journal of Human Resource Management Future Studies
Islamic Azad University, Marand Branch
Abstract: (3 Views)
experience.userimproveoBackground and Objectives: with the expansion of digital technologies and the use of artificial intelligence in human resource processes, especially recruitment, process efficiency has increased. However, the adoption of this technology by applicants depends on their perception of procedural justice. This study examines the effect of applicants' perception of AI use in the recruitment process on their percieved procedural justice, and the mediating roles of three Technilogy Acceptance Model constructs: percieved usefulness, percieved ease of use, and percieved trust.
Methods: This descriptive-correlational study with a quantitative approach used data collected from a questionaire adapted from Hossein et al. (2025) on a five-point Likert scale. The population consisted of 290 employees and branch manageres of an insurance company in Zanjan city. Cronbach's alpha=0.717, composite reliability=0.817, and AVE=0.518 were confirmed. Data analysis was conducted using Structural Equation Modeling in SmartPLS4.
Results: Findings showed that applicants' percieved use of AI in the recruitment process has a positive and significant relationship with percieved procedural justice. Percieved usefulness and percieved trust significantly mediate the relationship between AI use and procedural justice, while pecieved ease of use does not play this mediating role.
Conclusions: The results can provide a practical framework for designing intelligent recruitment systems that are fair, transparent, and trustworthy, and aligned with professional ethics and privacy to anhance acceptance and satisfaction among applicants. adding percieved trust to the Technology Acceptance Model and testing the mediating role of the three constucts addresses a research gap in emerging economies such as Iran and offers guideliness.
Methods: This descriptive-correlational study with a quantitative approach used data collected from a questionaire adapted from Hossein et al. (2025) on a five-point Likert scale. The population consisted of 290 employees and branch manageres of an insurance company in Zanjan city. Cronbach's alpha=0.717, composite reliability=0.817, and AVE=0.518 were confirmed. Data analysis was conducted using Structural Equation Modeling in SmartPLS4.
Results: Findings showed that applicants' percieved use of AI in the recruitment process has a positive and significant relationship with percieved procedural justice. Percieved usefulness and percieved trust significantly mediate the relationship between AI use and procedural justice, while pecieved ease of use does not play this mediating role.
Conclusions: The results can provide a practical framework for designing intelligent recruitment systems that are fair, transparent, and trustworthy, and aligned with professional ethics and privacy to anhance acceptance and satisfaction among applicants. adding percieved trust to the Technology Acceptance Model and testing the mediating role of the three constucts addresses a research gap in emerging economies such as Iran and offers guideliness.
Keywords: Digital Recruitment, Perceived Trust, Perceived Usefulness, Procedural Justice, Technology Acceptance Model (TAM)
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