Strategies for the Initiation Phase of IT Innovation Adoption
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Abstract
For decades, enterprises have to face transformational processes triggered by technological progress. At present, digital transformation and its effects are in the focus of companies in all industries. Compared to previous information technology enabled transformations, the digital transformation goes far beyond organization’s processes and changes enterprises, markets and society. The technological advances that are associated with this development present companies both game-changing opportunities and existential threats. New technologies are ubiquitous, available at low cost and can be applied and combined in various ways. Companies must therefore orient themselves in a multitude of technological possibilities and evaluate which technologies are most beneficial for them. Simultaneously, the digital transformation requires companies not only simply introduce new technologies, but also exploit them in innovative ways. Using the example of two current IT trends that reflect this development, this dissertation examines the research question of what approaches can be identified when organizations explore the potentials of IT driven innovations and what factors influence the choice of approach. Based on multiple case studies, it investigates how companies approach the adoption of big data and how cities adopt new technologies for smart services. Both trends are triggered by a large bundle of mostly similar technologies and methods. The diversity of new possibilities challenges organizations to identify and leverage the most valuable ones. In particular, the initiation phase, where organizations initially explore the manifold options of new technologies, poses a first serious obstacle. To study this in detail, two theories are used: The innovation adoption process of Rogers as a theoretical lens for the activities of organizations and the technology-organization-environment framework to structure decision criteria during innovation adoption. The results from the big data cases show that three different approaches exist: Companies start (1) with the identification of big data use cases considering only business aspects, (2) with a systematic build-up of a big data technology and data platform, (3) or with reducing data silos for traditional data analyses and a later systematic build-up of a big data platform. Two approaches could be recognized in the initiation phase of smart service adoption in cities: Smart city initiatives start either (1) with identifying use cases for smart services solving urban challenges or (2) with lowering the hurdles for the implementation of future use cases by a systematic build-up of a technological platform. Summing up the results, this thesis contributes to a better understanding of IT innovation adoption in the era of digitalization. Practitioners can compare and restructure their approaches for IT innovation adoption. Researchers gain insights into how innovation adoption is shaped by organizations and how innovation adoption theories can be applied to understand such phenomena.