{"id":{"repo_id":"vcu","oai_identifier":"oai:scholarscompass.vcu.edu:etd-1883"},"canonical_url":"https://search.dev.ndltd.org/etd/vcu/oai:scholarscompass.vcu.edu:etd-1883","repository":{"repo_id":"vcu","name":"Virginia Commonwealth University","base_url":"https://scholarscompass.vcu.edu/do/oai/"},"display":{"title":"Rebuilding Theories of Technology Acceptance: A Qualitative Case Study of Physicians' Acceptance of Technology","abstract":"The Technology Acceptance Model has been widely applied and has been quite successful at explaining the behavioral intention to use technology in many organizations. One of the most significant variables in the Technology Acceptance Model is perceived ease of use. The Technology Acceptance Model purports that perceived ease of use contributes to the behavioral intention to use technology. Additionally, the model purports that perceived ease of use is an antecedent of perceived usefulness. In the adoption and use of technology by physicians, previous studies show that the Technology Acceptance Model predictions have been incorrect. Specifically, the aforementioned perceived ease of use prediction is not repeatedly supported in health care environments. In order to further investigate and ultimately explain this abnormality in the Technology Acceptance Model's predictive ability in the health care industry, a positivist case study using various coding techniques was conducted to investigate physicians' behavioral intention to use a Personal Digital Assistant in their work environment. The Physicians' Technology Acceptance Model is a major result of this case study. The Physicians' Technology Acceptance Model, which is based on the Extended Technology Acceptance Model (Venkatesh et al. 2000), is absent of the perceived ease of use construct and includes two additional constructs: perceived substitution, which is defined as, \"the degree to which an individual perceives that alternate sources are available to deliver the same information or assistance as the technology in question\" and facilitating conditions (Venkatesh et al. 2003) , which is defined as, \"the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system\" (p. 453). This organizational case study rigorously follows a positivist approach (\"natural-science model\" of social-science research (Lee 1989b)).","abstract_html":"The Technology Acceptance Model has been widely applied and has been quite successful at explaining the behavioral intention to use technology in many organizations. One of the most significant variables in the Technology Acceptance Model is perceived ease of use. The Technology Acceptance Model purports that perceived ease of use contributes to the behavioral intention to use technology. Additionally, the model purports that perceived ease of use is an antecedent of perceived usefulness. In the adoption and use of technology by physicians, previous studies show that the Technology Acceptance Model predictions have been incorrect. Specifically, the aforementioned perceived ease of use prediction is not repeatedly supported in health care environments. In order to further investigate and ultimately explain this abnormality in the Technology Acceptance Model's predictive ability in the health care industry, a positivist case study using various coding techniques was conducted to investigate physicians' behavioral intention to use a Personal Digital Assistant in their work environment. The Physicians' Technology Acceptance Model is a major result of this case study. The Physicians' Technology Acceptance Model, which is based on the Extended Technology Acceptance Model (Venkatesh et al. 2000), is absent of the perceived ease of use construct and includes two additional constructs: perceived substitution, which is defined as, "the degree to which an individual perceives that alternate sources are available to deliver the same information or assistance as the technology in question" and facilitating conditions (Venkatesh et al. 2003) , which is defined as, "the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system" (p. 453). This organizational case study rigorously follows a positivist approach ("natural-science model" of social-science research (Lee 1989b)).","abstract_has_math":false,"creators":["Blue, Jon T."],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Dissertation","degree_discipline":"Information Systems","degree_department":null,"school":null,"contributors":["Dr. Gurpreet Dhillon","Dr. Allen S. Lee"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2006,"date_issued":"2006-01-01T08:00:00Z","date_published":"2006-01-01T08:00:00Z","updated_at":"2026-07-24T05:54:30Z","subjects":["organizational case study","PDA","electronic medical record","clinical system","informatics","telemedicine","natural-science model","health care","Business","Management Information Systems"],"languages":[],"rights":["© The Author"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarscompass.vcu.edu/etd/884"],"render_values":[{"text":"https://scholarscompass.vcu.edu/etd/884","href":"https://scholarscompass.vcu.edu/etd/884","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.25772/4FQN-2216","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Gurpreet Dhillon","Dr. Allen S. 