Document Type : Research Paper
Authors
1 PhD Student in Business Policy Management, Department of Business Management, Faculty of Management and Economics, University of Guilan, Rasht, Iran
2 Professor, Department of Business Administration, Faculty of Management and Economics, University of Guilan, Rasht, Iran.
Abstract
This study aims to develop a smart policy-making framework to enhance organizational agility in innovative companies, using a qualitative data-based approach. The research is applied-developmental in nature and employs a descriptive, non-experimental approach to data collection. The study participants included 17 experts: theoretical experts (professors in IT management and entrepreneurship) and practical experts (managers of innovative companies) who had knowledge of smart policy implementation. Qualitative data were gathered through semi-structured interviews based on six main questions, with the possibility of follow-up questions. Data were analyzed using the grounded theory method with the assistance of MAXQDA software. Subsequently, the fuzzy Delphi method was employed in MATLAB to screen the research indicators. Based on the proposed model, causal conditions—including environmental dynamism and transformative pressures, customers’ innovative demands, the advancement of smart technologies, and the need for data-driven governance—affect the core phenomenon of smart policy-making. This core phenomenon, along with contextual conditions (such as the maturity of internal digital infrastructure and an open, learning-oriented organizational culture) and intervening conditions (such as institutional barriers and organizational inertia to change), influence strategies and actions (such as developing a smart policy architecture aligned with digital transformation). These strategies and actions ultimately lead to outcomes such as enhanced organizational agility, strengthened systemic and collaborative innovation, and increased social capital and institutional trust.
Keywords
- Smart policy-making
- organizational agility enhancement
- innovative companies
- qualitative data-based approach
Main Subjects
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