Technology Acceptance Model in U.S. Extension: CRM Adoption

QUALITATIVE INVESTIGATION OF TAM

technologies have come to the attention of CES professionals and administrators, and the

findings from this research may have implications for the adoption of future artificial intelligence

technologies. Additionally, the CES is not the only organization that can benefit from the

findings of this study. This study also provides important insights to software developers that are

engaging with institutions of higher education or other business sectors that may apply TAM to

enhance user experience testing functions within their organizations and software development.

CRM would assist both CES professionals and the clients they serve by co-creating value

between the client and the organization, tracking lifecycle engagement with CES services and

programs, and potentially resolve communications, marketing, and onboarding challenges for

CES educators, administrators, specialists, and agents. Evidence suggests that CRM technology

implementation could improve customer service interactions with clients, increase the perceived

value of CES programs, and strengthen relationships between an organization like the CES and

its clients.

Nature of Study

This phenomenological research investigates the TAM within the CES regarding the

adoption of CRM technologies. Qualitative data is curated through two primary tools: an analysis

of participant responses from a landscape assessment related to usage, adoption, and perceptions

of CRM technologies, and one-on-one interviews with CES professionals to further investigate

CRM usage in a variety of land-grant university Extension programs. This research is completed

over a three-month period to allow enough time to conduct interviews with CES professionals at

a variety of universities, including 1862, 1890, and 1994 land-grant colleges and universities. A

third-party survey analysis tool is used to review the recent landscape assessment, along with

conducting statistical analyses in Python. The one-on-one interviews are conducted over Zoom