About
22
Publications
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Introduction
Hi, I'm Timo Sturm, an assistant professor / candidate for habilitation at the Software & Digital Business Group, TU Darmstadt. I graduated with a Master's degree in information systems specialized in data & web science. Since 2019, I study AI's impact on organizations' knowledge and processes, data science & machine learning methods, and data-driven innovation and ideation processes. My work appeared in several renowned outlets, including MIS Quarterly, JSIS, and IEEE T-ITS.
Current institution
Additional affiliations
June 2019 - March 2023
February 2025 - May 2025
February 2023 - May 2023
Education
April 2019 - February 2023
Field of study
- Information Systems (Focus: The Impact of Machine Learning on Organizations)
September 2016 - March 2019
October 2012 - February 2016
Publications
Publications (22)
Introduction: Quantitative computed tomography (qCT) is an emergent technique for diagnostics and research in patients with chronic obstructive pulmonary disease (COPD). qCT parameters demonstrate a correlation with pulmonary function tests and symptoms. However, qCT only provides anatomical, not functional, information. We evaluated five distinct,...
The technical maturity of autonomous driving enables the discussion of beneficial use cases to leverage its full potential. In this paper, we target one such use case: Platooning is the efficient convoying of vehicles by making use of self-driving capabilities and inter-vehicle communication. Many advantages arise from grouping vehicles in platoons...
Artificial intelligence (AI) is increasingly deployed in organizations, allowing information systems (IS) to incorporate self-learning mechanisms. Machine learning (ML) is commonly used as the underlying technology, as it enables IS to derive patters from collected data and perform tasks that were previously reserved for humans. While organizations...
With the rise of machine learning (ML), humans are no longer the only ones capable of learning and contributing to an organization’s stock of knowledge. We study how organizations can coordinate human learning and ML in order to learn effectively as a whole. Based on a series of agent-based simulations, we find that, first, ML can reduce an organiz...
In today’s organizations, both humans and machine learning (ML) systems jointly form routines. Yet, we do not know much about the underlying reciprocal interplay between them, which complicates their effective coordination. Taking an organizational learning perspective, we study the dynamics of human learning and ML to understand how organizations...
Although robo-advisors offer potential benefits for enhancing investment decisions, financial decision-makers remain reluctant to utilize advice from robo-advisors, a form of artificial intelligence designed to convey newfound investment insights in a particularly intuitive way. To increase robo-advice utilization, numerous scholars have investigat...
Culture is fundamental to our society, shaping the traditions, ethics, and laws that guide people's beliefs and behaviors. At the same time, culture is also shaped by people-it evolves as people interact and collectively select, modify, and transmit the beliefs they deem desirable. As artificial intelligence (AI) becomes more integrated into our li...
In order to achieve high-quality software, organizations use code reviews as an established quality assurance instrument in software development. With GenAI, organizations get the possibility to improve the time-consuming and cognitively demanding process of code review by assisting code reviewers with defect and improvement suggestions. As tools t...
Organizations must constantly align their operations with their environment in order to survive. To achieve this, organizations use two primary strategies: Organizations (1) learn about their environment to adapt to it and (2) enact their environment to adapt it to their own needs. With the rise of artificial intelligence (AI), humans are no longer...
Häufig wird argumentiert, dass Sprachmodelle im Laufe der Zeit immer besser und potentielle Schwachstellen bald ausgeräumt werden. Dies ist nur zum Teil richtig – in Zukunft werden neue Herausforderungen auf uns zukommen. Verfügbar unter: https://www.faz.net/pro/digitalwirtschaft/kuenstliche-intelligenz/wenn-kuenstliche-intelligenz-krank-wird-19902...
I. PURPOSE:
We aim to help better understand how organizations can develop their human capital in virtual teams through technological advances in the metaverse. To this end, we examine how virtual team collaboration with virtual reality technologies in the metaverse compares to traditional videoconferencing. Our study demonstrates how the metaverse...
Research has long underscored the critical role of effective team collaboration in surpassing the limits of individual members' capabilities. With organizations now increasingly integrating artificial intelligence (AI) as quasi-team members to enhance learning, problem-solving, and decision-making in teams, there is a pressing need to understand ho...
This paper explores the application of virtual reality (VR) technologies in the metaverse for team collaboration, focusing on its advantages over traditional videoconferencing. We examine the opportunities the metaverse offers for virtual teams' collaborative tasks and the factors that enable effective team collaboration. A lab experiment comparing...
Machine learning (ML) analyses offer great potential to craft profound advice for augmenting managerial decision-making. Yet, even the most promising ML advice cannot improve decision-making if it is not utilized by decision makers. We therefore investigate how ML analyses influence decision makers' utilization of advice and resulting decision-maki...
Organizational learning is a fundamental process that defines organizational behavior and thereby strongly influences organizational performance. As organizations increasingly adopt machine learning (ML) systems in their routines, the need to illuminate the impact of learning machines on organizational learning processes becomes increasingly urgent...
The metaverse is a virtual world that merges physical, virtual, and augmented reality, enabling collaboration between online users and offering limitless opportunities for connectivity and integration. While the metaverse has gained significant attention in organizations, it presents social challenges as organizations have unprecedented insight and...
To make sense of their increasingly digital and complex environments, organizations strive for a future in which machine learning (ML) systems join humans in collaborative learning partnerships to complement each other's learning capabilities. While these so-called artificial assistants enable their human partners (and vice versa) to gain insights...
To achieve great performance and ensure their long-term survival, organizations must successfully act in and adapt to the reality that surrounds them, which requires organizations to learn effectively. For decades, organizations have relied exclusively on human learning for this purpose. With today’s rise of machine learning (ML) systems as a moder...
The recent advent of artificial intelligence (AI) solutions that surpass humans’ problem-solving capabilities has uncovered AIs’ great potential to act as new type of problem solvers. Despite decades of analysis, research on organizational problem solving has commonly assumed that the problem solver is essentially human. Yet, it remains unclear how...
