Internet at Work and Play Track

Track Chairs

Alan Dennis

Indiana University Bloomington
Kelley School of Business
1309 East Tenth Street
Bloomington IN 47405
ardennis@iu.edu

Joe Valacich

University of Arizona
Eller College of Management
1130 E. Helen St.
Tucson, Arizona 85721-0108
valacich@arizona.edu

Papers from HICSS-59

The Internet at Work and Play Track recognizes that the Internet has transformed the way we work, learn, and play. Our track focuses on the ways in which the Internet affects people, groups, organizations, and societies (e.g., markets, social networks), as well as fundamental issues in the development and operation of the Internet and Internet applications (e.g., security, open source).

Achieving Digital Transformation Minitrack

Digital transformation (DT) remains a central challenge in the digital economy, but the phenomenon is evolving rapidly with generative AI, AI-enabled automation, platform ecosystems, and data-intensive operating models. Always-on connectivity and expanding data availability continue to reshape how organizations create value, coordinate work, and make decisions. Yet many organizations still struggle to realize DT outcomes, not only because of optimistic objectives and execution gaps, but because DT requires deep socio-technical reconfiguration. Beyond adopting technologies, organizations must redesign governance, processes, and capabilities, while often renegotiating strategy, organizational identity, and business models to align people, technology, and work practices.

Recently, DT has been twinned with sustainability, named twin transformation, bringing organizations to reconcile digital acceleration with environmental and social objectives by rethinking technology choices, work-life balance and other changes aiming to promote digital innovation and environmental progress and enhance human well-being while navigating trade-offs, risks, and unintended consequences in an intertwined transformation.

This minitrack provides a forum to examine how organizations navigate the multi-level complexity of digital and twin transformation—across individuals, teams, organizations, and inter-organizational ecosystems—and how they make technology choices, design AI-augmented work, and govern transformation to deliver economic value while advancing environmental sustainability and human wellbeing. We welcome theoretical, methodological, and applied papers, and we especially encourage submissions grounded in rich empirical settings (single or multiple cases, including “learning from failure” cases) that surface mechanisms, boundary conditions, and actionable implications. Proposed topics include, but are not limited to:

  • Business model and identity reconfiguration under DT, including platformization and ecosystem orchestration
  • AI-enabled and data-driven transformation strategies, including generative AI and AI agents
  • Governance of DT and twin transformation, including decision rights, data and AI governance, risk, compliance, and responsible innovation
  • Transformation practices and change processes, including capability building, reskilling, resistance, and technostress
  • Metrics and indicators for DT and twin transformation success, including value realization, ustainability outcomes, and human well-being measures

We expect contributions that address relevant topics related to the DT and its impacts. Exchanges and interactions among authors during the conference will promote fruitful discussions and perhaps new collaborations. As DT becomes more theoretically developed, we believe this minitrack will continue to contribute to the evolution of this relevant research topic by promoting real cases that could help advance new theoretical knowledge and practical knowledge that can be developed into cases for both policy and teaching.

Minitrack Co-Chairs:

Elaine Mosconi (Primary Contact)
Université de Sherbrooke
elaine.mosconi@usherbrooke.ca

Abayomi Baiyere
Queen’s University
a.baiyere@queensu.ca

Paul Drews
Leuphana University of Lüneburg
paul.drews@leuphana.de

Adoption, Diffusion, and Impact of ICTs and AI Minitrack

This minitrack explores the adoption, diffusion, and impact of Information and Communication Technologies (ICTs) and Artificial Intelligence (AI) across sectors, with a focus on societal, organizational, and technological transformation. It addresses how emerging technologies, such as AI, blockchain, the Internet of Things (IoT), and generative AI, are being adopted, used, and diffused, and the consequences of these processes for individuals, organizations, and society. Recent research highlights the role of ICTs in addressing critical societal challenges, including digital inclusion, sustainability, governance, and the integration of digital innovations with established practices. Studies demonstrate diverse applications of AI, IoT, and blockchain across healthcare, education, public administration, and industry, underscoring the transformative potential of technology adoption and diffusion. This mini-track welcomes contributions employing diverse research approaches, including but not limited to case studies, experiments, literature reviews, empirical, comparative, and applied studies. Submissions should advance understanding of ICT and AI adoption, use, diffusion, and impacts, and shed light on the rapidly evolving technological landscape.

  • The adoption, use, impact, and diffusion of ICTs, including broadband internet, mobile smart devices, electronic commerce, wearables, online social networks, and other technologies by households, organizations, communities, or society
  • The adoption, use, impact, and diffusion of any novel, innovative, and emerging ICT applications, including social commerce, cloud services, AI, Generative AI, machine learning, deep learning, blockchain, cryptocurrency, virtual reality, augmented reality, or IoT within large enterprises, small and medium-sized enterprises (SMEs), communities, and society
  • The adoption, use, impact, and diffusion of ICTs that enable organizations and governments to enhance their environmental and social impacts
  • Evaluation of the technological and non-technological aspects of the adoption, use, impacts, and diffusion of ICTs
  • Application of theories to explore, describe, explain, and predict the adoption, use, impacts, and diffusion of ICTs
  • Human Computer Interaction issues associated with adoption, use, and impact factors in the context of ICTs
  • Economics of the adoption, use, or diffusion of ICTs in society and in households
  • Working practices and their association with adoption, use, and diffusion within organizations
  • Resistance to change related to ICT adoption, use, and diffusion within society and organizations
  • Policies related to the adoption, use, and diffusion of broadband and emerging ICTs
  • Conceptual or empirical studies of how a particular ICT is adopted, used, and diffused in developing countries or within a specific community
  • Comparative studies of ICT adoption, use, impact, and diffusion between demographic groups, countries, or regions
  • Luminal innovation, assimilation, resistance, and changes to working practices that will duly inform the research community
  • Studies of the digital divide that include disadvantaged groups such as disabled and lower income families

Minitrack Co-Chairs:

Jyoti Choudrie (Primary Contact)
University of Hertfordshire
j.choudrie@herts.ac.uk

Sherah Kurnia
University of Melbourne
sherahk@unimelb.edu.au

David Sundaram
University of Auckland
d.sundaram@auckland.ac.nz

Gabrielle Peko
University of Auckland
g.peko@auckland.ac.nz

AI Ecosystems: Agents, Assistants, and Platforms Minitrack

Rainer Schmidt (Primary Contact)
Munich University of Applied Sciences
Rainer.Schmidt@hm.edu

Rainer Alt
Leipzig University
rainer.alt@uni‐leipzig.de

Alfred Zimmermann
Reutlingen University
alfred.zimmermann@reutlingen-university.de

AI, Emotions, Mental Health, and Explainability Minitrack

AI-enabled technologies have been permeating human lives and societies at a growing rate over the last three decades. They started at the mechanical task levels (e.g., manufacturing robots) and slowly made their way into analytical tasks (e.g., personal assistants, traders, schedulers, etc.). However, these technologies are still finding their way into the realm of human emotion and empathy. This next wave (known under various banners, including feeling AI, empathic AI, emotional AI, and empathetic AI) is expected to be the next frontier in AI development and deployment, making it a growing research area within AI research. Among the many profound impacts of feeling AI is its immense potential to influence human mental health and wellness, which is currently under-researched. Additionally, these developments are tainted by the lack of explainability of the AI system’s decision-making process to make such decisions cognitively appealing. As a result, the relationship between AI explainability and human emotions has been understudied.

