TRACK DESCRIPTIONS

Track Co-Chairs

Wonseok OhWonseok Oh
Korea Advanced Institute of Science and Technology
David Chee Wei PhangDavid Chee Wei Phang
University of Nottingham Ningbo China
Ofir TurelOfir Turel
University of Melbourne


Track Description

The world is entering an unprecedented era of AI-driven digital transformation in which artificial intelligence (AI) and other emerging digital technologies—including generative AI, physical AI robots, and agentic AI—are fundamentally reshaping economies, industries, governance systems, and everyday human experiences. These rapid technological advancements and innovations present extraordinary opportunities to enhance productivity, accelerate innovation, strengthen global connectivity, and improve quality of life on a scale previously unimaginable.

At the same time, however, the accelerating pace of digital disruption has also intensified critical societal challenges. Widening social and economic inequalities, uneven access to digital infrastructure and technological resources, ethical and governance concerns surrounding AI deployment, and growing disparities in digital participation continue to threaten equitable progress across communities, regions, and populations. As digital innovation continues to accelerate, ensuring that the benefits of AI and emerging technologies are distributed fairly, responsibly, and inclusively has become one of the defining challenges of the digital age.

Against this backdrop, the PACIS 2027 Theme Track, “Innovating a Digital Future for an Inclusive Tomorrow,” invites original research papers that examine how AI-driven innovation and emerging digital technologies can contribute to building a more inclusive, sustainable, resilient, and human-centered future. As societies become increasingly interconnected through intelligent systems and digital platforms, this track seeks to explore how these technologies can be responsibly designed, ethically governed, and effectively implemented to reduce social and economic inequalities, expand accessibility and participation, and enhance long-term societal well-being. We particularly welcome interdisciplinary and forward-looking research that investigates the role of AI and digital transformation in advancing inclusive growth, digital equity, social innovation, sustainability, and human flourishing.

Potential topics include, but are not limited to:

  • Design for inclusive digital platforms
  • AI and related technology accessibility for disadvantaged user groups
  • Human-computer interaction (HCI) for inclusive user experiences
  • Adaptive technologies and assistive information systems
  • Interface design for aging populations and elderly digital engagement
  • Ethical AI algorithms for fairness, bias mitigation, and non-discrimination
  • Explainable AI for inclusive decision-making in public and private sectors
  • Governance, regulation, and policy for AI deployment
  • Sustainable and ethical digital innovation for equitable growth
  • AI for social good and community-centric digital solutions
  • Smart cities and inclusive urban digital systems
  • Digital public infrastructure for equitable service delivery
  • Cloud and digital infrastructure for small businesses and grassroots organizations
  • Open data initiatives for transparent and inclusive governance
  • Social innovation and tech entrepreneurship for marginalized groups
  • Platform economy regulation for fair and inclusive market participation
  • Circular digital economy for inclusive sustainable development
  • Digital literacy education for inclusive societal participation
  • Inclusive digital policies for underserved and vulnerable populations

Associate Editors

  • Angela Choi (Korea University)
  • Raffaele Ciriello (University of Sydney)
  • Uri Gal (University of Sydney)
  • Wangyu Heo (American University)
  • Andrew Lee (University of Texas, Dallas)
  • Li (Lily) Liu (City University of Macau)
  • Libo Liu (University of Melbourne)
  • Cheng Luo (Tianjin University)
  • Julian Marx (University of Melbourne)
  • Yongjin Park (City University of Hong Kong)
  • Xixian Peng (Zhejiang University)
  • Sunghan Ryu (University of Nottingham Ningbo China)
  • Alexander Serenko (Ontario Tech University)
  • Camen Teh (NEOMA Business School)
  • Seokchae Yoon (Korea Advanced Institute of Science and Technology)
  • Mingxin Zhang (NTU Singapore)

Track Co-Chairs

 
Weiling Ke
Southern University of Science and Technology

John Qi Dong
Nanyang Technological University

Sabine Matook
The University of Queensland


Track Description

This track serves as a boundary-expanding space for research that advances the intellectual frontier of the Information Systems (IS) discipline. As digital technologies increasingly reshape economic, organizational, and societal structures, many important phenomena do not yet align with established research streams. This track is designed to capture such developments, providing a venue for theoretically ambitious, empirically novel, and interdisciplinary work that challenges existing paradigms and opens new directions for IS scholarship.

We particularly encourage submissions that go beyond incremental extensions of prior work and instead seek to theorize emerging digital phenomena, introduce new conceptual lenses, or explore novel contexts. This includes research that engages with evolving forms of organizing, novel governance mechanisms, and shifting human-technology relationships in increasingly complex sociotechnical environments. Both mature and early-stage works are welcome, provided they demonstrate strong potential to shape future IS conversations.

For instance, artificial intelligence (AI) is now deeply embedded across digital systems rather than confined to a single domain. In this track, we view AI as a pervasive infrastructural and organizational force that interacts with a wide range of emerging IS phenomena. We therefore welcome research examining how AI reconfigures coordination, decision-making, control, and value creation across diverse contexts, while complementing (rather than overlapping with) the dedicated GenAI track.

Potential topics include but are not limited to:

  • Theorizing new digital phenomena and emerging IS constructs
  • Interdisciplinary IS research spanning organizational, economic, and societal domains
  • Novel forms of organizing, coordination, and governance enabled by or developed for digital technologies
  • Algorithmic management and evolving digital work arrangements
  • Human–technology collaboration, augmentation, and control in emerging settings
  • Digital innovation under uncertainty, ambiguity, and rapid changes
  • New data ecosystems, data ownership, and value appropriation mechanisms
  • Ethical, societal, and regulatory implications of emerging digital technologies
  • IS in extreme, underserved, or non-traditional contexts
  • Design science for nascent technologies and applications
  • Methodological innovations for analytics and new forms of digital data
  • Evolution of digital infrastructures and sociotechnical systems

Track Co-Chairs


Sophia Duan
La Trobe University

Junming Liu
City University of Hong Kong

Tapani Rinta-Kahila
Hanken School of Economics


Track Description

This track explores the emerging tensions, opportunities and risks at the intersection of algorithmic management and AI governance, with a particular focus on how AI reconfigures control, coordination, and accountability in organizations. Firstly, we welcome conceptual, empirical, and design science research that investigates how algorithmic systems are deployed to manage, monitor, and coordinate human activities within and across organizations. Secondly, we hope to attract research on the governance mechanisms, whether regulatory, organizational, or technical in nature, which shape and constrain these systems and their outcomes. Given the pervasive role of AI in contemporary information systems, this track explicitly positions AI as a central enabler and subject of algorithmic management and governance practices. We encourage submissions that address how AI technologies (e.g., machine learning, natural language processing, automated decision-making systems) are integrated into management and governance frameworks, and how such integration creates both opportunities and challenges for individuals, organizations, and society.

