Tracks
Socio-technical Systems in Times of Artificial Intelligence
Artificial Intelligence (AI) is widely regarded as a 'general purpose technology' that fundamentally reshapes economic activity, organizational structures, and societal development. From an Information Systems perspective, the key question is not only how powerful AI technologies are, but how they are embedded in socio-technical systems and how this embedding transforms the role of humans within organizations.
As AI systems become increasingly autonomous, adaptive, and creative, their role shifts from supportive tools to active co-shapers of organizational processes and decisions. AI increasingly enters domains that traditionally required human judgment, experience, and moral-ethical reflection. This development raises fundamental questions regarding responsibility, agency, legitimacy, and control in hybrid human-AI systems.
While trust in AI has received considerable scholarly attention, the long-term transformation of the human role - particularly as a moral authority, decision-maker, and bearer of responsibility - remains insufficiently understood. Concepts such as 'Human-in-the-Loop' are often framed as mechanisms for improving efficiency or ensuring safety; however, they also entail deeper normative and organizational implications. What functions does human involvement actually fulfill? How do competency requirements, responsibility attributions, and professional identities evolve? And how can socio-technical systems be designed in ways that enable productive and responsible collaboration between human and artificial actors?
This track invites interdisciplinary contributions that advance theoretical and empirical understanding of socio-technical AI systems and the structural transformations they entail.
Topics of interest include, but are not limited to:
- Ethical guidelines and governance models for the use of AI
- Responsibility and accountability in hybrid human-AI decision systems
- Shifts in agency between humans and AI
- Delegation of decision rights and algorithmic authority
- New forms of division of labor between humans and AI
- Transformation of organizational decision architectures
- Implications for professional identities and role conceptions
- Design principles for Human-in-the-Loop and Human-on-the-Loop architectures
- Skill development and skill erosion in AI-enabled environments
- Emotional, social, and organizational dynamics (e.g., trust, anxiety, the 'uncanny valley of AI')
Track Chairs
Nils Urbach,
Frankfurt University
of Applied Sciences
Maria Madlberger,
Webster
University Vienna
General Track
The General Track invites high-quality research papers and short papers on topics that may not align specifically with other conference tracks. It is designed to attract unique, novel submissions and to provide authors with greater flexibility, particularly in terms of epistemological, ontological, and methodological perspectives.
We particularly welcome forward-looking topics and novel methodological approaches that challenge existing assumptions and advance the community. We recommend that you check other track descriptions before submitting to ensure the best possible fit for your paper. In addition, the General Track allows track chairs from other tracks to submit their own or their students' manuscripts.
Track Chairs
Stefan Thalmann,
Universität Graz
Christian Stary,
JKU Linz
Manuel Wimmer,
JKU Linz
Digital Transformation, Digital Strategies, and Digital Leadership
Digital transformation has been a central topic in Information Systems research for more than a decade. At its core lies the profound change in established organizations driven by digital technologies. A central question concerns how the process of digital transformation within an organization is designed or how it should be designed. This includes organizational structures as well as supporting instruments, for example for process governance (e.g., the definition of specific roles), for establishing the necessary prerequisites for digital transformation (e.g., competencies and IT landscape), and for the transformation of value creation itself (e.g., business model modeling or the evaluation of transformation initiatives). Furthermore, it is important to understand how digital transformation relates to the broader digital change within organizations and how it can be distinguished from other forms of digital change.
This track is dedicated to these issues. We welcome empirical and design-oriented contributions that ideally demonstrate both academic and practical relevance. Submissions may focus on specific technologies (e.g., AI) or on particular contexts (e.g., ecosystems or specific firm sizes). A clear organizational focus is essential.
Topics of interest include, but are not limited to:
- Design and emergence of digital transformation strategies and digital strategies
- The role of CDOs, CIOs, and CEOs in digital transformation
- Models for evaluating the economic viability of transformation projects
- Management of digital transformation programs and projects
- Capability development for digital transformation
- Enabling organizational structures for digital transformation
- Increasing the flexibility of IT landscapes to support digital transformation
- Cultural prerequisites of digital transformation
- Novel approaches to modeling digital products, digital processes, and digital business models
- Approaches for identifying and generating transformation project ideas
- Strategies for AI adoption
- Organizational embedding of AI
- Models for assessing the effects of AI use
- Contextualization of digital transformation concepts for specific segments of the economy (e.g., SMEs or particular industries)
- Approaches to measuring the degree of digital transformation
- Foundational models of digital transformation and digital change
Track Chairs
Thomas Hess,
LMU München
Lea Müller-Fortmann,
TU Darmstadt
Associate Editors
- Martin Adam, Universität Göttingen
- Alexander Benlian, Technische Universität Darmstadt
- Arne Buchwald, Hochschule Neu-Ulm
- Paul Drews, Leuphana Universität Lüneburg
- Khalid Durani, Heinrich-Heine-Universität Düsseldorf
- Simon Engert, Ludwig-Maximilians-Universität München und Ommax GmbH
- Maren Gierlich-Joas, Copenhagen Business School
- Angela Graf, Bayrisches Forschungsinstitut für Digitale Transformation (BIDT)
- Thomas Haskamp, Universität Münster
- Christian Matt, Universität Bern
- Anne-Sophie Mayer, Ludwig-Maximilians-Universität München
- Antonia Meythaler, Leuphana Universität Lüneburg
- Anna Oberländer, Universität Bayreuth und Fraunhofer FIT
- Alexander Teubner, Universität Münster
- Ferdinand Thies, Berner Fachhochschule
- Nihal Wahl, Technische Universität Darmstadt
- Bastian Wurm, Ludwig-Maximilians-Universität München
Data Science, Business Analytics & Operations Research
The growing availability and diversity of data is fundamentally changing not only companies, but also our society. Increasingly powerful technologies make it possible to collect, store and analyze huge amounts of data in real time. Whether AI-controlled logistics systems that optimize supply chains, predictive maintenance in Industry 4.0 or personalized recommendations in e-commerce - data-based applications are increasingly shaping operational and social reality. At the same time, data-driven systems are influencing our daily lives, from digital health applications to smart cities in which urban living spaces are designed more efficiently. Companies are faced with the particular challenge of analyzing and controlling complex and dynamic operational processes in a data-driven manner. Different data sources, often with heterogeneous formats and qualities, make a uniform view of business processes difficult. In addition, there are high demands on the integration, interpretation and use of data in order to create added value.
In order to exploit this potential, create added value with data, and make data-driven decisions, methods and tools of modern data analysis and data management are required, which are often summarized under the collective terms Data Science, Business Analytics and Operations Research (DS/BA/OR). This includes a variety of approaches from different disciplines such as statistics, artificial intelligence (AI), mathematical optimization, natural language processing, process mining, visual analytics, business intelligence, data quality management, data governance and many more.
Against this background, we welcome the entire diversity of business informatics-related research efforts in the areas of Data Science, Business Analytics and Operations Research in our track. These range, for example, from the generation, collection and representation of (big) data, the development of innovative theories, methods and procedures for solving business and social problems, the design of analytical artifacts to the adoption and integration of these approaches in companies. Research papers on the development of new statistical and machine learning methods are welcome, as long as they are related to the solution of a business or social problem. We encourage authors to submit relevant and original contributions that exploit the methodological breadth of the research field. Papers focused solely on AI and machine learning, without an explicit link to business applications, are not the primary focus of this track.
Topics of interest include, but are not limited to:
- Innovations and emerging trends in DS/BA/OR
- Business value and monetization of DS/BA/OR
- Introduction, establishment, maturity and use of DS/BA/OR
- DS/BA/OR for societal benefit, individual and societal empowerment and digital responsibility
- Explainable AI and interpretable machine learning
- Technical applications of generative AI and agentic AI
- Causal machine learning for business decisions
- Data protection, data quality and data governance
- Opportunities and challenges in data sharing and open data
- Digital manufacturing and the Internet of Things
- Operational, real-time or event-driven business analytics
- Process mining and the benefits of robotic process automation
- Visual analytics and the analysis of unstructured data (e.g. text, images, audio, video) to address organizational and/or societal challenges
- Predictive and prescriptive analytics
- Optimization (exact and heuristic approaches) and their integration with ideas from machine learning
- Data work and professions in the field of data science
Track Chairs
Sophie N. Parragh,
JKU Linz
Markus Sinnl,
JKU Linz
Christoph Schütz,
JKU Linz
Natalia Kliewer,
FU Berlin
Konstantin Hopf,
TU Chemnitz
Patrick Zschech,
TU Dresden
Digital Education & Learning
The growing availability and diversity of data is changing not only businesses but also fundamentally the educational landscape. This track is dedicated to topics in digital education and learning, with a focus on artificial intelligence and novel technologies such as Multi-Agent-Systems for education. With increasing digitalization, this track addresses existing and evolving challenges that focus on individualization and personalization towards lifelong learning. The track focuses on the impact on organizations and educational institutions such as universities, schools, and other educational institutions. The focus is on how AI is changing the design of teaching and learning processes, how educational offerings and structures can evolve to promote personalized and effective lifelong learning. This track will also discuss the changing role of human-machine interaction: AI as a supporter in the generation of information and the changing role of the learner as an analyst and critic of AI-generated content.
Another aspect of the track is the integration of innovative digital solutions into the socio-technical system and the teaching-learning arrangement. We consider concepts such as blended learning, flipped classroom, and fully digital teaching and learning concepts as well as the potential of new technologies such as the metaverse, augmented reality, and mobile learning solutions, and the role of AI in connection with these technologies. In doing so, we consider, among other things, the opportunities and challenges arising from the integration of AI into these areas. Our track especially welcomes empirical qualitative and quantitative studies or design science research studies.