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One of the most significant variables in the Technology Acceptance Model is perceived ease of use. The Technology Acceptance Model purports that perceived ease of use contributes to the behavioral intention to use technology. Additionally, the model purports that perceived ease of use is an antecedent of perceived usefulness. In the adoption and use of technology by physicians, previous studies show that the Technology Acceptance Model predictions have been incorrect. Specifically, the aforementioned perceived ease of use prediction is not repeatedly supported in health care environments. In order to further investigate and ultimately explain this abnormality in the Technology Acceptance Model's predictive ability in the health care industry, a positivist case study using various coding techniques was conducted to investigate physicians' behavioral intention to use a Personal Digital Assistant in their work environment. The Physicians' Technology Acceptance Model is a major result of this case study. The Physicians' Technology Acceptance Model, which is based on the Extended Technology Acceptance Model (Venkatesh et al. 2000), is absent of the perceived ease of use construct and includes two additional constructs: perceived substitution, which is defined as, \"the degree to which an individual perceives that alternate sources are available to deliver the same information or assistance as the technology in question\" and facilitating conditions (Venkatesh et al. 2003) , which is defined as, \"the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system\" (p. 453). This organizational case study rigorously follows a positivist approach (\"natural-science model\" of social-science research (Lee 1989b))."]},{"key":"dc:title","label":"Title","values":["Rebuilding Theories of Technology Acceptance: A Qualitative Case Study of Physicians' Acceptance of Technology"]}]}],"canonical_facts":{"dc:contributor":["Dr. Gurpreet Dhillon","Dr. Allen S. Lee"],"dc:creator":["Blue, Jon T."],"dc:date.available":["2014-07-09T07:00:00Z"],"dc:description.abstract":["The Technology Acceptance Model has been widely applied and has been quite successful at explaining the behavioral intention to use technology in many organizations. One of the most significant variables in the Technology Acceptance Model is perceived ease of use. The Technology Acceptance Model purports that perceived ease of use contributes to the behavioral intention to use technology. Additionally, the model purports that perceived ease of use is an antecedent of perceived usefulness. In the adoption and use of technology by physicians, previous studies show that the Technology Acceptance Model predictions have been incorrect. Specifically, the aforementioned perceived ease of use prediction is not repeatedly supported in health care environments. In order to further investigate and ultimately explain this abnormality in the Technology Acceptance Model's predictive ability in the health care industry, a positivist case study using various coding techniques was conducted to investigate physicians' behavioral intention to use a Personal Digital Assistant in their work environment. The Physicians' Technology Acceptance Model is a major result of this case study. The Physicians' Technology Acceptance Model, which is based on the Extended Technology Acceptance Model (Venkatesh et al. 2000), is absent of the perceived ease of use construct and includes two additional constructs: perceived substitution, which is defined as, \"the degree to which an individual perceives that alternate sources are available to deliver the same information or assistance as the technology in question\" and facilitating conditions (Venkatesh et al. 2003) , which is defined as, \"the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system\" (p. 453). This organizational case study rigorously follows a positivist approach (\"natural-science model\" of social-science research (Lee 1989b))."],"dc:identifier":["https://doi.org/10.25772/4FQN-2216","https://scholarscompass.vcu.edu/etd/884"],"dc:rights":["© The Author"],"dc:subject":["organizational case study","PDA","electronic medical record","clinical system","informatics","telemedicine","natural-science model","health care","Business","Management Information Systems"],"dc:title":["Rebuilding Theories of Technology Acceptance: A Qualitative Case Study of Physicians' Acceptance of Technology"],"thesis:degree_discipline":["Information Systems"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T05:54:30Z"}