For this minitrack, possible topics and research questions of interest include, but are not limited to:

  • How does AI explainability influence human emotions?
    1. What is the relationship between AI explainability levels and desired emotions in humans (trust, joyfulness, satisfaction, etc.)?
    2. What would be the desired level of explanation for different individuals or user groups?
    3. What would be the desired level of explanation for different kinds of decisions?
  • Emotional AI Impact on Businesses and Organizations
    1. How emotionally capable AI will impact business processes, business models, and outcomes?
    2. How would an emotional generative AI impact employee and user satisfaction?
    3. How can organizations harness the existing generative AI emotional capabilities to gain competitive advantages?
    4. How would emotional and emphatic AI impact government and public agency procedures and policies?
  • Human and AI interactions
    1. How is an AI capable of understanding and appropriately responding to human emotions going to impact existing theories of human-technology interactions?
    2. How can AI become empathic and emotional, and how would such changes impact human-AI interactions (Novel theories)?
    3. How might AI-evoked emotions in humans be different than those emotions evoked by other humans and living beings?
  • Emotional AI and Socio-Economical Systems
    1. What would be the legal and ethical implications of emotional and empathic AI for human societies and socio-economical systems?
    2. What are the potential advantages and risks associated with the development and deployment of emotional and empathic AI systems?
    3. What would be the role of AI explainability in this area?
  • AI Algorithms and Emotion Detection and Prediction
    1. How can AI and ML algorithms be better trained to detect and respond to human emotions appropriately?
    2. How does generative AI detect and affect user emotions? And how can it be improved?
    3. How people react emotionally to explanations provided by generative AI?
  • Feeling AI as a Mental Health Companion
    1. How does interaction with emotionally responsive AI systems influence users’ mental well-being (e.g., anxiety, loneliness, stress, mood regulation)?
    2. When does empathic AI function as beneficial emotional support, and when does it risk emotional dependency or displacement of human relationships?
    3. How do users emotionally differentiate between AI-based empathy and human empathy in mental health–related contexts?

Minitrack Co-Chairs:

Reza Vaezi (Primary Contact)
Kennesaw State University
svaezi@kennesaw.edu

Maryam Ghasemaghaei
McMaster University
ghasemm@mcmaster.ca

Mohsen Jozani
San Diego State University
mjozani@sdsu.edu

AI for Cybersecurity Minitrack

Cybersecurity and AI  are key domains whose intersection gives great promises and poses significant threats. The range and scope of how AI could be used for cybersecurity and how to improve the cybersecurity of AI remain relatively understudied yet critically important areas. This minitrack seeks to solicit papers that address, but are not limited to, the following areas.

  • Novel applications of AI, machine learning, GEN AI, LLMs, and deep learning in cybersecurity
  • Adversarial AI applications in cybersecurity, i.e., malware, phishing, AMG, LLMs, or any applicable threat/identification domain
  • Protecting AI, i.e., protecting Gen AI, LLMs, shared data sets, shared models, shared applications
  • Using AI to protect AI, AI applications, and the people using AI for work or play
  • The security and integrity of AI systems that people now engage with and trust with PII and intimate details of their work and lives both in the work setting and outside of work in their private lives or when at play
  • Novel approaches to leveraging and protecting emerging AI domains (agentic systems, multi-agentic systems, AI based swarm applications, AI based drones, AI based partners / collaborators / therapists / Other, etc.)
  • Sharing/disseminating tools, techniques, and applications of AI in cybersecurity and cybersecurity for AI

Examples of areas where AI is applied include:

  • Modern GEN AI / LLMs: Results integrity, prompt security, prompt attach detection, result error detection, dangerous output detection, hallucination detection, prompt jailbreaking
  • Cybersecurity Domain Data Analytics:
    1. Leveraging AI to analyze any of the myriad datasets in the cybersecurity domain such as log files, network traffic, data at rest, etc. for legitimate cybersecurity purposes
    2. Analyzing real-time data streams to identify immediate attacks as they occur
  • Vulnerability Assessment:
    1. Scanning Code for Vulnerabilities using AI / LLMS
    2. Tracking and identifying / labeling code, containers, or repositories based on their vulnerabilities and / or vulnerability persistence over time and forks
  • Secure Coding: Securing existing code or automatically generating new secure code either from scratch or by generating secure code clones
  • Remediation: Effectively and efficiently identifying appropriate remediations for detected vulnerabilities from the large amounts of existing data
  • Model Security for AI and LLM Models: Identifying models that have been perturbed, perturbing models to create model perturbation detection technologies, detecting the effect of model perturbations, identifying bias in models, identifying errors in models, removing perturbations from models
  • Security for GenAI, AI, ML, and LLM Datasets: Insuring distributed dataset integrity, detecting perturbations in datasets, identifying the effects of dataset perturbations, removing perturbations from datasets
  • Detection of phishing, fraud, and attacks including short-term and long-term multimodal attacks such as vishing, voice cloning, audio deepfakes, video deep fakes, and all forms of AI enabled multi-turn interactive attacks spanning varying time horizons

Minitrack Co-Chairs:

Mark Patton (Primary Contact)
University of Arizona
mpatton@arizona.edu

Sagar Samtani
University of Indiana
ssamtani@iu.edu

Hongyi Zhu
University of Texas at San Antonio
hongyi.zhu@utsa.edu

Hsinchun Chen
University of Arizona
hsinchun@arizona.edu

Circular Industrial Ecosystems: Collaborative Technologies Enabling Transparency, Resilience, and Innovation Minitrack

In recent years, circular industrial ecosystems have emerged as transformative enablers of enhanced data exchange across manufacturing, logistics, supply chain management, and beyond, such as actors offering services of general interests. These ecosystems leverage emerging collaborative and web-based technologies, such as digital twins, extended reality, and secure data-sharing infrastructures, to drive digitization and convergence with AI tools, foster trust, and improve transparency across industries. Advanced data analytics and machine learning further enhance these ecosystems by optimizing resource flows, predicting risks and demand patterns, and facilitating autonomous coordination among stakeholders. Thus, they create a collaborative environment for continuous information provision, which fulfills the main requirement for a circular economy. Despite their potential, significant challenges remain in designing, implementing, and scaling these ecosystems to address critical issues, including data sovereignty, open-source innovation, and resilient value chain operations.