Topics of interest include, but are not limited to:
- AI-powered individualization and personalization in learning
- Use of AI for automated assessment and feedback of learners
- Gamification to improve human-machine interaction in the learning context
- Ethical aspects of AI in learning
- AI-based learning analytics for predicting learning success
- Potentials and challenges of virtual and immersive, intelligent learning environments
- Augmented Reality for immersive knowledge transfer
- AI-powered tutoring systems and chatbots for individualized learning
- Development and evaluation of AI-based tools for educators
- The influence of AI on skill development in the digital age
- Changing digital skills in the context of human-machine interaction and working with generative AI
- Risks of using AI in teaching
Track Chairs
Andreas Janson,
Universität St.Gallen
Jan Marco Leimeister,
Universität Kassel &
St.Gallen
Niels Pinkwart,
Humboldt-Universität
zu Berlin
Sofia Schöbel,
Universität Osnabrück
Risk, Security, Fraud & Privacy Management
Until recently, economic issues surrounding trust, security, and privacy were still dominated by decades-old encryption techniques or data collection, particularly by platform operators with their algorithm-based business models. However, in recent years, several technologies have been developed that not only enable new applications in this area but are already being used worldwide. These include distributed ledger technologies (DLT, blockchain), but also AI applications that are both a challenge and a solution.
In particular, online access to GenAI systems and the embedding of AI in business information systems (BIS) let organization face new challenges between the increasing efficiency and optimizing processes on the one hand and preventing a growing shadow IT and the migration of sensitive data on the other. This raises the question for companies of how these new technologies can and must be integrated and managed within an organization. This also includes empowering employees through training, clear guidelines, and the targeted selection of tasks to be performed by AI.
With the increasing use of data for AI applications, data protection and privacy must also be viewed differently, and the requirements for traditional IT and cybersecurity protection goals must be rethought. What opportunities, applications, and risks does AI hold in the field of IT security? How are threat situations changing because of AI-supported cyber (fraud) attacks, and what protective measures can be supported by AI?
This conference track focuses on new developments in the field of “trust, security, and privacy” in the sense of socio-technical perspectives on IT-security, digital risks, and organizational resilience. Economic, organizational, and social implications and problem areas are considered at various levels, e.g., individuals, social groups, companies. We welcome interdisciplinary methods combining technical, social science, design-oriented or qualitative/quantitative approaches.
Topics of interest include, but are not limited to:
- Socio-technical dimensions of cybersecurity in context of AI- Interaction between technical security measures and human, organizational, and cultural factors
- Human factors and behavior in information security
- Security awareness, compliance, fatigue, and decision-aking under risk
- Security-by-design and security-by-default in organizational IT systems (BIS) - Integration of security concepts into processes, infrastructures, and cultures
- Future challenges of cybersecurity in highly digitalized societies - AI, automation, cloud infrastructures, and emerging threat landscapes
- Generative AI in organizations: efficiency gains vs. security and privacy risks - Shadow IT, data leakage, governance challenges, and control mechanisms
- AI-supported cyber attacks and fraud schemes - New threat models, automation of attacks, deepfakes, and social engineering
- AI-based cybersecurity and risk management solutions - Threat detection, incident response, vulnerability management, and decision support
- Data protection and privacy in AI-driven information systems - Rethinking confidentiality, purpose limitation, and data minimization
- Employee empowerment, training, and security awareness in AI-enabled workplaces
- Skills development, responsible AI use, and behavioral aspects of security
- Distributed ledger technologies for trust, transparency, and security - Use cases, limitations, and integration with AI-based systems
- Societal and organizational impacts of AI-driven security technologies - Power relations, inequality, surveillance, and social acceptance
Track Chairs
Ulrike Lechner,
Universität der
Bundeswehr München
Michaela Trierweiler,
JKU Linz
Nikolaus Obwegeser,
Berner Fachhochschule
Muriel-Larissa Frank,
Université de Luxembourg
Digital Markets, Platforms & Data Spaces
Digital markets and digital platform ecosystems are becoming increasingly important. Many of the world's most valuable companies (such as Uber, Airbnb, Google, Facebook) have committed themselves to this business model. Similarly, numerous established supply chain models are evolving into multi-sided platforms that are changing the competitive dynamics in many industries. We are seeing an increasing number of digitized and data-based marketplaces and platforms replacing traditional intermediaries and existing value creation structures. This affects both the B2C and B2B sectors.
Topics of interest include, but are not limited to:
- Competition in digital markets and platforms
- Algorithmic management on platforms
- Data and personalization on platforms
- Platforms and the future of work (e.g. crowdsensing, -sourcing, -working)
- Externalities and benefit asymmetries of digital markets and platforms
- Implications of antitrust and regulatory issues for digital marketplaces and platforms
- Behavior of platform users
- Organization and governance of digital markets and platforms
- Integration of services into digital markets and platforms (e.g. using IoT, DLT and blockchain technologies, AI applications)
Track Chairs
Verena Dorner,
Wirtschaftsuniversität Wien
Dominik Gutt,
RWTH Aachen
Christian Peukert,
HEC Lausanne
Digital Responsibility & Sustainability
The increasing pervasiveness of digital technologies across all sectors has created opportunities on many different levels. However, the use of digital technologies and information systems also brings about reversible changes and impacts on ecology, the economy, and society. In academia, research focuses primarily on these impacts and ways to manage them. Digital technologies and information systems can also contribute to measuring, managing, and mitigating these impacts. These efforts often involve interdisciplinary approaches that address sustainability and resilience. Resilience, defined as the ability to recover after crises and disasters, is influenced by various factors. At the societal level, these include education and awareness; at the corporate level, preparation for different eventualities. Another important aspect is the responsibility that arises from corporate actions.
This track invites submissions from diverse points of view - from Green IS/IT and Sustainable Information Systems to Digital Resilience—that have been researched using a variety of methods and interdisciplinary approaches.
Topics of interest include, but are not limited to:
- Green IS & Green IT in the Age of AI
- Environmental Information Systems and AI
- Energy Efficiency in and of Information Systems
- Information Systems for Addressing Ecological, Social, and/or Ethical Challenges
- Information Systems in the Context of Digital Resilience
- The Influence of Digital Ecosystems on Sustainability
- Information Systems as an Element of the Circular Economy
- Collaborative and Sustainable Digital Business Models
- Digital Decarbonization
- Influence of Sustainability Approaches on the Sourcing of Information Systems
- Digital Approaches and Stakeholder Involvement
- Responsible Action by Individuals and Companies in the Context of Digitalization
- Greenwashing and Brownwashing as Challenges for Information System Design
Track Chairs
Julia Zeller-Lanzl,
Universität Hamburg
Janina Sundermeier,
FU Berlin
Anna Ixmeier,
LMU München
Jeanine Kirchner-Krath,
FU Berlin
Human-Centered Information Systems & Social Computing
Human-computer interaction (HCI) and social computing are interdisciplinary fields of research that deal with the analysis and design of people’s interactions with and through information and communication technologies (ICT). The aim is to improve usability and user experience, thereby increasing productivity, quality of life, and user well-being. With the rapidly evolving potential of interactive technologies, sensor technologies, intelligent real-time data processing, and the almost universal presence of IT across all areas of life, new challenges and opportunities are emerging for HCI and social computing research in Information Systems.
This track focuses on research that improves understanding of user interaction with digital technologies and of people's behavior on social computing platforms, as well as on the effective design of these interactions. We are seeking contributions of any methodological orientation that advance the theoretical and practical understanding and design of information systems in HCI or social computing. Examples include human interactions with intelligent technologies such as Artificial Intelligence, novel (multimodal) interface designs, including concepts for wearables and augmented/virtual reality, and ongoing HCI practices for studying and designing specific interactive systems.
Additionally, we invite innovative ideas on user behavior and perceptions on social media. The track welcomes contributions that describe technically rigorous scientific advances in HCI and social computing, with clear links to Information Systems.
Topics of interest include, but are not limited to:
- Human interactions with intelligent technologies such as artificial intelligence
- Psychological, social, cultural, and ethical aspects of HCI in the design of information systems
- Novel (multimodal) interface designs, including concepts for wearables and augmented/virtual reality
- Design, use, and interaction of specific interactive systems, such as conversational agents, persuasive systems, or adaptive systems
- Use of NeuroIS methods and tools in HCI
- Participatory design and methods in HCI
- Investigation and design of personalization and user-adaptive systems (including the use of self-reported data and behavioral data) as well as biosignal-adaptive systems
- Social, individual, and company-related values of social media
- User behavior on social computing platforms
- Social media, health, and well-being
- Bias and discrimination in social media
- Cyberbullying and digital aggression on social media
- Social behavior in the digital space
Track Chairs
Hanna Krasnova,
Weizenbaum Institut &
Universität Potsdam
Alexander Maedche,
Karlsruhe Institute
of Technology
Jella Pfeiffer,
Karlsruhe Institute
of Technology
Julia Seitz,
Karlsruhe Institute
of Technology
IT Strategy, Governance & Management
Nowadays, digital technologies and IT systems are an elementary component of many products, services, processes, structures and business models. Corporate competitiveness and digital responsibility are therefore inextricably linked to the successful management of IT and digital innovations. IT is increasingly being called upon to play a strategic role in actively shaping the company’s value creation. To this end, the IT function not only deals with the requirements of customers, employees and partners of the company, but also develops, evaluates and introduces digital innovations and thinks about the transformation of the organization. For example, the business and IT sides of the organization must be increasingly integrated in terms of control, structure and process organization. The ecosystem of innovation partners and IT service providers must be increasingly included in strategy development and implementation. And last but not least, digital skills and competencies must be developed and promoted throughout the company.
This range of topics raises many important questions about the social, economic, organizational and technical aspects of strategic IT management and organizational change. We invite researchers to submit their work results and solutions to these questions in the “IT Strategy, Management & Governance” track. The track is open to different research methods.
