Business Analytics
BackPublishing Opportunities in Leading Journals
Selected papers of the ECIS 2026 Business Analytics track will be invited for fast-track options in the Journal of Business Analytics. In addition, submissions are relevant to many regular issues of IS and OR journals such as Decision Support Systems, Journal of Decision Systems, European Journal of Operational Research, or BISE (Business & Information Systems Engineering) but can also be relevant for IS basket journals.
In the past, we have successfully published a special issue with selected papers from our ECIS track in the Journal of Business Analytics and we are regularly in contact with the Editors-in-Chief of the journal.
Track Chairs
Patrick Zschech
TUD Dresden University of Technology, Germany
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Patrick Zschech is a Professor of Business Information Systems, esp. Intelligent Systems and Services at TU Dresden. Prior to this role, he held academic positions as an Associate Professor at Leipzig University, an Assistant Professor at FAU Erlangen-Nürnberg, and a postdoctoral researcher at TU Dresden, where he also received his PhD. Alongside his academic pursuits, he gained industry experience at Robotron Datenbank-Software GmbH, working as a developer and instructor in data science qualification programs. Patrick’s research focuses on business analytics, (interpretable) machine learning, and artificial intelligence, with particular emphasis on the analysis, design, and evaluation of intelligent information systems. His work has been published in leading IS and OR journals, including Decision Support Systems, Business & Information Systems Engineering, Health Care Management Science, European Journal of Operational Research, and Electronic Markets, and has been presented at major international conferences such as ICIS, ECIS, and HICSS.
Barbara Dinter
Chemnitz University of Technology, Germany
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Barbara Dinter is Professor and Chair of Business Information Systems at Chemnitz University of Technology, Germany. She holds a Ph.D. in Computer Science from the Technische Universität München. Her research interests include business intelligence and analytics, big data, data driven innovation, and information management. Barbara has published in renowned journals such as DSS, JDM, and JDS and at conferences like ICIS, ECIS, and HICSS. She has chaired the BA/BI track at ECIS for more than ten years, as well as (mini-) tracks at HICSS, AMCIS, IEEE CBI, International Conference on Wirtschaftsinformatik, etc. She also acted as Conference Co-Chair at a Pre-ICIS SIGDSA Workshop.
Ciara Heavin
University College Cork, Ireland
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Ciara Heavin is Professor of Business Information Systems at Cork University Business School, University College Cork, Ireland. Her research focuses on opportunities for using information systems (IS) in the global healthcare ecosystem and in digital transformation. Ciara has published articles in several top international IS journals and conference proceedings. She has co-authored three books with Daniel J. Power: Decision Support, Analytics, and Business Intelligence, Data-Based Decision Making and Digital Transformation, and Becoming Agile.
Patrick Mikalef
Norwegian University of Science and Technology, Norway
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Patrick Mikalef is a Professor in Data Science and Information Systems at the Department of Computer Science. In the past, he has been a Marie Skłodowska-Curie post-doctoral research fellow working on the research project “Competitive Advantage for the Data-driven Enterprise” (CADENT). He received his B.Sc. in Informatics from the Ionian University, his M.Sc. in Business Informatics for Utrecht University, and his Ph.D. in IT Strategy from the Ionian University. His research interests focus on strategic use of information systems and IT-business value in turbulent environments. He has published work in international conferences and peer-reviewed journals including the Journal of Business Research, British Journal of Management and Information and Management.
In an era defined by rapid digital transformation, organizations increasingly rely on business analytics to navigate complex environments, enhance decision-making, and drive innovation. Business analytics encompasses the methods, processes, technologies, skills, and organizational capabilities required to analyze past and present data in order to manage and shape future performance. It is inherently forward-looking, centering on diagnostic, predictive, and prescriptive insights that inform action.
Aligned with the conference theme, “Re-imagining Digital Technology for Business, Management, and Society,” this track explores how business analytics can be re-imagined supporting ethical, sustainable, and human-centered outcomes. As emerging digital technologies—such as artificial intelligence (AI), the Internet of Things (IoT), blockchain, digital twins, and quantum computing—reshape the business landscape, business analytics stands at the intersection of technological innovation and responsible decision-making. This track invites research that considers how business analytics can empower organizations and societies while maintaining a critical focus on transparency, accountability, and inclusiveness.
