Technology Acceptance in the Context of Digital Transformation Studies on How and Why People Use Connected Objects.

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Marz, David
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Göttingen : Cuvillier Verlag, 2021.
Colección:Göttinger Wirtschaftsinformatik.
Temas:
Information technology > Psychological aspects.
Information technology > Social aspects.
Technologie de l'information > Aspect psychologique.
Technologie de l'information > Aspect social.
Information technology > Psychological aspects
Information technology > Social aspects
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • List of Figures
  • List of Tables
  • Acronyms
  • A. Foundation
  • I. Introduction
  • I.1 Motivation
  • I.2 Research Agenda
  • I.3 Structure of the Dissertation
  • I.4 Research Context and Design
  • I.5 Contributions
  • II. Theoretical Background
  • II.1 Widespread Diffusion of Digital, Connected Objects
  • II.2 Digital Life
  • II.3 Technology Acceptance
  • B. Exploring Technology Acceptance in the Context of Digital Transformation
  • I. Setting the Context: Digital Transformation
  • 1 Study 1: A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change
  • 1.1 Introduction
  • 1.2 Research Design
  • 1.3 Findings
  • 1.4 Discussion of Findings
  • 1.5 Implications
  • 1.6 Conclusion
  • 1.7 Appendix A: Research Matrix
  • Contextual Conditions
  • 1.8 Appendix B: Research Matrix
  • Mechanisms
  • 1.9 Appendix C: Research Matrix
  • Outcomes
  • II. Studies on Individual Behavior in the Digital Age
  • 1 Study 2: Digital Connectedness Expectancy: Construct Development and Scale Validation
  • 1.1 Introduction
  • 1.2 Theoretical Background
  • 1.3 Methodology
  • 1.4 Discussion
  • 1.5 Appendix A: Items Used in the Questionnaires
  • 1.6 Appendix B: Sample Characteristics
  • 2 Study 3: A Needs-Affordances-Satisfaction Perspective on the Use of Connected Objects
  • 2.1 Introduction
  • 2.2 Conceptual Framework
  • 2.3 Theory and Hypotheses
  • 2.4 Methodology
  • 2.5 Data Analysis and Results
  • 2.6 Discussion of Findings
  • 2.7 Implications
  • 2.8 Limitations and Avenues for Future Research
  • 2.9 Appendix A: Survey Items Used in Questionnaires
  • 2.10 Appendix B: Sample Characteristics
  • 3 Study 4: Handling the Efficiency-Personalization Trade-Off in Service Robotics: A Machine-Learning Approach
  • 3.1 Introduction
  • 3.2 Background
  • 3.3 Research Setting
  • 3.4 A Division-of-Labor Application for Resolving the Efficiency- Personalization Trade-Off in Autonomous Vehicles
  • 3.5 Evaluation
  • 3.6 Discussion and Implications
  • 3.7 Appendix A: Additional Empirical Study on the Efficiency-Personalization Trade-Off
  • 3.8 Appendix B: Literature Review on Big Data Analytics and Autonomous Vehicles
  • 3.9 Appendix C: Vehicle Data and Preprocessing
  • 3.10 Appendix D: Tuning LSTM Hyperparameters
  • 3.11 Appendix E: Details Regarding the Evaluation of the Prediction Modules Using the Carsharing Data Set
  • 3.12 Appendix F: Variables used for Personalization in Prior Studies
  • C. Contributions
  • I. Findings
  • I.1 Summary of Findings
  • I.2 Synthesis of Findings: A Framework for the Study of Connected Objects
  • II. Implications, Limitations and Opportunities for Future Research
  • II.1 Implications for Research
  • II.2 Implications for Practice
  • II.3 Limitations
  • II.4 Opportunities for Future Research
  • III. Concluding Remarks

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