Identifying and Evaluating Native Patterns for Creating a Transformational Organizational Culture Based on Modern Public Services in the Context of Intelligent Governance (Case: National Iranian Oil Company)

نویسندگان

1 دانشگاه آزاد اسلامی

2 دانشگاه آزاد اسلامی

3 دانشگاه آزاد اسلامی

doi
چکیده

This research aims to identify and evaluate a native model for creating an organizational transformation culture based on new public services in smart governance and emerging technologies. This study is applied-developmental in nature. Based on purposive sampling, 15 managers of the National Iranian Oil Company were interviewed. In the quantitative section, all heads, managers, and staff working in the corporate sectors were considered; their number was unlimited, and based on Cochran’s formula, a sample size of 384 was determined. The qualitative method of Grounded Theory data analysis was used using ATLAS.ti software, and Structural Equation Modeling (SEM) in SmartPLS software was employed for validation. The results of model fit using structural equations, supported the coherence and empirical validity of the proposed model. It showed that the implementation of these strategies directly and indirectly leads to improved organizational efficiency, enhanced service quality, strengthened public trust, reduced operational costs, and the formation of competitive advantages in the public sector. Accordingly, the transformation culture in the National Iranian Oil Company is not merely a transient attitudinal change but a strategic mechanism for aligning economic missions with the values of new public services and the requirements of smart governance. This mechanism, if supported by continuous managerial and institutional backing, can pave the way for the transition of this organization into an agile, accountable, data-driven, and citizen-centric institution at both national and regional levels, laying the essential cultural foundation for the successful adoption of advanced technologies such as the Metaverse, Artificial Intelligence, and Digital Twins.