We invite researchers from diverse disciplinary backgrounds, including information systems, management, computer science, law, and public policy, to submit work that advances theoretical understanding, provides empirical insights, and/or offers practical guidance on the responsible design, deployment, and governance of algorithmic and AI-based management systems.

Potential topics relevant to this track include, but are not limited to, the following:

  • Algorithmic decision-making and accountability in organizational contexts
  • AI-driven workforce management and human resource analytics
  • Governance frameworks for algorithmic and AI systems
  • Organizational issues with algorithmic fairness, accountability, and transparency
  • Coordinating human-AI collaboration and augmentation in the workplace
  • Algorithmic control and governance on online labor platforms
  • AI regulation, policy, and organizational compliance
  • Ethical implications of algorithmic management practices
  • Workers’ responses to algorithmic management (e.g., resistance, workarounds, activism)
  • Algorithmic surveillance, worker autonomy, and power dynamics
  • Responsible AI design, implementation, and auditing in organizations
  • AI governance challenges in cross-cultural and Asia-Pacific contexts
  • Trust, explainability, and user acceptance of AI-driven decisions
  • Societal implications of algorithmic management for inclusive and sustainable futures

Associate Editors

  • Pouria Akbarighatar (University of Agder)
  • Allen Au (Edith Cowan University)
  • Reihaneh Bidar (The University of Queensland)
  • Josephine Chong Leng Leng (Nanyang Technological University)
  • Manting Hu (City University of Hong Kong)
  • Andrey Indukaev (Hanken School of Economics)
  • Michael Lane (University of Southern Queensland)
  • Yanqing Lin (Hanken School of Economics)
  • Sachithra Lokuge (University of Southern Queensland)
  • Yaxue Qin (City University of Hong Kong)
  • Sippo Rossi (Hanken School of Economics)
  • Joona Ruissalo (Aalto University)
  • Yunhui Wang (The University of Hong Kong)
  • Santoso Wibowo (Central Queensland University)
  • Miao Yu (City University of Hong Kong)
  • Xin Zhang (University of Science and Technology of China)

Track Co-Chairs


Shaokun Fan
Oregan State University

Blair Wang
Curtin University

Jianliang (Leon) Zhao
City University of Hong Kong (Shenzhen)


Track Description

Fintech, Blockchain, and Quantum Computing are innovative technologies with considerable implications for digital economy, business and society. Fintech and Blockchain have already fundamentally changed how we handle trust and value, and Quantum Computing is set to double down on this disruption, offering computational breakthroughs while simultaneously threatening the cryptographic foundations that keep current systems secure.

This track seeks to cultivate innovative research in the realms of Fintech, Blockchain, and Quantum Computing, while fostering discussions on their present and future trajectories. This track welcomes papers that explore these technologies individually or as a combined force, particularly in business and societal applications. We extend an invitation for both theoretical and empirical studies adopting diverse perspectives, including behavioral, computational, design science, economics, and organizational ones.

Potential topics include, but are not limited to:

  • Theoretical advancements in Blockchain, Fintech, and Quantum-ready systems
  • Security, privacy, and post-quantum cryptography in financial applications
  • Algorithms, architectures, and protocols for quantum-enhanced or decentralized financial solutions
  • Innovations in Fintech, including AI-driven services, digital banking, and quantum-assisted algorithmic trading
  • Blockchain-based fintech like Decentralized Finance (DeFi), Real World Asset (RWA) tokenization, and DAOs
  • Implications of token economies and quantum computing for organizational and business models
  • Applications of Blockchain and AI in financial market insights, risk management, and compliance
  • Case studies of blockchain and quantum computing implementations across industries
  • Central bank digital currencies (CBDCs), stablecoins, and the future of digital currencies

Associate Editors

  • Muhammad Usama Islam (Metropolitan State University)
  • Daning Hu (Southern University of Science and Technology)
  • Rong Liu (Florida International University)
  • Yidi Liu (The Chinese University of Hong Kong, Shenzhen)
  • Jiaqi Yan (Nanjing University)
  • Hongzhe Zhang (Shanghai Jiao Tong University)
  • Zhe (Jay) Shan (Miami University)
  • Noyan Ilk (Florida State University)
  • Daniel Treku (Worcester Polytechnic Institute)
  • Hong Zhang (University of Arizona)
  • Lin Yue (Macquarie University)
  • Mengyao Fu (Deakin University)
  • Mahdi Fahmideh (University of Southern Queensland)

Track Co-Chairs


Hsin-Lu Chang
National Chengchi University

Yulin Fang
University of Hong Kong

Zhongyun (Phil) Zhou
Tongji University


Track Description

This track invites rigorous research advancing theoretical and empirical understanding of digital transformation, innovation, and strategy. We are particularly interested in how organizations conceive, orchestrate, and sustain digital innovation, and how they navigate strategic challenges and paradoxes, including tensions between agility and stability, innovation and governance, and value creation and social inclusion. We also welcome contributions examining how digital innovation unfolds across ecosystems, platforms, and open innovation settings where boundaries between firms, industries, and users are increasingly blurred.

This track embraces a multi-level perspective spanning individual, organizational, ecosystem, and societal levels, raising questions about workforce disruption, digital inclusion, business value creation, and sustainable development. We particularly encourage research in Asia-Pacific contexts, where rapid economic growth, social diversity, and sustainability imperatives create a distinctive backdrop. All methodological traditions are welcome, and critical perspectives on unintended consequences, trade-offs, and paradoxes are equally encouraged.

Potential topics include, but are not limited to:

  • Digital transformation strategies, frameworks, and roadmaps
  • Digital innovation processes, capabilities, and business model creation
  • Open innovation and co-innovation in digital ecosystems
  • Emerging technologies (e.g., AI, IoT, blockchain) as drivers of transformation
  • Digital leadership, organizational change, and dynamic capabilities
  • Paradoxes and dark sides of digital transformation and innovation
  • Digital innovation for sustainability and SDG alignment
  • Digital inclusion, equity, and socioeconomic impact in Asia-Pacific
  • Digital transformation in the public sector and e-government
  • Platform ecosystems and digital market dynamics
  • Digital entrepreneurship and startup innovation
  • Digital governance, data governance, and ethical dimensions
  • Cultural and institutional factors shaping digital transformation in Asia

Associate Editors

  • Meng Chen (University of Science and Technology of China)
  • Wooje Cho (Seoul National University)
  • Yipu Deng (University of Hong Kong)
  • Han-Fen Hu (University of Nevada, Las Vegas)
  • Xixi Li (University of Science and Technology of Beijing)
  • Yan Lin (University of Macau)
  • Angela Lu (Monash University)
  • Jeffrey Chih-Feng Tai (National Chiayi University)
  • Tommi Tapanainen (Pusan National University)
  • Scott Thiebes (Tongji University)
  • Jack Tong (Nanyang Technological University)
  • Yu-Ju Tu (National Chengchi University)
  • Kai Wang (National University of Kaohsiung)
  • Le Wang (City University of Hong Kong)
  • Liu’an Wang (Beijing Institute of Technology)
  • Shohil Kishore (University of Auckland)
  • Aihua Yan (Lingnan University)
  • Yixiu “Ashley” Yu (Central Michigan University)
  • Jicheng Zeng (Hong Kong Baptist University)

