Now showing 1 - 10 of 57
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Navigating Uncertainty: Human vs. Algorithmic Forecasting Approaches in Times of Crisis

2024-03-01 , Alessandra Huydts , Klaus Möller

Forecasting plays a pivotal role in effective operational management, providing critical insights for decisiForecasting plays a pivotal role in effective operational management, providing critical insights for decision-makers. This study investigates the impact a crisis has on short-term forecasting performance, comparing human and algorithmic approaches. Drawing on data from a Swiss automotive distributor, the research distinguishes between four crisis types, where we focus on external sudden and external smoldering crises. Employing a mixed-method sequential explanatory research design, we find that algorithmic forecasts outperform human forecasts. Furthermore, variations in forecasting accuracy are observed across the different crisis situations. We find that independent of the specific business situation, overall, algorithmic forecasts outperform human forecasts. This study contributes valuable insights into the effectiveness of different forecasting methods in diverse crises, enhancing decision-making knowledge and resilience in times of uncertainty.on-makers. This study investigates the impact a crisis has on short-term forecasting performance, comparing human and algorithmic approaches. Drawing on data from a Swiss automotive distributor, the research distinguishes between four crisis types, where we focus on external sudden and external smoldering crises. Employing a mixed-method sequential explanatory research design, we find that algorithmic forecasts outperform human forecasts. Furthermore, variations in forecasting accuracy are observed across the different crisis situations. We find that independent of the specific business situation, overall, algorithmic forecasts outperform human forecasts. This study contributes valuable insights into the effectiveness of different forecasting methods in diverse crises, enhancing decision-making knowledge and resilience in times of uncertainty.

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The Impact of Controls on Collaboration and Motivation in Sales Teams

2023-09 , Sophie Stopp , Janine Burghardt , Klaus Möller

This paper investigates the design and use of two management control types, namely behavior activity control (BAC) and behavior capability control (BCC), to optimize the performance of salespeople working in teams. We examine the effect of these control types on social climate (intrateam collaboration) and individual behavior (motivation, work effort) by drawing on social psychological (Stewardship Theory) and individual psychological (Self-Determination Theory) theories. Based on a large cross-sectional survey in a global company (n = 502), our results confirm that BAC increases salespeople ́s work effort while BCC enhances intrateam collaboration climate and motivation, and thus, both controls need to be combined. The study contributes to prior management control research by considering social ties and social psychological aspects.

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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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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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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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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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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