The Relational Algorithm: Axiomatizing the Divergent Social Calculus of Trust in Collectivist and Individualist Market Ontologies

Abstract

Global brands incur annual losses of around $23 billion due to culturally incompatible trust practices, as demonstrated by Uber's contractual misalignment in China's guanxi-centric markets. This ongoing insufficiency highlights a significant theoretical void: cross-cultural marketing lacks a foundational framework that elucidates ontological differences in the formation of trust. This study employs ethnographic fieldwork (n = 42 industry experts), agent-based computer modelling, and discrete-choice experiments (DCEs; n = 1,200 participants across 4 markets) to address the issue. Findings indicate that trust functions through incommensurable cultural relational algorithms individualistic contractarian principles vs collectivist contextualist principles. Violating these ontological principles diminishes purchase intent by 38–61% (hierarchical Bayesian estimation, 95% HDI), highlighting the behavioral repercussions of infringing ontological expectations. This paper proposes a new axiomatic framework for market ontology that facilitates the algorithmic adaptation of trust methods across cultural barriers. The framework provides a theoretically informed method for mitigating relational friction in international trade, with clear implications for market entry strategy, partnership formation, and platform management.