Developing an Interpretive Structural Model of Agile Human Resources Using a Soft Capabilities Approach to Digital Transformation

Abstract

The present study aimed to develop an interpretive structural model of agile human resources using a soft capabilities approach to digital transformation in the Islamic Republic of Iran Railways.

Methods and Materials: This developmental-applied, exploratory-descriptive study employed an exploratory sequential mixed-methods design. In the qualitative phase, 15 experts, senior managers, human resource and information technology specialists, railway industry managers, and university faculty members were selected through purposive and snowball sampling until theoretical saturation was reached. Data were collected through semi-structured interviews and analyzed using MAXQDA 2020 through open, axial, and selective coding. Coding reliability was assessed using Holsti’s agreement coefficient. In the quantitative phase, the same 15 experts completed pairwise comparison checklists for Interpretive Structural Modeling (ISM), and the structural analyses were performed in MATLAB. In addition, 191 railway human resource employees were selected through stratified random sampling and completed a 40-item researcher-developed questionnaire.

Findings: Qualitative analysis identified seven major dimensions: digital transformation leadership and governance, human resource agility, organizational culture, information technology infrastructure, customer satisfaction and processes, financial and operational performance, and continuous learning and growth. Digital transformational leadership emerged as the core category. Holsti’s agreement coefficient was 0.857. ISM analysis revealed a five-level hierarchical structure. Digital transformation leadership and governance occupied Level V with the highest driving power of 7 and dependence of 1, indicating its fundamental role. Organizational culture was positioned at Level IV. Human resource agility, information technology infrastructure, and continuous learning and growth were placed at Level III. Customer satisfaction and processes occupied Level II, while financial and operational performance represented the final outcome at Level I. MICMAC analysis classified leadership and organizational culture as independent driving variables, the three Level III dimensions as linkage variables, and customer/process and financial/operational outcomes as dependent variables.

Conclusion: The findings indicate that agile human resources in digital transformation are primarily rooted in transformational digital leadership and organizational culture, which activate human, technological, and learning capabilities and ultimately improve organizational processes and financial and operational performance.