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

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

Guardat en:
Dades bibliogràfiques
Autor principal: Marz, David
Format: eBook
Idioma:English
Publicat: Göttingen : Cuvillier Verlag, 2021.
Col·lecció:Göttinger Wirtschaftsinformatik.
Matèries:
Information technology > Psychological aspects.
Information technology > Social aspects.
Information technology > Psychological aspects
Information technology > Social aspects
Accés en línia:Click for online access
Taula de continguts:
  • 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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