Track Co-Chairs


Zhang Cheng
Fudan University

Daniel Gozman
University of Sydney

Tat Koon Koh
Hong Kong University of Science and Technology

Ruonan Sun
Monash University


Track Description

Digital platforms have become a dominant organizational form, fundamentally reshaping how value is created, coordinated, and captured across industries. By connecting heterogeneous actors at scale, platforms enable new modes of exchange, innovation, and production across contexts such as mobility, finance, healthcare, and digital services. Increasingly, these platforms are embedded within broader ecosystems, where firms, users, and complementors co-evolve through complex interdependencies.
At the same time, platform-based organizing has transformed sourcing and production logics. Digital sourcing now extends beyond traditional outsourcing to include crowdsourcing, gig work, and distributed innovation, all coordinated through platform infrastructures. These developments call for renewed attention to governance, control, and value distribution in platform ecosystems.

Recent advances in artificial intelligence (AI) and data-driven and automation technologies further intensify these dynamics. AI-enabled platforms increasingly automate coordination, pricing, and decision-making, giving rise to new forms of algorithmic governance and digital labour management, while also introducing challenges related to trust, fairness, accountability, transparency, privacy, security, and regulation.

This track invites cutting-edge research that advances our understanding of digital platforms, sourcing, and ecosystems across multiple levels of analysis, including individuals, organizations, interorganizational networks, industries, and society. We welcome diverse theoretical perspectives and methodological approaches, including qualitative, quantitative, computational, experimental, and design science research.

Potential topics include, but are not limited to:

  • Platform governance and orchestration
  • Platform strategy, competition, complementarity, and value capture
  • Platform openness, modularity, and boundary resources
  • Enterprise platforms and internal platformization strategies
  • Platform-enabled business models and digital entrepreneurship
  • Digital sourcing, multi-sourcing, and platform-mediated outsourcing
  • Crowdsourcing, crowdfunding, and crowd-based innovation
  • Gig work, digital labour markets, and the future of work
  • Algorithmic management and AI-enabled labour coordination
  • AI/Agent for platform operations, pricing, matching, recommendation, and customer service
  • Trust, reputation, privacy, security, and risk in platform environments
  • Fairness, inclusivity, and transparency in digital platforms
  • Regulation, public policy, and antitrust in platform ecosystems
  • Platform sustainability, resilience, and societal impact
  • Cross-border platforms, geopolitics, and institutional differences
  • User participation, engagement, and decision-making on platforms
  • Platform innovation, ecosystem experimentation, and generativity

Associate Editors

  • Jiye Baek (Korea University)
  • Melissa Baba (University of Southampton)
  • Jiahe Chen (Western Sydney University)
  • Haowen Deng (Shanghai University of Finance and Economics)
  • Feng Guo (Tianjin University)
  • Andreas Hein (University of St. Gallen)
  • Frederico Iannacci (University of Sussex)
  • Yongsuk Kim (Sungkyunkwan University)
  • Geng Li (Fudan University)
  • Xishu Li (University of Birmingham)
  • Miaomiao Liu (Xi’an Jiaotong-Liverpool University)
  • Bingjie Qian (Tongji University)
  • Yingnan Shi (The University of Western Australia)
  • Furong Wang (Chongqing University)
  • Yancong Xie (RMIT University)
  • Qi Zhang (Southwest Jiaotong University)
  • Wenping Zhang (Renmin University of China)
  • Yingpeng Zhu (University of Macau)

Track Co-Chairs


Farkhondeh Hassandoust
University of Auckland

Wei Thoo Yue
City University of Hong Kong

Nina Schirrmacher
University of Sydney


Track Description

As digital technologies continue to reshape economies and societies, cybersecurity, privacy, and ethics have become central to building an inclusive and trustworthy digital future. The PACIS 2027 theme, “Innovating a Digital Future for an Inclusive Tomorrow,” highlights the need to ensure that innovation does not come at the cost of security, individual rights, or societal well-being.

Digital systems are now deeply interconnected, spanning platforms, infrastructures, and global supply chains. This creates expanding attack surfaces and complex risks that go beyond technical failures. Cyber threats such as ransomware, data breaches, and platform exploitation interact with human behavior, organizational practices, and institutional contexts. At the same time, growing concerns around data privacy, surveillance, and digital inequality raise critical ethical questions about fairness, accountability, and governance.

Artificial intelligence is increasingly embedded across digital environments, shaping both risks and responses. AI introduces new vulnerabilities, including data leakage, adversarial manipulation, and misinformation, while also enabling advanced threat detection and automated defense. It also raises ethical challenges related to bias, transparency, and responsible use. In this track, AI is treated as a cross-cutting element that both intensifies and transforms cybersecurity, privacy, and ethical issues.

This track invites research that advances understanding of how to design, govern, and use secure, privacy-preserving, and ethically responsible digital systems. We welcome a wide range of methodological approaches, including empirical, theoretical, and design-oriented work, as well as interdisciplinary perspectives. Submissions may examine individual, organizational, and societal levels, and should aim to inform both research and practice in building resilient and inclusive digital ecosystems.

Potential topics include, but are not limited to:

  • Cybersecurity governance, strategy, and risk management
  • Privacy regulation, compliance, and data governance
  • Ethical issues in digital platforms and information systems
  • Security and privacy in AI-enabled systems and applications
  • Algorithmic fairness, transparency, and accountability
  • Cybercrime, ransomware, and underground digital economies
  • Human behavior, insider threats, and security awareness
  • Privacy-enhancing technologies and secure data sharing
  • Digital surveillance, trust, and societal implications
  • Security and privacy in critical infrastructures and supply chains
  • Misinformation, deepfakes, and information integrity
  • Digital identity, authentication, and access control
  • Resilience, incident response, and recovery strategies
  • Ethical design and responsible innovation in IS
  • Cross-cultural and institutional perspectives on cybersecurity and privacy

Associate Editors

  • Christine Abdalla Mikhaeil (IESEG)
  • Tawfiq Alashoor (IESE Spain)
  • Leonardo Banh (University of Duisburg Essen)
  • Khalid Durani (University of Innsbruck)
  • Bowen Guan (University of Sydney)
  • Hwee-Joo Kam (University of Tampa)
  • Wilson Weixun Li (Deakin University)
  • Sean Maynard (University of Melbourne)
  • Cao Rui (City University of Hong Kong)
  • Maduka Subasinghage (UWA)
  • Pratik Tarafdar (Xavier School of Management)
  • Tamara Thuis (VU Amsterdam)
  • Tripti Singh (University of Alabama)
  • Bart van den Hooff (VU Amsterdam)
  • Jeremy Junmin Xu (Central South University)
  • Xiong Zhang (Beijing Jiaotong University)

Track Co-Chairs


Alexander Richter
University of Auckland

Eric W. T. Ngai
The Hong Kong Polytechnic University

Julian Prester
University of Sydney


Track Description

Technological developments, particularly the rapid advancement of generative AI and agentic systems, are fundamentally reshaping the landscape of work, leadership, and talent development. As organizations increasingly embed intelligent systems into their everyday processes, the established structures of work are transforming. The nature of employment is becoming more contingent and flexible, raising critical questions about how we design work that remains meaningful, productive, and distinctly human.

This track explores future of work through a “human-first” lens, examining how organizations, educational institutions, and society at large can cultivate meaningful collaboration. The integration of these technologies goes beyond mere automation and augmentation; it necessitates a reimagining of leadership models, human resource strategies, and managerial decision-making. Understanding these transformations calls for processual and relational perspectives that treat human-AI configurations not as fixed arrangements but as ongoing, emergent entanglements. As AI systems increasingly generate content, allocate tasks, and serve as integral teammates, organizations must reassess how talent is cultivated, managed, and retained in an era of algorithmic management.

Simultaneously, this transition requires a paradigm shift in education and continuous learning. Universities and enterprise learning ecosystems must innovate to deliver curricula and pedagogical methods that equip digital natives and established professionals alike with the skills to thrive. We must develop leaders capable of navigating the ethical, spatial, and temporal shifts of technology-mediated work, ensuring that human capital portfolios are as robust as the technologies they interact with.

Beyond the organizational boundary, the diffusion of AI raises imperative societal and policy questions. Designing the future of work involves speculative approaches to anticipate emerging career patterns and systemic shifts. Furthermore, as data-driven models dictate more of the human experience, issues of digital sovereignty, algorithmic fairness, and data rights must be at the forefront of the conversation.

We welcome rigorous research (conceptual, empirical, or design-oriented) that takes a broad, human-centric perspective on technology, talent, and the future of work. We seek submissions using a variety of theoretical and methodological approaches across levels of analysis—from individual learning and team dynamics to organizational strategy and public policy.

Potential topics include, but are not limited to:

  • Algorithmic management, algorithmic organising, people analytics, and human-centric AI-based decision systems
  • Generative AI, agentic systems, and their impact on job mobility and work design
  • Designing for meaningful human-AI collaboration and coordination
  • Mobile, nomadic, and platform-mediated labor supported by AI technologies
  • Cognitive load, well-being, and mental health in high-velocity digital work environments
  • Visibility practices, documentation norms, and coordination in all-remote and distributed work organisations
  • Curriculum design, pedagogical innovation, and adaptive learning in universities and workplaces
  • Developing leadership and managerial capabilities for AI-augmented environments
  • Continuous education, reskilling strategies, and the development of AI literacy
  • Digital sovereignty, data rights, and worker autonomy in algorithmically governed organizations
  • Public policy, global labor market regulation, and governance of AI and digital labor
  • Speculative foresight and the long-term strategic alignment of AI with human capital goals
  • The “Green-Digital Twin Transition”: How AI-driven work impacts environmental sustainability and corporate social responsibility goals

Associate Editors

  • Yi-Te Chiu (National Tsing Hua University)
  • Sangwook Ha (BNU-HKBU United International College)
  • Angtyasti Jiwasiddi (Bina Nusantara University)
  • Maggie Lee (Swinburne University of Technology)
  • Chun-Fong Lei (Macau University of Science and Technology)
  • Jialu Liu (Shanghai Jiao Tong University)
  • Bayu Nuswantoro (University of Marburg)
  • Saima Qutab (The University of Auckland)
  • Rora Sari (Universitas Padjadjaran)
  • Yuqiu Wang (South China Normal University)
  • Randy Wong (The University of Auckland)
  • Pengkun Wu (Sichuan University)
  • Yuanyuan Wu (Southwestern University of Finance and Economics)
  • Gerit Wagner (Frankfurt School of Finance and Management)
  • Yikai Yang (Hong Kong Polytechnic University)

Track Co-Chairs


Na Liu
University of Sydney

Zhiya Zuo
University of Macau

Saeed Akhlaghpour
University of Queensland


Track Description

Digital health is an area of robust growth. Health technologies continue to evolve rapidly and play a critical role in healthcare delivery by improving the quality of care, the transparency and accessibility of medical information, and the efficiency of information flows. The promise of digital health solutions, including those based on artificial intelligence (AI) and machine learning, is to support more cost-effective, patient-centred, and evidence-based healthcare through the appropriate and responsible use of data, process transformation, and the proactive involvement of patients in managing and sustaining their well-being.

At the same time, these advances raise important socio-technical challenges. These include (1) large-scale healthcare data integration and interoperability; (2) health data protection, privacy, cybersecurity, organisational resilience, and patient safety; (3) trust, responsible use, and the organisational and societal implications of digital health technologies; (4) explainability, transparency, and human oversight in the use of advanced analytics and AI; (5) the implementation, adoption, and scaling of healthcare innovations across diverse organisational and policy contexts; and (6) ensuring that healthcare information systems are accessible to and beneficial for all individuals, regardless of their socioeconomic status, geographic location, age, gender, ethnicity, or other characteristics.

The core aim of this track is to provide a forum for participants, including scholars, policy-makers, industry partners, and other stakeholders, to meet, interact, exchange ideas, and share innovations in healthcare information systems in the digital age. The track also seeks to address the complex organisational, social, and policy challenges associated with digital transformation in healthcare. We welcome research related to digital health and healthcare information systems and are open to conceptual, empirical, and design science research using a wide range of methods (e.g., simulation, survey, experimentation, literature review, case studies, and action research). Practice-based research is also encouraged. Both full research papers and research-in-progress papers are welcome.

Potential topics include, but are not limited to:

  • AI-driven health information systems for early detection and preventive care
  • Augmented reality (AR) and virtual reality (VR) in healthcare, including medical training and patient rehabilitation
  • Big data, applied AI, machine learning, and generative AI in healthcare
  • Conversational AI systems for patient interaction and self-management
  • Digital health inclusion, accessibility, and equity
  • Digital therapeutics
  • E-health, telehealth, mobile health, and their impacts
  • Health data sharing, interoperability, and health information exchanges
  • Health data protection, privacy, cybersecurity, and organisational resilience in healthcare
  • Health informatics and biomedical informatics
  • Diffusion, adoption, implementation, and scaling of digital health innovations
  • Personalised and precision medicine
  • Social, ethical, and value implications of digital health technologies
  • Technology-enabled patient care and self-management
  • Organisational, clinical, and economic impact of healthcare information systems
  • User-generated content, platforms, and participatory health practices
  • Wearable health devices and their health outcomes

