Organizational Systems and Technology

This minitrack provides a venue for design science researchers (DSR) to share their work and interact with like-minded scholars. DSR is a prominent form of engaged scholarship, which combines inquiry with a potential for action and intervention. DSR may be viewed as having four related subfields, from which we welcome submissions:

1. Science of design that focuses on creating ‘new-to-the-world’ socio-technical artifacts. We provide an outlet for researchers doing novel artifact-driven research in information systems (IS) and other fields such as entrepreneurship, operations management, pedagogics, or service research.
2. Design theory studies that focus on the development of theories and design principles concerned with creating new or improved systems based on the kernel or grand theories
3. Designed artifact research focusing on discovering revolutionary outcomes from design science research, i.e., ground-breaking solutions and their applications. Examples include the results of designing and deploying novel data representations, computational algorithms, business intelligence, data analytics, optimization techniques, design of markets, machine learning, and generative AI
4. Design research that focuses on how designers conduct design activities, e.g., the science of design research. Papers in this subfield could potentially come from IS and architecture and design studies

All four subfields are often (but not always) tightly engaged with design practice. Accordingly, they frequently embody participative forms of research that rest on the advice and perspectives of multiple stakeholders in understanding a complex social problem.

The minitrack welcomes submissions from the entire range of alternatives that integrate inquiry with the potential of creating and shaping alternative futures. New tools, such as generative AI and specific tools like GitHub co-pilot, allow for easier exploration and modification of alternative designs. Such work extends the boundaries of human and organizational capabilities by theorizing and/or creating new and innovative artifacts. The building and application of these designed artifacts produce knowledge and understanding of a problem domain and its solutions, potentially transferable to other domains.

Accordingly, this mini track’s scope includes research contributions from all four DSR subfields described above. These include computational and engaged approaches, studies of the practical use of DSR approaches, the use of such approaches to expand theory, and conceptual foundations that significantly and cogently broaden our understanding of the epistemology and methodology of such approaches and their philosophical underpinnings. These include:

1. Developing design artifacts and design theories
2. Evaluating and testing design artifacts and design theories
3. Different approaches to the design of artifacts and design theorizing
4. Design as a creative act in development for systems etc.
5. Advancing theory and practice in designing for systems, etc.
6. Design experiences in organizational systems and technology, etc.
7. New possibilities for design exploration afforded by generative AI
8. Concrete design projects and their outcomes

We will consider papers from the minitrack that advance knowledge in these areas, subject to another round of review(s) and some additional contribution following the Communications of the Association of Information Systems (CAIS) norms and standards to be considered for the Digital Design department of the journal.

Minitrack Co-Chairs:

Tuure Tuunanen (Primary Contact)
University of Jyväskylä
tuure@tuunanen.fi

Matti Rossi
Aalto University
matti.rossi@aalto.fi

Richard Baskerville
Georgia State University
baskerville@gsu.edu

Digital technologies increasingly mediate and shape our work, organization, and daily lives. Innovations such as artificial intelligence, the Internet of Things (IoT), robotics, blockchain, and other Web3 technologies enhance various internal and external activities, including decision-making, collaboration, coordination, and control. Relevant contexts of interest include, but are not limited to:

1. Flexible work arrangements and distributed teams
2. Human-AI interaction
3. Algorithmic workforce management
4. Data sharing
5. Transactional and innovation-based digital platforms
6. Security and compliance applications
7. Interorganizational and community collaboration
8. Cryptocurrency and supply chain management

These developments impact diverse industries, including healthcare, transportation, finance, military, and law enforcement.

While human-machine interaction is crucial for the effective adoption of new digital technologies, vulnerabilities extend beyond weaknesses in these interactions. Vulnerabilities with digital technologies can arise from but are not limited to the beliefs, availability, or condition of technologies; use of technologies by other entities; embedded complexities with physical objects; and a variety of environmental and societal factors.

The presence and interplay of trust traps, power asymmetries, and complacency significantly heighten these vulnerabilities for users and organizations. However, digital technologies can also mitigate such vulnerabilities. What challenges and opportunities arise from vulnerabilities with digital technologies and their mitigation? For example, how does digital responsibility play a role, and what is the role of trust, power, and complacency?

This minitrack aims to foster new understandings of vulnerabilities and explore strategies for counteracting and mitigating them in various organizational and work settings. We are particularly interested in under-explored aspects of trust, power, and complacency in relation to vulnerabilities across a wide array of digital technology contexts. The minitrack helps to advance discussion on vulnerabilities broadly speaking including but not limited to the following:

1. What questions regarding trust, power differences, or complacency should be raised but are currently overlooked in the context of digital technologies?
2. How are trust, power differences, or complacency manifested in ways that are rarely discussed in the literature?
3. How can novel computational approaches shed new insight to vulnerabilities and their dynamics?
4. How do different technological environments impact the trust, power, and complacency dynamics?

We welcome both theoretical and empirical papers that advance understanding of trust, power differences, and complacency in relation to digital technologies across various organizational and work settings. Submissions may employ any acceptable qualitative, quantitative (statistics and econometrics), or computational machine learning methods. We encourage interdisciplinary approaches and papers that consider multiple levels of analysis. We look forward to receiving innovative contributions that address these critical issues in the evolving landscape of digital technologies.

Minitrack Co-Chairs:

Sirkka Jarvenpaa (Primary Contact)
University of Texas at Austin
Sirkka.jarvenpaa@mccombs.utexas.edu

Gene Alarcon
Air Force Research Laboratory
gene.alarcon.1@us.af.mil

Kirsimarja Blomqvist
LUT University
Kirsimarja.blomqvist@lut.fi

Gorkem Turgut Ozer
University of New Hampshire
gt.ozer@unh.edu

Artificial intelligence (AI) is reshaping the manufacturing industry, driving advances in automation, predictive analytics, generative design, and smart production systems. In the context of Industry 5.0, which involves human-centric solutions and sustainable manufacturing, it is crucial to address the evolving interplay between AI and human workers. Industry 5.0 envisions a collaborative environment where humans and machines can potentially work together to enhance productivity and innovation.

However, the extent and nature of this collaboration remain subjects of ongoing research and debate. While AI enhances efficiency and decision-making, workforce competencies often lag behind. The emergence of AI-driven manufacturing roles and the transformation of traditional jobs present challenges for competence development, workforce adaptation, and training strategies.

This minitrack explores how AI is transforming workfroce competence, professional roles, skill requirements, and career trajectories in manufacturing. We seek papers that examine how AI is augmenting industrial work, how new professions are emerging, and how organizations are managing workforce transitions. A key focus is on competence management strategies, training frameworks, and ethical considerations in the AI-powered manufacturing environment. We invite researchers, industry professionals, and policymakers to submit empirical, conceptual, or design-oriented research on AI-driven workforce transformation in manufacturing.

Topics of Interest include:

1. New AI-Augmented Roles in Manufacturing – How AI is redefining job functions in production, quality control, and industrial engineering.
2. AI as a Translator Between Human Workers and Machines – Investigating human-AI collaboration in smart factories and industrial automation, and critically examining the challenges and limitations of such collaboration.
3. Bridging the Skills Gap in AI-Driven Manufacturing – Addressing the mismatch between workforce skills and AI-powered manufacturing processes, and exploring strategies to overcome these challenges.
4. AI in Workforce Reskilling and Training – Exploring new methodologies for upskilling and reskilling manufacturing professionals.
5. AI-Enabled Decision Support in Production and Operations – Examining human-AI collaboration in optimizing production efficiency and logistics.
6. Automation vs. Human Expertise – Identifying which manufacturing tasks AI can replace and which require human oversight, and analyzing the implications for workforce dynamics.
7. Ethical and Workforce Implications of AI in Manufacturing – Analyzing how AI adoption impacts employment, labor dynamics, and workplace ethics, and considering the broader societal implications.
8. Sustainability and Resilience in AI-Augmented Manufacturing – Exploring how AI contributes to sustainable production and resource optimization.
9. Industry 5.0 – Addressing human-centric solutions and sustainable manufacturing, and critically assessing the feasibility and effectiveness of such collaboration.

Selected papers from this minitrack will be invited for fast-track consideration in a special issue on “AI and Emerging Professions: Navigating New Skills and Practices” in the International Journal on Current Issues in Work-Integrated Learning (CIWIL).

Minitrack Co-Chairs:

Ulrika Lundh Snis (Primary Contact)
University West
ulrika.snis@hv.se

Livia Norström
University West
livia.norstrom@hv.se

Helena Vallo Hult
University West
helena.vallo-hult@hv.se

Fatemeh Saadatmand
University West
fatemeh.saadatmand@hv.se

The emergence and recent popularity of tools such as ChatGPT, Claude, DALL-E, midjourney, and Stable Diffusion show the potential of generative AI. Software tools based on artificial intelligence (AI) methods are now used within a variety of organizational routines and practices, creating new types of human-machine configurations and playing an increasing role in the context of contemporary organizing. Application areas include management decision making, manufacturing, and design and creativity. These tools use machine learning models to generate predictive insights. They act increasingly autonomously—i.e., with little or no user intervention—and constitute new types of material agency in the context of contemporary organizing.

