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Higher education institutions (HEIs) rely heavily on information technology (IT) to create innovations. Therefore, IT governance (ITG) is essential for education activities, particularly during the ongoing COVID-19 pandemic. However, the traditional concept of ITG is not fully equipped to deal with the current changes occurring in the digital age. Today's ITG requires an agile approach that can respond to disruptions in the HEI environment. Consequently, universities increasingly need to adopt agile strategies to ensure superior performance. This research proposes a conceptualization comprising three agile dimensions within the ITG construct: structures, processes, and relational mechanisms. An extensive qualitative evaluation of industry uncovered 46 agile governance mechanisms. Moreover, 16 professors rated these elements to assess agile ITG in their HEIs to determine those most effective for HEIs. This led to the identification of four structure elements, seven processes, and seven relational mechanisms.
The question of why individuals adopt information technology has been present in the information systems research since the past quarter century. One of the most used models for predicting the technology usage was introduced by Fred David: The Technology Acceptance Model (TAM). It describes the influence of perceived usefulness and perceived ease of use on attitude, behavioral intention and system usage. The first two mentioned factors in turn are influenced by external variables. Although a plethora of papers exists about the TAM , an extensive analysis of the role of the external variables in the model is still missing. This paper aims to give an overview ove the most important variables. In an extensive literature review, we identified 763 relevant papers, found 552 unique single extenal variables, characterized the most important of them, and described the frequency of their appearance. Additionally, we grouped these variables into four categories (organizational characteristis, system characteristics, user personal characteristics, and other variables). Afterwards we discuss the results and show implications for theory and practice.