College of Computing and Digital Media Dissertations

Date of Award

Spring 4-11-2014

Degree Type


Degree Name

Doctor of Philosophy (PhD)


School of Computing

First Advisor

Norma Sutcliffe

Second Advisor

Adam Steele

Third Advisor

Yujong Hwang


Technology acceptance has been studied extensively within the IS discipline. The introduction of the technology acceptance model (TAM) has given researchers the opportunity to produce a vast body of knowledge; however, existing gaps within the technology acceptance literature warrant further investigation of these understudied areas. Namely, few if any have studied end users’ acceptance of newly implemented technologies within organizational contexts before end-users start using the technology. Additionally, leadership is one of the areas that has not yet been sufficiently integrated with the technology acceptance literature. The Leader-Member Exchange (LMX) theory with its roots in the social exchange theory offers us an opportunity to investigate an overlooked facet of the social influence processes, specifically, the role of the direct leader (i.e. supervisor) as it relates to technology acceptance. In this research LMX, which captures the quality of the relationship between employees and their supervisors, is introduced as a moderating variable for many of the research model’s relationships. Thus, by integrating variables from multiple relevant literatures, this research attempts to answer this research question:

Will the introduction of a richer model for technology acceptance in a mandatory adoption environment, specifically in the pre-implementation phase, allow us to capture and account for the complexities of organizational technology implementations?

The research model was tested in an organizational setting where a new Content Management System was being implemented. One of the study’s major findings is that it reveals a relatively different pattern of relationships between the variables within the context of this research. A majority of the hypotheses were supported and the model has displayed relatively large explanatory and predictive power. LMX’s moderating role also highlighted the important role that direct supervisors play in the acceptance process; support was found that LMX strengthens the relationship between supervisor influence and behavioral intention, Perceived Behavioral Control, Appropriateness, Perceived Usefulness, Valence, and Perceived Ease of Use.



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