Abstract
Increasing digitalization in individual, organizational and societal contexts provides significant opportunities and challenges for all types of organizations. The capability of recognizing opportunities provided by Information Technology has been indicated as a central precondition for successful digital transformation. Yet, this capability has never been a focal area within Information Systems Research and therefore lacks conceptual and methodological underpinnings. Utilizing a mixed methods approach, this cumulative dissertation investigates organizational recognition of IT-induced opportunities from conceptual, organizational, and individual viewpoints. The capability of recognizing IT-induced opportunities is found to be dependent on a set of interconnected factors spanning the individual domains of skills and attitudes as well as the organizational domains of normative, operative, tactical, and strategic structures and processes. A framework providing a generic and holistic description tool for the involved microprocesses is developed to provide conceptual underpinnings for the capability of recognizing IT-induced potential. On the organizational level, a prototypical method for supporting the recognition of IT-induced opportunities is constructed; furthermore, factors relevant to the capability of recognizing IT-induced opportunities are identified and structured in accordance with traditional management perspectives. Finally, on the individual level, characteristics constituting individual digital transformation readiness are identified, and measurement models for the construct are developed.
Original language | English |
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Supervisors/Reviewers |
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Publication status | Published - 2020 |
Fields of science
- 303026 Public health
- 305909 Stress research
- 102 Computer Sciences
- 102006 Computer supported cooperative work (CSCW)
- 102015 Information systems
- 102016 IT security
- 502007 E-commerce
- 502014 Innovation research
- 502030 Project management
- 501016 Educational psychology
- 602036 Neurolinguistics
- 501030 Cognitive science
- 502032 Quality management
- 502043 Business consultancy
- 502044 Business management
- 502050 Business informatics
- 503008 E-learning
- 509004 Evaluation research
- 301407 Neurophysiology
- 301401 Brain research
JKU Focus areas
- Digital Transformation