Presentation of the Interpretive Structural Model (ISM) for the Development of the National Digital Oversight Ecosystem

In the era of digital transformation, traditional oversight mechanisms no longer suffice to address the complexity and speed of governance decision-making. The emergence of new technologies, data-driven approaches, and participatory models has intensified the need to design a digital oversight ecosystem. This study aims to identify and prioritize the factors influencing the formation and advancement of such an ecosystem at the national level. The research employs a mixed-method approach, conducted in two phases: meta-synthesis and interpretive structural modeling (ISM). First, through meta-synthesis of 15 reputable international scientific documents published between 2015 and 2025, key factors contributing to the development of a digital oversight ecosystem were identified. Then, using ISM analysis, expert opinions were examined to prioritize the identified factors.

Findings reveal that the factors influencing the digital oversight ecosystem fall into five conceptual levels:Leadership (the most fundamental factor),Digital technologies, data, nd culture (infrastructural factors),Support and oversight processes (operational factors),Ecosystem processes (structural factors),Governance values such as transparency, justice, and public trust (as the ultimate outcomes of the structure)

The proposed model demonstrates that successful implementation of digital oversight requires sustained interaction among technical, cultural, and institutional elements. Sole reliance on technology, without structural reforms and transformative leadership, is insufficient. The innovation of this study lies in presenting a multi-level, interactive, and generalizable model for analyzing the digital oversight ecosystem—one that is conceptually useful for policymakers and can serve as a foundation for designing indicators, evaluations, and digital transformation programs within national oversight institutions.