Associate Editors

  • Amir Andargoli (Swinburne University)
  • Shuixia Chen (Huazhong University of Science and Technology)
  • Honglin Deng (Hong Kong Baptist University)
  • Shuang Geng (Shenzhen University)
  • Haofeng Jin (Sun Yat-Sen University)
  • Faezeh Karimi (University of Technology Sydney)
  • Javad Pool (Griffith University)
  • Pooja Sengupta (University of Auckland)
  • Maryam Shahbazi (UNSW Business School)
  • Yani Shi (Southeast University)
  • Elena Vlahu-Gjorgievska (University of Wollongong)
  • Xi Wang (Central University of Finance and Economics)
  • Fei Xiao (Central China Normal University)
  • Jiamin Yin (Renmin University of China)
  • Jianhua Yu (Lingnan University)
  • Ya Zhou (Xiamen University)

Track Co-Chairs


Zhijun Yan
Beijing Institute of Technology

Fiona Nah
Singapore Management University

Jiayuan Zhang
University of Auckland


Track Description

The Human-Computer Interaction (HCI) track invites research that examines the interactions and evolving relationships between people and digital technologies, focusing on how these interactions shape experiences, behaviors, and outcomes across a wide range of contexts. As digital systems become increasingly embedded in everyday life and organizational processes, understanding how users engage with, adapt to, and derive value from these technologies has become more complex and important. This growing complexity underscores the importance of HCI in explaining how technologies are interpreted, coordinated, and integrated into everyday activities. It also raises questions about how such interactions may enable or constrain access, participation, and inclusion across diverse user groups and settings, with significant implications for equity and the societal impact of digital systems.

We invite research exploring the interplay between humans and technologies across organizational, managerial, and societal settings. Potential research questions include how individuals and groups make sense of digital environments, integrate technological features into their tasks and workflows, and how these interactions influence decision-making, learning, and performance. We are also interested in research on new forms of human-GenAI interaction and the emerging interaction patterns introduced by GenAI-enabled systems. We welcome both theoretical and empirical studies using a wide range of methodological approaches, including experiments, qualitative studies, design science, and econometric analyses. The track also welcomes studies that develop and extend methodological approaches for investigating user behavior and interaction in complex, technology-rich environments.

Potential topics include, but are not limited to:

  • Adaptive and context-aware interface design
  • Usability evaluation, engineering, and metrics
  • Human-in-the-loop systems and automated decision-making
  • Human-computer interaction in the metaverse and immersive environments
  • Feature-level IT adoption, use, and appropriation
  • Inclusive interface design for elderly users, children, and other populations with special needs, promoting accessibility and equity
  • Inclusive human-computer interaction in organizational and societal contexts
  • Human dignity, ethics, and responsible technology design
  • NeuroIS perspectives on information systems design and use (e.g., neurocognition, neurophysiology, and eye-tracking)
  • Aesthetic and affective computing
  • Human-robot interaction
  • New paradigms of human-GenAI interaction
  • GenAI-driven transformation in human-computer interaction
  • Human-GenAI collaboration and its impact on decision-making
  • Governance, ethics, and interaction design for GenAI-enabled systems

Associate Editors

  • Nils Augustin (City University of Hong Kong)
  • Ben Choi (Nanyang Technological University)
  • Muller Y.M. Cheung (Deakin University)
  • Duong Dang (University of Vaasa)
  • Kai Wing Kevin Ho (University of Tsukuba)
  • Jack Shih-Chieh Hsu (National Sun Yat-sen University)
  • Saira Khan (University of Auckland)
  • Hongfei Li (The Chinese University of Hong Kong)
  • Lun Li (Fudan University)
  • Yan Li (ESSEC Business School Singapore)
  • Yangjun Li (Beijing Institute of Technology)
  • Wanxin Qiao (Beijing University of Technology)
  • Pattharin Tangwaragorn (Chulalongkorn Business School)
  • May Ying Wang (Beijing Normal-Hong Kong Baptist University)
  • Yichuan Wang (King Fahd University of Petroleum and Minerals)
  • David Xu (City University of Hong Kong)
  • Jiayu Yao (Nanyang Technological University)
  • Haonan Yin (Iowa State University)
  • Haoyu Yuan (Shanghai University of Finance and Economics)
  • Xiaowei (Elliott) Zhang (Tsinghua University)

Track Co-Chairs


Tsai-Hsin Chu
National Chiayi University

Ron Kwok
City University of Hong Kong

Julian Marx
University of Melbourne


Track Description

The rapid development of emerging technologies—specifically Generative AI (GenAI), extended reality (XR), and pervasive data analytics—is fundamentally transforming the field of Information Systems (IS) education. To effectively address the complexities of a socio-technical future, IS education must go beyond traditional delivery models and recognize the increasingly intertwined roles of human and machine agencies.

This track invites scholarly contributions that explore the transformation of Information Systems (IS) pedagogy, curricula, and learning ecosystems. Our focus is on moving beyond digitizing content to emphasize theoretical foundations, design-science applications, and empirical evaluations of educational paradigms that prepare students for the future. We encourage research examining how IS education can develop the digital dexterity, ethical awareness, and technical skills essential to the next generation of digital leaders. Additionally, we welcome studies that investigate the co-evolution of human intelligence and artificial intelligence in both formal and informal learning environments.

We invite original research submissions, including conceptual papers, empirical studies (quantitative, qualitative, computationally intensive, or mixed-methods), and design-science research.

Potential topics include, but are not limited to:

  • Integrating Emerging Technologies into the IS Curriculum: Strategies for including emerging topics such as Quantum Computing, Blockchain, Cybersecurity, and Green IS in core curricula
  • Epistemological Shifts in the Age of Generative AI: Exploring how large language models (LLMs) and Generative AI redefine knowledge acquisition, cognitive offloading, and the necessity of the “human-in-the-loop” framework in information systems (IS) learning
  • Human-AI Collaborative Learning: Exploring the collaboration between students, educators, and AI agents in co-creation and problem-solving in the classroom
  • Adaptive and Personalized Learning Environments: Designing and evaluating AI-driven systems that customize educational content and pacing to meet individual student needs
  • Generative AI and Large Language Models (LLMs) in education: The impact of GenAI on teaching methods, automated assessment, and maintaining academic integrity
  • Designing Intelligent Learning Systems with a Socio-Technical Approach: Research focused on developing and evaluating AI-enhanced platforms, emphasizing human-AI collaboration and user-centered pedagogical design
  • Virtual reality simulations, gamification, and experiential learning in IS education: Designing and evaluating immersive and game-based IS learning experiences that help students rehearse decision-making in complex, data-rich environments
  • Learning analytics and educational data science: Utilize big data to identify patterns in student engagement, attrition, and success, while addressing challenges associated with data-driven instructional interventions
  • Ethics, Equity, and Responsible AI in Education: Addressing algorithmic bias, the digital divide, data privacy, and the socio-ethical responsibilities of technologists
  • Digital Dexterity and the Future of Work: Research on the development of “dual-competencies”—the integration of advanced technical skills with high-order critical thinking and digital resilience

Associate Editors

  • Hui-Fen Chen (National Taipei University of Education)
  • Yi-Cheng Ku (Fu Jen Catholic University)
  • Shanshan Zhang (Zhejiang University of Technology)
  • Gabriel Chun Hei Lai (Hong Kong Shue Yan University)
  • Weiwei Sun (Harbin Institute of Technology)
  • Lingling Yu (Shanghai University)
  • Haochen Song (Suzhou University of Science and Technology)
  • Xiaodong Li (Auhui Polytechnic University)

Track Co-Chairs


Joyce Yi-Hui Lee
National Chengchi University

Felix Ter Chian Tan
University of New South Wales

Van-Hau Trieu
Deakin University


Track Description

Sustainability is a moral and existential imperative of our time. In response to the various societal, economic, and environmental challenges, the United Nations’ 2030 Agenda has outlined this through the Sustainable Development Goals which prioritize addressing poverty, inequality, and economic growth while confronting urgent threats such as climate change, resource depletion, biodiversity loss, and the degradation of our oceans and forests. As we urgently seek solutions for these grand challenges, digital technologies stands out as central tools to address grand societal challenges. However, the same technological promises also create new concerns around environmental cost, infrastructural fragility, and systemic risks.

