Computational Foundations for Strategic Coopetition: Formalizing Sequential Interaction and Reciprocity

2026-03-29

AI Summary

This study addresses the unresolved question of how cooperative behavior persists over time in multi-stakeholder systems lacking enforceable contracts. The authors propose a computational framework that integrates i* conceptual modeling with game-theoretic reciprocity analysis to unify the characterization of sequential cooperation-competition dynamics in both human and multi-agent systems. The framework incorporates bounded reciprocity response functions, finite memory windows, structural reciprocity sensitivity, and a trust-gating mechanism. Evaluated across 15,625 configuration settings, it achieves full compliance on six behavioral metrics and demonstrates 84.3% validation accuracy (p < 0.001, Cohen’s d = 1.57) in the Apple App Store ecosystem, significantly outperforming baseline approaches.

Abstract

Strategic coopetition in multi-stakeholder systems requires understanding how cooperation persists through time without binding contracts. This technical report extends computational foundations for strategic coopetition to sequential interaction dynamics, bridging conceptual modeling (i* framework) with game-theoretic reciprocity analysis. We develop: (1) bounded reciprocity response functions mapping partner deviations to finite conditional responses, (2) memory-windowed history tracking capturing cognitive limitations over k recent periods, (3) structural reciprocity sensitivity derived from interdependence matrices where behavioral responses are amplified by structural dependencies, and (4) trust-gated reciprocity where trust modulates reciprocity responses. The framework applies to both human stakeholder interactions and multi-agent computational systems. Comprehensive validation across 15,625 parameter configurations demonstrates robust reciprocity effects, with all six behavioral targets exceeding thresholds: cooperation emergence (97.5%), defection punishment (100%), forgiveness dynamics (87.9%), asymmetric differentiation (100%), trust-reciprocity interaction (100%), and bounded responses (100%). Empirical validation using the Apple iOS App Store ecosystem (2008-2024) achieves 43/51 applicable points (84.3%), reproducing documented cooperation patterns across five ecosystem phases. Statistical significance confirmed at p < 0.001 with Cohen's d = 1.57. This report concludes the Foundations Series (TR-1 through TR-4) adopting uniaxial treatment where agents choose cooperation levels along a single continuum. Companion work on interdependence (arXiv:2510.18802), trust (arXiv:2510.24909), and collective action (arXiv:2601.16237) has been prepublished. Extensions Series (TR-5 through TR-8) introduces biaxial treatment where cooperation and competition are independent dimensions.

Problem

• strategic coopetition
• sequential interaction
• reciprocity
• multi-stakeholder systems
• cooperation persistence

Innovation

• strategic coopetition
• sequential reciprocity
• bounded response functions
• memory-windowed history
• trust-gated reciprocity