This minitrack invites submissions that explore innovative technologies and data-driven approaches shaping the future of circular industrial ecosystems. We welcome empirical studies, theoretical advancements, and comprehensive reviews that provide fresh perspectives and practical solutions to advance this field. This minitrack welcomes papers addressing, but not limited to, the following themes:

  • Artificial Intelligence & Retrieval Augmented Generation in Industrial Ecosystems, e.g., to enhance decision-making, predictive analytics, and process automation within circular industrial ecosystems.
  • Data Sovereignty & Trust in Ecosystems through governance models, data privacy frameworks, and secure data exchange and portability techniques.
  • Digital Twins in Circular Systems, including design principles, synchronization mechanisms, AIpowered agents, and shared digital twins to drive operational efficiency and integration.
  • Web 4.0 Technologies to ensure open, fair, trustworthy, secure, and inclusive digital environments for industrial applications.
  • Resilience and Sustainability in Value Chain Networks utilizing collaborative platforms and decentralized systems to enhance value chain resilience, adaptability, and circularity through data-driven insights and web-based technologies.
  • Decentralized & Secure Technologies & Data Spaces integrating interoperable infrastructures, data spaces, blockchain, and other decentralized solutions to enable secure and efficient data sharing across ecosystems, e.g., for FinTech applications in industrial ecosystems.
  • Data Acquisition, Preparation, & Storage Techniques to feed smart service systems and collaborative platform concepts in industrial operations.
  • Digital Product Passports for the continuous provision of information within the circular economy.
  • System Engineering & Modeling Techniques for the conceptualization of circular ecosystems.
  • Data Readiness Frameworks to include extensive data sets in data processing applications.
  • Industrial Metaverse & Simulation to achieve transparency and optimization along circular value chains
  • Digital Technologies and Data-Driven Approaches for creating a circular and smart economy

This minitrack seeks contributions from academics, industry practitioners, and policymakers at the forefront of industrial digitization and ecosystem design. Whether focusing on conceptual frameworks, empirical insights, or innovative prototypes, we welcome submissions with practical relevance and forward-looking perspectives.

Minitrack Co-Chairs:

Hendrik van der Valk (Primary Contact)
TU Dortmund University
hendrik.van-der-valk@tu-dortmund.de

Tan Gürpinar
Quinnipiac University
tan.gurpinar@quinnipiac.edu

Nick Große
TU Dortmund University
nick.grosse@tu-dortmund.de

Joachim Hunker
Fraunhofer Institute for Software and Systems Engineering
joachim.hunker@isst.fraunhofer.de

Data and AI Ecosystems: Design, Management, and Institutionalization Minitrack

Data is the foundational substrate for the next generation of value creation. To remain competitive, organizations must leverage Artificial Intelligence (AI) both to optimize internal Data Management and to fuel inter-organizational innovation. This applies to incumbents and digital natives alike: the former must modernize via AI-ready data infrastructures, while the latter can establish novel Data and AI Ecosystems that enable different actors (e.g., companies, public institutions) to share data and models for reciprocal benefit.

The management of these systems begins with internal capabilities. AI is revolutionizing data handling by automating tasks such as deriving data quality rules and tagging metadata. Beyond internal boundaries, AI is the primary driver of ecosystem innovation, with shared data enabling the training of robust AI models. However, the design of these systems must consider the complex regulatory landscape. Emerging regulations, such as the EU Data Act and AI Act, drive the institutionalization of “compliant by design” architectures that balance innovation with data sovereignty and formal governance. Thus, questions arise one the one hand surrounding “good” policy-making and on the other hand regarding the implementation and evaluation in context of data and AI ecosystems and beyond.

Thus, this minitrack also gives opportunity to research that both, directly and indirectly, addresses policy and regulatory discourses. This track focuses on the fundamentals of Data and AI Ecosystems from multiple perspectives, including the technical design of infrastructures and the strategic management of shared resources. We invite contributions that examine the business value of data sharing across domains (e.g., mobility, healthcare, manufacturing) and the impact of the formal institutionalization of data-sharing rules. Complementarily, we welcome studies on the associated governance mechanisms, technical frameworks for Generative AI, and the policy-driven evolution of digital networks. We invite papers investigating the field both empirically and theoretically, such as (but not limited to):

  • AI-driven data management (e.g. data quality profiling)
  • Design and modeling of AI-ready infrastructures
  • Inter-organizational innovation and business models fueled by shared AI models
  • Institutionalization of ecosystems through the EU Data Act and AI Act
  • Data sharing, data sovereignty, usage control, and policy-aware architectures
  • Management of Generative AI and LLMs in decentralized networks
  • Economic, ecological, and social sustainability of data ecosystems
  • Paradigmatic differences between data ecosystems and traditional networks
  • Risks and Ethics (e.g., algorithmic bias, cyber threats, or data misuse)
  • Reciprocal influence of IS on regulation (e.g., regarding data protection)
  • Increasing focus on AI regulations (e.g., European AI Act)
  • Impact of regulation on organizations (e.g., ecosystems, enterprise architectures, AI systems)
  • Studies at the intersection of IS and law (e.g., novel interdisciplinary approaches)
  • Comparative analysis of global regulatory frameworks
  • Detrimental effects from legal frameworks (e.g., on innovation)

Minitrack Co-Chairs:

Ilka Jussen-Lengersdorf (Primary Contact)
Fraunhofer Institute for Software and Systems Engineering
ilka.jussen-lengersdorf@isst.fraunhofer.de

Frederik Möller
TU Braunschweig
frederik.moeller@tu-braunschweig.de

Christian Kurtz
University of Hamburg
christian.kurtz@uni-hamburg.de

Gero Strobel 
University of Duisburg-Essen
Gero.Strobel@paluno.uni-due.de

Digital Supply Networks: Technologies, Resilience and Sustainability Minitrack

The business environment in which companies must compete today is changing more than ever. Increasingly dynamic customer demands, external disruptions and shocks, more frequent material shortages and the worsening effects of climate change are putting additional pressure on global supply chains. Increasing flexibility and agility and improving the responsiveness and resilience of established supply chains are necessary to remain competitive. In the long term, the only way to address the increasing scarcity of materials for a variety of reasons is to transform today’s “take, make, waste” supply chains into much more sustainable circular systems.

Digitalization is undoubtedly a key enabler for the implementation and management of resilient and sustainable supply chains. Traditional supply chains are evolving into digital supply networks. This mini-track explores the transformative role of digital technologies, including IoT, AI, digital twins, blockchains, and digital platforms in developing, planning, executing, and controlling resilient and sustainable supply chains. It addresses challenges such as increasing supply chain volatility, resource scarcity and climate change by highlighting data-driven innovations, optimization, and new business models. Therefore, we welcome research papers including but not limited to the following aspects:

  • Contribution of digital technologies to supply chain resilience, sustainability and circularity
  • Increasing supply chain visibility based on IoT technologies
  • AI methods supporting forecasting, planning, decision making and optimization
  • Division of labour and interactions between humans and machines in AI-supported SCs
  • Virtualization and simulation of supply chains based on digital twins
  • Blockchain and smart contracts in logistics and supply chain management
  • The role of digital platforms in supply chain management
  • Effects of smart product-service-systems on supply chains and supply chain management
  • Federated data ecosystems enabling new data-driven supply chain strategies
  • Models, methods and tools for the digitalization of supply chains
  • Barriers and challenges hindering the digitalization of supply chains
  • Data security and cyber security challenges in digital supply chain structures
  • Governance structures and legal aspects within the digital supply chain

Minitrack Co-Chairs:

Alexander Pflaum (Primary Contact)
Otto-Friedrich University Bamberg
alexander.pflaum@uni-bamberg.de

Günter Prockl
Copenhagen Business School
gp.digi@cbs.dk

Haozhe Chen
Iowa State University
hzchen@iastate.edu

Freimut Bodendorf
University of Erlangen-Nürnberg
freimut.bodendorf@fau.de

Electronic Marketing Reimagined: AI, Platforms, and Tech-Empowered Markets Minitrack

This minitrack provides a forum for research on how digital technologies (platform architectures, data systems, algorithms, and AI) reshape marketing strategy, consumer behavior, and market outcomes. We welcome research that advances theory and method on technology-mediated value creation in B2C and B2B contexts, including work that examines performance, welfare, trust, and governance in digitally intermediated markets.

The minitrack remains a strong home for foundational electronic marketing questions (how firms attract customers, increase purchase incidence and share, and build satisfaction and loyalty through digital channels and consumer-generated media) while explicitly inviting scholarship that engages the most consequential contemporary developments in digital marketing.

We aim to convene a high-signal scholarly conversation in which the best papers do more than document patterns: they clarify mechanisms, specify boundary conditions, and articulate strategic and societal implications for marketing and responsible market design. Below are illustrative topic areas (not exhaustive). We intentionally frame these as broad buckets to welcome foundational Electronic Marketing work alongside new and rapidly developing streams in AI and platformed markets.

  • AI and algorithmic marketing Research on how AI systems and algorithmic infrastructures shape marketing decisions and outcomes, including (but not limited to) generative AI in marketing communications and customer service; agentic commerce and decision aids; recommendation and ranking dynamics; algorithmic targeting, nudging, and persuasion; auction and bidding systems; and the consequences of automation for firms, consumers, and market structure
  • Platforms, ecosystems, and digital market organization Research on multi-sided platforms, digital ecosystems, and new intermediation logics, including platform governance and moderation, creator economies and influencer/affiliate infrastructures, complementor strategies, marketplace design, network effects, ecosystem coordination, gatekeeping, and competition/market power in digital settings
  • Data, privacy, trust, and responsible digital marketing Research on privacy, consent, security, and trust in data-intensive environments, including consumer responses to data collection and surveillance; privacy-preserving personalization; bias and fairness; transparency and explainability; trust erosion and repair; dark patterns and manipulative design; and regulatory/policy implications for marketing practice and platform governance
  • Measurement, experimentation, and causal inference in digital Research that strengthens inference and measurement in technology-mediated markets, including attribution and incrementality, marketing mix modeling, online/offline linkage, field experiments and A/B tests at scale, causal machine learning, audit studies, computational approaches to platform data, and methods that improve replicability and validity in digital environments
  • Tech-enabled customer experience and journeys Research on how digital infrastructures reorganize customer experiences and consumer/family/organizational work, including omnichannel coordination, service automation and selfservice, conversational interfaces, social and livestream commerce, community-based engagement, immersive and extended reality, and connected products/IoT-enabled services
  • 6) Classic electronic marketing Research on enduring electronic marketing topics, especially where authors refresh, extend, or reframe established phenomena in light of new technologies and governance conditions. Illustrative areas include eWOM and reviews, e-commerce strategy, digital advertising effectiveness, CRM and loyalty, pricing and promotion, personalization and recommendation systems, search and mobile marketing, and digital persuasion

We invite submissions from academics, practitioners, policy makers, and independent thinkers. We welcome theoretical, bibliometric, analytical, and empirical work, including experiments, field studies, case studies, econometric and computational modeling, qualitative and mixed methods (including ethnography and netnography), and computational approaches such as NLP, machine learning, and platform/trace data analyses. Each submission should demonstrate clarity, rigor, and novelty, and ideally spark stimulating discussion that encourages new research agendas and durable collaborations across marketing, analytics, and IS communities.

Minitrack Co-Chairs:

Hope Jensen Schau (Primary Contact)
University of California Irvine
schauh@uci.edu

Melissa Akaka
University of Denver
Melissa.Akaka@du.edu

Martin Key
University of Colorado, Colorado Springs
tmkey@uccs.edu

Esports Minitrack

Esports is a rapidly growing area of research, presenting both opportunities and challenges. Despite significant progress, esports research offers numerous occasions for academics and industry professionals to examine electronic games and their impact on people and societies worldwide. Esports represents a transformative intersection of technology, competitive play, and social organization that has evolved from a niche subculture into a global multi-billion-dollar industry.

As a burgeoning field of academic inquiry, esports offers a multifaceted lens through which researchers examine the impact of digital competition on human cognition, social structures, and economic systems. The rapid convergence of electronic gaming technology, including, but not limited to AR, VR, MR, XR, and the burgeoning “metaverse” represents a paradigm shift in global sports and social interaction. This evolution is not merely a technological advancement but a socio-economic transformation that positions esports as a dominant, technically advanced sports world with a global reach across all layers of society. All fields of esports and electronic games research need to keep pace with esports advancement, recognizing the global reach of this play-based activity across layers of society. Moreover, there are abundant opportunities for collaboration with related fields such as technology development, game development, internet policy, gamification, and tools for connectivity and the digital economy.

This minitrack aims to provide insight into all areas of esports’ theoretical development and practical understanding, without excluding any methodological approach or scientific disciplines. Conceptual, theoretical, empirical, and methodological contributions that enrich our understanding of esports are welcome. Given the diverse goals of this minitrack, possible topics include, but are not limited to:

  • Business, e.g. discovering esports consumers’ motivations; designing effective marketing tools; understanding players’/esports’ networks and organizations; gamers/fans as consumers
  • Cognitive Science/Psychology, e.g. studying factors influencing athletes’ performance; their abilities and skills; cognitive and behavioral differences between athletes
  • IT and Computer Science, e.g. using game telemetry, biometrics, user-generated data, or text mining to study esports, e.g. team dynamics, interactions of players; in-game performance
  • Artificial Intelligence and Virtual Reality, e.g., developing AI-powered game analytics; creating intelligent training systems for players; machine learning; VR technology for immersive spectator experiences and player training simulations.
  • Law, e.g. copyright issues, IT solutions for anti-corruption and integrity, (Policy?)
  • Sociology and Anthropology, e.g. governance, online ethics, gamers’ and athletes’ interactions, experiences, and identities; live events and streaming dynamics; gender issues (gender gap)
  • Media Studies, e.g. relations between esports, traditional sports, and the media; offline spaces versus live-streaming, understanding esports in terms of virtual versus real; how technology mediates gaming, and how esports’ communities fit here.
  • Sport Science, e.g., comparing esports and ‘traditional’ sports; esports as ‘real’, ‘genuine’ sports or new quality
  • Video Game Developers, e.g., creating popular and competitive esports involves improving numerous game elements, including, but not limited to game mechanics, balance (e.g., nerfing), and player and spectator engagement and collaboration

Accepted research will be considered for publication in a special issue of the Journal of Electronic Gaming and Esports (JEGE).