As organizations become more reliant on AI tools, they need new management theories, frameworks, and methodologies that can help them understand the implications of using these tools—both at the level of organizational structures and practices. AI based agents often rely on complex internal processing and their behavior is less predictable than that of the types of IT artifacts. This opens up a number of problem areas with regards to managing and organizing AI tools. For example:

1. What is the impact of using AI on those processes that have traditionally been seen as being entirely driven and controlled by humans? What are early examples of such use?
2. In particular, how can AI be useful in group and collective creative processes? Is it proving useful?
3. How does coordination shift as AI tools are used, and what new types of organizational hierarchies and structures are emerging?
4. How do power relations change, and how do different organizational actors use these new technologies to reshape power relations?
5. How can the organization evaluate the ethical implications of deployed AI tools? How can they regulate AI tools?
6. What are relevant KPIs and metrics for assessing the effectiveness of AI applications?
7. How should an organization manage, staff and coordinate AI development teams?

This minitrack aims to contribute to our understanding of the mechanisms through which humans organize together with AI-based tools as well as the process organizations use to develop them. We aim to provide a platform for thought and discussion in this important and emergent field within information systems and IT research. We invite conceptual as well as empirical contributions using different methodological approaches (qualitative, quantitative, design-oriented, simulation, etc.). We think there is a need for case studies, trace data analysis, and ethnographies. We would prefer theory development pieces to frameworks and lit reviews. In addition to the questions raised above, potential topics include, but are not limited to:

1. Trace data: how is AI actually being used?
2. Case Studies and ethnographies: What are people learning? What are the machines learning? What are organizations learning?
3. AI & coordination: How does AI change the way humans coordinate?
4. AI & crypto: How can smart contracts and DAOs create new organizational forms? Are there interesting examples in enterprises? In the public sphere?
5. AI & power: How does AI affect corporations, markets, and peer production structures? Who is capturing value?
6. AI & governance: Who runs the technology? What does the technology run?
7. AI & software development: How to manage AI project and deployment risk?
8. AI as coder: how well do co-pilot and other tools work in terms of increasing programmer productivity?
9. AI & creativity: How can AI be creative? How can humans and AI be co-creators? How does and should attribution work when AI synthesizes based on human-created artifacts?
10. AI & design: What has AI designed? Can it and should it design itself?
11. AI & innovation: How does AI foster or corrupt innovation?
12. AI & news work: How does AI change news and civic engagement?
13. AI & crowds: What do crowds do for machine learning, and what’s in it for the crowds?
14. AI & organizational routines: How does AI change the nature of work?

Minitrack Co-Chairs:

Aron Lindberg (Primary Contact)
Stevens Institute of Technology
aron.lindberg@stevens.edu

Stefan Seidel
University of Cologne
stefan.seidel@uni.li

Jeffrey Saltz
Syracuse University
jsaltz@syr.edu

Jeff Nickerson
Stevens Institute of Technology
jnickers@stevens.edu

Blockchain, the foundational technology behind cryptocurrencies such as Bitcoin, has garnered significant attention in recent years due to its potential to either improve current practices or create new ones in both the public and private sectors. Originally designed to address the double-spending problem, it is now being explored as a fundamental technology in scenarios where traditionally a trusted third party is required. Once transactions are incorporated into the entirety of the chain, the records become immutable, making alterations impossible. Only new transactions and blocks can be added, safeguarded by one-way cryptographic functions. What’s crucial is that this system facilitates authenticated data communication among participants in the distributed ledger, such as a supply chain, without the need for intermediation from a trusted central organization. Essentially, it empowers individuals who may not be acquainted with each other to place trust in a shared record of events.

Moreover, blockchains use smart contracts which represent self-executing agreements wherein the terms of the contract are explicitly encoded into computer code. These contracts autonomously enforce and execute their terms once predetermined conditions are satisfied, contributing to the reduction of uncertainty and fostering confidence among stakeholders who may not typically trust one another. In addition, with the emergence of the decentralized web for fostering a more secure, private, innovative, and inclusive digital environment, challenging the traditional centralized models that dominate the current internet landscape, as well as the convergence of other technologies such as IoT, AI, VR/AR and so on, at present, few, if any, can anticipate the complete scope of disruptive innovations that will arise from this evolving technology.

Recent advancements in blockchain technology have also catalyzed the rapid development of stablecoins and central bank digital currencies (CBDCs), sparking global policy debates regarding financial stability, monetary sovereignty, and regulatory oversight. Stablecoins—cryptographic assets pegged to fiat currencies or commodities—have emerged as a pivotal component of decentralized finance (DeFi), enabling faster transactions and reducing price volatility in digital payments. However, their widespread adoption raises concerns about systemic risks, liquidity mismatches, and the potential for regulatory arbitrage. Meanwhile, CBDCs are a paradigm shift in monetary systems with governments exploring digital fiat alternatives to enhance financial inclusion, improve payment efficiency, and strengthen central bank control over monetary policy. However, the implications of CBDCs on financial privacy, commercial banking stability, and the decentralization ethos of blockchain remain contentious. As policymakers and institutions navigate the regulatory landscape, this minitrack invites research that critically examines the intersection of blockchain, stablecoins, and CBDCs—assessing their impact on global finance, economic sovereignty, and the evolving digital economy.

For these reasons, it is important for academics to systematically research this field, at various levels. Conferences play a key role in disseminating knowledge about Distributed Ledger Technology (DLT – including blockchains) due to the speed at which developments occur, outpacing the rate that journals can accommodate submissions for more length peer review and revisions. The minitrack explores the transformative potential of blockchain technology in fostering decentralized systems and innovation across industries. Sessions will cover key topics such as decentralized finance (DeFi), smart contracts, tokenization, and blockchain’s role in enhancing transparency, security, and trust, providing insights into real-world applications, emerging trends, and the challenges of scaling decentralized solutions. Topics of interest include, but are not limited to:

1. Innovative uses of Blockchain technology
2. Blockchain case studies, applications, and implementations
3. Blockchain and privacy, security, and identity
4. Blockchain and digital transformation
5. Decentralized Finance (DeFi)
6. Decentralized Autonomous Organizations (DAOs)
7. Decentralized Applications
8. Central Bank Digital Currency (CBDC)
9. Non-Fungible Tokens (NFTs)
10. Tokenization
11. The social and organizational impact of blockchain
12. Barriers and enablers in blockchain adoption
13. Blockchain and business model innovation
14. Regulatory frameworks for Blockchain
15. Governance and Blockchain
16. Verticals using Blockchain (financial, healthcare, energy, transportation, others)
17. Blockchain in e-government and public administration
18. Blockchain and the Internet-of-Things
19. Blockchain in education
20. Blockchain in solving migration and refugee issues
21. Blockchain-driven marketplaces
22. Uses and challenges of smart contracts
23. Technology and infrastructure issues in Blockchain
24. Blockchain and Metaverse
25. Organizational adoption of Blockchain technologies
26. The labor market for talent in building and applying DLTs
27. Leveraging blockchain technology for sustainable practices.

Minitrack Co-Chairs:

Soulla Louca (Primary Contact)
University of Nicosia
louca.s@unic.ac.cy

Roman Beck
Bentley University
romanbeck@bentley.edu

Christos Makridis
University of Nicosia
makridis.c@unic.ac.cy

For decades, organizations have sought to better understand, analyze, improve, and auto-mate their business processes. Recent advancements in Process Technology have introduced entirely new ways to achieve these goals. In particular, Process Mining and AI-driven approaches have unlocked unprecedented opportunities. Process Mining enables organizations to leverage transactional data recorded by Information Systems to enhance process performance in areas such as efficiency, quality, and compliance. Meanwhile, AI and Generative AI (Gen-AI) Process Technology support business process management across various lifecycle stages. For example, AI can assist modelers through co-modeling, automate process improvements, or apply predictive monitoring to identify and mitigate potential bottle-necks and inefficiencies. While these innovations present exciting possibilities, they also raise important organizational considerations, such as ensuring fairness, compliance, and responsible AI usage through Explainable AI (XAI) techniques.

