Categorization of Blockchain Technology Applications in Human Resource Management: An Interpretive Structural Modeling Approach

Abstract

Human resource stores large amounts of employee data, vulnerable to sabotage and theft. Blockchain cybersecurity programs restrict access to authorized information, reducing internal violations. This research used a comparative approach with exploratory and qualitative methods. Library and field methods, including interviews and questionnaires, were used for theoretical and model development. The qualitative part involved family experts and psychologists, while the quantitative part involved families in Kermanshah province in Iran. Qualitative sampling used purposive approach, while random sampling was done for the quantitative part. Thematic analysis and fuzzy Delphi were used for data analysis. Interpretive structural modeling and MICMAC software were used for factor categorization. Eight factors were categorized across three levels of applications. Level 1 includes three applications: "management of fake job certificates," "certificate issuing system and training scores," and "employer branding improvement." Level 2 includes "recruitment and talent management" and "data security management," while Level 3 includes "salary information processing," "solving information asymmetry and reducing risk," and "reducing the skills gap in the workforce. Blockchain in HRM promotes participation from employees and managers, updating information and analyzing skills and employment experiences.