Topics of interest include, but are not limited to:
- Development, alignment, and implementation of IT strategies
- Governance of IS/IT (e.g., changing C-Level roles and challenges (CIO, CDO, etc.), portfolio management)
- IS/IT management (e.g., Agile, projects, software development, structures, processes, algorithms for matching and control)
- Management and transformation of enterprise architectures
- Organizational development and IS/IT (e.g., Scaled-Agile, (Biz)DevOps, Bimodal-IT, organization of AI deployment, blockchain, analytics, platforms for organization)
- Management of skills and competencies in IS/IT
- IS/IT ecosystem management (e.g., supplier management, IT outsourcing, cloud computing, hybrid work alignment, gig and freelancer integration)
Track Chairs
Marina Fiedler,
Universität Passau
Anne-Sophie Mayer,
LMU München
Daniel Beimborn,
Universität Bamberg
Process Science
Business process management (BPM) has established itself as a cross-disciplinary management tool. By using BPM methods and tools, companies aim to identify, evaluate, design, implement, manage, and monitor business processes in order to effectively and efficiently provide added value to internal and external customers. BPM encompasses various areas such as the (re)design of business processes, process mining, robotic process automation, and predictive and prescriptive process control. In many of these areas, the use of artificial intelligence (AI) is currently being considered. The aim of this track is to discuss the various facets of BPM from a management and technology perspective and to identify how BPM can be further developed to address current challenges at the individual, organizational, and societal levels. We welcome contributions from all methodological directions that shed light on a broad spectrum of BPM research from both an organizational/social and a technical perspective.
Topics of interest include, but are not limited to:
- Exploratory process management and process innovation
- Business process management and co-creation
- Business process management and the management of digital transformation
- AI-based process analysis and process mining
- Organizational routines and routine dynamics
- Process mining in organizations
- Process automation using technologies such as (Gen)AI, RPA, Chatbots, etc.
- Workarounds and ambidexterity in process innovation
- User-driven BPM
- Responsible, human-centric, and socially sustainable BPM
- Green BPM
Track Chairs
Christian Bartelheimer,
Universität Göttingen
Kate Revoredo,
Humboldt-Universität
zu Berlin
Ralf Plattfaut,
Universität
Duisburg-Essen
Digital Government & Smart Cities
Digitalization presents opportunities to strengthen public value and address societal, economic, and ecological challenges. However, public organizations, which play a key role in delivering public value, often struggle to realize this potential. Reasons for this can be manifold, including technological impediments, organizational inertia, or individuals’ lack of competences and resistance to change.
In the public sector’s quest to redesign urban areas with regard to climate-neutrality and intelligent networks, the concept of the Smart City gains particular importance. The shift towards intelligent, interconnected cities extends beyond the mere digitalization of services, aiming for a more efficient, greener, and socially integrated city. This development intensifies the debate about potentials and applications, as well as the limits of digital trends such as data-driven governance, blockchain, and AI in the public sector.
Public organizations should create the framework conditions to facilitate the implementation of Smart Cities, making our cities more efficient, sustainable, and livable. This includes networked urban infrastructure, smart traffic management, energy-efficient building management, access to digital education, or improved provision of digital public services. Thereby, ecological, social, ethical, and economic aspects must be regarded simultaneously, which makes the implementation of digital government and smart cities a complex endeavor. A key aspect therein is the cooperation between and management of actors at local, national, and international levels, as well as cities, businesses, research institutions, and civil society.
This track attracts innovative research on the topics “Smart Cities & Digital Government” from various disciplinary approaches and methodological perspectives. The focus is on how integrated, intelligent urban development can shape a sustainable and equitable future. The track is aimed at scholars from the fields of Information Systems / business informatics, administrative sciences, urban planning, and adjacent disciplines, proposing new perspectives and solutions to the development of digital government and smart cities.
Topics of interest include, but are not limited to:
- Data-Driven Government
- Open Data and Open Government
- Smart Government and Smart Governance
- Smart Cities: Projects, platforms and applications
- Liveability and quality of life in Smart Cities
- Digital sovereignity and trust mangement
- Adoption and use of digital trends (e.g., block chain, RPA, AI, automation of public service)
- AI in public organizations
- Transformative effects of public sector digitalization
- Transformational government and innovation management
- Digital government strategies
- Online Acces Act: Implementation, potentials, problems
- Digital competences, vocational training, education in the public sector
Track Chairs
Michael Koddebusch,
Universität Münster
Tobias Guggenberger,
Universität Bayreuth
Bettina Distel,
Bundesinstitut für Bau-,
Stadt- und Raumforschung
Digital Twins
Digital twins form an interdisciplinary field of research at the intersection of information sciences, computer sciences, logistics, and mechanical engineering. This field of research deals not only with the technical design of digital twins, but also with the organizational and societal consequences of their use, as well as the conditions for their value-adding and sustainable use in companies and value creation networks. A digital twin can be understood as a digital representation of real systems that integrates various data sources and creates a bidirectional link between the digital and physical worlds.
The continuous synchronization of these two levels is essential in order to reliably reflect changes in the real state in the digital model. The aim of such systems is to significantly increase the quality of decisions, the efficiency of technical processes, and transparency throughout the entire life cycle. Through advanced data analytics and IoT connectivity, it is able to map various attributes and thus realistically reflect almost every facet of a product, process, service, or even an entire organization. However, with the growing possibilities for data collection, processing, and evaluation, especially in the context of artificial intelligence, new challenges and questions are emerging for research on digital twins within information sciences.
This track focuses on findings that contribute to a better understanding, modeling, and use of digital representations of physical artefacts, processes, or value creation networks. We are looking for contributions of an empirical or design-oriented nature We are looking for contributions of an empirical or design-oriented nature that provide theoretical or practical advances in the design, implementation, or use of digital twins. This includes, for example, questions about real-time capability, hybrid modeling, semantic interoperability, simulation- and AI-based decision support, or the embedding of digital twins in operational and strategic information systems. In addition, papers are welcome that deal with the perception, acceptance, and use of digital twins in organizations or analyze their impact on work processes, governance structures, and economic value creation, also taking sociological approaches into account.
Topics of interest include, but are not limited to:
- Architectures and implementation methodologies
- Data models and advanced data analytics tools for Digital Twins
- Data security for Digital Twins
- Smart interfaces and connectors to information systems
- Software architectures for next-generation MES
- Artificial Intelligence (AI) for Digital Twin Design and Operations
- Sustainability and energy-efficient operation of Digital Twins
- Virtual Commissioning and emulations
- Digital Product Passports
- Digital Twins and the Circular Economy
- Digital Twins in domain-specific contexts, e.g., manufacturing, healthcare, fintech
- Case studies and industrial applications of Digital Twins
Track Chairs
Hendrik van der Valk,
TU Dortmund
Christian Koldewey,
Universität Paderborn
Dimitri Petrik,
Universität Stuttgart
From Generative AI to Agentic IS: Impact on Individuals, Organisation and Society
In recent years, advances in Artificial Intelligence have not only opened new avenues for the machine processing of data and information but have also heralded the transition from purely data-focused tasks to complex, knowledge-based, and even creative endeavors. Consequently, information systems are evolving from passive tools into autonomous entities capable of learning, adapting content, interacting, and acting independently. This fundamental shift of agency from humans to agentic IS artifacts forms the foundation for the next generation of information systems. Collaborative forms of work are emerging in which tasks are no longer merely supported but bidirectionally delegated, necessitating extensive opportunities for research as well as a reevaluation of existing concepts and mindsets.
While it remains challenging to precisely assess the influence of GenAI and agentic systems on our global society, the impact of this new type of information system is already evident at organizational, technological, and behavioral levels. However, alongside transformative benefits, new challenges and potential drawbacks are also arising. With the increasing autonomy of these systems, questions regarding accountability and responsibility in the delegation of decisions are moving into focus. Therefore, it is imperative to evaluate this next generation of information systems from a scientific perspective and to develop socio-technical solutions that harness these technologies for the benefit of individuals, organizations, and society.
Against this background, this track offers a forum for researchers across all streams of Information Systems to shape the next generation of information systems. We particularly welcome contributions at the individual, organizational, and societal levels that focus on the design and impact of GenAI and Agentic IS. This includes new design methodologies, conceptual frameworks, and tools, as well as studies on the behavioral implications of this paradigm. We encourage authors to critically examine the implications of the shift in agency and the associated consequences at all levels, particularly regarding decision delegation, questions of accountability, and the influence on human skills and judgment in interactions with agentic systems, to advance the discourse between science and practice.
Topics of interest include, but are not limited to:
- From Human-GenAI Collaboration to Human-Agent Teaming
- The Psychology of Delegation: Trust and Control in Agentic IS
- Shifting Agency: From Passive Tools to Autonomous Entities
- Designing Delegation in Agentic Systems
- Data Infrastructures for Agentic IS
- Accountability, Responsibility, and Liability in Agentic IS
- The Role of Human Judgment and Oversight in Automated Decisions
- Agent-driven Data Curation and Quality Management
- Design Principles and Methodologies for Agentic IS
- Privacy, Security, and Risk in Autonomous Agent Ecosystems
- Autonomous Knowledge Management Systems
- Co-Creation and Value Generation with Agentic IS
- Workforce Transformation: Skills for Supervising and Managing Agents
- Data Governance and Sovereignty in Autonomous Systems
- Generative AI in Organizational Data Management
- Risk assessment in the use of agentic IS in Data Management
Track Chairs
Gero Strobel,
Universität
Duisburg-Essen
Sarah Hönigsberg,
ICN Business School,
France
Frederik Möller,
Technische Universität
Braunschweig
Design, Development, Engineering & Management of Services & Software-Systems
Services are an essential part of our everyday lives and of business relationships between companies and organizations. At the same time, they are significantly influenced by innovations such as generative AI and agentic AI. Services come in various forms that fulfill different functions: human-centric services; digital, data-based and AI-based services; smart, AR- and VR-based services; services based on hybrid intelligence; B2C, B2B, B2B2C services and many more. As services are typically offered within complex service systems that include a large number of stakeholders and new technologies, this ecosystem of human and other (AI, etc.) agents requires an integration of diverse resources for value creation. A consistent customer and user orientation as well as an intelligent orchestration of these service systems are crucial here; not only to make services successful, but also to ensure the efficient and effective development and provision of services. In this context, Service Engineering and Service Systems Engineering aim to provide methods, models, and tools that enable the systematic development of services and service systems and their corresponding ecosystems.
This track invites the submission of papers that present current and relevant research results on services and service innovation, as well as service engineering and service systems engineering. The context of services in this track is not restricted, but can range from personal services, innovative technologies in service processes to fully automated services and service offerings integrating various service types. We invite design-oriented papers as well as qualitative and quantitative-empirical contributions. Conceptual or theoretical contributions that contribute to a better understanding of all types of services and service systems are also welcome.