Given the large interest in this topic in both academia and practice, the goal of this mini-track is to promote scientific exchange on Business Process Technology. The minitrack shall enable researchers to present and discuss innovative approaches, techniques, methodologies, and models to design, adopt, implement, operate, evaluate, and govern the data-driven analysis of business processes. The Business Process Technology minitrack invites contributions on topics including, but not limited to:

1. Process Discovery
2. Conformance Checking and Analysis
3. Decision Mining, Decision Analytics, Decision Drift Analysis
4. Declarative and Hybrid Process Analysis
5. IoT-Aware Process Analysis and Technology
6. Predictive-/Prescriptive Process Monitoring
7. (X)AI/Gen-AI Process Technology
8. LLM-driven Process Analysis
9. Robotic Process Automation
10. Hyper-automation
11. Cognitive Process Automation
12. Automated Process Analysis and Improvement
13. Adoption of Process Technology
14. Governance of Process Technology
15. Digital Twin Technologies

Minitrack Co-Chairs:

Despite all the benefits of artificial intelligence (AI) and digitalization, recent research findings and anecdotal observations have consistently revealed concerning evidence that these technologies may also be hiding potentially serious “dark sides” at individual, organizational, and societal levels. For example, from the organizational perspective, studies have shown that employees waste approximately one-fourth of their workday on digital interruptions. Similarly, employees’ misuse of organizational IT could account for 50-75 percent of all information security breaches. The situation is similarly concerning on the user’s side. For example, the increasing popularity of social media platforms has led to a significant rise in technology-mediated dangerous behaviors, including addictive and problematic IT use, sharing private information and falling victim to phishing scams, and individual deviant behaviors such as online harassment and swearing.

Furthermore, the rise of AI, i.e., “AI”ization, has added several new and complex concerns to this array of issues. Specifically, the rise of AI affords unfair and biased recommendations and deviant behaviors, such as algorithm aversion. Moreover, recent advancements in generative AI, such as large language models, their ability to generate human-like, convincing claims, and their innate tendency to “hallucinate” and generate fake images and videos (e.g., “deepfake” technology), are of particular concern. As these technologies are used for content generation on social media, their hard-to-detect hallucinations can further increase users’ likelihood of falling victim to misinformation. These concerns also raise questions about the social responsibility of technology giants as well as possible negative effects of technologies on children and youth.
To make matters worse, digital and AI technologies are increasingly facilitating both organizational and organized cybercrimes. Sadly, rarely a week goes by without a cybercrime being reported in the media, from cyberterrorism to hijacking individual accounts and hacking organizational systems, extortion, exit scams, fake investments, and blatant information manipulation for financial gain. The recent AI advancements, their accessibility, and the lack of regulations regarding their use have further intensified these concerns.
The fact that the digital and AI artifacts that we develop and the process we support may underlie such negative effects behooves us, as a research community, to pay closer attention to the “dark sides” of AI and digital technologies. Over the last eight years, this minitrack has advanced the understanding of such issues and the efficacy of solutions for mitigating them. We would like to continue this endeavor.

To that end, this minitrack welcomes theoretical, empirical, and technical papers examining the negative consequences of AI, digitalization, and IT use, in general, at individual, organizational, and societal levels, and potential solutions for mitigating them. The objective of this minitrack is to focus not only on the antecedents, development processes, and consequences of numerous phenomena related to the negative consequences of AI and digital technologies but also on potential strategies, techniques, and design considerations for behavioral and technological interventions. We seek to build a forum of discussions that can provide a deeper understanding of the potential consequences regarding the dark sides of these technologies. Further, we hope this forum continues to shape guidelines for designing and implementing solutions to minimize the negative consequences of AI and digital technologies.

Submitted papers can focus on, but are not limited to, the following areas related to the dark sides of AI and digital technologies. We acknowledge that new forms and types of “dark sides” will emerge over time, and we are open to topics that may extend this list.

1. Dark sides of artificial intelligence and/or robots, including ethical and moral concerns
2. Dark sides of datafication
3. Algorithmic bias, fairness, and prejudice
4. Technology-mediated dangerous behaviors, such as IT addictions, misuse, abuse, and impulsive use
5. IT interruptions and Cyber loafing
6. Adverse psychological and physiological effects of AI and digital technologies, including Technostress
7. Cyberviolence (e.g., cyberstalking, cyberbullying)
8. Dark sides of social media
9. Online Misinformation, disinformation, and fake news
10. Cyberterrorism (e.g., online extremist networks)
11. Privacy concerns about AI and digital technologies
12. Cybercrimes and security concerns of AI and digital technologies, such as cybertrespass (e.g., unauthorized system access), cyber-deception and cyber-theft (e.g., online fraud, identity theft), Ransomware, and Phishing and scamming

Submissions are welcome and encouraged from different schools of thought (e.g., information systems, psychology, cognitive science, decision sciences, communications, sociology, social networks, organizational behavior, neuroscience, computer science, marketing, and criminology), which can advance our knowledge of the antecedents, processes, interventions, and consequences of the dark sides of AI and digital technologies. This minitrack invites relevant and rigorous studies without restriction for the methodologies used, units of analyses, and levels of theorization.

Minitrack Co-Chairs:

Hamed Qahri-Saremi (Primary Contact)
Colorado State University
Hamed.Qahri-Saremi@colostate.edu

Ofir Turel
University of Melbourne
oturel@unimelb.edu.au

Isaac Vaghefi
Baruch College, The City University of New York
isaac.vaghefi@baruch.cuny.edu

Piotr Siuda
Kazimierz Wielki University
piotr.siuda@ukw.edu.pl

Data analytics (DA) often refer to information technologies and processes that support timely and efficient data mining, statistical analyses, and business reporting. The use of DA techniques and tools can help firms optimize operational processes, improve customer experiences, detect fraud, and drive strategic growth. Given the growth in the use of DA, it has become imperative for the top management of firms to use DA to gain a competitive edge and make data-driven decisions.

DA is typically accompanied by data visualization, which is the graphical representation of data using charts, graphs, maps, and other visual tools to communicate complex information. Data visualization plays a crucial role in DA by making patterns, trends, and outliers easier to comprehend by users of DAs.

While DA and visualization provide valuable insights into business processes, not all top executives and management teams rely on DA to optimize their business processes because of different strategic choices, risks in governance, economic concerns, and environmental uncertainties. Despite the well-established importance of DA and visualization, there is less research examining the factors that influence the effectiveness of DA and visualization in facilitating management to optimize business processes and outcomes.

In this minitrack, we seek research papers and experience reports that explore whether and how top management teams use state-of-the-art DA and visualization applications to detect inefficiencies in business processes and to maximize the odds of success under micro- and macro-uncertainties. Analyzing and visualizing data enable top management teams to gain insights into their internal and external environments and to better sense changes in their markets. With data becoming increasingly rich and multiple-dimensional, how businesses can take advantage of the insights generated by DA to better understand uncertainties and opportunities, detect anomalies, and improve workflows are important questions. Further, we seek to focus on some key areas, including the use of generative AI in innovating business strategies and processes, new visualization methodologies and techniques, and process optimization empowered by unstructured data.

This minitrack will be beneficial for interdisciplinary communities focusing on Information Systems, Management, Leadership, Strategic innovation, and Business Value Measures. Possible topics of interest include but are not limited to:

1. Using Data Analytics to Optimize Business Processes
2. Enhancing the Data Visualization of Business Processes
3. The Role of Data Analytics in Supply Chain Management
4. Data Analytics and Operations Management
5. Applications of Generative AI in Business Processes
6. Current Practices of Data Visualization in Control Processes and Risk Management
7. Data Analytics and Continuous Monitoring and Optimization
8. The Use of Data Analytics and AI in Process Mining

Authors will be encouraged to submit papers which can be selectively considered for publication in the Journal of Information Systems (JIS) at the authors’ prerogative.

Minitrack Co-Chairs:

Jee-Hae Lim (Primary Contact)
University of Hawaii at Manoa
jeehae@hawaii.edu

Tu Xu
Renmin University of China
xutu@rmbs.ruc.edu.cn

Societies are now migrating into a futuristic legal space whose structural conditions depend increasingly on the enabling and inhibiting aspects of cutting-edge digital technology. Private and public actors alike must therefore understand how data-driven and AI-enabled technologies can be used in a legitimate, necessary, and proportional way, and at the same time assess risks attached to their particular use trajectories. This is a complex balancing act that inevitably creates legal and ethical uncertainty, which generates ambiguous dilemmas and paradoxical tensions at different societal levels. As a result, these actors face a dynamically changing landscape in constant search of legal and ethical standards.

Given this complex digital transformation, AI governance, data regulation, and digital compliance have become front and center of legal and ethical debates. These discussions are fueled by a societal urge to ensure data use that meets desired levels of transparency, accountability, and privacy. Indeed, at the same time, emerging frameworks such as the EU AI Act, GDPR, and global data governance policies are ultimately reshaping how data is collected, processed, and managed.