This track invites research that examines how digital technologies both enable and constrain sustainability and resilience across organizational, societal, and ecological contexts. We welcome contributions exploring the design, implementation, and consequences of digital innovations, such as artificial intelligence, robotics, platforms, digital twins, and the Internet of Things, in fostering sustainable practices and resilient systems. We are particularly interested in processual and sociotechnical perspectives that examine how sustainability and resilience emerge through the interplay of technologies, institutions, and communities.

We encourage theoretically grounded work that advances core information systems debates, including the role of digital technologies in shaping organizational resilience, tensions between efficiency and sustainability, and the temporal dynamics of long-term system transformation. Interdisciplinary contributions drawing on organizational practices, development studies, and environmental research are also highly valued.

Potential topics include, but are not limited to:

  • Sustainable digital ecosystems
  • Digital sustainability for dealing with environmental and societal challenges
  • Circular economy enabled by information systems
  • Governance of digital platforms for resilience
  • Digital inclusion and community resilience
  • Unintended consequences of digital technologies (e.g., discrimination, digital divide, technostress, surveillance, unethical uses of digital technologies) that result from implementing digital technologies for sustainability and/or societal impact
  • Smart cities and sustainable urban infrastructure
  • Digital technology and rural development
  • Tensions and trade-offs in sustainable digitalization

Associate Editors

  • Sebastian Böll (University of Sydney)
  • Kam-Fung (Henry) Cheung (UNSW Business School)
  • Frank Chuang (National Chengchi University)
  • Chien-Yi Hsiang (National Chengchi University)
  • Ping-Jen Kao (Sussex University)
  • Yohannes Kurniawan (Binus University)
  • Yanpei Li (Stockholm School of Economics)
  • Angela Lu (Monash University)
  • Andy Nguyen (University of Oulu)
  • Minh Nguyen (Florida Atlantic University and University of Hawaii)
  • Sungjun (Steven) Park (Queen Mary University of London)
  • Harminder Singh (Auckland University of Technology)
  • Stephen Smith (Macquarie University)
  • Ayushi Tandon (Trinity Business School)
  • Thi Tran (Binghamton University)
  • Henry Hung-Jui Wu (Tilburg School of Economics and Management)
  • Jack Yang (Deakin University)

Track Co-Chairs


Hsin-Min Lu
National Taiwan University

Mengxiang Li
Hong Kong Baptist University

Nila Zhang
Fudan University


Track Description

The exponential growth of digital data and the rapid advancement of artificial intelligence (AI) are fundamentally reshaping how organizations operate, innovate, and create value across industries, sectors, and geographies. This track invites scholarly contributions that develop, apply, or critically examine state-of-the-art data science methodologies, analytical frameworks, and AI-integrated techniques to address pressing business, organizational, and societal challenges. We welcome research that interrogates not only what analytics can achieve, but also who benefits, who may be excluded or harmed, and how data-driven systems can be designed, governed, and deployed to serve diverse communities equitably and sustainably.

Submissions may investigate the development, deployment, application, and broader implications of business analytics and data science across organizations, markets, and society. We particularly encourage theoretically grounded and methodologically rigorous studies that examine how data-driven technologies support strategic decision-making, operational excellence, innovation, digital transformation, and emerging forms of value creation. Given the deepening convergence of analytics with AI, we especially encourage research on AI-augmented analytics, including machine learning, large language models, generative AI, and human-AI collaboration.

Recognizing the global and pluralistic nature of the Pacific Asia information systems community, we encourage submissions that draw on diverse organizational contexts (including small and medium-sized enterprises, public sector institutions, non-profit organizations, and underrepresented industries), diverse cultural and regional settings, and a wide range of epistemological and methodological traditions, including quantitative, qualitative, design science, computational, and mixed-methods approaches. We also welcome interdisciplinary perspectives that connect analytics and AI with management, behavioral science, ethics, law, and the humanities.

Potential topics include, but are not limited to:

  • AI-enabled analytics and intelligent business systems
  • Generative AI applications in organizations and business processes
  • Data-driven decision making and strategy, and organizational learning
  • Data governance, privacy, and algorithmic transparency
  • Responsible, ethical, and trustworthy AI and analytics
  • Fairness, accountability, bias mitigation, and inclusive design in data-driven systems
  • Consumer behaviour analytics
  • Data-driven business model innovation and entrepreneurship
  • Unstructured and multimodal data analytics (e.g., text, image, audio, video, sensor data)
  • Data products, data monetization, and digital business models
  • Big data platforms, cloud analytics, and analytics infrastructures
  • AI and analytics for digital transformation
  • Analytics and AI for sustainability, social good, and the United Nations Sustainable Development Goals
  • Analytics for healthcare, education, public services, and other societally critical domains
  • Critical, ethical, and socio-technical perspectives on data, algorithms, and AI
  • Open data, open science, and reproducibility in analytics and data science research

Associate Editors

  • Hui Yuan (Shanghai International Studies University)
  • Yueyue Zhang (University of Nottingham Ningbo China)
  • Yimiao Zhang (Singapore University of Social Sciences)
  • Hongfei Li (Chinese University of Hong Kong)
  • Yinan Yu (University of Oklahoma)
  • Po-An Chen (National Yang Ming Chiao Tung University)
  • Jian-Ren Hou (National Cheng Kung University)
  • Keng-Pei Lin (National Sun Yat-Sen University)
  • Chih-Chieh Hung (National Chung Hsing University)
  • Yuan-Long Peng (National Chiayi University)
  • Chin-Yu Hsieh (Fu Jen Catholic University)
  • Zhao Du (Beijing Sport University)
  • Rui Gu (University of International Business and Economics)
  • Yuhao Li (Shanghai International Studies University)
  • Nan Shi (Shanghai University of International Business and Economics)

Track Co-Chairs


Younghoon Chang
University of Nottingham Ningbo China

Wei He
Texas Tech University

Stan Karanasios
University of Queensland


Track Description

Social media and digital collaboration have become foundational infrastructures shaping how individuals, organizations, and societies interact, create value, and coordinate activities in the digital era. These technologies have evolved beyond communication platforms into complex socio-technical ecosystems that enable knowledge co-creation, collective intelligence, and digitally mediated collaboration.

Recent technological advancements in artificial intelligence, generative AI, and immersive technologies such as augmented reality, virtual reality, and mixed reality are rapidly transforming the landscape of social media and digital collaboration. The emergence of metaverse platforms and immersive digital environments is redefining how users interact, collaborate, and experience digital presence. These developments extend collaboration beyond traditional screen-based interfaces toward embodied, spatial, and experiential forms of interaction.

At the same time, AI-powered agents, algorithmic curation, and multimodal content generation are reshaping digital engagement and co-creation processes. Emerging phenomena such as virtual communities, influencer economies, digital labor, and hybrid work systems continue to blur the boundaries between physical and digital collaboration spaces.

Despite these opportunities, significant challenges remain. Issues such as misinformation, algorithmic bias, digital inequality, privacy concerns, and the governance of platform ecosystems are becoming increasingly critical. Furthermore, the integration of AI and immersive technologies raises new questions about trust, identity, embodiment, and ethical design in socio-technical systems.

Against this backdrop, this track aims to advance cutting-edge research on social media and digital collaboration by exploring emerging technologies, novel theoretical perspectives, and innovative methodologies. We particularly encourage interdisciplinary research that bridges information systems, marketing, organizational behavior, human–computer interaction, and data science.

We welcome empirical, analytical, design science, and conceptual studies that provide novel insights into the evolving dynamics of social media and digital collaboration across both traditional and immersive digital environments.

Potential topics include, but are not limited to:

  • AI agents and agentic collaboration in social media and digital platforms
  • Human-AI taming, coordination, and control in digital environments
  • Role reconfiguration between human and AI in social media and collaboration systems
  • Generative AI and content co-creation in digital platforms
  • Social media analytics and computational social science
  • Digital collaboration in hybrid and remote work environments
  • Platform ecosystems and digital community governance
  • Trust, transparency, and accountability in algorithmic systems
  • Social influence, digital identity, and online behavior
  • Digital labor, gig economy, and crowd-based collaboration
  • Social media and digital innovation (e.g., open innovation, co-creation)
  • Privacy, surveillance, and data governance in social platforms
  • Metaverse platforms and immersive social interaction
  • AR/VR/MR-based collaboration and user experience design
  • Embodiment, presence, and identity in immersive environments
  • Virtual communities and collaboration in extended reality (XR)
  • Knowledge sharing, collective intelligence, and digital coordination

Associate Editors

  • Agam Gupta (Indian Institute of Technology)
  • Jakia Sultana (University of Dhaka)
  • Liqiang Huang (Zhejiang University)
  • Ting Xu (Southern University of Science and Technology)
  • Zihong Huang (Texas Tech University)
  • Juan Qin (University of Science and Technology of China)
  • Dongming Xu (University of Queensland)
  • Xin Wei (Beijing University of Technology)
  • Xiaobo Bo Ke (The Education University of Hong Kong)
  • Sodam Kim (Sunway University)
  • Minjeong Ham (Nagoya University of Commerce and Business)
  • Hwansoo Lee (Dankook University)
  • Kyung Young Lee (Dalhousie University)
  • Shan Wang (University of Saskatchewan)
  • Christian Libaque-Saenz (Universidad Del Pacifico)
  • Sooil Shin (Kennesaw State University)
  • Haejung Yun (Ewha University)
  • Sunghan Ryu (University of Nottingham Ningbo China)
  • Juyeon Ham (Chosun University)
  • One-Ki Daniel Lee (Virginia Commonwealth University)

Track Co-Chairs


Tailai Wu
Huazhong University of Science and Technology

Christoph Breidbach
University of Queensland

Kristijan Mirkovski
Deakin University

Xinwei Wang
University of Auckland


Track Description

The deep integration of digital and intelligent technologies into social, professional, and organizational contexts has elevated the dynamic interplay between user behavior, engagement, and their multifaceted consequences as a core research agenda in information systems. Advanced technologies—including general artificial intelligence (AI), generative AI, immersive systems, and personalized digital services—serve as transformative catalysts, powering personalized engagement, reshaping human‑technology interaction patterns, enabling data‑driven behavioral interventions, and introducing novel ethical and behavioral challenges.

At the same time, this interplay is reciprocal: while intelligent technologies shape user cognition, motivation, decision making, and social interactions, user behavior, experience, and feedback also inform the design, adaptation, and iterative improvement of information systems and IT artifacts. As understanding user behavior and cultivating meaningful engagement remain critical to the success of information systems and digital services, this track investigates how system design features—such as user-centered design, adaptive interfaces, personalization, gamification, digital nudges, and incentive mechanisms—foster, sustain, regulate, or undermine engagement across varied contexts.

This track invites high quality theoretical, empirical, design science, and mixed methods research that reveals the drivers, mechanisms, and impacts of user behavior and engagement. We welcome work that rigorously examines both positive outcomes and dark side consequences such as digital addiction, over reliance, privacy risks, and social polarization. Research across individual, group, team, organizational, societal, or multi-level analyses is encouraged, particularly studies exploring under-investigated contexts, evolving user experiences, and cutting-edge technological advances in areas such as social and mobile platforms, knowledge-sharing communities, health informatics, online education, live streaming, gaming, and career platforms.

Potential topics include, but are not limited to:

  • Impacts of AI and generative AI on user behavior and engagement dynamics
  • Calibrated trust and appropriate reliance on AI-powered information systems
  • Drivers, measurement, and governance of healthy and sustainable digital engagement
  • Determinants and mitigation of dark-side outcomes: addiction, polarization, over-reliance, skill erosion
  • Immersive technologies and metaverse effects on user interaction and engagement
  • Individual well-being, organizational performance, and societal impacts of digital engagement
  • Cross-cultural and vulnerable-group (seniors, youth) IT usage and behavioral consequences
  • AI-driven personalization, content moderation, and algorithmic regulation of user behavior
  • Ethical and privacy implications of intelligent systems on user behavior and engagement
  • Cyberspace governance and policy for responsible and inclusive user engagement
  • Post-adoptive usage, persistence, and disengagement behaviors and consequences
  • Incentive mechanisms and digital nudges for positive user engagement
  • The role of user feedback in the design and iterative improvement of IT artifacts
  • User-centred design, adaptive interfaces, and the creation of engaging information systems
  • Human-technology interaction in digital platforms, services, and online communities
  • User behaviour and engagement in contexts such as health informatics, online education, live streaming, gaming, mobile, and social platforms