Topics of interest include, but are not limited to:
- Methods and models for Service Engineering and Service Systems Engineering
- Design, modularization, and evaluation of (smart) product-service systems
- Human-centered and experience-driven service design
- Artifact design for digital service innovation
- Digital servitization and data-driven service innovation
- Organizational capabilities and transformation for service innovation
- Success factors, risks, and failures in service innovation
- Value co-creation, co-destruction, and service ecosystem dynamics
- AI-, data- and GenAI-based services and business models
- AI-based service systems engineering and automation
- Hybrid intelligence in service provision (human-AI collaboration)
- Conversational agents, service robots, and autonomous service technologies
- Responsible and trustworthy AI in service contexts
- Design and management of service and work processes
- Integration of service and work systems in modern work environments
- Changing roles, skills, and human-technology interaction in service delivery
- Digital service ecosystems and platform-based business models
- Interorganizational and ecosystem-based service systems
- Governance, orchestration, and value creation in service ecosystems
Track Chairs
Christoph Peters,
Universität der
Bundeswehr München
Martin Semmann,
Universität Hamburg
Juuli Lumivalo,
University of Jyväskylä
Digital Wellbeing, Digital Healthcare & Healthcare Management
Healthcare systems around the world continue to face increased pressure and ongoing challenges, including a shortage of staff, increased demand, and budget cuts. The World Health Organization, for example, estimates a global shortage in healthcare workforce of approximately 10 million health workers by 2030, mainly in low- and lower-middle-income countries (WHO, 2024). Therefore, efficient use of (staff) resources, attractive working conditions, and increasing digitization efforts are crucial. The need for decision support for healthcare processes and services based on optimization, simulation, and information technology research is only increasing. In their review motivated by the short-term use but rapid implementation of digital solutions during the COVID pandemic, Majcherek et al. (2024) concluded that there is still a need to build a digital infrastructure for the healthcare industry in most European countries. Recent developments further emphasize the importance of integrated planning with a system’s perspective, as well as the need for interdisciplinary approaches that combine knowledge from different areas together with strong collaboration between research and practice.
Research into how designing information systems (IS) can help to digitally transform health care practices, organizations, and industries is a classical topic that has concerned researchers in our field for many years (Agarwal et al., 2010; Baird et al., 2018; Burton-Jones et al., 2019). The transformative effects that digital technologies have on the delivery of health care services is significant as data and evermore potent algorithms contribute to changes in the roles that citizens, patients, clinicians, health care managers, and researchers play in the delivery of health care services (Essén & Värlander, 2019; Jarvenpaa & Essén, 2023; Sunyaev et al., 2024). At the centre of all these dynamics lies a key design challenge: how to integrate systems, algorithms, and data in a human-centred way (see also, Bardhan et al., 2020).
Decision support systems (DSS) play a crucial role in healthcare, not only in the form of clinical decision support systems to assist physicians and other health professionals in medical decision making, but also to support logistical and organizational processes. Holistic and interdisciplinary research on decision support systems is crucial for a successful application of DSS in healthcare practice. This includes not only the design of the underlying algorithms and methods, e.g. from the areas of Operational Research and Artificial Intelligence (AI), but also the overall design of the DSS and the design of the user interface, the interaction of users with a DSS and the integration of a DSS into the processes in practice.
Asking ourselves how we design for human-centred health care services is not trivial because technological designs are one question, but the other is how these designs interact with persons, providers, platforms, and professionals over time. The importance of getting these interactions ‘right’ is as straightforward as finding answers to this question is complicated (Wessel et al., 2023). ‘Classical’ information systems in hospitals such as electronic medical records (Agarwal et al., 2010; Burton-Jones & Volkoff, 2017; Hansen & Baroody, 2020; Oborn et al., 2011) serve as repositories of data that assist professionals in making decisions and, potentially, improve diagnostics in the digital age (Lebovitz et al., 2021, 2022). However, it is not only hospitals that transform, and it is not only electronic medical records that matter for transformations to occur. Laypersons have become more active when it comes to self-managing chronic conditions (Dadgar & Joshi, 2018; Wessel et al., 2019), using platforms to exchange ideas, self-help and find advice (Barrett et al., 2016; Fürstenau et al., 2021), as well as using artificial intelligence-based systems that help to prevent chronic conditions (Wessel et al., 2023). Building on these developments is an increasingly important discussion in health policy asking how digital technologies can be used to reorient incentives and make providers gain from patient outcomes as opposed to the volumes of services provided (Agarwal et al., 2020; M. Porter, 2010; M. E. Porter & Teisberg, 2006). Finally, the renewed interest of researchers in the role that data play for innovation in services, digital tools, and applications (Jarvenpaa and Markus 2018; Rothe et al. 2019; Thiebes et al. 2020; Vassilakopoulou et al. 2018), extends far beyond incremental improvement of diagnostic and therapeutic tools. Broader availability of new health data types such as from single-cell or multi-omic sequencing, 3-dimensional x-rays, and new MRT approaches, life sciences increasingly gain insights into early disease development. New health care applications, thus, can therefore become prospective, suggesting interventions on citizens who have not yet become “patients”. What matters then is to design in ways that effectively integrate these innovations in humans’ everyday lives.
We cast the net wide and welcome submissions that speak to the above-mentioned issues. Our understandings of the terms ‘design(s)’ and ‘designing’ are broad and not limited to applications of well-established approaches such as design science research (DSR) or action design research (ADR), which we welcome to our track. Indeed, we ask for submissions of all types that have the potential to contribute to our understanding of the above-mentioned phenomena, be these related to the importance of classical health care IT topics in the digital age, or questions related to the transformative potentials and impacts of digital data objects, and digital tools. Papers may be focused on original theory-oriented research, design-oriented research, empirical studies, or conceptual work. We are agnostic in terms of methodologies applied.
Topics of interest include, but are not limited to:
- The changing role and management of digital health data for digital innovation for health and well-being
- New impact of digital health tools and digital data objects in- and outside of healthcare, e.g., in times of crisis
- A process perspective explaining dynamics of digital transformation in healthcare
- Change of professional roles, identities, and institutions for value creation in health
- New design of digital innovations for improving patients’ self-management of chronic conditions
- The role of data and tools as inhibitors or promoters for a disease-based health care system
- The role of data and tools like sensors, wearables technologies, and digital health apps as inhibitors or promoters for a patient-centric health care
- The role of digital tools like virtual coaching for autonomy of health care providers and patients
- The role of data and tools for disease intervention vs. prevention
- The relationship between classical hospital information systems and more recent digital innovations in health care
- Changing business models in the context of digital innovation in health care
- Changes in support for people in need for care, including elderly or handicapped, through digital technologies
- The role of new digital technologies like XR, web3.0 and machine learning for creating health data and for creating value from health data
- New modes of capturing value from digital health data, e.g., reimbursement strategies
- New ethical challenges from health data, considering privacy and security
- Digital tools and use of digital health data to connect different participants of health service networks, to support decision making and to improve logistical and organisational processes
- Design of digital tools and the role of IS to support integrated and patient-centred care and integrated planning spanning multiple care forms and/or steps in a patient’s pathway
Track Chairs
Melanie
Reuter-Oppermann,
Technische Hochschule
Würzburg-Schweinfurt
Hannes Rothe,
Universität
Duisburg-Essen
Till Winkler,
FernUniversität Hagen
Michael S. Dohan,
Lakehead University
Artificial Intelligence & Digital Transformation in Industry & Production (Industry Track)
As an applied discipline, business informatics is in direct contact with companies and employs scientific methods to offer insights for practical application. At the same time, practical problems serve as the starting point for new research ideas. This track focuses particularly on industry and manufacturing, and related sectors that have undergone significant transformation in recent years, even though they are traditionally considered part of the "old economy." This transformation is characterized by the digitalization of production and processes and has presented companies with new challenges due to the opportunities arising from AI. In terms of relevance, research findings that examine digital transformation in companies, as well as the application of AI within these companies, are prioritized.
The practical track invites the presentation of research findings on socio-technical solutions that contribute to digitalization in a business context and consider the application of AI. Direct participation by one or more companies—for example, as authors—is required for this track. The research can be based on individual, corporate, or societal levels, examining the application and resulting impacts of these systems. In addition to the relevance of this research, the corresponding scientific rigor must also be considered. This track will particularly focus on methods that exist directly at the interface with practical application.
Topics of interest include, but are not limited to:
- Strategic Approaches to Digitalization
- Practical Solutions for IT Governance in the Digital Age
- Implementation of AI Applications in Industry and Production
- Robotic Process Automation in Various Contexts
- Automation in the Age of AI
- Methods for Introducing AI Applications
- Infrastructural Challenges for Implementing AI
- Efficiency Criteria for the Use of AI
- Digitalization as a Competitive Factor in Production
Track Chairs
Hermann Sikora,
JKU Linz
David Rückel,
JKU Linz
Christian Stary,
JKU Linz
Student Track
The aim of this track is to involve students with their own research results in WI2026. The track is primarily aimed at master's level students who would like to present the results of an academic paper (bachelor's or master's thesis, project work) to a specialist audience. Students from all fields of business informatics and related disciplines are invited to submit high-quality papers. Students who do not submit a paper are also welcome to attend the presentations and participate in the Student Track's supporting program.
Submissions must be authored by a student as the first author. The inclusion of PhD researchers is possible if the contribution is predominantly authored by students. The track is open to all methodological approaches and particularly welcomes interdisciplinary contributions.
Specific deadlines apply to the Student Track for submission (April 13, 2026) and notification to authors (June 8, 2026) – all other deadlines are the same as for the other tracks!
Topics of interest include, but are not limited to:
- AI applications and AI implementations
- Digitalization and digital transformation
- Business process management
- E-health and e-government
- Strategic aspects of digitalization
- Software and systems development
- IT governance
- Methodology development and integration of methods from other disciplines
Track Chairs
Richard Heininger,
JKU Linz
Ursula Niederländer,
JKU Linz
Socio-technical Systems in Times of Artificial Intelligence
Artificial Intelligence (AI) is widely regarded as a 'general purpose technology' that fundamentally reshapes economic activity, organizational structures, and societal development. From an Information Systems perspective, the key question is not only how powerful AI technologies are, but how they are embedded in socio-technical systems and how this embedding transforms the role of humans within organizations.
