The critical need for access to network technology resources supporting advanced tools of academics and research is evident across disciplines and locations around the world. As research conducted by and in partnership with higher education institutions continues to increase in demand, it is incumbent on institutions to ensure the resources for this work are available as standard features for their faculty and students. The purpose of this study was to identify opinions of end users on the challenges to adoption of research and education (R&E) network resources at their local higher education institutions. The intent is to inform the R&E community about these challenges and to consider them when planning for the life cycle of network design and deployment. Study participants represented Information Technology (IT) leadership at 23 higher education institutions located within a regional R&E network consortium. Q methodology was applied to an established technology adoption model, the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, G. Davis, F. Davis, 2003) and informed by Rogers’ (2003) theory on the diffusion of innovations. The UTAUT model was modified to address attitudes toward technology resources enabled through access to R&E networks. Statistical analysis of the Q-sort data and examination of additional qualitative data were completed on data collected in this study. The combined methods served to identify factors based on the most prominent characteristics of each group and interpreted in alignment to the study framework. Results demonstrated the diversity of institutions and locations represented. Salient viewpoints expressed by respondents implied themes related to the value of a collegial environment within which to develop and deploy new projects, the critical need for institutional capacity and support, and the challenges of accessing and use of network resources. Theory can benefit from these results as a resource for exploring further modification of the initial UTAUT model to include technologies and audiences not previously included. Practitioners will benefit through reference to the findings when planning for the human and technological infrastructure capacity needed to support research and academic at their institutions.