Recognizing that people are the ultimate stakeholders of digital transformation, this track emphasizes the importance of integrating human judgment, ethical reasoning, and contextual awareness into data-driven decision-making. A human-centered approach requires attention to fairness, privacy, and social impact, as well as a recognition of the limitations of purely algorithmic reasoning. At the same time, emerging agentic AI systems based on advanced generative models are reshaping the analytics landscape.
These systems can autonomously generate content, simulate decisions, and adapt to evolving contexts, thereby influencing how analytics insights are created and applied. Their integration into business analytics introduces both opportunities and challenges—particularly regarding explainability, governance, and the evolving role of human oversight. In this context, human-machine co-creation becomes increasingly relevant. The combination of human expertise—intuition, creativity, and ethical insight—with computational power and analytical efficiency can lead to more meaningful, responsible, and actionable outcomes.
We welcome interdisciplinary contributions that examine the organizational, technological, cultural, ethical, and societal dimensions of business analytics. Submissions may draw on a range of methodologies, including quantitative, qualitative, theoretical, design science, action, or behavioral research. In line with the conference theme, we particularly welcome papers that offer novel perspectives on re-imagining the role of business analytics in shaping responsible digital futures. Papers focused solely on AI and machine learning, without an explicit link to business analytics and human-centered concerns, are not the primary focus of this track.
Track topics
Suggested topics include, but are not limited to:
The role of business analytics and business intelligence in re-imagining digital futures
Human-centered and socially responsible approaches to business analytics- Human-machine collaboration and co-creation
- The role of agentic AI systems and generative models in shaping analytics practices
- Explainable and interpretable AI for comprehensible decision support
- Causal machine learning for prescriptive organizational decision-making
- Business analytics for human dignity, social good, empowerment, and digital responsibility
- Operational, real-time, and event-driven analytics
- Process mining and robotic process automation
- Analytics architectures and ecosystems
- Data literacy, data humanism, data harm, and the societal impact of datafication
- Privacy, data quality, transparency, and governance in data ecosystems
- Data-driven business model innovation, entrepreneurship, and platform ecosystems
- Challenges and opportunities in open data and data sharing
Track Associate Editors
Alexander Mädche, Karlsruhe Institute of Technology, Germany
Alexander Schilller, University of Regensburg, Germany
Ashish Gupta, Auburn University, USA
Ayushi Tandon, Trinity College Dublin, Ireland
Bernhard Lutz, University of Freiburg, Germany
Caddie Gao, Monash University, Australia
Christian Janiesch, TU Dortmund University, Germany
Christoph Flath, University of Würzburg, Germany
Cristina Trocin, Católica Porto Business School, Portugal
Dimitri Petrik, University of Stuttgart, Germany
Frederik Möller, TU Braunschweig, Germany
Greg Richards, University of Ottawa, Canada
Gunther Gust, University of Würzburg, Germany
Henning Baars, University of Stuttgart, Germany
Hippolyte Lefebvre, University College Dublin, Ireland
Huanhuan Xiong, University College Cork, Ireland
Imad Bani Hani, Halmstad University, Sweden
Ivo Blohm, University of St. Gallen, Switzerland
John Krogstie, Norwegian University of Science and Technology, Norway
Kai Heinrich, University of Magdeburg, Germany
Karoline Glaser, TU Dresden, Germany
Konstantin Hopf, Chemnitz University of Technology, Germany
Konstantina Valogianni, IE Business School, Spain
Laura Ruiz, University of Granada, Spain
Mathias Kraus, University of Regensburg, Germany
Maximilian Förster, University of Ulm, Germany
Natalia Kliewer, Universität Berlin, Germany
Niklas Kühl, University of Bayreuth, Germany
Nuno Laranjeiro, University of Coimbra, Portugal
Oliver Müller, University of Paderborn, Germany
Patrick Delfmann, University of Koblenz, Germany
Reda Hassan, Norwegian University of Science and Technology, Norway
Rogier van de Wetering, Open Universitat, Netherlands
Sambit Tripathi, Portland State University, USA
Sandra Zilker, Technische Hochschule Nürnberg Georg Simon Ohm, Germany
Sven Weinzierl, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Thomas Setzer, Catholic University of Eichstätt-Ingolstadt, Germany
Tobias Brandt, University of Münster, Germany
Tobias Mettler, University of Lausanne, Switzerland
Veeresh Thummadi, Dublin City University, Ireland
Willam Yeoh, Hong Kong Metropolitan University