As AI systems become increasingly autonomous, adaptive, and creative, their role shifts from supportive tools to active co-shapers of organizational processes and decisions. AI increasingly enters domains that traditionally required human judgment, experience, and moral-ethical reflection. This development raises fundamental questions regarding responsibility, agency, legitimacy, and control in hybrid human-AI systems.
While trust in AI has received considerable scholarly attention, the long-term transformation of the human role - particularly as a moral authority, decision-maker, and bearer of responsibility - remains insufficiently understood. Concepts such as 'Human-in-the-Loop' are often framed as mechanisms for improving efficiency or ensuring safety; however, they also entail deeper normative and organizational implications. What functions does human involvement actually fulfill? How do competency requirements, responsibility attributions, and professional identities evolve? And how can socio-technical systems be designed in ways that enable productive and responsible collaboration between human and artificial actors?
This track invites interdisciplinary contributions that advance theoretical and empirical understanding of socio-technical AI systems and the structural transformations they entail.
Topics of interest include, but are not limited to:
- Ethical guidelines and governance models for the use of AI
- Responsibility and accountability in hybrid human-AI decision systems
- Shifts in agency between humans and AI
- Delegation of decision rights and algorithmic authority
- New forms of division of labor between humans and AI
- Transformation of organizational decision architectures
- Implications for professional identities and role conceptions
- Design principles for Human-in-the-Loop and Human-on-the-Loop architectures
- Skill development and skill erosion in AI-enabled environments
- Emotional, social, and organizational dynamics (e.g., trust, anxiety, the 'uncanny valley of AI')
Track Chairs
|
|
| Nils Urbach, Frankfurt University of Applied Sciences |
Maria Madlberger, Webster University Vienna |
General Track
The General Track invites high-quality research papers and short papers on topics that may not align specifically with other conference tracks. It is designed to attract unique, novel submissions and to provide authors with greater flexibility, particularly in terms of epistemological, ontological, and methodological perspectives.
We particularly welcome forward-looking topics and novel methodological approaches that challenge existing assumptions and advance the community. We recommend that you check other track descriptions before submitting to ensure the best possible fit for your paper. In addition, the General Track allows track chairs from other tracks to submit their own or their students' manuscripts.
Track Chairs
|
|
|
| Stefan Thalmann, Universität Graz |
Christian Stary, JKU Linz |
Manuel Wimmer, JKU Linz |
Digital Transformation, Digital Strategies, and Digital Leadership
Digital transformation has been a central topic in Information Systems research for more than a decade. At its core lies the profound change in established organizations driven by digital technologies. A central question concerns how the process of digital transformation within an organization is designed or how it should be designed. This includes organizational structures as well as supporting instruments, for example for process governance (e.g., the definition of specific roles), for establishing the necessary prerequisites for digital transformation (e.g., competencies and IT landscape), and for the transformation of value creation itself (e.g., business model modeling or the evaluation of transformation initiatives). Furthermore, it is important to understand how digital transformation relates to the broader digital change within organizations and how it can be distinguished from other forms of digital change.
This track is dedicated to these issues. We welcome empirical and design-oriented contributions that ideally demonstrate both academic and practical relevance. Submissions may focus on specific technologies (e.g., AI) or on particular contexts (e.g., ecosystems or specific firm sizes). A clear organizational focus is essential.
Topics of interest include, but are not limited to:
- Design and emergence of digital transformation strategies and digital strategies
- The role of CDOs, CIOs, and CEOs in digital transformation
- Models for evaluating the economic viability of transformation projects
- Management of digital transformation programs and projects
- Capability development for digital transformation
- Enabling organizational structures for digital transformation
- Increasing the flexibility of IT landscapes to support digital transformation
- Cultural prerequisites of digital transformation
- Novel approaches to modeling digital products, digital processes, and digital business models
- Approaches for identifying and generating transformation project ideas
- Strategies for AI adoption
- Organizational embedding of AI
- Models for assessing the effects of AI use
- Contextualization of digital transformation concepts for specific segments of the economy (e.g., SMEs or particular industries)
- Approaches to measuring the degree of digital transformation
- Foundational models of digital transformation and digital change
Track Chairs
|
|
| Thomas Hess, LMU München |
Lea Müller-Fortmann, TU Darmstadt |
Associate Editors
- Martin Adam, Universität Göttingen
- Alexander Benlian, Technische Universität Darmstadt
- Arne Buchwald, Hochschule Neu-Ulm
- Paul Drews, Leuphana Universität Lüneburg
- Khalid Durani, Heinrich-Heine-Universität Düsseldorf
- Simon Engert, Ludwig-Maximilians-Universität München und Ommax GmbH
- Maren Gierlich-Joas, Copenhagen Business School
- Angela Graf, Bayrisches Forschungsinstitut für Digitale Transformation (BIDT)
- Thomas Haskamp, Universität Münster
- Christian Matt, Universität Bern
- Anne-Sophie Mayer, Ludwig-Maximilians-Universität München
- Antonia Meythaler, Leuphana Universität Lüneburg
- Anna Oberländer, Universität Bayreuth und Fraunhofer FIT
- Alexander Teubner, Universität Münster
- Ferdinand Thies, Berner Fachhochschule
- Nihal Wahl, Technische Universität Darmstadt
- Bastian Wurm, Ludwig-Maximilians-Universität München
Data Science, Business Analytics & Operations Research
The growing availability and diversity of data is fundamentally changing not only companies, but also our society. Increasingly powerful technologies make it possible to collect, store and analyze huge amounts of data in real time. Whether AI-controlled logistics systems that optimize supply chains, predictive maintenance in Industry 4.0 or personalized recommendations in e-commerce - data-based applications are increasingly shaping operational and social reality. At the same time, data-driven systems are influencing our daily lives, from digital health applications to smart cities in which urban living spaces are designed more efficiently. Companies are faced with the particular challenge of analyzing and controlling complex and dynamic operational processes in a data-driven manner. Different data sources, often with heterogeneous formats and qualities, make a uniform view of business processes difficult. In addition, there are high demands on the integration, interpretation and use of data in order to create added value.
In order to exploit this potential, create added value with data, and make data-driven decisions, methods and tools of modern data analysis and data management are required, which are often summarized under the collective terms Data Science, Business Analytics and Operations Research (DS/BA/OR). This includes a variety of approaches from different disciplines such as statistics, artificial intelligence (AI), mathematical optimization, natural language processing, process mining, visual analytics, business intelligence, data quality management, data governance and many more.
Against this background, we welcome the entire diversity of business informatics-related research efforts in the areas of Data Science, Business Analytics and Operations Research in our track. These range, for example, from the generation, collection and representation of (big) data, the development of innovative theories, methods and procedures for solving business and social problems, the design of analytical artifacts to the adoption and integration of these approaches in companies. Research papers on the development of new statistical and machine learning methods are welcome, as long as they are related to the solution of a business or social problem. We encourage authors to submit relevant and original contributions that exploit the methodological breadth of the research field. Papers focused solely on AI and machine learning, without an explicit link to business applications, are not the primary focus of this track.
Topics of interest include, but are not limited to:
- Innovations and emerging trends in DS/BA/OR
- Business value and monetization of DS/BA/OR
- Introduction, establishment, maturity and use of DS/BA/OR
- DS/BA/OR for societal benefit, individual and societal empowerment and digital responsibility
- Explainable AI and interpretable machine learning
- Technical applications of generative AI and agentic AI
- Causal machine learning for business decisions
- Data protection, data quality and data governance
- Opportunities and challenges in data sharing and open data
- Digital manufacturing and the Internet of Things
- Operational, real-time or event-driven business analytics
- Process mining and the benefits of robotic process automation
- Visual analytics and the analysis of unstructured data (e.g. text, images, audio, video) to address organizational and/or societal challenges
- Predictive and prescriptive analytics
- Optimization (exact and heuristic approaches) and their integration with ideas from machine learning
- Data work and professions in the field of data science
Track Chairs
|
|
|
|
|
|
| Sophie N. Parragh, JKU Linz |
Markus Sinnl, JKU Linz |
Christoph Schütz, JKU Linz |
Natalia Kliewer, FU Berlin |
Konstantin Hopf, TU Chemnitz |
Patrick Zschech, TU Dresden |
Digital Education & Learning
The growing availability and diversity of data is changing not only businesses but also fundamentally the educational landscape. This track is dedicated to topics in digital education and learning, with a focus on artificial intelligence and novel technologies such as Multi-Agent-Systems for education. With increasing digitalization, this track addresses existing and evolving challenges that focus on individualization and personalization towards lifelong learning. The track focuses on the impact on organizations and educational institutions such as universities, schools, and other educational institutions. The focus is on how AI is changing the design of teaching and learning processes, how educational offerings and structures can evolve to promote personalized and effective lifelong learning. This track will also discuss the changing role of human-machine interaction: AI as a supporter in the generation of information and the changing role of the learner as an analyst and critic of AI-generated content.
Another aspect of the track is the integration of innovative digital solutions into the socio-technical system and the teaching-learning arrangement. We consider concepts such as blended learning, flipped classroom, and fully digital teaching and learning concepts as well as the potential of new technologies such as the metaverse, augmented reality, and mobile learning solutions, and the role of AI in connection with these technologies. In doing so, we consider, among other things, the opportunities and challenges arising from the integration of AI into these areas. Our track especially welcomes empirical qualitative and quantitative studies or design science research studies.
