Formation of a cluster model of stakeholders taking into account the interdependence of interests, resources, and influences

Abstract

The formation of a stakeholder cluster model in construction development is a key stage in creating a management system based on the interdependence of interests, resources, and influences. In today’s environment of complexity and dynamism in development processes, traditional hierarchical management approaches are losing effectiveness, giving way to network-based models built on the principles of complementarity and mutual balance. The cluster model ensures the integration of participants in the construction process into a unified system, where the efficiency of interaction is determined not only by the distribution of resources but also by the structure of communications, the level of trust, and the alignment of interests. The foundation of cluster formation is the vector model of multidimensional stakeholder positioning in the I–R–V space (Interests – Resources – Influences). Its application makes it possible to determine the degree of interdependence between actors and identify potential zones of instability. Each cluster functions as an adaptive subsystem with its own management logic, depending on the dominant type of connections – resource-based, interest-based, or political. Determining the threshold limits of interaction helps to prevent destabilization and maintain dynamic equilibrium within the system.

Particular attention is given to the concept of resource complementarity, according to which stability is achieved through the mutual balancing of deficits. Stakeholders are viewed not as autonomous actors but as interconnected nodes of exchange, where one participant’s resource compensates for another’s shortage. This approach promotes a shift from competition to cooperation, which is critically important for enhancing the resilience of development clusters. Additionally, the model considers the dynamic aspect – the changing roles of stakeholders depending on the project phase. This ensures adaptation to external environmental changes and maintains institutional flexibility. The use of formalized interaction indicators (Ψ, Ω, Θ) allows for the quantitative assessment of connectivity levels and the identification of critical coordination points. The integration of these parameters into the management system creates a self-regulating mechanism that enables the prediction of network tension and its timely mitigation.

The proposed cluster model combines mathematical analytical tools with the managerial logic of modularity, making it an effective instrument for strategic planning under uncertainty. It provides a balance between centralized control and decentralized initiative, creating the preconditions for sustainable industry development and strengthening the competitiveness of development systems.