Dissertation/Thesis Abstract

Perceived Value Technology Adoption Model for Accelerating Enterprise Transformation
by Estridge, Craig Steven, D.Engr., The George Washington University, 2018, 100; 10751934
Abstract (Summary)

Executives and directors are seeking to transform their enterprises into more efficient operations to achieve a competitive advantage and increase shareholder value. In addition, modern enterprises are deploying new technologies to attain the desired efficiencies inherently promised by technology advancements. However, the transformation and technology adoption results vary considerably between failure and success. Therefore, to identify an efficient and consistent method for guiding transformation efforts, we conducted a literature review of the technology adoption models, enterprise transformations, systems of systems, and human factors to identify efforts directed at integrating these research areas. This holistic approach guided the research method in which we subsequently conducted a qualitative action research case study to identify the influencers of technology adoption factors. The results of the case study identified the factors of human perception (salience, effort, expectancy, and value) are key influencers that accelerate technology adoption during the deployment phase similar to the application of human factors during the development phase of the technology lifecycle. These influencers generate perceived value for the technology and tools employed during enterprise transformations. Furthermore, we propose a model for using technological capabilities to enhance enterprise transformations based on context, process-based work instructions, work-instruction-based training, and subject-matter-expert desk-side support. Consequently, we determined that this perceived value technology adoption model should be a preferred tool for new technology deployments in addition to updating existing deployed technology for increased value that can be leveraged for lasting enterprise transformations.

Indexing (document details)
Advisor: Islam, Muhammad, Boyd, Robert
Commitee: Etemadi, Amirhossein, Malalla, Ebrahim
School: The George Washington University
Department: Engineering Management
School Location: United States -- District of Columbia
Source: DAI-B 79/08(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Engineering, Information science, Systems science
Keywords: Enterprise transformation, Human factors, Systems of systems, Technology adoption model
Publication Number: 10751934
ISBN: 9780355828740
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