Now showing 1 - 10 of 56
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Best Fit in Context: an Analysis of the Target-Specific Application of Agile Project Management Practices

2023-05-24 , Jasmin Schmid , Maël Schnegg , Klaus Möller

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Beyond Pay for Performance – Change enough or don’t change at all

2022-12-15 , Schnegg, Maël , Solbach, Jonas , Möller, Klaus

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The Use of a Management Control System to Enhance the Perception of Meaningful Work – A Bibliometric Analysis and Literature Review

2021-05-27 , Burghardt, Janine , Möller, Klaus

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Strategies for Data Analytics projects in Business Performance Forecasting: A Multiple Case Study

2021 , Schnegg, Maël , Möller, Klaus

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Identifying and Overcoming Organization and Ethical Barriers to AI Adoption

2023-05-26 , Richard Sentinella , Elita Sabani , Maël Schnegg , Klaus Möller

Technology companies are leading the pack in the use of Artificial Intelligence (AI) and other industries are taking advantage of AI to streamline processes and increase competitive advantage. On the way to implementing AI, organizations face ethical and organizational obstacles, which this study identifies through a structured literature review. It identifies six general ethical barriers to AI adoption, i.e., human well-being, trust, fairness, transparency, oversight & regulation, and accountability and four organizational barriers, i.e., resources, governance, culture, and employee intention to use AI. The study then examines two AI organizational governance frameworks and discusses how they might be useful in overcoming the barriers.

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A Management Control oriented Governance Framework for Artificial Intelligence

2022-11-07 , Sentinella, Richard , Schnegg, Maël , Möller, Klaus

In an age of increasing access to and power of artificial intelligence (AI), ethical concerns, such as fairness, transparency, and human well-being have come to the attention of regulators, standard setting bodies, and organizations alike. In order to build AI-based systems that comply with new rules, organizations will have to adopt systems of governance. This study develops, based on existing frameworks and a multiple case study, a governance framework specifically designed with these challenges in mind: The St. Gallen Governance Framework for Artificial Intelligence focuses on identifying stakeholder concerns and strategic goals, building a management control system, assigning roles and responsibilities, and incorporating dynamism into the system of governance.

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The design and use of performance management systems in rapid growth ventures

2021 , Engelhardt, Philipp , Möller, Klaus , Schnegg, Maël

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Control Configurations and Organizational Learning: The Impact of Environmental Uncertainty

2022-05 , Möller, Klaus , Schmid, Flavia , Verbeeten, Frank

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Meaningful work through formal controls? The use of the levers of control and the tendency to be innovative

2021-03-01 , Burghardt, Janine , Möller, Klaus

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Augmented Intelligence in Cash Forecasting: Optimizing the Human-Machine Interaction in Machine Learning based Forecasting

2021-11-17 , Michael Weiser , Möller, Klaus