Associate Editors

  • Jiaxin Xue (Wuhan University of Science and Technology)
  • Jifeng Ma (Wuhan Textile University)
  • Manli Wu (Huazhong University of Science and Technology)
  • Yang Wang (Shenzhen University)
  • Guorui Fan (Huazhong University of Science and Technology)
  • Da Ma (University of Electronic Science and Technology of China)
  • Jie Tang (Erasmus University Rotterdam)
  • Ping Wang (Central China Normal University)
  • Yvonne Hong (Victoria University of Wellington)
  • Eleni Lioliou (Queen Mary University of London)
  • Shahrzad Gohar (The University of Queensland)
  • Yao Zhao (The University of Queensland)
  • Daniel Heinz (Karlsruhe Institute of Technology)
  • Xinyue Zhang (Deakin University)
  • Hao Liu (Deakin University)
  • Bingqing Xiong (Deakin University)
  • Chunxiao Yin (Southwest University)
  • Jun Zhang (Monash University)
  • Chongyang Chen (Zhejiang University of Finance and Economics)

Track Co-Chairs

Chih-Hung Peng
National Taiwan University

Yi-Jen (Ian) Ho
Tulane University

Martha Indulska
University of Queensland


Track Description

Generative Artificial Intelligence (Gen AI) is increasingly shaping both how Information Systems (IS) research is conducted and what it studies. Large language models, multimodal foundation models, and agentic AI systems are beginning to influence how researchers formulate questions, gather and analyse data, build theory, and present their work. At the same time, the widespread diffusion of Gen AI has created a compelling empirical and conceptual setting for IS research, prompting renewed attention to issues such as human–AI collaboration, trust, governance, productivity, creativity, and the changing nature of knowledge work.

This track seeks rigorous and insightful research that engages with these developments in a substantive way. We welcome work that advances the IS discipline while critically examining the possibilities and limitations introduced by Gen AI. Submissions may (a) use Gen AI as a research tool or method in IS inquiry, and/or (b) study Gen AI as a phenomenon in its own right. We encourage a broad range of contributions, including conceptual, empirical (quantitative and qualitative), design science, and methodological studies.

Potential topics include, but are not limited to:

  • GenAI as a research method for reviews, analysis, prompting, and simulation
  • Rigour, ethics and disclosure in GenAI–enabled research
  • Human–AI collaboration in knowledge-intensive work
  • Trust, over/reliance, and responses to hallucinations
  • Explainability, transparency, bias, and fairness in generative models
  • Adoption, use, and governance of GenAI in organisations
  • Business value, productivity, and performance impacts of GenAI
  • Agentic and multi-agent systems
  • Implications for teaching, learning, skills, and the future of work
  • Regulation, policy, IP, privacy, security, and misuse risks

Track Co-Chairs

Sandeep Mysore Seshadrinath
University of New South Wales

Cheng Suang Heng
National University of Singapore

Carmen Leong
University of New South Wales


Track Description

Rooted in the design science paradigm, this track emphasizes the purposeful creation of constructs, models, methods, and systems that extend the capabilities of individuals and organizations. Reflecting the diversity of design science traditions, spanning computational, optimisation, representation, and economics perspectives, the track recognises the field’s broad and evolving contributions to both theory and practice (Rai, 2017). Beyond explanatory insight, it calls for actionable solutions that are theoretically grounded and practically relevant, demonstrating how design knowledge is generated, justified, and transferable across contexts.

A defining emphasis of this track is impact, understood as extending across academic, business and societal domains, with the most ambitious contributions designed at the intersection of these areas. Submissions should articulate the intended impact area(s), specify impact objectives at an appropriate level (individual, organizational, market or societal), and identify partners with whom the research is co-produced. Furthermore, submissions should clearly articulate problem relevance, stakeholder context, and measurable outcomes, showing how artefacts deliver tangible benefits such as efficiency gains, behavioural change, enhanced user experience, or policy value (Benbya et al., forthcoming). We expect authors to treat impact not as a retrospective claim but as a designed property of the research. In an era shaped by rapid advances in technologies, including generative AI, large language models, blockchain, and cyber-physical systems, design science research must also address emerging concerns such as interpretability, fairness, security, and privacy. Recent discourse highlights the need for stronger integration between artefact design and theoretical contribution, particularly in AI-related contexts (Abbasi et al., 2024).

Strong contributions will therefore combine iterative design cycles with rigorous evaluation strategies, ensuring robustness, generalisability, and contextual validity (Larsen et al., 2025). The track further encourages methodological innovation and reflection, including novel evaluation techniques, participatory design practices, and mechanisms for scaling artefacts across organisational and ecosystem settings. Interdisciplinary perspectives are particularly valued where they deepen both the design process and its broader impact.

Design science research necessitates close engagement with practice. Submissions involving co-creation, industry collaboration, or longitudinal deployment are especially encouraged, as they enhance both rigor and relevance. Overall, Track 17 seeks to showcase how thoughtfully designed, rigorously evaluated artefacts can drive meaningful change and shape the future of information systems research.

References:
(i) Larsen, et al. 2025. “Validity in Design Science,” MIS Quarterly, (Vol. 49, No. 4), pp.1267–1294.
(ii) Abbasi et al. 2024. “Editorial: Pathways for Design Research on Artificial Intelligence,” Information Systems Research (Vol. 35, No. 2) pp.441-459.
(iii) Arun Rai. 2017. “Editorial: Diversity of Design Science Research,” MIS Quarterly, (41: 1) pp.iii-xviii.
(iv) Benbya, Hind and Möhlmann, Mareike and vom Brocke, Jan, Expanding The Scope of IS Research Impact: A Framework and Guidelines (April 01, 2025). Journal of the Association of Information Systems. Forthcoming, Available at SSRN: https://ssrn.com/abstract=5377521″

Potential topics include, but are not limited to:

  • Design science and innovation
  • Design science in the era of artificial intelligence
  • Emerging technologies and tools in design science research
  • Responsible and ethical design science
  • Measuring and evaluating impact of design science research
  • Other emerging methods for design science research
  • Action research and action design research for organisational and societal change
  • Participatory design and co-design with communities and stakeholders
  • Designing for social good, sustainability, and digital inclusion
  • Behavioural design and interventions for policy and public sector innovation
  • Scaling and institutionalising design artefacts across organisations and ecosystems
  • Translating design knowledge for practice
  • Planning, designing and evaluating impact in design science

Associate Editors

  • Ayushi Agarwal (Indian Institute of Management, Rohtak)
  • Jing Elaine Chen (Beihang University)
  • Xi Chen (Zhejiang University)
  • Michael Cahalane (UNSW Sydney)
  • Yi Ding (Warwick Business School)
  • Mingyue Guo (UNSW Sydney)
  • Sam Seongmin Jeon (Gachon University)
  • Chong Ma (University of International Business and Economics)
  • Mairead O’Connor (UNSW Sydney)
  • Yi Shen (Soochow University)
  • Belinda Wang (University of Sydney)
  • Maggie Yazhu Wang (UNSW Sydney)
  • Xiangyu Wang (UNSW Sydney)
  • Yichao Xu (UNSW Sydney)
  • Jack Yang (Deakin University)
  • Chenxu Zheng (University of Sydney)

TBC