Topics of interest include, but are not limited to:
- AI-powered individualization and personalization in learning
- Use of AI for automated assessment and feedback of learners
- Gamification to improve human-machine interaction in the learning context
- Ethical aspects of AI in learning
- AI-based learning analytics for predicting learning success
- Potentials and challenges of virtual and immersive, intelligent learning environments
- Augmented Reality for immersive knowledge transfer
- AI-powered tutoring systems and chatbots for individualized learning
- Development and evaluation of AI-based tools for educators
- The influence of AI on skill development in the digital age
- Changing digital skills in the context of human-machine interaction and working with generative AI
- Risks of using AI in teaching
Track Chairs
|
|
|
|
| Andreas Janson, Universität St.Gallen |
Jan Marco Leimeister, Universität Kassel & St.Gallen |
Niels Pinkwart, Humboldt-Universität zu Berlin |
Sofia Schöbel, Universität Osnabrück |
Risk, Security, Fraud & Privacy Management
Until recently, economic issues surrounding trust, security, and privacy were still dominated by decades-old encryption techniques or data collection, particularly by platform operators with their algorithm-based business models. However, in recent years, several technologies have been developed that not only enable new applications in this area but are already being used worldwide. These include distributed ledger technologies (DLT, blockchain), but also AI applications that are both a challenge and a solution.
In particular, online access to GenAI systems and the embedding of AI in business information systems (BIS) let organization face new challenges between the increasing efficiency and optimizing processes on the one hand and preventing a growing shadow IT and the migration of sensitive data on the other. This raises the question for companies of how these new technologies can and must be integrated and managed within an organization. This also includes empowering employees through training, clear guidelines, and the targeted selection of tasks to be performed by AI.
With the increasing use of data for AI applications, data protection and privacy must also be viewed differently, and the requirements for traditional IT and cybersecurity protection goals must be rethought. What opportunities, applications, and risks does AI hold in the field of IT security? How are threat situations changing because of AI-supported cyber (fraud) attacks, and what protective measures can be supported by AI?
This conference track focuses on new developments in the field of “trust, security, and privacy” in the sense of socio-technical perspectives on IT-security, digital risks, and organizational resilience. Economic, organizational, and social implications and problem areas are considered at various levels, e.g., individuals, social groups, companies. We welcome interdisciplinary methods combining technical, social science, design-oriented or qualitative/quantitative approaches.
Topics of interest include, but are not limited to:
- Socio-technical dimensions of cybersecurity in context of AI- Interaction between technical security measures and human, organizational, and cultural factors
- Human factors and behavior in information security
- Security awareness, compliance, fatigue, and decision-aking under risk
- Security-by-design and security-by-default in organizational IT systems (BIS) - Integration of security concepts into processes, infrastructures, and cultures
- Future challenges of cybersecurity in highly digitalized societies - AI, automation, cloud infrastructures, and emerging threat landscapes
- Generative AI in organizations: efficiency gains vs. security and privacy risks - Shadow IT, data leakage, governance challenges, and control mechanisms
- AI-supported cyber attacks and fraud schemes - New threat models, automation of attacks, deepfakes, and social engineering
- AI-based cybersecurity and risk management solutions - Threat detection, incident response, vulnerability management, and decision support
- Data protection and privacy in AI-driven information systems - Rethinking confidentiality, purpose limitation, and data minimization
- Employee empowerment, training, and security awareness in AI-enabled workplaces
- Skills development, responsible AI use, and behavioral aspects of security
- Distributed ledger technologies for trust, transparency, and security - Use cases, limitations, and integration with AI-based systems
- Societal and organizational impacts of AI-driven security technologies - Power relations, inequality, surveillance, and social acceptance
Track Chairs
|
|
|
|
| Ulrike Lechner, Universität der Bundeswehr München |
Michaela Trierweiler, JKU Linz |
Nikolaus Obwegeser, Berner Fachhochschule |
Muriel-Larissa Frank, Université de Luxembourg |
Digital Markets, Platforms & Data Spaces
Digital markets and digital platform ecosystems are becoming increasingly important. Many of the world's most valuable companies (such as Uber, Airbnb, Google, Facebook) have committed themselves to this business model. Similarly, numerous established supply chain models are evolving into multi-sided platforms that are changing the competitive dynamics in many industries. We are seeing an increasing number of digitized and data-based marketplaces and platforms replacing traditional intermediaries and existing value creation structures. This affects both the B2C and B2B sectors.
Topics of interest include, but are not limited to:
- Competition in digital markets and platforms
- Algorithmic management on platforms
- Data and personalization on platforms
- Platforms and the future of work (e.g. crowdsensing, -sourcing, -working)
- Externalities and benefit asymmetries of digital markets and platforms
- Implications of antitrust and regulatory issues for digital marketplaces and platforms
- Behavior of platform users
- Organization and governance of digital markets and platforms
- Integration of services into digital markets and platforms (e.g. using IoT, DLT and blockchain technologies, AI applications)
Track Chairs
|
|
|
| Verena Dorner, Wirtschaftsuniversität Wien |
Dominik Gutt, RWTH Aachen |
Christian Peukert, HEC Lausanne |
Digital Responsibility & Sustainability
The increasing pervasiveness of digital technologies across all sectors has created opportunities on many different levels. However, the use of digital technologies and information systems also brings about reversible changes and impacts on ecology, the economy, and society. In academia, research focuses primarily on these impacts and ways to manage them. Digital technologies and information systems can also contribute to measuring, managing, and mitigating these impacts. These efforts often involve interdisciplinary approaches that address sustainability and resilience. Resilience, defined as the ability to recover after crises and disasters, is influenced by various factors. At the societal level, these include education and awareness; at the corporate level, preparation for different eventualities. Another important aspect is the responsibility that arises from corporate actions.
This track invites submissions from diverse points of view - from Green IS/IT and Sustainable Information Systems to Digital Resilience—that have been researched using a variety of methods and interdisciplinary approaches.
Topics of interest include, but are not limited to:
- Green IS & Green IT in the Age of AI
- Environmental Information Systems and AI
- Energy Efficiency in and of Information Systems
- Information Systems for Addressing Ecological, Social, and/or Ethical Challenges
- Information Systems in the Context of Digital Resilience
- The Influence of Digital Ecosystems on Sustainability
- Information Systems as an Element of the Circular Economy
- Collaborative and Sustainable Digital Business Models
- Digital Decarbonization
- Influence of Sustainability Approaches on the Sourcing of Information Systems
- Digital Approaches and Stakeholder Involvement
- Responsible Action by Individuals and Companies in the Context of Digitalization
- Greenwashing and Brownwashing as Challenges for Information System Design
Track Chairs
|
|
|
|
| Julia Zeller-Lanzl, Universität Hamburg |
Janina Sundermeier, FU Berlin |
Anna Ixmeier, LMU München |
Jeanine Kirchner-Krath, FU Berlin |
Human-Centered Information Systems & Social Computing
Human-computer interaction (HCI) and social computing are interdisciplinary fields of research that deal with the analysis and design of people’s interactions with and through information and communication technologies (ICT). The aim is to improve usability and user experience, thereby increasing productivity, quality of life, and user well-being. With the rapidly evolving potential of interactive technologies, sensor technologies, intelligent real-time data processing, and the almost universal presence of IT across all areas of life, new challenges and opportunities are emerging for HCI and social computing research in Information Systems.
This track focuses on research that improves understanding of user interaction with digital technologies and of people's behavior on social computing platforms, as well as on the effective design of these interactions. We are seeking contributions of any methodological orientation that advance the theoretical and practical understanding and design of information systems in HCI or social computing. Examples include human interactions with intelligent technologies such as Artificial Intelligence, novel (multimodal) interface designs, including concepts for wearables and augmented/virtual reality, and ongoing HCI practices for studying and designing specific interactive systems. Additionally, we invite innovative ideas on user behavior and perceptions on social media. The track welcomes contributions that describe technically rigorous scientific advances in HCI and social computing, with clear links to Information Systems.
Topics of interest include, but are not limited to:
- Human interactions with intelligent technologies such as artificial intelligence
- Psychological, social, cultural, and ethical aspects of HCI in the design of information systems
- Novel (multimodal) interface designs, including concepts for wearables and augmented/virtual reality
- Design, use, and interaction of specific interactive systems, such as conversational agents, persuasive systems, or adaptive systems
- Use of NeuroIS methods and tools in HCI
- Participatory design and methods in HCI
- Investigation and design of personalization and user-adaptive systems (including the use of self-reported data and behavioral data) as well as biosignal-adaptive systems
- Social, individual, and company-related values of social media
- User behavior on social computing platforms
- Social media, health, and well-being
- Bias and discrimination in social media
- Cyberbullying and digital aggression on social media
- Social behavior in the digital space
Track Chairs
|
|
|
|
| Hanna Krasnova, Weizenbaum Institut & Universität Potsdam |
Alexander Maedche, Karlsruhe Institute of Technology |
Jella Pfeiffer, Karlsruhe Institute of Technology |
Julia Seitz, Karlsruhe Institute of Technology |
IT Strategy, Governance & Management
Nowadays, digital technologies and IT systems are an elementary component of many products, services, processes, structures and business models. Corporate competitiveness and digital responsibility are therefore inextricably linked to the successful management of IT and digital innovations. IT is increasingly being called upon to play a strategic role in actively shaping the company’s value creation. To this end, the IT function not only deals with the requirements of customers, employees and partners of the company, but also develops, evaluates and introduces digital innovations and thinks about the transformation of the organization. For example, the business and IT sides of the organization must be increasingly integrated in terms of control, structure and process organization. The ecosystem of innovation partners and IT service providers must be increasingly included in strategy development and implementation. And last but not least, digital skills and competencies must be developed and promoted throughout the company.
This range of topics raises many important questions about the social, economic, organizational and technical aspects of strategic IT management and organizational change. We invite researchers to submit their work results and solutions to these questions in the “IT Strategy, Management & Governance” track. The track is open to different research methods.
