Document Type : Research Paper

Author

• Valiallah Vahdaninia

Assistant Professor, Department of Public Policy, IRI Military Command and Staff University, Tehran, Iran.

Abstract

Introduction
Over the past three decades, public policy studies have undergone a fundamental paradigm shift from traditional government centric models toward governance approaches that emphasise multi actor networks, cross sectoral collaboration, and nonlinear policy processes. This “governance turn,” initially articulated by Rhodes (1997) and further developed by the Anglo governance school, portrays the state as increasingly hollowed out, its power dispersed across functionally distinct networks of public, private, and voluntary organisations. While this perspective has enriched policy analysis by highlighting complexity and interdependence, it has also attracted substantial criticism. Stewart and Crowley (2020) argue that the governance turn has created an epistemological and operational dead end: excessive reliance on network governance and systematic marginalisation of the state have weakened policy coordination, undermined accountability, and contributed to state failures in addressing wicked problems such as climate change, health emergencies, and economic instability.
In the global literature, three main approaches have sought to explain the role of the state in public policy. First, state less approaches (e.g., Rhodes’ network governance) remove the state from the centre of analysis, thereby neglecting its macro coordination capacity. Second, state centric approaches (Bell & Hindmoor, 2009; Jessop, 2016) reaffirm the central authority of the state but pay insufficient attention to systemic dynamics and nonlinear feedbacks. Third, new institutionalist approaches (March & Olsen, 1989; Schmidt, 2010) focus on formal and informal rules, norms, and values but fail to recognise the active role of the state as coordinator and guarantor of accountability. To fill this theoretical gap, Stewart and Crowley (2020) proposed a hybrid framework – here termed “systemic institutionalism” – which integrates three core components: (a) systems thinking (to identify feedback loops, interdependencies and leverage points); (b) institutional analysis (to understand formal and informal rules governing actor behaviour); and (c) state centric governance (to redefine the state as coordinator, regulator and guarantor of accountability).
Despite its theoretical richness, the applicability of systemic institutionalism to countries with centralised state structures and multi layered complex problems, such as Iran, remains unexplored. Iran’s policy system is characterised by (1) extreme structural centralisation; (2) a high density of wicked problems (water crisis, energy imbalances, air pollution, health system instability, national security tensions, multi layered sanctions); and (3) a historical weakness in inter sectoral coordination and systemic feedback mechanisms. Indigenous research has shown that imported governance models, without deep adaptation to Iran’s institutional and political realities, have not only been ineffective but have sometimes exacerbated complexities. No systematic study has yet examined the feasibility of operationalising systemic institutionalism in Iran. Therefore, the main research question is: How can Stewart and Crowley’s (2020) systemic institutionalism framework be operationalised to analyse and improve public policy in Iran? Two sub questions are: (1) What are the core components of systemic institutionalism, and how do they differ from conventional governance and institutionalist approaches? (2) What are the main obstacles and opportunities for implementing this framework in Iran’s centralised policy system?
Research Method
The study adopts a qualitative, developmental applied approach using directed content analysis (Hsieh & Shannon, 2005). The primary source is Stewart and Crowley’s (2020) Reconsidering Policy: Complexity, Governance and the State, complemented by fifteen domestic academic articles (2016 2023), two policy reports (the Development and Foresight Research Centre, 2021; WHO Iran COVID 19 report, 2021), and two Iranian case studies: (a) COVID 19 pandemic management (2020 2021) and (b) the gasoline price reform (November 2019). The unit of analysis was the paragraph. Coding proceeded in three stages: open coding (extracting all paragraphs related to policy systems, the state’s role, and institutions); axial coding (grouping the open codes into seven main categories); and selective coding (comparing the seven categories with the two Iranian case studies to determine whether each category has a strong instance, a weak instance, or is absent in Iran). Validity was ensured through data triangulation and peer debriefing; reliability was assessed by a second coder on 20% of the data, yielding an inter coder agreement of 86%.
Findings
The analysis extracted seven main categories with 28 sub codes:

1. Systemic boundaries and leverage points: Policymakers often assume boundaries are fixed, whereas boundaries themselves are policy objects. Changing boundaries (e.g., merging institutions) is the most effective but most difficult intervention.
2. Positive and negative feedback: Policy failure typically results from positive feedback (self reinforcing cycles) overpowering negative (balancing) feedback. Delayed feedback is regularly ignored.
3. Inter sectoral coordination and the state’s regulatory role: Effective coordination requires a strong cross sectoral body; the state must maintain a “shadow of hierarchy” even when delegating implementation.
4. Advisory systems and evidence based policy: A mature advisory system balances “cold” (scientific, replicable) and “hot” (values based, politically sensitive) advice. Excess of either leads to policy failure.
5. Policy implementation: Implementation is not linear but a dynamic, negotiated process where street level bureaucrats reinterpret policy. The separation of design from implementation is a dangerous illusion.
6. Policy change and double loop learning: Crises open windows for double loop learning (questioning fundamental assumptions), but most governments only engage in single loop learning (adjusting tools).
7. Accountable governance and transparency: Accountability is multi dimensional: vertical (to superiors), horizontal (to peers and stakeholders), and social (to citizens). Information transparency is the operating system of all accountability.

Applying these categories to the two Iranian case studies revealed significant weaknesses. Regarding boundaries and leverage points, Iranian policymakers consistently prefer parametric adjustments (e.g., sudden price changes) over structural interventions. The November 2019 gasoline price hike, rather than targeting the underlying positive feedback loop of the subsidy system, triggered widespread protests. The energy subsidy system exhibits a classic positive feedback loop (higher subsidies → lower prices → higher consumption → higher subsidy needs), yet policymakers failed to design negative feedback mechanisms such as progressive taxation or targeted transfers. Delayed feedback was systematically ignored. Inter sectoral coordination is weak and crisis driven; permanent cross sectoral bodies are absent, although the state demonstrated relative resilience (“steering” capacity) during both crises. Iran’s advisory system is heavily tilted toward “hot” advice (political, factional considerations), while “cold” scientific advice is often marginalised. Policy implementation remains linear and centralised, ignoring local feedback and the interpretive power of street level bureaucrats. Double loop learning is absent: fundamental assumptions underlying both COVID 19 management and energy policy were never critically revisited. While vertical accountability is relatively acceptable, horizontal and social accountability are extremely weak, and information transparency is very low.
Despite these weaknesses, opportunities exist: the centralised state structure is suitable for intervening in systemic boundaries; longitudinal data are available for modelling; the state has shown relative crisis resilience; and a pool of skilled scientific personnel is present.
Conclusion
Systemic institutionalism can be operationalised in Iran along seven dimensions: (1) identifying systemic boundaries and leverage points; (2) designing negative feedbacks to stabilise unstable systems; (3) creating permanent cross sectoral coordination bodies; (4) redesigning the advisory system to balance scientific and political advice; (5) shifting from linear to adaptive implementation with street level bureaucrats’ participation; (6) institutionalising double loop learning; and (7) strengthening information transparency as a prerequisite for horizontal and social accountability.
Five concrete policy recommendations are offered: (i) establish or strengthen a Supreme Council for Policy Coordination as a permanent cross sectoral strategic body; (ii) create boundary spanners within the state’s advisory system to translate scientific evidence into political language and vice versa; (iii) mandate ex ante assessment of delayed feedbacks for all major policies using system dynamics modelling; (iv) institutionalise double loop learning through periodic “fundamental assessments” of policies older than five years; and (v) develop a National Policy Transparency System making all non classified policy documents and evaluation reports publicly accessible. Future research should pursue comparative studies with similarly centralised states, design tools to measure double loop learning capacity, conduct longitudinal studies of feedback patterns, and explore cultural and political barriers to information transparency.

Keywords

• Reconsidering public policy
• Systemic institutionalism
• Governance transition
• Return to the state
• Government centricity
• COVID 19 crisis management
• Gasoline price reform

Main Subjects

• Public Policy