Each relational zone can be modeled as a state in a non-linear Markov process, with transition probabilities influenced by:
Historical trajectory and memory traces
Actor types and strategic tendencies
Perceived utility and moral framing
Institutional scaffolding and adaptive learning
This yields a six-state adaptive system, incorporating both micro-level dyadic relations and macro-level emergent structures.
Conclusion
By formalizing relational zones, the RZE framework offers a novel lens to reinterpret classical economic behaviors---from market entry to systemic collapse, from coalition formation to moral hazard. Unlike most existing models, it embeds trust, ambiguity, betrayal, andÂ
B. Interests and Zone Transitions as Strategic Parameters
In traditional economic and game-theoretic models, strategies are often viewed as static or dynamically optimized responses to exogenous payoffs under defined rules. However, such approaches frequently neglect the endogeneity of intent, the evolution of relational positioning, and the multi-layered temporality of decision-making under ambiguity. The Relational Zone Economics (RZE) framework advances this conversation by treating agent interests and zone transitions as central, dynamic parameters in strategic economic behavior.
1. Interests as Multidimensional Strategic Inputs
Rather than modeling agents as utility-maximizing entities operating on fixed or exogenously defined preferences, RZE considers interests as:
Temporally layered: encompassing both short-term incentives and long-term aspirations.
Context-sensitive: shaped by social norms, history of interaction, and structural environments.
Strategically malleable: subject to intentional modulation or concealment (e.g., in the Yellow Zone).
We formalize interests Ii(t)I_i(t) of agent ii at time tt as a vector:
Ii(t)=[is(t),il(t),(t)]I_i(t) = \left[ i_s(t), i_l(t), \theta(t) \right]
where:
