TRACK DESCRIPTIONS

Track co-chairs

• Muller Cheung Deakin University
• Fei Liu Hong Kong Polytechnic University
• Tian Lu Arizona State University

Track description

Artificial Intelligence (AI) has been significantly reshaping the work and talent development landscape. Among recent breakthroughs, generative AI stands out for its transformative potential. It enabled novel forms of content creation, automation, and collaboration that redefine how work is done and talent is developed. Advances in AI-driven automation, augmentation, and intelligent systems are redefining job roles and relevant skill requirements, prompting businesses and educational institutions to reassess how talent is cultivated, managed, and retained. AI integration notably alters managerial decision-making, leadership models, and human resource strategies, impacting areas such as recruitment, personalized training, career development, and performance management. Organizations are adapting to the increasing dynamism in human-AI collaboration within teams, as AI tools become integral teammates, changing the nature of team interactions and performance.

This track explores the AI-driven future of work and talent development across workplace and educational settings, focusing on how organizations and individuals can prepare for AI-driven changes. For organizations, AI applications offer opportunities for personalized employee experiences, predictive workforce analytics, and improved learning outcomes through adaptive training systems. For individuals, the track considers how workers and students are adapting to AI-enhanced environments, acquiring new skillsets, and navigating evolving career paths in collaboration with AI tools and systems. Universities and educational providers are innovating to deliver new curricula and pedagogical methods, equipping learners with competencies to thrive alongside intelligent technologies.

We welcome rigorous research (conceptual, empirical, or design-oriented) exploring the intersection of AI, work, and talent development. We particularly encourage submissions that provide insights into the integration of AI in organizational practices and educational strategies.

Potential Topics include (but are not limited to):

1. AI-enabled talent development in organizational settings
2. Adaptive learning technologies in universities and workplaces
3. AI-driven leadership development and management practices
4. AI-enabled talent development in organizational settings
5. AI in employee recruitment, onboarding, and retention practices
6. AI-supported career planning and employee development
7. Applications of generative AI in training, knowledge sharing, and content creation for workplace learning
8. Continuous education and workforce reskilling strategies
9. Curriculum design and pedagogical innovation driven by AI
10. Development of digital and AI literacy in educational institutions
11. Emerging professional identities and careers in AI-driven contexts
12. Employee engagement and retention in AI-enhanced workplaces
13. Ethical considerations in AI-driven talent and educational strategies
14. Human-AI collaboration in workplace learning environments
15. Implications of AI for educators and trainers
16. Intelligent systems for personalized learning and employee training
17. Managing diversity and inclusion through AI-enabled systems
18. Opportunities and challenges of integrating generative AI into educational ecosystems
19. Organizational capabilities required for effective AI integration
20. Personalized student experiences through AI-driven platforms
21. Role of AI in redefining skill requirements and professional competencies
22. Strategic alignment of AI investments with talent development goals
23. Workforce analytics and predictive models for talent management

Associate editors

1. Azizul, Azizan (Universiti Teknologi Malaysia)
2. Dennis, Benner (University of Kassel)
3. Reihane, Boghrati (Arizona State University)
4. Yue, Cheng (Nanchang University)
5. Yi-Te, Chiu (National Tsing Hua University)
6. Wilson, Li (Deakin University)
7. Jialu, Liu (Shanghai Jiao Tong University)
8. Yuan, Sun (Zhejiang Gongshang University)
9. Derui, Wang (University of Science and Technology of China
10. Gongtai, Wang (Dalian University of Technology)
11. Jiding, Zhang (Arizona State University)
12. Nan (Andy), Zhang (Harbin Institute of Technology)
13. Yao, Zhao (University of Queensland)

Track co-chairs

• Ben Choi Nanyang Technological University
• Carmen Leong UNSW Sydney
• Ying Zhang University of Auckland

Track description

As AI reshapes industries and societies, it raises profound ethical and societal concerns. Although AI and machine learning offer potential breakthroughs in sectors such as healthcare, finance, education, and transportation, they also pose challenges related to privacy, fairness, and social equity. This track considers the ethical dilemmas and societal implications of AI, with a focus on responsible design and use. Key issues include the role of AI in exacerbating social inequalities, the risks associated with biased algorithms, and concerns regarding the accountability and transparency of AI-driven decisions. 

Potential Topics include (but are not limited to):

1. Algorithmic Bias and Fairness
2. Privacy and Surveillance
3. Transparency and Accountability in AI Decision-Making
4. AI and Job Displacement
5. Social Inequality and AI-Driven Exclusion
6. The Future of Human Autonomy and AI Decision-Making
7. AI and Social Good

Associate editors

1. Fenfen, Zhu (Nanyang Technological University)
2. Xinxue, Zhou (Guangxi University)
3. Ruonan Sun (Monash University)
4. Randy Wong (University of Auckland)
5. Yi, Wu (Tianjin University)
6. Cheng, Luo (Tianjin University)
7. Saima, Qutab (University of Auckland)
8. Maggie Yazhu, Wang (UNSW Sydney)
9. Elaine Jing, Chen (Beihang University)
10. Noorminshah, Lahad (Universiti Teknologi Malaysia)
11. Yichao, Xu (UNSW Sydney)
12. Maylis, Saigot (The University of Queensland) 
13. Lusi, Yang (Georgia State University)
14. Yang, Liu (Xi’an Jiaotong University)