Minitrack Co-Chairs:

David Hedlund (Primary Contact)
St. John’s University
hedlundd@stjohns.edu

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

Emma Witkowski
RMIT University
Emma.witkowski@rmit.edu.au

Lindsey Darvin
Syracuse University
ledarvin@syr.edu

Game-based Learning Minitrack

Game-Based Learning (GBL) is an evolving field that integrates game elements, mechanics, and principles into education and training to enhance students’ experience and learning outcomes. As digital learning landscapes rapidly expand, GBL continues to evolve, incorporating cutting-edge technologies such as artificial intelligence (AI), extended reality (XR), and adaptive learning systems. This minitrack explores the latest advancements in GBL and its intersections with emerging fields, fostering discussions on the future of learning through play, interactivity, and immersive experiences.

This minitrack invites interdisciplinary contributions that explore empirical research, theoretical advancements, design methodologies, and applications of GBL across diverse contexts. It welcomes a wide range of research methodologies, including experimental studies, longitudinal research, mixed‑methods approaches, case studies, design‑based research, and systematic literature reviews. Our goal is to push the boundaries of GBL by examining how emerging technologies, interdisciplinary frameworks, and innovative pedagogical models can shape the future of learning through games. We encourage submissions that address both foundational and forward‑looking aspects of GBL, including, but not limited to:

  • Artificial Intelligence & Learning Analytics: AI-driven adaptive learning in GBL, predictive analytics, dynamic game-mechanics adjustments based on learner data, and ethical considerations in AI-driven game-based learning
  • Computational & Technological Developments: Procedural content generation, AI-powered NPCs for dynamic learning interactions, multi-agent simulations, blockchain applications in GBL, and cloud-based GBL platforms.
  • Cultural & Social Dimensions: Socio-cultural perspectives on GBL, inclusive design, accessibility, diversity in game narratives, gamification of social learning, and ethical concerns in game-based educational interventions.
  • Ethical & Societal Implications: Addressing privacy, bias, fairness, and the responsible use of gamification and game-based approaches in education and training
  • Health & Wellbeing: GBL for mental health, physical rehabilitation, behavior change interventions, mindfulness training, and exergaming applications
  • Human Factors & Learner Experience: Studies on user engagement, motivation, cognitive load, player typologies, adaptive learning pathways, and personalized learning experiences in GBL
  • Immersive & Emerging Technologies: Applications of XR (VR/AR/MR), the metaverse, spatial computing, and haptic technologies in GBL; implications of generative AI in content creation and adaptive learning, e.g., in blended physical-digital ecosystems
  • Applications & Haptic Technologies: Serious games, simulations, and hybrid learning formats combining digital environments with physical artifacts (e.g., tangible interfaces, smart objects, cyber-physical systems)
  • Civil Resilience & Preparedness: GBL approaches to foster civil resilience and preparedness through application systems (apps) and hybrid physical-digital systems; serious games, simulations, and scenario based training for crisis awareness, disaster response, risk communication, and decision-making under uncertainty
  • Pedagogical Innovation: Integration of GBL with instructional strategies, intelligent tutoring systems, competency-based education, and immersive storytelling for deeper learning

Authors of accepted papers have the option to fast-track extended versions of their HICSS papers to Smart Learning Environments.

Minitrack Co-Chairs:

Wilk Oliveira (Primary Contact)
Tampere University
wilk.oliveira@tuni.fi

Samuli Laato
University of Turku
samuli.laato@utu.fi

Juho Hamari
Tampere University
juho.hamari@tuni.fi

Jochen Scheeg
University of Applied Sciences Brandenburg
scheeg@th-brandenburg.de

Generative AI for Organizational, Societal, and Emotional Relationships and Partnerships Minitrack

This minitrack examines the profound impacts of generative AI (GenAI) technologies on organizational collaboration, human relationships, and social structures as well as investigating new cognitive perspectives of (Gen)AI solutions.

From the organizational perspective, GenAI significantly impacts collaboration across various levels, including organizational, project/team, and individual levels. It offers unique advantages and introduces notable challenges. This technology facilitates innovative partnerships ranging from bilateral collaborations to complex AI-driven ecosystems. GenAI revolutionizes organizational collaboration by automating repetitive tasks and augmenting human capabilities through co-intelligence. It is crucial to investigate its role in partner selection, specifically how it ensures strategic alignment, technological compatibility, and mutual trust. It is also important to explore the outcomes of GenAI on organizational collaboration. For instance, how adopting AI solutions enhances value co-creation with external partners by streamlining communication, empowering stakeholders, and strengthening social networks. Additionally, at the project level, it is necessary to study how AI reduces failure rates by improving decision-making, mitigating risks, and optimizing resource allocation.

From a human-centric societal perspective as these AI systems become more pervasive in our daily lives, it is crucial to examine how they may impact the essential fabric of human existence – the relationships between friends, romantic partners, family members, coworkers, ingroup and outgroup members, communities, and cultural groups.

GenAI has the capability to act as a new type of “relationship” for individuals, potentially replacing or complementing traditional human-to-human interactions. For example, GenAI is already being used to simulate and complement human interactions, alleviating loneliness but also probably reducing genuine human interactions. There is a growing consensus among AI researchers that cognitive architectures will play a pivotal role in the future development of GenAI. However, Large Language Models (LLMs) exhibit significant limitations in several respect, such as social and emotional intelligence, commonsense reasoning, and context understanding.

    The minitrack welcomes sociotechnical contributions that address, but are not limited to, the following research areas:

    • Organizational Collaboration Perspectives of GenAI:
      1. Empirical studies examining how the use of GenAI for partner selection and evaluation affects trust between companies
      2. Design of GenAI-powered systems that influence the balance between knowledge sharing and the protection of sensitive information in complex multi-partner collaborations
      3. Empirical investigations into the potential impacts of human-(Gen)AI interactions on the physical and mental health of employees
      4. Empirical studies on the role of GenAI in bridging cultural gaps in international joint ventures and its contribution to building trust
      5. Design of GenAI-mediated communication and collaboration tools that enhance organizations’ innovation capabilities through improved collaboration and communication processes with external partners
      6. Design of GenAI as a knowledge broker in collaborative environments, focusing on knowledge management and protection against opportunistic behavior
      7. Empirical studies on the implementation of formal and informal governance mechanisms in inter-organizational collaborations supported by GenAI, and its impact on the sustainability and success of such partnerships
    • Human-centric Societal Perspective on Relationships with GenAI as Partner:
      1. Empirical studies examining the impact of GenAI on trust in institutions, professionals, and decision-making processes
      2. Design principles that foster transparency, accountability, and trustworthiness in human-GenAI interactions
      3. Investigations into the effects of GenAI-generated content on intergroup perceptions, stereotypes, and prejudice
      4. Investigation into the integration of GenAI into social media platforms, examining how it transforms individual relationships and its implications for social structures and cultural norms
      5. Investigations into the psychological, social, and physiological impacts of human-GenAI interactions, particularly in the context of substituting human-human interactions
      6. Design principles that promote healthy and meaningful human-AI relationships, fostering social connectedness and emotional well-being
    • Multidisciplinary Cognitive Architecture Perspective for AI and GenAI Development:
      1. Empirical research on how cognitive architectures can enhance the explainability and transparency of (Gen)AI systems
      2. Design of approaches to imbue (Gen)AI systems with social-emotional intelligence comparable to that of humans
      3. Empirical studies on how (Gen)AI systems can be trained to understand and appropriately respond to emotional cues in various social contexts
      4. Empirical advancements necessary to improve the commonsense reasoning capabilities of GenAI systems
      5. Empirical research on the role of context in the development of more adaptive and responsive (Gen)AI systems
      6. Investigations into how trust and empathy can be cultivated in human-(Gen)AI interactions to ensure harmonious and effective collaboration
      7. Empirical studies on the foreseeable challenges in the development and deployment of advanced cognitive architectures in (Gen)AI