Against this background, this minitrack explores the challenges, frameworks, and strategies associated with governance, regulation, and compliance in the era of data-driven and AI-enabled technologies. We seek papers that examine the intersection of these technologies and emerging regulatory trends, data protection laws, algorithmic accountability, and compliance mechanisms.

We invite researchers, policymakers, and practitioners to submit empirical, conceptual, or design-oriented research on AI governance, data regulation, and digital compliance related to areas such as legal and ethical constraints on algorithmic data processing, cross-border data governance, privacy-enhancing technologies, and socio-technical implications of regulatory enforcement. Topics of Interest include:

1. AI and data protection – Investigating challenges related to personal privacy, privacy-enhancing technologies, and consent mechanisms.
2. Algorithmic accountability and transparency – Addressing regulatory demands for explainability, bias mitigation, and fairness in AI decision-making.
3. Cross-border data regulation and governance – Analyzing global trends in data sovereignty, data localization, and cross-jurisdictional governance challenges.
4. Compliance automation and AI-driven governance – Exploring AI’s role in automated compliance monitoring, risk assessment, and regulatory enforcement.
5. Compliance in AI governance and data regulation – Examining how organizations adapt to evolving data laws, including GDPR, the EU AI Act, and global regulatory frameworks.
6. Ethical AI and responsible data use – Investigating ethical considerations in AI-driven data processing, including fairness, trust, and human oversight.
7. Balancing regulation and innovation – Examining how regulatory frameworks impact AI development, business models, and data-intensive research.
8. Security, risk, and AI in regulatory compliance – Exploring AI’s role in cybersecurity, data protection, and risk management.
9. Emerging global standards and interoperability – Analyzing international efforts to harmonize AI governance and data regulation across jurisdictions.

Minitrack Co-Chairs:

Rickard Lindgren (Primary Contact)
University of Gothenburg
rikard.lindgren@ait.gu.se

Fatemeh Saadatmand
University West
fatemeh.saadatmand@hv.se

Organizations are increasingly integrating data and BI&A into their business models. However, achieving this transformation is not only a question of technology; it demands profound changes in how organizations think, organize, and lead. Both data management and BI&A play critical roles in this transformation, each contributing uniquely to business success. Data management ensures the foundations for data quality, governance, and strategic alignment, providing the necessary infrastructure to manage data as a strategic asset. BI&A, on the other hand, turn this data into insights, predictions, and innovations that drive business value and competitive advantage.

While the importance of data management and BI&A is well-recognized in practice, research on their distinct and combined contributions remains limited. Much remains to be learned about the artifacts, methods, and organizational capabilities necessary to harness them effectively—both independently and in tandem—and ultimately translate them into business value.

This minitrack seeks to spark forward-looking conversations on how organizations can navigate the individual and joint contribution of data management and BI&A to unlock business value. Papers using theory building, design research, action research, case studies as well as analyses of existing or innovative applications are welcome. Due to the practical relevance of the minitrack scope we also invite practitioners to submit their work, provided it includes a conceptual or generalizable contribution. We invite papers that investigate topics which include, but are not limited to, the following:

1. Business Intelligence & Analytics (BI&A) in the Data-Driven Organization
   • Applications and organizational outcomes of BI&A
   • Data visualization and storytelling
   • Visual analytics and augmented analytics
   • Collaborative analytics
   • Data and analytics as a service, Self-service BI
   • Case studies of data and analytics-driven organizations
   • User-driven innovation approaches for BI&A and/or data projects
   • Citizen science for data and analytics
2. Modern Data Management
   • Data productization, valuation and monetization
   • Data quality, data cataloging
   • Data/analytics/AI governance and strategy
   • Next level data and analytical architectures such as data mesh architecture
   • Successful cases of data-driven transformation
   • Data/analytics/AI Literacy as a democratizing force for value creation
   • Data culture and data ethics
   • Data management and AI as two sides of a coin, e.g. AI for data quality and data quality for AI

Minitrack Co-Chairs:

Barbara Dinter
Chemnitz University of Technology
barbara.dinter@wirtschaft.tu-chemnitz.de

Sule Balkan
Ameriprise Financial
balkansule@gmail.com

Hippolyte Lefebvre
University of Lausanne
hippolyte.lefebvre@unil.ch

Roland Mueller
Berlin School of Economics and Law
roland.mueller@hwr-berlin.de

Deep into the digital age, organizations must continually and relentlessly innovate with digital technologies to succeed or to just survive. This innovation involves generation of digital products and services (digital innovation), and the consequent fundamental changes to organizations, organizational networks and industries (digital transformation). These innovations are often created and realized through new ventures either in startups or existing organizations (digital entrepreneurship). The goal of this minitrack ‘Digital Innovation, Transformation, & Entrepreneurship’ is to examine the nexus between digital technologies, consequent innovation and entrepreneurial action by offering a venue for original and innovative research that focuses on digital technologies, associated innovation, and related entrepreneurial activities and forms.

The minitrack solicits three types of submissions: (1) the antecedents, processes, infrastructures, outcomes, and organizational settings associated with the generation and appropriation of novel product and service innovations enabled by digital technologies; (2) new organizing structures and processes enabled by digitalization, as well as associated novel organizational arrangements and business models, the transformation process, antecedents, and outcomes; and (3) new ventures that involve the identification and deployment of emerging, radical innovations in digital technologies such as blockchain, 5G, IoT, and bots, robots, and the host of technologies rooted in different sorts of artificial intelligence. Next we will describe each of these types of submissions with examples of each.

1. Digital Innovation
These submissions investigate the role and functions of digital technologies within innovative products or services, and how these technologies impact consequent organizational innovation and strategy (e.g., questions of architecture, modularity, platform governance, standards and means of systems integration). Topics can include:
• Organizing for digitally-enabled products and services
• Products and services developed around novel and emerging digital technologies
• Digital technologies and service science
• Digital convergence and organizational and industrial organization
• Digitalization of physical products and changes in product strategies
• Design thinking for digital
• Innovating within digital service ecosystems and on platforms
• Digital product architectures
• Digitalization, product modularity, and modes of organizing
• Digital controls and control points and organizing
• Machine Learning, AI, and related product capabilities
• Products and services enabled by emerging generic digital technologies (e.g., robots, 3D printing, sensor networks, blockchain, quantum computing, etc.) and novel digital phenomena such as mobility, social, big data, cloud computing, service architectures, virtual/augmented reality, Internet of Things.

2. Digital Transformation
As organizations transition from the industrial to the digital age, they need to undergo a transformation in how they organize and control for new digital processes. Submissions that investigate the role of digital technologies in inducing and enabling organizational change, including innovative strategies, new business models, new organizing structures, processes and tasks enabled by digital technologies and their adaptation to digitally enabled forms of organizing. Topics include:
• Industrial vs. digital innovation regimes and related analyses of change
• Short and long term analyses of digital transformation and innovation waves
• Digitally enabled business models and strategies,
• Digital strategies, agility, and organizational learning
• Digital platform ecosystems
• New approaches for organizing problem solving driven by the use of Machine Learning technologies
• Sociotechnical and sociomaterial conceptualizations and forms of organizational change
• Digital technologies and organizational design, digital business units
• Digital technologies and organizational routines and business processes
• Business process change in organizations and the role of digital technologies
• Digital innovation units and their role in digital transformation
• Digital technologies and re-configuration of value-chains
• Industrial organization and the impact of digital technologies
• Embedding digital technologies in tools and changes in work practices
• Organizational identity, culture and digital transformation
• Digital innovation platforms (such as mobile platforms, crowd-sourcing platforms, etc.) and organizing

3. Digital Entrepreneurship
Digital innovation opens continual opportunities for entrepreneurial action. New ventures and established organizations alike are concerned with generating radical business models and solutions that leverage digital technologies. Topics exploring digital innovation and entrepreneurship, broadly conceived are welcomed including:
• New venturing with and by digital technologies and digital business models
• Entrepreneurship forms and models within organizations enabled by digital technologies
• Entrepreneurial launch processes with digital technologies such as agile and lean startup
• Structuring of organizations to generate and enable new ventures (structural, contextual ambidexterity)
• Incubators, accelerators, and ecological processes to launch and sustain digital ventures
• Finance of digital technology entrepreneurship including corporate funding, venture capital, private equity, angel investing, etc.
• Digital tools enabling creativity, design, engineering, and other innovative entrepreneurial activities.
• Infrastructures and ecosystems of emerging generic digital technologies (e.g., robots, 3D printing, sensor networks, blockchain, etc.) and digital phenomena such as mobile, social, big data, cloud computing, Internet of Things and related entrepreneurial forms

The types of studies that we welcome in the minitrack include an explicit focus on a particular form or function of digital technology in the context of organizational innovation, transformation, and entrepreneurship. Beyond this requirement, we welcome all forms of research inquiry, including qualitative, quantitative, mixed, and conceptual papers. In particular, we prefer novel applications of:

1. Quantitative and computationally-intensive studies including mixed methods, machine learning, and simulations
2. Case studies and detailed interpretive work
3. Design science and action research in organizational settings
4. Ambitious, provocative, and creative conceptual or theoretical analyses of the nature and effects of digitalization

Minitrack Co-Chairs:

Julian Lehmann (Primary Contact)
Arizona State University
j.lehmann@asu.edu

Nicholas Berente
University of Notre Dame
nberente@nd.edu

Kalle Lyytinen
Case Western Reserve University
kalle@case.edu

This minitrack solicits high quality research that uses analytical, empirical, and experimental modeling approaches to explore the increasing complex interplays between information technology and business operations, strategies, and consumer decisions and activities. In particular, we seek novel studies that systematically explore the complex roles that artificial intelligence (AI), digitization, information technology, and business analytics play in consumer behavior, customer relationship management, organizational architectures, product design and development, healthcare, education, marketing, sales and services, and supply chain management to provide business insights and implications. We also solicit comprehensive reviews of relevant research, rigorous case studies, and applications highlighting the use of business analytics, new technologies, methods, and techniques in various business operations. Topics of interest include, but are not limited to:

1. Application of business analytics and big data in healthcare
2. Digital health and telemedicine
3. New applications of healthcare IT
4. AI and business operations
5. Digital platforms and autonomous systems
6. Impact of LLM and ChatGPT on business operations
7. Robotic office work
8. Emerging of new operating models for the “sharing economy”
9. Applications of real-time mobile analytics in business
10. New technologies for enhanced consumers’ engagement
11. Impact of business analytics on competition and cooperation
12. Managing big data and business analytics
13. Crowdsourcing and product innovation
14. Social media implications for operations management and customer services
15. Innovations in using social data and business analytics
16. Products’ ranking algorithms, reputation systems and the performance of online markets sales
17. Using advanced web analytics to influence consumer decision-making
18. Analytical models and machine learning applications in logistics
19. IOT and supply chain coordination
20. Impact of innovations in blockchain and fintech on business operations
21. Creative ideas and new approaches in IS&OM teaching

Minitrack Co-Chairs:

Abraham Seidmann (Primary Contact)
Boston University
AVIS@bu.edu

Yabing Jiang
Florida Gulf Coast University
yjiang@fgcu.edu

Jie Zhang
University of Texas at Arlington
jiezhang@uta.edu

The “Futuring and Future Epistemologies in IS” minitrack invites submissions which explore future and possible worlds rather than provide analysis of what is or has been. We are looking for contributions that break with well-trodden empirical and conceptual conventions to help academic and practice build novel concepts, instruments and designs by focusing on digital futures.

This objective is anchored in the Information Systems discipline’s increasing interest in the processes and implications of global, societal, economic, and individual digitalization which will have enormous impact in futures which have not been well considered. We particularly think of this challenge as one where analyses and extrapolation from the present fails to provide meaningful insights beyond projecting the status quo into the future, albeit in a more technicized version of itself. Rather, we seek ways for science to become more insightful, informative, and instructive to active shapers of digital life worlds – or even to become an active shaper itself.

We hope to see exciting submissions that approach the challenge by addressing one of two distinct directions: Futuring (applied approaches) and Future Epistemologies (theoretical perspectives).

Futuring contributions may focus on a) the implications of current theorizing using futures-studies approaches to IS and related topics or b) the development of forward-looking methods, tools, and frameworks for engaging with possible futures. Submissions may explore speculative and scenario-based methodologies, technology foresight, and participatory approaches for involving stakeholders in future-oriented IS research. Moreover, futuring contributions may also engage with design science, the creation of speculative future worlds, and the role of design in shaping alternative futures. Current future-studies approaches (e.g., scenarios, Delphi studies, and technology foresight) can be expanded through innovative methodological frameworks, speculative experimentation, and creative techniques for re-imagining the techno-cultural landscape we inhabit—while envisioning the futures we aspire to create.

Future Epistemologies contributions will advance conceptual discussions on how knowledge about the future is constructed, assessed, and debated. This includes theoretical explorations of how IS can contribute to the epistemology of futures, how speculation challenges existing paradigms of IS knowledge production, and how alternative ways of knowing (e.g., posthumanist or speculative epistemologies) shape our understanding of future technological systems and societal transformations.
We welcome both empirical and theoretical submissions that address one of these two directions or bridge them, offering novel insights into the intersection of applied futuring and future epistemologies in IS research.

We continue our minitrack’s mission to challenge scholars to focus attention on “new phenomena, disclose new perspectives on phenomena, and illuminate new research agendas and programs” against the background of, and pushing past existing methods and establish theories. We encourage interested contributors to review the minitrack’s calls for papers from previous years to further illuminate the thinking which will guide our review and editorial decision processes.

Prospective authors are advised that the minitrack does not look for topical contributions which are best submitted to one of the conference’s other (mini-)tracks. Papers in this minitrack must explicitly provide the basis for more speculative future-leaning conceptualizations of phenomena or provide insight on how to provide such concepts.

Minitrack Co-Chairs:

Dirk Hovorka (Primary Contact)
University of Sydney
dirk.hovorka@sydney.edu.au

Katja Thoring
Technical University of Munich
katja.thoring@tum.de

Benjamin Mueller
University of Bremen
muellerb@uni-bremen.de

The complexity introduced by digitalization across sectors has challenged established ways of thinking, working, and living. While technological development is often described as a hallmark of human progress, the use of digital technology can sometimes limit people’s ability to cultivate their virtues and flourish. A growing body of research highlights negative consequences of digitalization, such as increased stress, inequality, anxiety, social disconnection, and more.

This minitrack provides a forum to explore, present, and discuss a broad range of issues related to flourishing in digitally enabled environments. Flourishing is a multidimensional concept that extends beyond individual well-being. It involves the optimal and continuing development of human potential while acknowledging the interconnectedness of human lives with non-human entities and ecosystems. To promote flourishing, we must consider the diverse conditions that enable individuals and communities to thrive, including health, economic stability, community cohesion, financial well-being, and political systems—all of which are increasingly shaped by digitalization. Several critical questions arise when examining human flourishing in contemporary organizations and society:

1. What do humans and non-humans need to flourish in life?
2. How does digital technology impact individual, collective, and planetary flourishing?
3. How can flourishing be promoted through digital innovation?
4. How can organizations embed flourishing—beyond human-centric goals—into their digital transformation strategies?
5. How do people utilize digital technologies to enable flourishing across species, systems, and communities?
6. In what ways does digital technology enhance flourishing, and how does it detract from it

Understanding flourishing requires a shift from traditional anthropocentric views to an approach that recognizes the interdependence of all living and non-living systems. As digital technologies become central to human and ecological futures, determining their role in fostering both individual and collective flourishing becomes a critical challenge.

This minitrack seeks to advance new insights and perspectives on these topics. By including a post-anthropocentric perspective, we encourage scholars to explore how digital technologies can create opportunities for mutual flourishing—bridging the well-being of humans, non-humans, and the environments we inhabit. We aim to continue our minitrack’s vision of fostering research agendas on well-being and flourishing, offering hope for a better future shaped by digital technology.

We welcome papers that aim to advance our understanding of flourishing in digital environments across various levels (e.g., individual, group, organizational, societal) and from diverse perspectives (e.g., cultural, ethical, design, ecological). We encourage not only empirical research but also conceptual, analytical, and theoretical contributions that expand our understanding of flourishing in the digital age. Topics of interest include, but are not limited to:

1. Novel approaches to digitally innovating for human flourishing, well-being and human potential
2. Management practices and their impact on human flourishing
3. Consequences of digital technology on human flourishing
4. The socio-technical nature of human flourishing
5. Use of digital technologies for human flourishing
6. Ethical and moral dimensions of human flourishing
7. The role of wisdom, emotions, dignity and desires
8. Environmental sustainability and flourishing
9. Post-anthropocentric perspectives on human flourishing

This minitrack invites research that broadens the concept of flourishing beyond traditional anthropocentric views. By recognizing the complex interplay between humans, technology, and the environment, we encourage scholars to engage with these questions and offer novel insights that pave the way for a more holistic understanding of flourishing and well-being in the digital era.

Minitrack Co-Chairs:

Human-in-the-loop (HITL) hybrid-augmented intelligence is one in which AI models and human intelligence each play a role in the overall system. It is defined as “an intelligent model that requires human interaction.” In this type of intelligent system, human is always part of the system and consequently influences the outcome in such a way that human gives further judgment if a low confident result is given by a computer.

HITL systems can combine human and machine intelligence in a variety of ways:  One prominent way is to introduce humans into the training loop of artificial intelligence (AI), leveraging the robustness and adaptability of human intelligence to enrich the machine learning algorithms. This can be done during initial training, in supervised learning methods, and after initial deployment, such as through Reinforcement Learning Through Human Feedback (RLHF). There are many other ways that human intelligence and AI con work together to improve over what either AI or humans can achieve on their own.