Topics of interest include, but are not limited to:
- Development, alignment, and implementation of IT strategies
- Governance of IS/IT (e.g., changing C-Level roles and challenges (CIO, CDO, etc.), portfolio management)
- IS/IT management (e.g., Agile, projects, software development, structures, processes, algorithms for matching and control)
- Management and transformation of enterprise architectures
- Organizational development and IS/IT (e.g., Scaled-Agile, (Biz)DevOps, Bimodal-IT, organization of AI deployment, blockchain, analytics, platforms for organization)
- Management of skills and competencies in IS/IT
- IS/IT ecosystem management (e.g., supplier management, IT outsourcing, cloud computing, hybrid work alignment, gig and freelancer integration)
Track Chairs
|
|
|
| Marina Fiedler, Universität Passau |
Anne-Sophie Mayer, LMU München |
Daniel Beimborn, Universität Bamberg |
Process Science
Business process management (BPM) has established itself as a cross-disciplinary management tool. By using BPM methods and tools, companies aim to identify, evaluate, design, implement, manage, and monitor business processes in order to effectively and efficiently provide added value to internal and external customers. BPM encompasses various areas such as the (re)design of business processes, process mining, robotic process automation, and predictive and prescriptive process control. In many of these areas, the use of artificial intelligence (AI) is currently being considered. The aim of this track is to discuss the various facets of BPM from a management and technology perspective and to identify how BPM can be further developed to address current challenges at the individual, organizational, and societal levels. We welcome contributions from all methodological directions that shed light on a broad spectrum of BPM research from both an organizational/social and a technical perspective.
Topics of interest include, but are not limited to:
- Exploratory process management and process innovation
- Business process management and co-creation
- Business process management and the management of digital transformation
- AI-based process analysis and process mining
- Organizational routines and routine dynamics
- Process mining in organizations
- Process automation using technologies such as (Gen)AI, RPA, Chatbots, etc.
- Workarounds and ambidexterity in process innovation
- User-driven BPM
- Responsible, human-centric, and socially sustainable BPM
- Green BPM
Track Chairs
|
|
|
| Christian Bartelheimer, Universität Göttingen |
Kate Revoredo, Humboldt-Universität zu Berlin |
Ralf Plattfaut, Universität Duisburg-Essen |
Digital Government & Smart Cities
Digitalization presents opportunities to strengthen public value and address societal, economic, and ecological challenges. However, public organizations, which play a key role in delivering public value, often struggle to realize this potential. Reasons for this can be manifold, including technological impediments, organizational inertia, or individuals’ lack of competences and resistance to change.
In the public sector’s quest to redesign urban areas with regard to climate-neutrality and intelligent networks, the concept of the Smart City gains particular importance. The shift towards intelligent, interconnected cities extends beyond the mere digitalization of services, aiming for a more efficient, greener, and socially integrated city. This development intensifies the debate about potentials and applications, as well as the limits of digital trends such as data-driven governance, blockchain, and AI in the public sector.
Public organizations should create the framework conditions to facilitate the implementation of Smart Cities, making our cities more efficient, sustainable, and livable. This includes networked urban infrastructure, smart traffic management, energy-efficient building management, access to digital education, or improved provision of digital public services. Thereby, ecological, social, ethical, and economic aspects must be regarded simultaneously, which makes the implementation of digital government and smart cities a complex endeavor. A key aspect therein is the cooperation between and management of actors at local, national, and international levels, as well as cities, businesses, research institutions, and civil society.
This track attracts innovative research on the topics “Smart Cities & Digital Government” from various disciplinary approaches and methodological perspectives. The focus is on how integrated, intelligent urban development can shape a sustainable and equitable future. The track is aimed at scholars from the fields of Information Systems / business informatics, administrative sciences, urban planning, and adjacent disciplines, proposing new perspectives and solutions to the development of digital government and smart cities.
Topics of interest include, but are not limited to:
- Data-Driven Government
- Open Data and Open Government
- Smart Government and Smart Governance
- Smart Cities: Projects, platforms and applications
- Liveability and quality of life in Smart Cities
- Digital sovereignity and trust mangement
- Adoption and use of digital trends (e.g., block chain, RPA, AI, automation of public service)
- AI in public organizations
- Transformative effects of public sector digitalization
- Transformational government and innovation management
- Digital government strategies
- Online Acces Act: Implementation, potentials, problems
- Digital competences, vocational training, education in the public sector
Track Chairs
|
|
|
| Michael Koddebusch, Universität Münster |
Tobias Guggenberger, Universität Bayreuth |
Bettina Distel, Bundesinstitut für Bau-, Stadt- und Raumforschung |
Digital Twins
Digital twins form an interdisciplinary field of research at the intersection of information sciences, computer sciences, logistics, and mechanical engineering. This field of research deals not only with the technical design of digital twins, but also with the organizational and societal consequences of their use, as well as the conditions for their value-adding and sustainable use in companies and value creation networks. A digital twin can be understood as a digital representation of real systems that integrates various data sources and creates a bidirectional link between the digital and physical worlds.
The continuous synchronization of these two levels is essential in order to reliably reflect changes in the real state in the digital model. The aim of such systems is to significantly increase the quality of decisions, the efficiency of technical processes, and transparency throughout the entire life cycle. Through advanced data analytics and IoT connectivity, it is able to map various attributes and thus realistically reflect almost every facet of a product, process, service, or even an entire organization. However, with the growing possibilities for data collection, processing, and evaluation, especially in the context of artificial intelligence, new challenges and questions are emerging for research on digital twins within information sciences.
This track focuses on findings that contribute to a better understanding, modeling, and use of digital representations of physical artefacts, processes, or value creation networks. We are looking for contributions of an empirical or design-oriented nature We are looking for contributions of an empirical or design-oriented nature that provide theoretical or practical advances in the design, implementation, or use of digital twins. This includes, for example, questions about real-time capability, hybrid modeling, semantic interoperability, simulation- and AI-based decision support, or the embedding of digital twins in operational and strategic information systems. In addition, papers are welcome that deal with the perception, acceptance, and use of digital twins in organizations or analyze their impact on work processes, governance structures, and economic value creation, also taking sociological approaches into account.
Topics of interest include, but are not limited to:
- Architectures and implementation methodologies
- Data models and advanced data analytics tools for Digital Twins
- Data security for Digital Twins
- Smart interfaces and connectors to information systems
- Software architectures for next-generation MES
- Artificial Intelligence (AI) for Digital Twin Design and Operations
- Sustainability and energy-efficient operation of Digital Twins
- Virtual Commissioning and emulations
- Digital Product Passports
- Digital Twins and the Circular Economy
- Digital Twins in domain-specific contexts, e.g., manufacturing, healthcare, fintech
- Case studies and industrial applications of Digital Twins
Track Chairs
|
|
|
| Hendrik van der Valk, TU Dortmund |
Christian Koldewey, Universität Paderborn |
Dimitri Petrik, Universität Stuttgart |
From Generative AI to Agentic IS: Impact on Individuals, Organisation and Society
In recent years, advances in Artificial Intelligence have not only opened new avenues for the machine processing of data and information but have also heralded the transition from purely data-focused tasks to complex, knowledge-based, and even creative endeavors. Consequently, information systems are evolving from passive tools into autonomous entities capable of learning, adapting content, interacting, and acting independently. This fundamental shift of agency from humans to agentic IS artifacts forms the foundation for the next generation of information systems. Collaborative forms of work are emerging in which tasks are no longer merely supported but bidirectionally delegated, necessitating extensive opportunities for research as well as a reevaluation of existing concepts and mindsets.
While it remains challenging to precisely assess the influence of GenAI and agentic systems on our global society, the impact of this new type of information system is already evident at organizational, technological, and behavioral levels. However, alongside transformative benefits, new challenges and potential drawbacks are also arising. With the increasing autonomy of these systems, questions regarding accountability and responsibility in the delegation of decisions are moving into focus. Therefore, it is imperative to evaluate this next generation of information systems from a scientific perspective and to develop socio-technical solutions that harness these technologies for the benefit of individuals, organizations, and society.
Against this background, this track offers a forum for researchers across all streams of Information Systems to shape the next generation of information systems. We particularly welcome contributions at the individual, organizational, and societal levels that focus on the design and impact of GenAI and Agentic IS. This includes new design methodologies, conceptual frameworks, and tools, as well as studies on the behavioral implications of this paradigm. We encourage authors to critically examine the implications of the shift in agency and the associated consequences at all levels, particularly regarding decision delegation, questions of accountability, and the influence on human skills and judgment in interactions with agentic systems, to advance the discourse between science and practice.
Topics of interest include, but are not limited to:
- From Human-GenAI Collaboration to Human-Agent Teaming
- The Psychology of Delegation: Trust and Control in Agentic IS
- Shifting Agency: From Passive Tools to Autonomous Entities
- Designing Delegation in Agentic Systems
- Data Infrastructures for Agentic IS
- Accountability, Responsibility, and Liability in Agentic IS
- The Role of Human Judgment and Oversight in Automated Decisions
- Agent-driven Data Curation and Quality Management
- Design Principles and Methodologies for Agentic IS
- Privacy, Security, and Risk in Autonomous Agent Ecosystems
- Autonomous Knowledge Management Systems
- Co-Creation and Value Generation with Agentic IS
- Workforce Transformation: Skills for Supervising and Managing Agents
- Data Governance and Sovereignty in Autonomous Systems
- Generative AI in Organizational Data Management
- Risk assessment in the use of agentic IS in Data Management
Track Chairs
|
|
|
| Gero Strobel, Universität Duisburg-Essen |
Sarah Hönigsberg, ICN Business School, France |
Frederik Möller, Technische Universität Braunschweig |
Design, Development, Engineering & Management of Services & Software-Systems
Services are an essential part of our everyday lives and of business relationships between companies and organizations. At the same time, they are significantly influenced by innovations such as generative AI and agentic AI. Services come in various forms that fulfill different functions: human-centric services; digital, data-based and AI-based services; smart, AR- and VR-based services; services based on hybrid intelligence; B2C, B2B, B2B2C services and many more. As services are typically offered within complex service systems that include a large number of stakeholders and new technologies, this ecosystem of human and other (AI, etc.) agents requires an integration of diverse resources for value creation. A consistent customer and user orientation as well as an intelligent orchestration of these service systems are crucial here; not only to make services successful, but also to ensure the efficient and effective development and provision of services. In this context, Service Engineering and Service Systems Engineering aim to provide methods, models, and tools that enable the systematic development of services and service systems and their corresponding ecosystems.
This track invites the submission of papers that present current and relevant research results on services and service innovation, as well as service engineering and service systems engineering. The context of services in this track is not restricted, but can range from personal services, innovative technologies in service processes to fully automated services and service offerings integrating various service types. We invite design-oriented papers as well as qualitative and quantitative-empirical contributions. Conceptual or theoretical contributions that contribute to a better understanding of all types of services and service systems are also welcome.