Track co-chairs

• Zixiu Guo UNSW Sydney
• Sherah Kurnia University of Melbourne
• Yulia Sullivan Baylor University

Track description

Digital technologies and artificial intelligence (AI) are transforming the Information Systems (IS) education landscape. AI tools, such as adaptive learning systems and generative AI, offer new opportunities to modernize teaching practices. They also enhance the alignment between educational offerings and the evolving demands of the digital economy, positioning IS education at the forefront of change. However, AI also presents significant challenges, including concerns around academic integrity, ethical implications, lack of transparency, and algorithmic bias. 

This track invites IS scholars to explore how digital learning and AI reshape the future of IS education across academic and professional contexts. We seek high-quality submissions that explore the development, implementation, and evaluation of digital and AI-enhanced educational practices, systems, and frameworks to improve teaching and learning. The track welcomes both innovative approaches and critical perspectives that examine not only the promises of AI-driven transformation but also its challenges and unintended consequences in education. 

 Potential Topics include (but are not limited to):

1. Adaptive learning systems, learning analytics and personalization in IS education
2. AI-driven intelligent tutoring systems, generative AI and automated instructional support in IS teaching, learning and assessment 
3. Virtual simulations, gamification, and experiential learning in IS education
4. Design and impact of digital learning environments for IS courses
5. Pedagogical frameworks for integrating AI into IS curricula
6. Strategies for curriculum modernization to include AI and digital competencies
7. Theories of IS and digital learning
8. Ethical implications of AI in IS education: data privacy, fairness and transparency.
9. Academic integrity and assessment design in the age of AI
10. Interdisciplinary approaches to digital learning in IS education
11. Governance and policy implications for AI in educational settings
12. Faculty development and organizational change for digital learning integration

Associate editors

1. Alemayehu Molla (RMIT) 
2. George Joukhadar (UNSW Sydney) 
3. Imairi Eitiveni (Universitas Indonesia) 
4. Marc Cheong (University of Melbourne) 
5. Michel Fathi (University of North Texas)
6. Pranit Anand (UNSW Sydney)
7. Ramayah Thurasamy (Universiti Sains Malaysia and Sunway University)
8. Sharon Tan (National University of Singapore)
9. Uchenna Peters (Augustana University)
10. Winn Chow (University of Melbourne)
11. Xunyi Wang (Baylor University)
12. Yuchao Jiang (UNSW Sydney)
13. Maciel M. Queiroz (FGV EAESP)
14. Tanya Linden (University of Melbourne)
15. Rachelle Bosua (University of Deakin)
16. Willy Gunadi (Bina Nusantara University)
17. Chedia Dhaoui (UNSW Sydney)
18. Satish Krishnan (Indian Institute of Management Kozhikode)
    

Track co-chairs

• Yijing Li Hong Kong Polytechnic University
• Dandan Qiao National University of Singapore
• Cheng Zhang Fudan University

Track description

Data analytics has become an indispensable tool for organizations seeking not only to gain competitive advantages but also drive social innovations. This track welcomes research work that employs and/or develops state-of-the-art data science and analytical methods, techniques, algorithms, and theories to solve real-world business and societal problems. Although we do not limit the scope of research domains, some recommended areas are social media analytics, digital business transformations, social innovation models, responsible e-commerce practices, the judicial system and democratic processes, social cohesion and inclusivity, privacy and security, as well as sustainability issues. This track is open to all varieties of research, including conceptual, theoretical, analytical, and empirical studies. The overarching goal is to enhance our understanding of how data science and analytics can play greater roles in enhancing business processes and economic frameworks, catalyzing business and social innovations, and addressing a wide range of contemporary societal issues.

Potential Topics include (but are not limited to): 

1. Capturing changing consumer behaviours and leveraging data analytics to innovate products and services.  
2. Responsible use of data analytics that balances business objectives and social welfare.
3. Developing and applying analytics capabilities to enhance firm competitiveness.  
4. Applying data analytics to tackle societal issues, such as promoting social cohesion and inclusion, and enabling new social innovation models  
5. Employing data-driven policy initiatives to address challenges related to sustainability issues.  
6. Navigating complex social networks while managing related privacy challenges.  
7. Examining societal dimensions of data, including data monetization, information businesses, and data products.  
8. Effective ways of processing, analysing, and presenting findings from unstructured data (e.g., text, images, audio, video)  

Associate editors

1. Mengyao Fu (Deakin University)
2. Yuxin Huang (Soochow University)
3. Yidi Liu (The Chinese University of Hong Kong)
4. Jakia Sultana (Deakin University)
5. Mingwei Sun (The University of Texas at Arlington)
6. Haoyu Yuan (Shanghai University of Finance and Economics)
7. Lin Yue (Macquarie University)
8. Hong Zhang (The University of Texas at Dallas)
9. Jinyang Zheng (University of Rochester)
10. Nila Zhang (Fudan University)
11. Qi Zhang (Southwest Jiaotong Universit)
12. Yueyue Zhang (University of Nottingham Ningbo)
13. Sunny Zheng (University of Nottingham Ningbo)