The HITL approach is used in many types of Artificial Intelligence, such as Natural Language Process (NLP) and Computer Vision (CV). In NLP, HITL approaches have been developed for text classification, syntactic and semantic parsing, dialogue and question answering, sentiment analysis. In computer vision domain, HITL approaches have been applied in object detection, image restoration, image segmentation. Human-guidance-based-deep reinforcement learning (DRL) method has been used for policy training in an end-to-end autonomous driving case.

A core stream of research on HITL systems is related to overcoming the human-computer interaction barrier, so that machines can be trained in a natural way: HITL augmented intelligence systems pose several risks and research challenges. Is bias introduced in HITL based machine learning algorithms? How to overcome these biases? How to build trust?  When humans disagree amongst themselves, how should that be reflected in how models are trained? Intelligent systems, such as deep-learning algorithms, are changing the ways knowledge is created and shared in organizations. What are the consequences of emerging knowledge worker – intelligent machine reconfigurations? This minitrack aims to address some of these research questions. We also welcome research on the design and development of the technology that aids human agents, the perceptions, attitudes, and responses of the human agents towards the technology, the impact of the systems on various levels (individual, group, organizational, and even social level) from multiple angles.

Additionally, we would like to position this minitrack as a place for researchers or practitioners from diverse backgrounds to share their research and ideas on a variety of important issues and topics of importance, such as the development of algorithms to support HITL hybrid augmented intelligence systems, behavioral, emotional, and even physical responses of the human agents while using HITL systems, the impact of HITL systems on the firm level or industry level, and ethical issues and considerations of HITL systems.

Research could be wide ranging, such as rich descriptive statistics, theories, emergent and innovative topics, models and frameworks related to technologies and their impact on marketing, case studies, methods, qualitative research, etc. Topics of interest include but are not limited to:

1. Benefits from HITL hybrid augmented intelligence
2. New design patterns for combining human intelligence with AI?
3. Challenges and problems with HITL hybrid augmented intelligence
4. The augmentation of cognition, emotion, and creativity with HITL hybrid augmented intelligence
   Interplay of the individual and collaborative processes that lead to co-creation of knowledge and collective intelligence
5. Designing improved methods of human-artificial intelligence collaboration
6. Development of HITL hybrid augmented intelligence technologies, algorithms, and visual design
7. Biases in HITL systems
8. Social impact and ethics related to HITL hybrid augmented intelligence

Minitrack Co-Chairs:

Souren Paul (Primary Contact)
Drexel University
souren.paul@gmail.com

Alex Kass
Accenture Labs
alex.kass@accenture.com

Himadri Mukherjee
AILABS
himadri@ailabs.finance

Alexander Dennis
Iowa State University
asdennis@iastate.edu

Over many decades, the biggest achievement of Enterprise-level Information Systems (EntSys) was to integrate fragmented IT support functionalities, and the biggest challenge was to align business and technology capabilities to yield a coherent infrastructure for integrated business operations. Over the last years, digital transformation made clear that the changing needs of both, strategy and business on the one side, and technology affordances on the other, demand that EntSys must continuously and quickly evolve. Yet, EntSys is investigated less frequently in the Information Systems community than the investigation of individual and team/workgroup level IS design and use. EntSys has many levels, processes, interfaces, and interactions, so they may be studied on different levels. Complexity and boundary spanning are inherent in EntSys that may require analysis from different points of view and from multiple perspectives.

The challenge to integrate technological innovations and adapt business processes within the organization and between organizations continues. Integration is often sought, slightly different but related are the industry-level perspective and the ecosystem perspective. Extending and enhancing EntSys with new innovations and interfaces brings many challenges on an enterprise-level and inter-organizational (e.g., ecosystem-) level. The integration of business processes and systems within and between companies remains complicated and difficult. The challenge for organizations includes both internal and external integration challenges, but also needs to explore the establishment of new IT infrastructure business models.

This minitrack seeks to explore current issues surrounding the evolution of integrated IS both from an academic and practitioner perspective. We welcome all themes related to internal and external integration of information systems. This minitrack spans many topics, but is not limited to:

1. Strategic initiatives and impacts
2. Implementation, operations, cost management
3. Data governance and management with and across enterprises
4. Productivity and impact on corporate profitability
5. Administration, internal controls, and assurance issues
6. Social effects, change management, human interfaces and change management
7. Business processes, project and process management
8. Inter-organizational, supply chain logistics
9. Integrating emerging technologies into the core of enterprise information systems
10. Architectures, cloud and platform-approaches of EIS
11. Risk assessment and management, cybersecurity and threats to the ecosystem
12. Integration of AI, blockchain, analytics, Internet of Things or other technology into the enterprise ecosystem, particularly as features for DIY (Do It Yourself) use by end users

This minitrack will constitute a forum for the following topics on an enterprise-level, ecosystem-level and industry-level:

1. Design and management of integrated systems in the enterprise
2. Industry-specific design and adoption of EntSys
3. Reference models for enterprise-wide systems and processes
4. Approaches for enterprise application integration
5. Enterprise architecture management
6. Enterprise-wide and cross-enterprise coordination (e.g., design principles, data standards, governance in digital platform-based business networks)
7. Interoperability of enterprise-wide systems within the firm and along the supply-chain
8. The role of EntSys to support decisions (data-driven decisions)
9. Decision support for managerial decision-making on EntSys (e.g., cloud vs. on-premise vs. hybrid, costs and benefits of ERP/Cloud/ SOA installations, total cost of ownership (TCO) or true cost of ERP, cloud hosted and extended ERP operations, switching vendors or moving to cloud-based ERP)
10. Artificial Intelligence and Machine Learning in EntSys systems
11. EntSys as digital platforms: Openness, modularity, governance
12. Workflow management systems as part of EntSys, Business Process Modeling (BPM) and process management innovation in the enterprise ecosystem
13. Data management on enterprise-level (information logistics management, corporate data management, data current and emerging data management infrastructures, data platforms)
14. Emerging business models for the enterprise as enabled by technology (e.g., platform business models)

All research methods welcomed. Submissions may include, but are not limited to research papers (conceptual, theoretical, and empirical studies), as well as case studies, and best practices with actionable managerial guidance. Both explanatory/descriptive and design research studies are invited.

Papers accepted for presentation at HICSS in this minitrack are considered for fast-track submission into four different journals:

1. American Accounting Association (AAA) Journal of Information Systems
2. AIS Transaction on Enterprise Systems
3. International Journal of Accounting Information Systems
4. Data & Analytics for Good

Minitrack Co-Chairs:

Robert Winter (Primary Contact)
University of St. Gallen
robert.winter@unisg.ch

Benedict Bender
University of Potsdam
Benedict.Bender@uni-potsdam.de

Pamela Schmidt
Washburn University
pamela.schmidt@washburn.edu

Sathya Narasimhan
Google
nsathya@google.com

In many organizations, information and digital technology have become crucial in the support, sustainability, and growth of their business. The pervasive use of technology has created a critical dependency that calls for a specific focus on its governance, which can be referred to as Enterprise Governance of IT. Enterprise governance of IT “(…) involves the definition and implementation of processes, structures and relational mechanisms that enable both business and IT stakeholders to execute their responsibilities in support of business/IT alignment, and the creation and protection of IT business value.”

This minitrack is soliciting conceptual and empirical research papers on IT governance, and the governance of other IT-related and digital artifacts (e.g., data/information governance, data analytics governance, information security governance, digital platform governance, AI governance etc.); business/IT alignment (e.g., IT strategy, digital business strategy, digital transformation strategy); and digital transformation issues from the perspective of the board and executive management (e.g., organizational culture, organizational structure, leadership, roles and responsibilities, aligning business strategy etc.). Topics of interest include:

1. Conceptual and empirical papers related to IT governance (e.g. IT-decision making structures, investment, IT infrastructure etc.),
2. IT governance and value creation or value protection
3. Digital Transformation Initiatives
4. Cybersecurity governance and resilience
5. IT governance & IS leadership: Digital transformation issues from the perspective of the board and executive management (e.g., organizational culture, organizational structure, leadership, credibility of IT leadership, roles and responsibilities of the board of directors and CIO, aligning business strategy etc.)
6. Digital business strategy, Digital posture, and Value creation
7. IT Governance and Generative AI
8. Governance of smart robot initiatives
9. IT-business alignment, Social alignment between business & IT
10. IT project portfolio governance
11. IT agility, Governance of bi-modal IT, IT ambidexterity
12. Governance of Cloud computing, Cloud strategy
13. Governance of IT outsourcing, IT innovation
14. Governance of digital platforms, digital infrastructures, and digital ecosystems
15. Data governance, Data Ethics, Data Privacy, and Data Security
16. Governing AI-driven organizations
17. Enterprise IT governance frameworks: COBIT, ITIL, SAFe and other IT governance(-related) frameworks and standards
18. Conceptual and empirical papers dealing with the regulatory perspective on the governance of IT and digital technology (e.g., GDPR, privacy, corporate governance codes, etc.)