Topics of interest include, but are not limited to:
- Methods and models for Service Engineering and Service Systems Engineering
- Design, modularization, and evaluation of (smart) product-service systems
- Human-centered and experience-driven service design
- Artifact design for digital service innovation
- Digital servitization and data-driven service innovation
- Organizational capabilities and transformation for service innovation
- Success factors, risks, and failures in service innovation
- Value co-creation, co-destruction, and service ecosystem dynamics
- AI-, data- and GenAI-based services and business models
- AI-based service systems engineering and automation
- Hybrid intelligence in service provision (human-AI collaboration)
- Conversational agents, service robots, and autonomous service technologies
- Responsible and trustworthy AI in service contexts
- Design and management of service and work processes
- Integration of service and work systems in modern work environments
- Changing roles, skills, and human-technology interaction in service delivery
- Digital service ecosystems and platform-based business models
- Interorganizational and ecosystem-based service systems
- Governance, orchestration, and value creation in service ecosystems
Track Chairs
|
|
|
| Christoph Peters, Universität der Bundeswehr München |
Martin Semmann, Universität Hamburg |
Juuli Lumivalo, University of Jyväskylä |
Digital Wellbeing, Digital Healthcare & Healthcare Management
Healthcare systems around the world continue to face increased pressure and ongoing challenges, including a shortage of staff, increased demand, and budget cuts. The World Health Organization, for example, estimates a global shortage in healthcare workforce of approximately 10 million health workers by 2030, mainly in low- and lower-middle-income countries (WHO, 2024). Therefore, efficient use of (staff) resources, attractive working conditions, and increasing digitization efforts are crucial. The need for decision support for healthcare processes and services based on optimization, simulation, and information technology research is only increasing. In their review motivated by the short-term use but rapid implementation of digital solutions during the COVID pandemic, Majcherek et al. (2024) concluded that there is still a need to build a digital infrastructure for the healthcare industry in most European countries. Recent developments further emphasize the importance of integrated planning with a system’s perspective, as well as the need for interdisciplinary approaches that combine knowledge from different areas together with strong collaboration between research and practice.
Research into how designing information systems (IS) can help to digitally transform health care practices, organizations, and industries is a classical topic that has concerned researchers in our field for many years (Agarwal et al., 2010; Baird et al., 2018; Burton-Jones et al., 2019). The transformative effects that digital technologies have on the delivery of health care services is significant as data and evermore potent algorithms contribute to changes in the roles that citizens, patients, clinicians, health care managers, and researchers play in the delivery of health care services (Essén & Värlander, 2019; Jarvenpaa & Essén, 2023; Sunyaev et al., 2024). At the centre of all these dynamics lies a key design challenge: how to integrate systems, algorithms, and data in a human-centred way (see also, Bardhan et al., 2020).
Decision support systems (DSS) play a crucial role in healthcare, not only in the form of clinical decision support systems to assist physicians and other health professionals in medical decision making, but also to support logistical and organizational processes. Holistic and interdisciplinary research on decision support systems is crucial for a successful application of DSS in healthcare practice. This includes not only the design of the underlying algorithms and methods, e.g. from the areas of Operational Research and Artificial Intelligence (AI), but also the overall design of the DSS and the design of the user interface, the interaction of users with a DSS and the integration of a DSS into the processes in practice.
Asking ourselves how we design for human-centred health care services is not trivial because technological designs are one question, but the other is how these designs interact with persons, providers, platforms, and professionals over time. The importance of getting these interactions ‘right’ is as straightforward as finding answers to this question is complicated (Wessel et al., 2023). ‘Classical’ information systems in hospitals such as electronic medical records (Agarwal et al., 2010; Burton-Jones & Volkoff, 2017; Hansen & Baroody, 2020; Oborn et al., 2011) serve as repositories of data that assist professionals in making decisions and, potentially, improve diagnostics in the digital age (Lebovitz et al., 2021, 2022). However, it is not only hospitals that transform, and it is not only electronic medical records that matter for transformations to occur. Laypersons have become more active when it comes to self-managing chronic conditions (Dadgar & Joshi, 2018; Wessel et al., 2019), using platforms to exchange ideas, self-help and find advice (Barrett et al., 2016; Fürstenau et al., 2021), as well as using artificial intelligence-based systems that help to prevent chronic conditions (Wessel et al., 2023). Building on these developments is an increasingly important discussion in health policy asking how digital technologies can be used to reorient incentives and make providers gain from patient outcomes as opposed to the volumes of services provided (Agarwal et al., 2020; M. Porter, 2010; M. E. Porter & Teisberg, 2006). Finally, the renewed interest of researchers in the role that data play for innovation in services, digital tools, and applications (Jarvenpaa and Markus 2018; Rothe et al. 2019; Thiebes et al. 2020; Vassilakopoulou et al. 2018), extends far beyond incremental improvement of diagnostic and therapeutic tools. Broader availability of new health data types such as from single-cell or multi-omic sequencing, 3-dimensional x-rays, and new MRT approaches, life sciences increasingly gain insights into early disease development. New health care applications, thus, can therefore become prospective, suggesting interventions on citizens who have not yet become “patients”. What matters then is to design in ways that effectively integrate these innovations in humans’ everyday lives.
We cast the net wide and welcome submissions that speak to the above-mentioned issues. Our understandings of the terms ‘design(s)’ and ‘designing’ are broad and not limited to applications of well-established approaches such as design science research (DSR) or action design research (ADR), which we welcome to our track. Indeed, we ask for submissions of all types that have the potential to contribute to our understanding of the above-mentioned phenomena, be these related to the importance of classical health care IT topics in the digital age, or questions related to the transformative potentials and impacts of digital data objects, and digital tools. Papers may be focused on original theory-oriented research, design-oriented research, empirical studies, or conceptual work. We are agnostic in terms of methodologies applied.
Topics of interest include, but are not limited to:
- The changing role and management of digital health data for digital innovation for health and well-being
- New impact of digital health tools and digital data objects in- and outside of healthcare, e.g., in times of crisis
- A process perspective explaining dynamics of digital transformation in healthcare
- Change of professional roles, identities, and institutions for value creation in health
- New design of digital innovations for improving patients’ self-management of chronic conditions
- The role of data and tools as inhibitors or promoters for a disease-based health care system
- The role of data and tools like sensors, wearables technologies, and digital health apps as inhibitors or promoters for a patient-centric health care
- The role of digital tools like virtual coaching for autonomy of health care providers and patients
- The role of data and tools for disease intervention vs. prevention
- The relationship between classical hospital information systems and more recent digital innovations in health care
- Changing business models in the context of digital innovation in health care
- Changes in support for people in need for care, including elderly or handicapped, through digital technologies
- The role of new digital technologies like XR, web3.0 and machine learning for creating health data and for creating value from health data
- New modes of capturing value from digital health data, e.g., reimbursement strategies
- New ethical challenges from health data, considering privacy and security
- Digital tools and use of digital health data to connect different participants of health service networks, to support decision making and to improve logistical and organisational processes
- Design of digital tools and the role of IS to support integrated and patient-centred care and integrated planning spanning multiple care forms and/or steps in a patient’s pathway
Track Chairs
|
|
|
|
| Melanie Reuter-Oppermann, Technische Hochschule Würzburg-Schweinfurt |
Hannes Rothe, Universität Duisburg-Essen |
Till Winkler, FernUniversität Hagen |
Michael S. Dohan, Lakehead University |
Artificial Intelligence & Digital Transformation in Industry & Production (Industry Track)
As an applied discipline, business informatics is in direct contact with companies and employs scientific methods to offer insights for practical application. At the same time, practical problems serve as the starting point for new research ideas. This track focuses particularly on industry and manufacturing, and related sectors that have undergone significant transformation in recent years, even though they are traditionally considered part of the "old economy." This transformation is characterized by the digitalization of production and processes and has presented companies with new challenges due to the opportunities arising from AI. In terms of relevance, research findings that examine digital transformation in companies, as well as the application of AI within these companies, are prioritized.
The practical track invites the presentation of research findings on socio-technical solutions that contribute to digitalization in a business context and consider the application of AI. Direct participation by one or more companies—for example, as authors—is required for this track. The research can be based on individual, corporate, or societal levels, examining the application and resulting impacts of these systems. In addition to the relevance of this research, the corresponding scientific rigor must also be considered. This track will particularly focus on methods that exist directly at the interface with practical application.
Topics of interest include, but are not limited to:
- Strategic Approaches to Digitalization
- Practical Solutions for IT Governance in the Digital Age
- Implementation of AI Applications in Industry and Production
- Robotic Process Automation in Various Contexts
- Automation in the Age of AI
- Methods for Introducing AI Applications
- Infrastructural Challenges for Implementing AI
- Efficiency Criteria for the Use of AI
- Digitalization as a Competitive Factor in Production
Track Chairs
|
|
|
| Hermann Sikora, JKU Linz |
David Rückel, JKU Linz |
Christian Stary, JKU Linz |
Student Track
The aim of this track is to involve students with their own research results in WI2026. The track is primarily aimed at master's level students who would like to present the results of an academic paper (bachelor's or master's thesis, project work) to a specialist audience. Students from all fields of business informatics and related disciplines are invited to submit high-quality papers. Students who do not submit a paper are also welcome to attend the presentations and participate in the Student Track's supporting program.
Submissions must be authored by a student as the first author. The inclusion of PhD researchers is possible if the contribution is predominantly authored by students. The track is open to all methodological approaches and particularly welcomes interdisciplinary contributions.
Specific deadlines apply to the Student Track for submission (April 13, 2026) and notification to authors (June 8, 2026) – all other deadlines are the same as for the other tracks!
Topics of interest include, but are not limited to:
- AI applications and AI implementations
- Digitalization and digital transformation
- Business process management
- E-health and e-government
- Strategic aspects of digitalization
- Software and systems development
- IT governance
- Methodology development and integration of methods from other disciplines
Track Chairs
|
|
| Richard Heininger, JKU Linz |
Ursula Niederländer, JKU Linz |