Track co-chairs

• Yang Liu University of Science and Technology of China
• Gen Li Fudan University
• Yi Ding Warwick Business School

Track description

This track explores Blockchain, Distributed Ledger Technology (DLT), and Fintech, focusing on their individual and combined transformative impact. Since Bitcoin’s emergence, Blockchain and DLT have expanded beyond cryptocurrency, driving innovation in finance, supply chain, healthcare, and more. Key areas include Decentralized Finance (DeFi), smart contracts, and token economies. Simultaneously, Fintech revolutionizes financial services using AI, big data, and cloud computing, enhancing customer interactions and accessibility. This track welcomes research on both Blockchain/DLT-based and non-Blockchain Fintech innovations. This track aims to foster discussions on topics ranging from foundational technology challenges to specific applications, the convergence of technologies, and the organizational and social impact. We invite papers using diverse methodologies (theoretical frameworks, case studies, design science) that offer novel insights into these technologies’ roles in reshaping industries, addressing challenges like scalability, interoperability, governance, and the societal implications of their adoption. 

Potential Topics include (but are not limited to):

1. Theoretical advancements in Blockchain and Fintech
2. Security, privacy, trust, and governance in Blockchain and Fintech applications
3. Algorithms, architectures, and protocols for decentralized or centralized financial solutions
4. Innovations in Fintech, including AI-driven financial services, digital banking, and algorithmic trading
5. Blockchain-based fintech like Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), Decentralized Autonomous Organizations (DAOs), and metaverse economies
6. Implications of token economies for organizational and business models
7. Applications of Blockchain and AI in financial market insights, risk management, and compliance
8. Sustainable finance and ESG compliance solutions in Fintech and Blockchain ecosystems
9. User engagement and interaction design within Fintech and Web3 applications
10. The social and economic impact of Blockchain and Fintech on emerging markets
11. Case studies of blockchain implementations across industries
12. Central bank digital currencies (CBDCs) and stablecoins

Associate editors

1. Ran Li (The Chinese University of Hong Kong)
2. Xiang He (Hong Kong Baptist University)
3. Tong Xu (Chinese University of Hong Kong, Shenzhen)
4. Chen Li (City University of Hong Kong)
5. Yuting Gao (ESCP Business School) 
6. Ying Lu (IE Business School)
7. Haris Krijestorac (HEC Paris) 
8. Aseem Pahuja (The University of Manchester)
9. Ashkan Eshghi (Warwick Business School)
10. Tao Lu (Southern University of Science and Technology)
11. Wanci Yuan (Hong Kong University of Science and Technology)
12. Luying Qiu (Hong Kong University of Science and Technology)
13. Jiayu Yao (Nanyang Technological University)

Track co-chairs

• Yue (Katherine) Feng Hong Kong Polytechnic University
• Tat Koon Koh Hong Kong University of Science and Technology
• Yicheng Zhang Huazhong University of Science and Technology

Track description

Sharing economy, digital platforms, and crowds are important phenomena in today’s technology-centric environment. They bear profound economic and societal implications, transforming how individuals, organizations, and institutions interact, innovate, and create value. This track invites cutting-edge research that examines the dynamics, challenges, and opportunities associated with these topics.

The sharing economy presents new business models that allow individuals to provide services to others using their underutilized assets or resources. Prototypical examples are Airbnb, Didi/Grab/Uber, and ToolShare. Another form of sharing economy involves company-owned resources, as seen in Bird, CitiBike, Lime, and Zipcar, where users access shared vehicles through pay-per-use or subscriptions

Powering this transformation are digital multi-sided platforms that seamlessly connect diverse actors across various domains—including hospitality, transportation, finance, education, entertainment, and beyond—often with little marginal cost. These platforms facilitate interactions and transactions and act as catalysts for socio-economic change, offering both promising opportunities and raising critical concerns about equity, sustainability, and governance.

Equally important is the rise of crowd-based modes that tap into distributed and heterogeneous individuals and organizations to drive innovation, content creation, problem-solving, and project funding. Enabled by robust digital infrastructures, these modes support new models of production and collaboration, from mobile app development to open knowledge communities and crowdfunding ecosystems.

In this track, we welcome papers that explore these themes through diverse theoretical lenses, methodological approaches, and levels of analysis (individual, organizational, platform, societal). We encourage submissions that bridge disciplinary boundaries and offer fresh insights into the future of the sharing economy, platform ecosystems, and crowd-based innovation.