    Minitrack Co-Chairs:

    Frank Bodendorf (Primary Contact)
    Research and Innovation Center BMW Group Headquarters Germany
    frank.BF.bodendorf@bmw.de

    Thomas Kude
    University of Bamberg
    thomas.kude@uni-bamberg.de

    Governing the Digital Commons Minitrack

    In modern sociotechnical systems, digital commons, as the co-production of data or knowledge and community via networked systems, are increasingly prevalent and visible. Along with the people and digital resources produced, governance regarding participation, access, and use of data and knowledge is necessary to foster engagement. Such commons governance is polycentric, with many centers of decision-making, addressing both dilemmas associated with underlying knowledge resources and dilemmas associated with shared communication and coordination strategies needed to produce effective governance itself.

    Wikipedia, and FoldIt—to emergent subcommunities dedicated to everything from social movements to niche hobbies, via Facebook Groups or specific Toks, modern networked interactions produce significant information resources as digital commons. This mini-track will explore community governance of innovation and creativity, immaterial resources long associated with intellectual property from an interdisciplinary perspective. Case studies across a broad range of social, cultural, and economic contexts are invited; empirical documentation of knowledge commons governance, dilemmas, and shared resource management in communities may be informed by institutional theory, such as the Institutional Analysis and Development (IAD) or Governing Knowledge Commons (GKC) frameworks. The mini-track also welcomes critiques and theorization regarding data and knowledge commons in the digital economy.

    • Collective action problems in the modern digital economy
    • Community management of deepfakes, misinformation, and online manipulation
    • Crowd sourcing
    • Data Commons
    • Data governance and protection
    • Digital ownership
    • Knowledge commons
    • Online collaboration and creation communities
    • Peer production
    • Social norm formation, such as around privacy, security, or community expectations
    • Subcommunities on online platforms

    Papers accepted for presentation in this minitrack will be invited to submit extended manuscripts. The manuscripts will be fast-tracked through the review process for a special issue of Information Research to be published in Spring 2027.

    Minitrack Co-Chairs:

    Madelyn Rose Sanfilippo (Primary Contact)
    University of Illinois at Urbana-Champaign
    madelyns@illinois.edu

    Sara Benson
    University of Illinois Urbana-Champaign
    srbenson@illinois.edu

    Melissa Ocepek
    University of Illinois Urbana-Champaign
    mgocepek@illinois.edu

    Anjanette Raymond
    Indiana University Bloomington
    Angraymo@iu.edu

    Human-Computer Interaction Minitrack

    This minitrack examines how humans engage with digital technologies within rapidly evolving socio-technical ecosystems. We welcome research that advances theoretical, design-oriented, and empirical understanding of human engagement with systems, as well as their cognitive, behavioral, emotional, organizational, and societal implications. Potential topics include, but are not limited to:

    • Human-Centered Design and Usability Engineering: Principles, standards, and evaluation methods for designing effective, usable, inclusive, and friction-reducing interactive systems across platforms
    • Human-AI Interaction and Intelligent Systems: Design and evaluation of human-AI collaboration; interaction with generative, adaptive, and personalized systems; prompt design; explainability; and AI-mediated decision environments
    • User Experience (UX), Cognition, and Behavior: Cognitive, emotional, and behavioral responses to digital interaction; user behavior analytics; neurophysiological and neuroscientific approaches to HCI; and measurement of user states and performance outcomes
    • Trust, Governance, Privacy, and Security in HCI: Interaction-based mechanisms for fostering trust and transparency; usable privacy and security; behavioral biometrics and authentication; and ethical considerations in nudging, data capture, and AI-mediated interactions
    • Digital Choice Architecture and Behavioral Interaction Design: Design of digital choice environments; nudging and persuasion; behavioral economics in interaction design; and impacts on judgment, risk perception, and decision-making
    • Inclusive, Accessible, and Universal Interaction Design: Design for diverse populations, including older adults, children, and individuals with disabilities; accessibility standards; and inclusive innovation
    • Emerging Interaction Technologies and Modalities: Multimodal, sensor-based, immersive, mobile, ubiquitous, and neuroadaptive interaction paradigms; and innovative input/output technologies
    • Collaborative and Social Computing: Group HCI, collaboration platforms, digitally mediated teamwork, and the social and organizational dynamics of interactive technologies
    • Domain-Specific HCI Applications: Interaction design in contexts such as FinTech, m-commerce, healthcare, education, and other organizational or industry settings
    • Organizational and Societal Impacts of HCI: Human and societal consequences of digitally mediated interaction, including impacts on productivity, performance, governance, and digital ecosystems
    • HCI Education and Research Methods: Pedagogical approaches to teaching HCI; experimental, analytical, and design science methods for studying human interaction with technology

    There are opportunities for best papers of this minitrack to be fast-tracked to AIS Transactions on Human-Computer Interaction.

    Minitrack Co-Chairs:

    Christoph Schneider (Primary Contact)
    Washington State University
    schneiderc@wsu.edu

    Jeffrey Jenkins
    Brigham Young University
    jeffrey_jenkins@byu.edu

    Fiona Fui-Hoon Nah
    Singapore Management University
    fionanah@smu.edu.sg

    Alexander Dennis
    Iowa State University
    asdennis@iastate.edu

    Human-Like Conversational Agents: Chatbots, Companions, Digital Humans, and Virtual Influencers Minitrack

    This minitrack explores the transformative role of AI-powered conversational agents (e.g., chatbots and digital humans) in reshaping both professional and personal aspects of daily life. As AI-driven interactions become more prevalent in workplaces, social media, entertainment, and customer service, understanding their impact is crucial. This mini-track delves into key topics such as trust formation, emotional engagement, user adoption, and the ethical implications of integrating human-like AI agents into digital spaces. It also examines how these technologies influence human behavior, decision-making, and social interactions, ultimately redefining the way we communicate, collaborate, and engage within the digital environment in both work and life.

    Recent studies underscore key advancements in virtual influencers, emotional interactions with AI avatars, and the implications of digital human realism on credibility and engagement. As AI-powered digital humans become increasingly prevalent in marketing, social media, customer service, and virtual environments, understanding their psychological and behavioral effects is critical. This minitrack aims to explore themes such as consumer trust in AI-driven personas, the persuasive power of digital humans, ethical dilemmas in AI-generated content, and the role of synthetic media in shaping social perceptions. Additionally, we seek to examine the intersection of AI, human identity, and digital embodiment, providing a platform for interdisciplinary discussions on the future of AI-driven social interactions.

