The Diffusion Process of Strategic Motivating Language: An Examination of the Internal Organizational Environment and Emergent Properties

Abstract

Motivating language (ML) is a leader oral-communication strategy which has been significantly linked to such positive employee outcomes as higher job performance, increased job satisfaction, lower intention to turnover, and decreased absenteeism. However, most ML research has not targeted an organizational system at multiple levels. In brief, we have not looked at how this beneficial form of communication is actually implemented throughout an organization, including at the CEO level. In response to this gap, our main goals were to identify robust hypotheses on ML diffusion for future empirical testing, better understand the emergent processes of ML adoption within an organization, and advance development of related theory. These goals were achieved through an agent-based simulation model, drawn from management, communication, and social network scholarship. More specifically, overview, design concepts, and details protocol and NetLogo software were applied to simulate ML diffusion among all leader levels within an organization. This model also captured the influences of predicted moderators, and results were then interpreted to create testable hypotheses. Findings suggest that top-leader oral language use and organizational culture have the most profound impact on ML diffusion, followed by rewards, with partial weak support for the effects of training, turnover, and time. Recommendations were also made for future research on this topic, especially for empirical tests.