Potential Topics include (but are not limited to):

1. Novel theories and perspectives for understanding the sharing economy, platforms, and crowd-based models 
2. Novel methodological approaches for researching the sharing economy, platforms, and crowd-based models 
3. Economic, societal, and regulatory impacts of sharing economy and digital platforms
4. Digital labor markets, gig economy, workforce transformation, and future of work
5. Individual behaviors and trust mechanisms in platform ecosystems
6. Crowdsourcing and crowdfunding 
7. Ethical considerations, responsible AI, and governance challenges in platform-based economies
8. Case studies on sharing economy and crowd-based platforms
9. Critical reviews and meta-analyses of the sharing economy and crowd-based platforms

Associate editors

1. Mark Boons (Vrije Universiteit Amsterdam) 
2. Qianzhou Du (University of Science and Technology of China) 
3. Yong Suk Kim (Sungkyunkwan University) 
4. Hongfei Li (The Chinese University of Hong Kong)
5. Shengjun Mao (The University of Hong Kong)  
6. Jiahui Mo (Clemson University) 
7. Marion Poetz (Copenhagen Business School)   
8. Bingjie Qian (Tongji University) 
9. Jing Tian (The Pennsylvania State University) 
10. Xiang (Shawn) Wan (Santa Clara University)   
11. Jun Yan (Huazhong University of Science and Technology) 
12. Hui Yang (Fuzhou University) 
13. Ling Zhao (Huazhong University of Science and Technology) 
14. Mi Zhou (University of British Columbia)  
15. Yingpeng Zhu (University of Macau)
16. Jack Tong (Nanyang Technological University)
17. Yongsuk Kim (Sungkyunkwan University)
    

Track co-chairs

• Ping Fan Ke Singapore Management University
• Alvin Chung Man Leung City University of Hong Kong
• Qiuhong Wang National University of Singapore

Track description

As digital technologies continue to evolve and become deeply embedded in all aspects of society, the challenges surrounding cybersecurity, data privacy, and ethical governance are becoming increasingly complex. Emerging threats such as cybercrime-as-a-service, invasive data practices, algorithmic bias, and AI-driven misinformation are becoming more prevalent and sophisticated. This track explores how individuals, organizations, and governments can respond to emerging security and privacy concerns while fostering digital resilience. We invite research that examines the security, privacy, and ethical risks associated with technologies, along with their implications, consequences, and potential solutions. This track welcomes a range of research methodologies, including theoretical, empirical, and design-oriented work, to advance understanding of secure and ethical digital ecosystems.

 Potential Topics include (but are not limited to):

1. Security, privacy, and ethics in Human-AI collaboration
2. Security/privacy risks in generative AI and autonomous systems
3. Algorithmic fairness and discrimination in decision support systems
4. Cybercrime and underground economy (e.g., ransomware-as-a-service)
5. Ethics and regulation in synthetic media and AI-generated content (e.g., Deepfake)
6. Digital forensics, cybersecurity regulations, compliance, and data sovereignty
7. Privacy-enhancing technologies and data protection
8. Privacy and ethical concern in AI-powered surveillance
9. User behavior, trust, and accountability in security/privacy
10. Building and designing security/privacy resilient information systems and architecture
11. Business, legal, social, and political consequences of security and privacy
12. Security of highly interdependent systems

Associate editors

1. Amanda Chu (Education University of Hong Kong)
2. Chaoyue Gao (University of Science and Technology of China)
3. Ruibin Geng (Northwestern Polytechnical University)
4. Farkhondeh Hanssandoust (University of Auckland)
5. Nan Hu (Singapore Management University)
6. Xuanqi Liu (Hunan University)
7. Anik Mukherjee (Indian Institute of Management Calcutta)
8. Leting Zhang (University of Delaware)
9. Jiexin Zheng (Peking University)
10. Jiali Zhou (American University)
11. Xiong Zhang (Beijing Jiao Tong University)

Track co-chairs

• Frank Chan ESSEC Business School
• John Dong Nanyang Technological University
• Silviana Tana Australian National University

Track description

Digital technologies, such as artificial intelligence, big data analytics, digital platforms, blockchain, and the Internet of Things, are reshaping innovation and business models of organizations and our lives in society. Digital innovation and transformation emerge within organizations and across broader societal contexts, driven by collaboration, emerging capabilities, and evolving socio-technical systems. These technologies present new opportunities and challenges for innovation and entrepreneurship in large or small enterprises, startups, and the public sector. Unlocking the full potential of digital technologies requires exploring strategies and opportunities to create new products, services, processes, organizational forms, and business models.

This track seeks original research that advances our understanding of digital transformation, innovation, and entrepreneurship. We invite contributions that explore these phenomena at the individual, organizational, and/or societal level. Conceptual and empirical studies are welcome, particularly those that refine existing theories or introduce new theoretical frameworks to understand the evolving digital landscape better.

Potential Topics include (but are not limited to):

1. Digital transformation strategies and framework
2. The impact of digital transformation on individuals, organizations, and societal levels
3. Digital transformation of small and medium-sized enterprises (SMEs)
4. Digital startups, ventures, and platforms
5. Digital innovation and business models with emerging digital technologies 
6. Digital transformation for sustainability and sustainable digital innovation
7. The dark side of digital transformation and innovation
8. Digital transformation in the public sector and government services
9. Digital leadership and organizational change
10. Digital skills and capabilities for the future of work
11. Challenges of data-driven innovation and digital business models

Associate editors

1. 1. Duong Dang (University of Vaasa)
   2. Wenyu (Derek) Du (Beihang University)
   3. Nicolai Fabian (University of Groningen)
   4. Chunmian Ge (South China University of Technology)
   5. Yiwei Gong (Wuhan University, China)
   6. Sarah Hönigsberg (ICN Business School)
   7. Haoyuan Liu (Nanyang Technological University) 
   8. Shiyuan (Eric) Liu (Wenzhou-Kean University)
   9. Yanran Liu (University of Cincinnati)
   10. Khoi Nguyen (Open University of the Netherlands)
   11. Yongjin Park (City University of Hong Kong)
   12. Luthfi Ramadani (Telkom University, Indonesia)
   13. Yingnan Shi (University of Western Australia)
   14. Dongyi Wang (Hainan University)
   15. Amali Wijekoon (University of Moratuwa)
   16. Yu Xia (University of Hong Kong)
   17. Lin Zhang (Northwestern Polytechnical University)
   18.  Durek Du (Beihang University)
   19. Lin Zhang (Northwestern Polytechnical University)

Track co-chairs

• Zike Cao Zhejiang University
• Hyeokkoo Eric Kwon Nanyang Technological University

Track description

The Internet of Things (IoT) plays a vital role in advancing smart cities, sustainability efforts, and digital government services. With recent breakthroughs in AI, including generative and reasoning AI, new opportunities have emerged for intelligent urban planning, improved citizen services, and more responsive governance. By integrating IoT with AI and machine learning, cities and governments can deliver more efficient, seamless, and citizen-centered solutions. This track explores how IoT technologies are transforming urban environments and public services. We invite research on the development, deployment, and impact of IoT-based systems that contribute to smart cities, sustainability, and digital governance. We also welcome studies addressing broader topics, such as digital inclusion, digital democracy, and public sector innovation, through a socio-technical lens. Submissions using all methodological approaches, including qualitative, quantitative, design science, and mixed methods, are encouraged.

 Potential Topics include (but are not limited to):

1. Artificial Intelligence and Digital Government
2. GenAI and Digital Government
3. Cybersecurity and Digital Government
4. Digital Democracy
5. Digital Government and Sustainability
6. Digital Inclusion
7. IoT and Smart Cities
8. IoT and Digital Government
9. Open Government and Open Government Data
10. Private-Public Partnership
11. Smart Resilient Cities

Associate editors

1. Sihan, Fang (Shanghai Jiao Tong University) 
2. Jaecheol, Park (Nanyang Technological University) 
3. Aditya, Karanam (University of Texas Dallas) 
4. Le, Wang (City University of Hong Kong) 
5. Junyeong, Lee (Chungbuk National University) 
6. Hongpeng Wang (Lanzhou University)
7. Xi Wang (Central University of Finance and Economics)
8. Wuyue Shangguan (Xiamen University)
9. Peng Wang (Northwestern Polytechnical University)
10. Jie Tang (Erasmus University Rotterdam)

Track co-chairs

• Mengxiang Li Hong Kong Baptist University
• Shaobo Wei Hefei University of Technology

Track description

The rapid proliferation of digital technologies—including artificial intelligence (AI), blockchain, cloud computing, analytics, generative AI, IoT, and platforms—has fundamentally reshaped organizational strategies, operations, and value creation. These technologies offer unprecedented innovation opportunities but pose complex challenges in governance, leadership, sourcing, and strategic alignment. Organizations must navigate questions of centralization vs. decentralization, ethical AI deployment, sustainable transformation, and evolving interorganizational dynamics while maintaining agility and competitiveness.

This track seeks to advance research on how organizations strategically design, govern, and lead IT initiatives to harness digital innovations. We invite interdisciplinary research that bridges theory and practice, exploring the interplay of IT strategy, leadership decisions, sourcing models, and governance mechanisms. Submissions may employ qualitative, quantitative, experimental, or design science methodologies. We particularly encourage studies that challenge traditional assumptions, propose novel frameworks, or offer actionable insights for practitioners navigating digital disruption.

 Potential Topics include (but are not limited to):

1. Digital business strategy and transformation leadership
2. Resilience in digital strategy
3. Digital strategizing and strategy implementation
4. Digital capability creation and management
5. A digital solution for business value (co-)creation and capture
6. Strategy to leverage advanced technologies, such as analytics, GenAI, blockchain, etc.
7. Strategic business/IT alignment and value co-creation
8. Digital architectures and IT governance models
9. Governance of enterprise, inter-organizational IS/IT applications and services, and platform
10. The impact of digital strategy and transformation on societal issues of CSR and sustainability
11. New business models enabled by digital innovations
12. The management and governance of digital sourcing

Associate editors

1. Xiayu, Chen (Hefei University of Technology) 
2. Meng, Chen (University of Science and Technology of China) 
3. Shenyang, Jiang (Hong Kong Polytechnic University)
4. Zach W. Y. Lee (City University of Hong Kong)
5. Hua, Liu (Anhui University)
6. Yi Wang (Southwestern University of Finance and Economics)
7. Xueyan, Yin (City University of Hong Kong)
8. Jicheng Zeng (Hong Kong Baptist University)
9. Jun, Zhang (Monash University) 
10. Liang Zhao (Hong Kong Baptist University)
11. Xueyan Yin (City University of Hong Kong)
12. Yongju Li (University of Science and Technology of China)
13. Jinmei Yin (Nanjing University of Aeronautics and Astronautics)

Track co-chairs

• Kevin Kuan UNSW Sydney
• Libo Liu University of Melbourne
• Yixin Zhang University of Gothenburg

Track description

The HCI and Robotic Interface Design track explores how humans interact with a variety of digital technologies and robotic systems in organizational, managerial, cultural, and social contexts. As intelligent systems, smart devices, and robotic technologies become integral to everyday life and work, effective interface design is critical to improving user experience, task performance, and user engagement. It is important to understand how different technologies, from traditional computing to AI-driven systems, can be designed to enhance collaboration, address usability challenges, and impact human behavior, organizational, and societal outcomes. 

We invite research that advances our understanding of human-computer and human-robot interactions and interfaces at various levels. We welcome theoretical and empirical studies that apply all methodological approaches (e.g., experiments, analytical work, qualitative studies, design science, econometric analysis, and so forth).

 Potential Topics include (but are not limited to):

1. Adaptive, context-aware interface design
2. Human-AI and human-robot collaboration/interaction
3. User-centered interface design and evaluation
4. Cognitive biases, emotional responses, and digital nudging
5. Trust and user satisfaction in interactive technologies
6. HCI design for mobile, web, wearable, and pervasive computing systems
7. Usability engineering, testing, and metrics
8. Interaction design for autonomous systems (e.g., self-driving cars)
9. Interface design for individual and/or collective usage
10. Interface design for the elderly, the young children, and/or other communities with special needs, promoting inclusivity and accessibility

Associate editors

1. Aleksandre Asatiani (University of Gothenburg)
2. Aihui Chen (Tianjin University)
3. Qian Chen (Northwestern Polytechnical University)
4. Jocelyn Cranefield (Victoria University of Wellington)
5. Jia Jia (Hong Kong University of Science and Technology)
6. Juho Lindman (University of Gothenburg) 
7. Robert Lowe (University of Gothenburg)
8. Vivien Ma (Deakin University)
9. Kristijan Mirkovski (Deakin University)
10. Jimmy Ren (Hong Kong Metropolitan University)
11. Heng Tang (University of Macau)
12. Nannan Xi (Tampere University)
13. Chunxiao Yin (Southwest University)
14. Ling Zhao (Huazhong University of Science and Technology)
15. Xiabing Zheng (University of Science and Technology of China)
16. Tingru Cui (University of Melbourne)

Track co-chairs

• Van-Hau Trieu Deakin University
• Xiaojun Zhang Hong Kong University of Science and Technology
• Zhongyun (Phil) Zhou Tongji University

Track description

Digital technologies—especially the rapidly evolving field of AI and agentic IS artifacts—have profoundly reshaped the landscape of IS development, implementation, and use. While these emerging technologies offer substantial benefits, ranging from enhanced user experience to transformative business solutions and increased productivity, organizations face significant hurdles in their design, development, and use, highlighting the urgent need for a generation equipped with the skills, insights, and mindset necessary to navigate these emerging IT artifacts, bridge knowledge gaps, and foster collaboration among stakeholders.  This underscores the importance of adopting a human-centric approach in the design, development, adoption, and use of IS. 

This track invites research that enhances our understanding of how a human-centric perspective can transform the future of IS, aiming to guide the design, development, adoption, and use of various types of IS in different contexts—at the individual, group, organizational, and societal levels, as well as at the intersections across these levels. We welcome papers that draw on diverse theories, perspectives, and methodologies to address real-world challenges. Submissions that introduce innovative theoretical insights or employ a variety of research approaches—including conceptual development, as well as qualitative and quantitative methods such as field studies, laboratory experiments, simulations, and modeling—are encouraged.

 Potential Topics include (but are not limited to):

1. Explore how individuals, organizations, and societies innovate to create value through the design, development, adoption, and use of digital technologies in diverse contexts.
2. Nurture skills necessary for effective development and growth of talent for IS design and development. 
3. Investigate interdependencies between individual, group, organizational, or societal IT/IS design and development decisions and use multilevel perspectives on adoption and use. 
4. Explore novel philosophical, theoretical, and methodological perspectives to tackle the issues of digital technology design, development, adoption, and use.
5. Tackle the social and ecological problems, such as systemic discrimination, social justice, societal crises, and climate change, through IS design, development, adoption, and use.
6. Investigate IS design, development, adoption, and use in environments with interconnected devices, services, and ecosystems, considering path dependencies, social interactions, and network externalities.
7. To understand context-related factors, examine the contextual factors influencing IT/IS design, development, adoption, and use at micro and macro levels.
8. Analyze how specific features or affordances of IT/IS influence design, development, adoption, and use.
9. Understand IT/IS design, development, adoption, and use in global or cross-cultural contexts.
10. Identify diffusion patterns in the use of emerging technologies.
11. Examine the ethical issues arising with the design, development, adoption, and use of IS with surveillance capabilities.

Associate editors

1. Zhenjiao, CHEN (University of International Business and Economics)
2. Xueyan, DONG (Northwestern Polytechnical University)
3. Chun Fong, LEI (The Hong Kong Polytechnic University)
4. Xixi, LI (University of Science and Technology Beijing)
5. Vivian MA (Deakin University)
6. Zhen, SHAO (Harbin Institute of Technology)
7. Zhenya (Robin), TANG (University of Northern Colorado)
8. Bingqing, XIONG (Deakin University)
9. Thi, TRAN (Binghamton University)
10. Aihua, YAN (Lingnan University)
11. Pengzhen, YIN (Hefei University of Technology)
12. Yixiu “Ashley”, YU (Central Michigan University)
13. Melody, ZOU (Warwick Business School)
14.  Yanpei Lin (Stockholm School of Economics)
15. Chintha Kaluarachchi (Deakin University)
16. Yin, Zhitao (The Hong Kong University of Science and Technology)
17. Neo Quang Bui (Rochester Institute of Technology)
18. Wangsheng Zhu (The Hong Kong University of Science and Technology)
    

Track co-chairs

• Ching-I Teng Chang Gung University
• Yu Tong Zhejiang University
• Haifeng Xu Shanghai Jiao Tong University

Track Description

The advancement of cutting-edge technologies such as artificial intelligence (AI), big data analytics, embodied intelligence, and wearable devices continue to push and reshape medical practice. Healthcare IS remains an area of robust growth, with the promises of streamlining healthcare workflow efficiency, enhancing the transparency of medical service and information, and elevating the quality of care. 

While healthcare IS could bring great benefits to healthcare, it also poses many challenges related to design, ethics, policy, and equity in healthcare. At the individual level, it is imperative to understand how digital health innovations affect individuals’ adherence to medical treatment plans and health-related behaviors. At the organizational level, hospitals and healthcare institutions are eager to know how to manage and assess AI-related healthcare innovations effectively. Such an understanding is vital for them to distribute healthcare resources mindfully. At the societal level, as the various healthcare ISs are embedded in the healthcare ecosystem, ensuring equality in health service access, assessing the changes in healthcare structure, and setting meaningful regulatory standards can be more challenging yet vital to societal well-being.   

This track aims to understand how human-technology-healthcare systems could co-evolve, ranging from AI-enabled decision support, technology-enhanced clinical workflows to patient-centric telehealth ecosystems, while addressing critical challenges in human-AI collaboration, system interoperability, telehealth platform management, and patient-centric care. We invite original, innovative research that explores the role of healthcare IS in addressing contemporary healthcare challenges, and welcome a diverse range of methodological approaches, including qualitative, quantitative, business analytics, computational, conceptual, and design science research, offering insights from multiple perspectives within the healthcare IS domain.

Potential topics include (but are not limited to):

1. Design and implementation of healthcare information technologies
2. Healthcare dis– and mis-information issues
3. Economics of healthcare IS/IT
4. Healthcare analytics and AI in healthcare
5. Impact of Generative AI on healthcare IS
6. New methods of care delivery and payment
7. Organizational, operational, clinical and financial implications of healthcare IS use
8. Safety, security and privacy of health information
9. Telehealth and mobile applications and their impacts in reshaping healthcare
10. Patient-centered healthcare IS/IT and patient empowerment
11. Wearable health devices and their health outcomes
12. Advancing IS theories in healthcare settings
13. Public and community health informatics

Associate Editors

1. Fang-Kai Chang (National Kaohsiung University of Science and Technology)
2. Chongyang Chen (Zhejiang Gongshang University)
3. Tzu-Ling Huang (National Central University)
4. Gujie Li (National University of Singapore)
5. Jiaoyang Li (Southwestern University of Finance and Economics)
6. Wenlong Liu (Nanjing University of Aeronautics and Astronautics)
7. Xixian Peng (Zhejiang University)
8. Soumya Ray (National Tsing Hua University)
9. Agrim Sachdeva (University of Arizona)
10. Garry Wei Han Tan (UCSI University)
11. Yidan Xiang (National University of Singapore)
12. Yujing Xu (Zhejiang University of Technology)
13. Yang Yang (Royal Holloway University of London)
14. Jiamin Yin (Renmin University)
15. Yuxiang Zhao (Nanjing University)
16. Thi Tuan Linh Pham (Thai Nguyen University)
17. Hsin-Yi Huang (Soochow University, Taiwan)
18. Xuan Liu (East China University of Science and Technology)
19. Shuang Geng (Shenzhen University)
20. Xiaofei Zhang (Harbin Institute Of Technology)
21. Yi Shen (Soochow University)
22. Yuanyuan Dang (South China University of Technology)

Track co-chairs

• Kevin K. W. Ho University of Tsukuba
• Wen-Lung Shiau Chang Gung University

Track description

This track invites scholars to engage with fundamental philosophical, theoretical, and methodological questions in Information Systems (IS) research. This year, we are, in particular, inviting papers that critically explore the transformations driven by Artificial Intelligence (AI) and the evolution of mixed and multiple methods. We hope this track will provide a forum for IS researchers to discuss how new ideas related to methods, theories, and philosophy can synthesize new ideas and pathways for new IS research paradigms.

