Dyadic Communication Relationships in Organizations: An Attribution/Expectancy Approach

Research in organizational communication has examined the structure and content of interaction, but has paid little attention to research traditions outside the organizational sciences that explore the social-psychological interconnections between relationship development and interaction. In this paper we draw upon and extend those traditions to develop a model of how communication relationships develop within organizational dyads. The proposed model examines organization-based communication relationships through a synthesis of theoretical perspectives on communication relational communication, interpersonal attribution, and social expectancy. We also call upon precepts of structuration theory to embed these microlevel processes in an organizational context.The relational outcome in the model is interactional richness, a dyad-level construct that assesses the extent to which communication within the dyad is high in shared meaning. Model antecedents are aspects of interaction through which communicators reciprocally define their relationships, including relational message properties, message patterns that emerge over time, and relational perceptions. We propose that these communication properties and behaviors give rise to relationship attributions. We then incorporate processes of expectancy confirmation and violation to explain how specific communication encounters lead individuals to reformulate attributions regarding the status of a given relationship. Research propositions articulate how attribution/expectancy processes mediate between relational communication behavior and relationship development outcomes. We also develop propositions addressing how relational communication behavior is influenced by macrolevel factors, including hierarchy, structure, and culture.In a concluding section we discuss the model's potential contribution to research and practice, address its limitations, and offer recommendations for future research aimed at testing its embedded hypotheses.