Minitrack Co-Chairs:

Steven De Haes (Primary Contact)
University of Antwerp and Antwerp Management School
steven.dehaes@uantwerpen.be

Tim Huygh
Open Universiteit
tim.huygh@ou.nl

Anant Joshi
Maastricht University, University of Antwerp, and Antwerp Management School
a.joshi@maastrichtuniversity.nl

Understanding modern-day competition and the survival of organizations oftentimes requires an ecosystem lens. This is because digital technologies have enabled new complementarities between actors within and across industries. The increasing platformization of firms and technologies has important implications in how companies create and capture value. In this new “digital first” economy, transaction and innovation platforms have become dominant forms of organization. As scholars interested in platforms and ecosystems, we…
(1) face new phenomena, providing insights from (2) new empirics, that might (3) require new methods, and (4) new theories.

In general, the minitrack seeks contributions that problematize or build on diverse theoretical backgrounds such as management science, information systems, computer science, decision science, system science, organizational design, policy making, and behavioral economics to continue the scholarly exploration of concepts, theories, models, and tools for managing platforms and ecosystems. We are open to a wide set of methodological approaches, including empirical research, case-based research, field studies, design science, behavioral decision-making experiments, and conceptual research.

In the following, we provide exemplary provocations for research at the intersections of platforms and ecosystems that provide first glances into the research of interest to this minitrack.

1. Platforms & Ecosystems + Data, Analytics, and AI:
In the past decade(s), platform research has introduced important mechanisms for explaining platform emergence and growth, such as network externalities, generativity, or legitimization. Beyond traditional views on the growth of users, complementors, and firm size, platform providers collect more and more data to produce superior machine learning and AI applications. At the same time, ML and AI applications produce new data to provide growth of platforms. Large language model platforms such as (Chat)GPT indicate a shift from producing value through matching complementors and users to learning how to produce content and services from data over time. Data has become a vital resource and decentralized infrastructures such as the emerging data spaces  might challenge current forms of organizing ecosystems via polycentric platforms where data and rights to use data are shared under new terms.

2. Platforms & Ecosystems + Global Grand Challenges:
As we reached the halftime mark of UN Agenda 2030, demand and supply sides are increasingly concerned about their impact on the 17 sustainable development goals. None of these challenges can be solved by single actors. Instead, they involve many actors across organizations and beyond the reach of regular organizational control. Thus, platform ecosystems are considered tools to address grand challenges and societal challenges. At this point, however, despite exceptions focusing on platforms and development, platform theorizing has mostly been concerned with mechanisms explaining economic growth and development rather than digital sustainability, responsibility, or circular economies in ecosystems. This is surprising, considering that platforms play a vital role in sharing and reporting data related to these Grand Challenges (e.g., ESG reporting, digital product passports). This gives platforms a pivotal role in measurements of societal, ecological, and economic impact of market offerings.

3. Platforms & Ecosystems + Innovation, Policy, and Purpose
Platforms and ecosystems promise accessibility and democratization of value creation and capture by inverting the firm or producing new labour markets in a sharing economy. We have, however, learned that platform providers accumulate power, sometimes leading to the misuse of market dominance. This is important because platforms and ecosystems affect their environment. Recommendation systems of Instagram, for example, have been perceived as harmful for teenagers, eventually inducing testimonies of leading managers before the US Congress. Peer-to-peer lending platforms affected personal decisions on abortion and women’s health. Thereby platforms have an impact on important societal issues. Sometimes, however, these impacts are unintended or against initially proclaimed intentions, for instance when crowdfunding platforms fail to tear down socioeconomic barriers.

4. Platforms & Ecosystems + New Methodological Approaches
We are eager to widen the set of methodological approaches, including empirical research, case-based research, field studies, design science, behavioral decision-making experiments, and conceptual research. At the same time, we acknowledge that with greater availability of usage, process, or environmental data, novel approaches towards computational research might allow the creation of insights that are able to unravel micro mechanisms in platforms or shed light on the greater complexities of ecosystems. In addition, new ML capabilities suggest novel avenues for qualitative inquiries.

In summary, we encourage authors to submit their best work on managing platforms and ecosystems to our HICSS minitrack and invite them to engage in collaboration between academia, industry, and policymaking for their research. We thereby welcome submissions from industry and around the world.

In collaboration with the Editorial Board of Electronic Markets (EM), we are proud and happy to provide a fast-track option for selected papers to EM. EM is considered among the leading journals in information systems (impact factor 7.1). The journal is well-known for its research on platforms and ecosystems and thereby provides a perfect fit for submissions to this minitrack.

Minitrack Co-Chairs:

Hannes Rothe (Primary Contact)
University of Duisburg-Essen
hannes.rothe@icb.uni-due.de

Vladimir Sobota
Delft University of Technology
V.C.M.Sobota@tudelft.nl

Jukka Huhtamäki 
Tampere University
jukka.huhtamaki@tuni.fi

Kaisa Still
University of Oulu
kaisa.still@oulu.fi

We invite submissions describing novel research results, best practices, and/or industry programs and experiences related to the continuous, efficient, and effective design, engineering, implementation, operation, and management of cyber defense, cyber analytics, and security operations systems and processes within the enterprise. This includes technical aspects, ethical and legal issues, governance, risk assessment and management, compliance, system audits, and strategic initiatives. The minitrack welcomes papers from human, technical, and process perspectives on organizational cybersecurity. Potential paper topics include, but are not limited to:

1. Techniques and approaches for effective, efficient, and continuous event analysis and incident detection and response
2. Techniques and approaches for effective, efficient, and continuous cyber defense and security operation programs
3. Design and implementation of systems, techniques, and tools, and policies and procedures for successful security operation programs and Security Operation Centers (SOC)
4. Frameworks, specifications, and verification languages and techniques for design, implementation, and management of cyber defense and security operations and system processes, policies, and configurations
5. Techniques, processes, and tools for continuous risk management, identification, analysis, and governance, risk, and compliance (GRC) strategies
6. Techniques, processes, and tools for continuous cyber defense and advanced system, software, and application hardening, including machine learning, artificial intelligence, mobile devices, Internet of Things (IoT), cloud computing, and critical infrastructures
7. Advanced techniques, processes, and tools for malware and malicious activity prevention and detection
8. Advanced techniques, processes, and tools for continuous vulnerability assessment, cyber defense, and security operations
9. Development of effective and efficient programs for security education, training, and awareness (SETA) programs across the organization
10. Strategies for establishing successful organizational policies for social media privacy, workplace and public space monitoring, data protection, bring your own device (BYOD), mobile device management (MDM), and intellectual property protections
11. Assessment and improvement of user perceptions of security practices and user acceptance of policy and technology

Selected papers from this minitrack will be recommended to the editors of Organizational Cybersecurity: Practice, Process, and People for fast-track review and publication of an extended version of the HICSS paper. The extended version must include at least 30% new material, cite the HICSS paper, and include an explicit statement about the increment (e.g., new results and findings, better description of materials, etc.) in the cover letter.

Minitrack Co-Chairs:

Morgan Shepherd (Primary Contact)
University of Colorado at Colorado Springs
mshepher@uccs.edu

David Kocsis
University of Colorado at Colorado Springs
dkocsis@uccs.edu

Daniel Conte de Leon
University of Idaho
dcontedeleon@uidaho.edu

Sandeep Suntwal
University of Colorado at Colorado Springs
ssuntwal@uccs.edu

Overall, this minitrack aims to:

1. Showcase high-quality practice-oriented IS research
2. Promote practice-oriented IS research as a key source of insight and guidance for digital leaders
3. Provide researchers a platform to present and discuss their practice-oriented IS research findings and expose the community to current challenges in creating value with IT.
4. Help identify the most challenging managerial issues for digital/IT leaders and frame them as new questions to guide future practice-oriented IS research.

Additional guidance for authors of practice-based IS research papers

This practice track has run for many years at HICSS. We seek research with strong relevance for practitioners and manuscripts written to make them easily accessible to such a reader. This means that any accepted manuscript will not follow the traditional “rules” of writing for an academic audience.

If you are not a regular reader of MISQ Executive, we advise you to read a few articles to understand their style, structure, focus, and content. Some general guidelines for writing such articles include:

1. Simplify reality, but do not be simplistic
2. Keep theory and methodology in the background (include your methods in an appendix, but write it to be accessible to non-academic readers).
3. Use literature and in-depth evidence to give credibility and generalizability.