    Topics of interest include but are not limited to:

    • Visualization technology to advance digital humans
    • Challenges and problems with creating digital humans or scanning and sampling users.
    • Human-computer interactions, instilled with digital humans, including affective computing issues.
    • Design of digital humans by combining human and computer cognitive power.
    • Use of GANs and VAEs to infer digital human faces, including approaches building on ‘Deep Fakes’ technology.
    • Analysis of machine learning, big data, data mining, and other underlying technologies and algorithms of digital humans
    • Taxonomy of digital humans
    • Virtual influencers and YouTube digital celebrities
    • Impact of digital humans on the individual level (decision-making, problem-solving, negotiation, and creativity/innovation)
    • Psychological and emotional effects of interacting with realistic digital humans
    • Biases in interacting with digital humans and biases in the digital humans deployed
    • The use of digital humans beyond individuals and its consequences in organizations
    • Management of deployment (e.g., corporate governance, data management)
    • Case studies on industry adoption of digital humans
    • Use and economic implications of digital humans in e-commerce, social media, and the combinations of multiple industries involving e-commerce and social media.
    • Social impact and ethics related to digital humans and their use
    • Philosophical questions surrounding the idea of ‘using’ digital humans

    Minitrack Co-Chairs:

    Lingyao Yuan (Primary Contact)
    Iowa State University
    lyuan@iastate.edu

    Mike Seymour
    University of Sydney
    mike.seymour@sydney.edu.au

    Petri Parvinen
    University of Helsinki
    petri.parvinen@helsinki.fi

    IS Security and Privacy Minitrack

    This minitrack specifically focuses on behavioral aspects of IS safety, security and privacy, focusing on human-centric risks, decision-making processes, and strategies to mitigate internal and external threats. Topics include leadership, risk management, and emerging technologies.

    The focus is on internal and external threats exacerbated or mitigated by human capabilities and/or behaviors. This includes research on security compliance, the weaponization of emotions in cybersecurity, the impact of cognitive heuristics, accessibility & inclusivity in cybersecurity, decision-making in phishing and cyber resilience contexts, and behavioral (cognitive or affective) biases affecting secure and privacy-preserving behaviors. Topics include, but are not limited to:

    • Creative rigorous investigations of actual user security behavior, both positive and negative including modeling of security and privacy behavioral phenomena and relationships
    • Cyber leadership
    • Detecting and mitigating insider threats
    • The impact of AI on personal cybersecurity and privacy
    • Security policy compliance research – motivations, antecedents, levers of influence; Research contrasting policy compliance with actual secure behaviors
    • Analysis of known and unknown modes and vectors of internal and external attack; Frameworks for assessing the effectiveness of interventions that intend to reduce organizational vulnerability to attacks
    • Explorations of the impact of generative AI and ML/LLM on security outcomes, for all stakeholders, including employees, citizens and organizations.
    • Studies examining privacy-related behaviors from a “privacy paradox” perspective
    • Merging methodological topics related to addressing research strategies in IS security
    • Translational science perspectives and strategies for IS security/privacy research
    • Dark patterns and their impact on secure and privacy-preserving behavior

    This mintrack will provide IS/IT researchers a collaborative forum to share their research approaches. We hope to attract the skills and insights of scholars from a wide set of disciplines, presenting a mix of theoretical and applied papers on threats and mitigation. Areas of research may include the following.

    • Research related to insider threats to information security and privacy represent the first and most important thread for the minitrack. Insider threats include activities ranging from non-malicious and nonvolitional behaviors (accidents and oversights) to volitional, but not malicious, actions to malicious actions such as theft, fraud, blackmail, sabotage, and embezzlement.
    • External vectors of attack by individuals and organizations outside the security perimeter represent the second thread for this minitrack. Specific topics of interest include hacker behaviors, cyber-warfare, identity theft (and electronic deception), and cyber-espionage, including most offensive and defensive methods of prevention, detection, and remediation. Other external parties are motivated to use IT to damage or steal trade secrets, national security information, sensitive account information, or other valuable assets.
    • We have a particular interest in emerging, rigorous research methods for investigating these phenomena. Organizational-level research can be improved, but studies conducted at the individual level, in particular, can benefit from new experimental designs and new data collection methods. Examples include neurophysiological (NeuroIS) methods such as EEG or fMRI, the factorial survey method, mixedmethods designs, and simulations.
    • The era of Artificial Intelligence is upon us, and it will change the cybersecurity landscape in significant ways. Organizations are likely to harness it to improve their detection mechanisms. On the other hand, cyber criminals are already using these tools to generate novel attacks, challenging all existing employee-focused training mechanisms and mandating a re-evaluation of these.
    • Papers that challenge the status quo in cybersecurity practice are welcomed, when backed up by strong argumentation and empirically-obtained evidence.

    Every coauthor of a paper submitted to our minitrack is obligated to review at least one other paper for the minitrack. Failure of any one coauthor to review for the minitrack may result in the rejection of the coauthor’s paper from the minitrack.

    Minitrack Co-Chairs:

    Karen Renaud (Primary Contact)
    University of Strathclyde
    karen.renaud@strath.ac.uk

    Allen Johnston
    University of Alabama
    ajohnston@cba.ua.edu

    Anthony Vance
    Virginia Tech
    Anthony@Vance.name

    Merrill Warkentin
    Mississippi State University
    m.warkentin@msstate.edu

    Metaverse for Work and Play Minitrack

    The Metaverse is a decentralized, shared, immersive, and persistent virtual environment. It is afforded by socially constructed and materially enabled IT artifacts that allow users to have unique identities represented by their avatars and authentic interactions with other users, human-like AI agents, and virtual assets. In other words, the Metaverse is a connection between the real and virtual world where one can work, study, play, shop, travel, socialize, and accomplish many other daily activities similar to the physical world. The Metaverse offers various opportunities, from creating new revenue streams for businesses to reducing operational costs, enabling distributed training, and fostering intellectual capital. The Metaverse is also an extension of the physical world, with opportunities beyond what the physical world offers to individuals. Especially with the immersion capabilities of the current powerful standalone head-mounted extended reality (XR) displays, one can experience what is not usually possible, such as spending a day in ancient Greece, walking on Mars, or exploring the mysteries of Kīlauea, in the Metaverse.

