Dyadic communication relationships in organizations: An attribution/expectancy approach

Research in organizational communication has examined the structure and con tent of interaction, but has paid little attention to research traditions o utside the organizational sciences that explore the social-psychological in terconnections between relationship development and interaction. In this pa per we draw upon and extend those traditions to develop a model of how comm unication relationships develop within organizational dyads. The proposed m odel examines organization-based communication relationships through a synt hesis of theoretical perspectives on communication richness, relational com munication, interpersonal attribution, and social expectancy. We also call upon precepts of structuration theory to embed these microlevel processes i n an organizational context. The relational outcome in the model is "interactional richness," a dyad-lev el construct that assesses the extent to which communication within the dya d is high in shared meaning. Model antecedents are aspects of interaction t hrough which communicators reciprocally define their relationships, includi ng relational message properties, message patterns that emerge over time, a nd relational perceptions. We propose that these communication properties a nd behaviors give rise to relationship attributions. We then incorporate pr ocesses of expectancy confirmation and violation to explain how specific co mmunication encounters lead individuals to reformulate attributions regardi ng 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 proposition s addressing how relational communication behavior is influenced by macrole vel factors, including hierarchy, structure, and culture. In a concluding section we discuss the model's potential contribution to re search and practice, address its limitations, and offer recommendations for future research aimed at testing its embedded hypotheses.