Klaus Möller

Klaus Möller

Title

Prof. Dr.

Last Name

Möller

First name

Klaus

Email

klaus.moeller@unisg.ch

Phone

+41 71 224 7406

Homepage

http://www.aca.unisg.ch

Now showing 1 - 10 of 56

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

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/118768
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.

Type: conference paper

Journal: 1ST INTERDISCIPLINARY CONFERENCE ON MANAGEMENT, INFORMATION TECHNOLOGY AND COMPUTER SCIENCES

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/117428
Control Configurations and Organizational Learning: The Impact of Environmental Uncertainty

( 2022-05)
Möller, Klaus
;
Schmid, Flavia
;
Verbeeten, Frank

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/108769
Beyond Pay for Performance – Change enough or don’t change at all

( 2022-12-15)
Schnegg, Maël
;
Solbach, Jonas
;
Möller, Klaus

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/107970
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.

Type: conference paper

Journal: EIASM WORKSHOP ON GOVERNANCE AND MANAGEMENT OF DIGITALIZATION

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/108096
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

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/110602
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

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/110386
The design and use of performance management systems in rapid growth ventures

( 2021)
Engelhardt, Philipp
;
Möller, Klaus
;
Schnegg, Maël

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/110951
Strategies for Data Analytics projects in Business Performance Forecasting: A Multiple Case Study

( 2021)
Schnegg, Maël
;
Möller, Klaus

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/111316
Augmented Intelligence in Cash Forecasting: Optimizing the Human-Machine Interaction in Machine Learning based Forecasting

( 2021-11-17)
Weiser, Michael
;
Möller, Klaus

Type: conference paper

URI: https://www.alexandria.unisg.ch/handle/20.500.14171/109719

Klaus Möller

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