Identification and Classification of Factors Influencing the Regulation of Priority Goods Markets Based on Network Governance with an Interpretive Structural Modeling Approach

Objective
The increasing complexity within economies and societies, coupled with the limited capacity of governments to address these challenges, has brought network forms of governance into focus. Traditional interactions between the market—how households and firms connect—and government interventions have consistently presented challenges across various economic sectors. Predominantly, governmental organizations have been structured on hierarchical principles, wherein managers must navigate authority, law compliance, and accountability. These managers have traditionally embraced hierarchical management styles. However, the emergence of the New Public Management movement in the 1980s also introduced market governance. Additionally, network governance has become essential, particularly as solitary public sector efforts have proven inadequate in solving complex social issues. This increased societal pressure for cooperation and co-production with the community, rather than mere governance. An area where network governance can be effectively applied is in the regulation of priority goods markets. This study, therefore, proposes a model for regulating the priority goods market using a network governance approach.
Methods
This research utilizes an exploratory mixed-method design, combining thematic analysis—from expert interviews and document reviews—with interpretive structural modeling (ISM). The study targets market regulation experts, selected through purposive sampling, as the statistical population for both qualitative and quantitative phases. The data collection tools include semi-structured interviews and qualitative document analysis in the qualitative phase, and structured interpretive questionnaires in the quantitative phase.
Results
The model developed comprises seven levels, encompassing actor diversity, specialized and flexible human resources, and various functional domains of the network. These domains range from policy-making within the network to the legal and informational infrastructure, financial resource allocation, network strategy and orientation, multi-level control and oversight, market regulation network support, network policy cycles, and network management.
Conclusion
The diversity of network actors forms the foundation of the model, featuring specialized, semi-specialized, and indirectly influential institutions in market regulation. Specialized and flexible human resources are recognized as critical, positioned prominently within the model. Effective market regulation requires decision-makers who are well-versed in network dynamics and information and communication technology. The functional areas of the network, including supply, storage, distribution, logistics, commercial infrastructure, and pricing, are integral to the model. The formulation of both horizontal and vertical policies within network policy-making is crucial for cohesion and effectiveness. Legal and information technology infrastructures, alongside financial resources, form the third level, emphasizing the necessity for robust legal frameworks and technological connectivity among stakeholders. Financing strategies for the market regulation network must ensure timely and appropriate allocation of both local and foreign currency resources. The model places strategic direction and multi-level oversight near the top, advocating for a self-regulatory, bottom-up approach that fosters social dialogue and understanding. Government oversight remains paramount, with trade unions playing a supervisory role and public participation in field supervision. Policy cycles within the market regulation network should facilitate a clear division of labor, implementation, and rigorous monitoring at both national and provincial levels. Lastly, network management should focus on transparency and accountability among all actors. Additionally, network support must prioritize safeguarding against unauthorized access and cyber threats to maintain the integrity of market regulation network resources.