Typically, such articles loosely follow this structure:

1. Short lead-in: Motivate the practitioner reader in 2-3 sentences. Why should they read the article? What you write should resonate closely with them; perhaps it is a problem that they recognize that you will now help them solve.
2. Short introduction to the topic: Frame the topic of the article. Use footnotes rather than the traditional academic referencing style when using prior research.
3. Extensive research findings: Use headings and figures/tables to communicate findings. Address solutions to managerial challenges. Present lessons learned from the research and recommendations. Possibly develop and/or use a practice-oriented framework to organize and present findings.
4. Actionable guidelines: Actionable guidelines include action verbs, not passive verbs like “understand,” “assess, “think,” or “get commitment.” Tell the reader what to do, or what to change. For example, if getting commitment is important, say how to get the required level of commitment.
5. Appendix: Present an overview of research methods. Remember to write in a way accessible to an audience unfamiliar with academic research’s nuances.

Minitrack Co-Chairs:

Bill Kettinger (Primary Contact)
Clemson University
wkttngr@clemson.edu

Gabe Piccoli
Louisiana State University
gpiccoli@lsu.edu

Michael Milovich, Jr.
Rowan University
milovich@rowan.edu

Joaquin Rodriguez
Grenoble Ecole de Management
joaquin.rodriguez@grenoble-em.com

This minitrack focuses on research areas within information systems (IS) that lie at the intersection of humans and technology in an organizational context. A central aspect of this research agenda is to explore and understand the role of digital technology and information in shaping organizational life. The minitrack is interested in various socio-technical issues in both traditional organizational settings and emerging and alternative forms of organizing, such as digital labor platforms, online communities, and social movements enabled by platforms and social media. Socio-technical issues include information systems design, development, implementation, and use research topics. These topics mainly concern the underlying social and organizational relations within such systems.

Such topics involve conceptualizing specific socio-technical issues alongside the practices and processes that emerge and are enacted. They empirically illustrate and validate established or new conceptual perspectives and include case studies that provide insights into the socio-technical processes of success and failure.

Key topics may include (1) organizational culture and identity, (2) inter-organizational relationships and organizational ambidexterity, (3) algorithmic management and control. Authors are invited to submit papers that address, but are not limited to, the following topics related to socio-technical issues in organizational or inter-organizational contexts.

1. Organizational Culture and Identity
   • Digital culture (Digital mindset, Cross-functional collaboration)
   • Organizational change and routines
   • Organizational identity and major organizational changes (e.g., Sourcing, Mergers and Acquisitions)
2. Inter-organizational Relationships
   • Development of digital ecosystem partnerships
   • Boundary spanners, boundary objects, knowledge transfer
   • Organizational ambidexterity
   • Absorptive capacity
   • Open Innovation
   • Distributed forms of working and organizing, Hybrid work models
3. Digital Transformation
   • Recruitment and retention of digital talent
   • Agility
   • Digital leadership, Paradoxical leadership
   • Algorithmic management
   • Work-related stressors (worker surveillance/monitoring, technostress)

We invite contributions that engage philosophically, theoretically, methodologically, and/or empirically with various socio-technical phenomena. Submissions may include, but are not limited to, research papers (conceptual, theoretical, and empirical), case studies, and best practices/lessons learned. We also welcome research-in-progress studies that strive to problematize or transcend established boundaries (theoretical, disciplinary, methodological, etc.).

Minitrack Co-Chairs:

Dragos Vieru (Primary Contact)
TELUQ University
dragos.vieru@teluq.ca

Simeon Vidolov
University of Galway
simeon.vidolov@universityofgalway.ie

Albert Plugge
Nyenrode Business University
a.plugge@nyenrode.nl

Nura Jabagi
Laval University
nura.jabagi@fsa.ulaval.ca

This minitrack is special. It is set up to provide a forum for papers in the Organizational Systems and Technology track that do not “fit” exactly in a specific track. We often serve as an incubator for new ideas.

Over the years we have actively solicited non-traditional, imaginative, and thought-provoking research in any IT area. We are particularly interested in papers that break new ground in new areas, or those that apply existing research to new industry groups or fields. The papers that we accept generally have the following characteristics:

1. They are cross-disciplinary – can be disciplines other than MIS.
2. They address current topics that are important to today’s managers.
3. They have a practitioner “flavor.”
4. Case studies are welcomed, particularly if they propose questions that will stimulate discussion among session attendees.

Minitrack Chairs:

Jim Ryan (Primary Contact)
Worcester Polytechnic Institute
jryan@wpi.ed

Christopher Califf
Western Washington University
califfc@wwu.edu

In an era where data is the foundation of digital transformation, well-designed and managed sustainable and trustworthy digital and data ecosystems are critical for artificial intelligence (AI), strategic innovation, governance, competitive advantage, and trust in increasingly digital societies. With the rise of new data architectures (e.g., data meshes and data lakehouses), the shift from centralized to decentralized systems, and the integration of AI in data governance and management among others emerging technologies (e.g., blockchain, cloud computing), these ecosystems are becoming more dynamic, interconnected, and complex. However, alongside their potential benefits that is a common focus of the research around these ecosystems, challenges related to trustworthiness, transparency, security, sustainability, and governance must be addressed.

This minitrack invites research on how digital and data ecosystems evolve in terms of resilience, trustworthiness, and sustainability while enabling strategic innovation and societal transformation. We welcome studies that explore the interplay between AI, data governance, policies, methodologies, human factors, and digital transformation across sectors such as finance, government, healthcare, and education.
We seek theoretical, empirical, design science, case study, and interdisciplinary contributions on topics including, but not limited to:

1. AI, trustworthiness, and governance in digital and data ecosystems:
   • AI as an actor and stakeholder in data ecosystems;
   • AI-augmented governance, security, and data quality management;
   • human factors in AI-integrated ecosystems (trust, user acceptance, participation);
   • interoperability, observability, and data linking across ecosystems;
2. Emerging technologies and strategic innovation:
   • transition from centralized to decentralized data architectures (e.g., data lakehouses, data meshes);
   • emerging technologies for trustworthy ecosystems;
   • AI-driven business process augmentation and decision-making;
   • industry and government case studies on evolving data ecosystems;
3. Resilience and sustainability of data ecosystems:
   • ethical AI and responsible innovation in data ecosystems;
   • sustainability and long-term governance of digital and data infrastructures;
   • cross-sectoral and interdisciplinary approaches for building sustainable ecosystems;
   • impact of data democratization on digital transformation and innovation.

By combining the strengths of strategic innovation, trustworthy AI, and data ecosystem governance, this track expects to offer a holistic perspective at the intersection of information systems, AI governance, data science, and digital transformation. It will serve as a platform for researchers and practitioners to explore how digital and data ecosystems can be sustainable, resilient, and trustworthy while driving innovation and societal transformation.

We welcome conceptual, empirical, design science, case study, and theoretical papers from fields such as information systems, computer science, data science, management and process science, policy-making, behavioral economics, and social sciences.

Minitrack Co-Chairs:

Anastasija Nikiforova (Primary Contact)
University of Tartu
nikiforova.anastasija@gmail.com

Daniel Staegemann
Otto von Guericke University Magdeburg
daniel.staegemann@ovgu.de

Asif Gill
University of Technology Sydney
Asif.Gill@uts.edu.au

The COVID-19 pandemic brought an unprecedented global crisis, reshaping nearly every aspect of daily life. Its rapid spread created unique challenges but also presented a valuable opportunity to examine the critical role of Information Systems and Technology in navigating pandemics and other large-scale disruptions. This minitrack considers topics related to the impact of local and global crises on jobs and work (for both employers and employees), education and educational institutions (including learners and educators), family and home life (including life-changes for adults and children), and global society.

In this minitrack, we welcome submissions of full research papers or research in progress, including theory articles, literature reviews, teaching cases, or studies employing qualitative, quantitative, mixed methods, and design science research methods. Topics of interest include, but are not limited to, technology’s role in addressing:

1. Use of Artificial Intelligence (AI) during times of local or global crises
2. Opportunities and challenges during local or global crises
3. Consequences of local and global crises (e.g. COVID-19), on work, education, and society
4. Working from home during crises
5. Best practices in education and work contexts
6. Digital transformation and the future of work and education
7. Using ICT to foster learning, working, and social activities
8. Social isolation and well-being
9. Work-life boundaries and conflicts
10. Implications for policy and practice
11. Nontraditional virtual teams
12. Social and business norms
13. Disaster plans and business continuity planning

Minitrack Co-Chairs:

Dawn Owens (Primary Contact)
University of Texas at Dallas
dawn.owens@utdallas.edu

Deepak Khazanchi
University of Nebraska at Omaha
khazanchi@unomaha.edu