    While many opportunities exist for the Metaverse, it also has diverse challenges that may prevent successful adoption, such as surveillance, user tracking, deviant behavior design issues, unintended consequences such as addiction, technostress, anxiety, and cognitive overload, and the new security and privacy threats. By addressing both opportunities and challenges, this mini track aims to offer valuable insights into the impact of the Metaverse on users and organizations, as well as the policies and regulations necessary to ensure its responsible and ethical development. Topics of interest include, but are not limited to, the following:

    • Challenges and Risks in the Metaverse:
      1. Cybersecurity and privacy threats
      2. New attack vectors and surfaces (e.g., adversarial AI, biometric data breaches)
      3. The Darkverse – illegal and criminal activities in the Metaverse (e.g., illicit markets, cybercrimes, money laundering)
      4. Anti-forensics techniques user by hackers to evade detection in the Metaverse
      5. Deception and deep fakes (e.g., AI-generated misinformation and identity fraud)
      6. Deviant behavior (e.g., harassment, bullying, stalking, organized trolling, radicalization)
      7. Ethical concerns and implications for freedom of expression in the Metaverse (e.g., user surveillance, tracking, and censorship)
      8. Adverse physical, mental, and emotional effects (e.g., addiction, technostress, cyberpsychoses, misuse, etc.)
      9. Unintended consequences of AI-driven moderation and personalization (e.g., algorithmic biases and digital discrimination)
      10. Weaponization of virtual spaces (e.g., the use of the Metaverse for social engineering, radicalization, and digital warfare)
      11. Psychological manipulation (e.g., exploitative game mechanics, behavioral reinforcement, and persuasive design for engagement, surveillance, or deception)
    • Opportunities and Innovations in the Metaverse:
      1. Novel and sustainable business models (e.g., meta-tourism, Metaverse in eCommerce)
      2. User-centric monetization strategies (e.g., play-to-earn, digital economies, tokenization)
      3. Cost reduction, operational efficiency, and improved firm performance through Metaverse adoption
      4. Corporate training, distributed learning, and virtual collaboration for improved team performance
      5. Knowledge creation, retention, and dissemination in immersive environments
      6. Metaverse applications (meta-apps) for healthcare (e.g., telemedicine, virtual therapy, rehabilitation)
      7. Mental and physical health benefits (e.g., meta-fitness, stress reduction, gamified wellness programs)
      8. Opportunities for vulnerable populations (e.g., improving accessibility for elderly individuals and people with disabilities)
      9. Positive behavioral reinforcement through gamification (e.g., reward systems for healthy habits, ecoconscious behavior, and social good initiatives in virtual environments)
    • Governance and Regulation of the Metaverse
      1. Intellectual property, copyright, and ownership
      2. Data privacy, transparency, anonymity, and virtual identities
      3. New standards, regulations, compliance, and governance mechanisms for the Metaverse
      4. Hardware (e.g., haptics, trackers) and software (e.g., digital twins, asset management) ecosystems
      5. Integration with complementary and enabling technologies (e.g., Blockchain, AI, NFT, XR, VR, AR, MR, IoT, wearables)
      6. Digital divide, accessibility, and diversity, equity, and inclusion (DEI)
      7. Digital personas, avatars, and virtual assets
      8. Safeguarding and well-being of vulnerable populations (e.g., children, neurodivergent individuals, marginalized communities)
      9. Fairness in virtual environments
      10. Ethical AI and algorithmic accountability
      11. Metaverse governance frameworks and decentralized decision-making
      12. Public vs. private governance models
      13. Game-theoretic approaches to Metaverse policy and governance

    High-quality and relevant papers from this minitrack will be selected for a fast-track opportunity at the Journal of Intellectual Capital.

    Minitrack Chairs:

    Ersin Dincelli (Primary Contact)
    University of Colorado Denver
    ersin.dincelli@ucdenver.edu

    Merrill Warkentin
    Mississippi State University
    m.warkentin@msstate.edu

    Paul Benjamin Lowry
    Virginia Tech
    Paul.Lowry.PhD@VT.edu

    Juho Hamari
    Tampere University
    juho.hamari@tuni.fi

    Socio-Economic Impacts of AI and Algorithmic Systems Minitrack

    Advancements in computing technologies and algorithms are driving a new wave of innovation. In recent years, generative AI (Gen AI) and machine learning (ML) have achieved remarkable breakthroughs in areas such as chatbots, software development, autonomous driving, speech and facial recognition, and image and video generation.

    As AI continues to evolve, businesses across industries are eager to harness its potential to improve operations, create value, and gain a competitive edge. However, successful AI adoption requires more than technical expertise—it also demands business insights and ethical responsibility. Since AI’s performance relies on the data it learns from, ensuring transparency and fairness is crucial. Moreover, as AI becomes deeply embedded in economic activities, its broader impact needs to be carefully assessed. How will automation reshape jobs, skills, wages, and labor markets? How will personalized recommendations influence business models and consumer behavior? What risks and challenges does AI pose for decisionmaking and society at large? These questions demand careful study in the years ahead to ensure AI benefits both businesses and society.

    This minitrack examines the socio-economic impacts of AI and algorithmic systems, with a focus on business value, transparency, user behavior, and applications in various domains including operations, finance, healthcare, and digital platforms. It addresses human-AI interaction and systemic challenges in adopting AI technologies. While submissions employing ML and AI algorithms are highly encouraged, they ideally need to explore the broader impacts and implications of these technologies. We welcome both research-in-progress and practical studies that have the potential to make meaningful contributions to the business community.

    • User behavior, response, and reaction to algorithm fairness, bias, and aversion
    • Economic and societal impacts/implications of AI and ML algorithms
    • Digital platform and market design driven by algorithms
    • The algorithmic economy
    • Agentic AI
    • Human-algorithm interaction and its implications
    • Explainability, interpretability, and accountability in AI and ML
    • Theory-driven development and evaluation of AI and ML algorithms
    • AL and ML applications in fintech, operations, cybersecurity, healthcare, accounting

    Minitrack Co-Chairs:

    Zhongju John Zhang (Primary Contact)
    Arizona State University
    Zhongju.Zhang@asu.edu

    Yong Ge
    University of Arizona
    yongge@arizona.edu

    Tech-Enabled Customer Experience: Experience Design and Impact Minitrack
    Customer experience (CX) has expanded beyond the marketing domain and become an increasingly important topic in information systems research, driven by the rapid proliferation of digital technologies, data analytics, platforms, and artificial intelligence (AI). Contemporary information systems increasingly shape how customers perceive, interpret, and interact with products, services, brands, and organizations. Digital infrastructures such as mobile applications, recommendation systems, AI assistants, and platform ecosystems influence sensations, cognitive and emotional responses, and decision-making processes across both digital and physical touchpoints. As customer journeys become more complex and interconnected, understanding the role of information systems in shaping technology-enabled CX has become a critical research agenda.
     
    This minitrack focuses on how information systems and emerging technologies contribute to the design, management, and transformation of CX. It aims to advance a socio-technical understanding of technology-enabled CX by examining how system architectures, algorithms, interfaces, and digital platforms shape customer interactions and outcomes. 
     
    The minitrack welcomes research that investigates both the design of technology-enabled experiences and the behavioral, organizational, and societal implications of such experiences. We encourage interdisciplinary work that bridges information systems, human–computer interaction, service marketing, and innovation research. Both conceptual and empirical contributions are welcome, including qualitative, quantitative, experimental, computational, and design-oriented approaches.
     
    Topics of interest include, but are not limited to:
    • AI-assisted experience personalization and its effects on trust, autonomy, and satisfaction
    • Algorithmic experience design and explainable interaction models
    • Omnichannel and cross-platform experience management
    • Data ethics, privacy, and user autonomy in digital customer journeys
    • Platform ecosystems and experience co-creation
    • Behavioral and emotional customer experience analytics

    Minitrack Co-Chairs:

    Huimin Liu (Primary Contact)
    Hong Kong Metropolitan University
    huliu@hkmu.edu.hk

    Liang Zhao
    Sichuan Tourism University
    zhaoliang@sctu.edu.cn