In recent years, we have seen how AI technologies increasingly permeate the social, organizational, and individual spheres. Therefore, IS research faces profound epistemological, ethical, and methodological challenges that demand rigorous reflection and innovation. Therefore, apart from inviting papers that focus on studying the overall methodological, theoretical, and philosophical questions grounded in IS research, we specifically seek contributions that interrogate how AI reshapes the nature of “information,” “systems,” and “research,” that propose new frameworks for theorizing digital phenomena. We want to explore further how AI will transform and lead our society to the next golden era.

In addition to the call for papers focusing on AI, we embrace the current trend of mixed and multiple methods research and invite papers that critically assess how mixed and multiple methods can be integrated with IS research. As a result, this track encourages submissions that explore the opportunities and limitations of combining qualitative and quantitative approaches with AI-assisted data generation, analysis, and interpretation.

By embracing philosophical depth, methodological pluralism, and technological foresight, this track aspires to chart a future where IS research reflects on its foundations and innovates in response to the complexities of a digitally and algorithmically mediated world.

Potential Topics include (but are not limited to):

1. How can phenomenon-driven research in IS adapt to the challenges and opportunities of mixed and multiple methodologies?
2. What is the role of critical realism, design science, and engaged scholarship in a methodologically pluralistic IS research environment?
3. What frameworks can guide the evaluation of rigor and relevance in IS studies using mixed methods?
4. How does AI redefine the philosophical foundations of information systems research?
5. What new epistemological questions emerge from AI-driven knowledge generation?
6. How should IS scholars theorize digital phenomena mediated or produced by IS?
7. What are the methodological implications of using AI tools (e.g., machine learning, large language models) in IS research?
8. How can AI enhance or complicate theory development in information systems?
9. In what ways can mixed methods and multiple methods be integrated with IS research practices?
10. How do AI-assisted methods (e.g., automated content analysis and synthetic data generation) influence theory development and validation?
11. What are the philosophical implications of AI as a “research partner” rather than merely a tool?
12. How can IS researchers foster transparency, reflexivity, and ethical responsibility when using AI in mixed-method studies?
13. What are emerging methodological best practices for integrating AI-driven insights into traditional IS theoretical frameworks?

Associate editors

1. Chi-Yuen (Ben) Chou (National Chengchi University) 
2. Pei-Hsuan (Patience) Hsieh (National Chengchi University)
3. Yen-Yao, Wang (Auburn University)
4. Ling-Yen Pan (National Taipei University)
5. Allen Au (Edith Cowan University)
6. Wei-Chao Lin (Chang Gung University)

Track co-chairs

• Leona Chandra University of Adger
• Yu-chen Yang National Sun Yat-sen University

Track description

This track invites authors (academics and practitioners) to submit credible research that provides rich stories, unique insights, and useful conceptual frameworks for information systems practice. The target audience includes practitioners and researchers, with a primary focus on immediately relevant and useful research for practice.

Perspective authors can base their papers on single or multiple cases, field interviews, field experiments, action research, design research, and/or descriptive surveys coupled with in-depth cases. We particularly welcome research that employs design science research to develop and evaluate innovative solutions and action research and other intervention approaches that engage directly with organizations to address real-world challenges.

Papers submitted to this track should focus on pressing problems or opportunities directly relevant to IS practitioners. Authors should demonstrate the research’s potential to make a positive impact on practice, discussing how digital leaders can apply results to solve problems or seize opportunities. To do so, submissions should flesh out best practices and/or actionable, prescriptive recommendations and design knowledge. We do not expect submissions aimed at only contributing to theory, but rather those that directly tackle and solve practical challenges

Potential Topics include (but are not limited to):

1. Design, implementation, use of artificial intelligence (AI) in organizations
2. Business applications of blockchain
3. Digital innovation and transformation
4. Generating revenues with generative AI
5. Emerging technologies and business ethics
6. Cybersecurity initiatives in organizations
7. Digital capabilities in manufacturing
8. Digital service innovation (healthcare, for instance)
9. Strategic applications of digital twins
10. Robotic process automation

Associate editors

1. Martin, Brehmer (University of Augsburg)
2. Blerim Emruli (Lund University)
3. Ya-Han Hu (National Central University)
4. Chia-Yu Lai (National Pingtung University of Science and Technology)
5. Yen-Hsien Lee (National Chiayi University)
6. Frederik Metzger (Fraunhofer Institute)
7. Ziyi Wang (Huazhong University of Science and Technology)
8. Hanna Buyssens (ESCP Berlin)
9. Alexander Chung (University Laval)
10. Jonas Sjöström (University of Borås)
11. Gemza Ademaj (Lund University)
12. Sanaz Nabavian (Memorial University of Newfoundland)
13. Fang-Kai Chang (National Kaohsiung University of Science and Technology)
14. Yi-Chen Lee (National Sun Yat-sen University)
15. Botong Xue (Kennesaw State University)
16. Xiaoyu Xu (Xi’an Jiaotong University)

Track co-chairs

• Boying Li University of Nottingham Ningbo China
• Chih-Hung Peng National Taiwan University
• Diah Priharsari Deakin University

Track description

Information Technology (IT) continues to drive transformative changes across industries, organizations, and societies worldwide. As technological innovation accelerates, the future of IT holds boundless opportunities and complex challenges that demand critical inquiry and fresh perspectives. This track invites research that examines emerging trends, foundational issues, and visionary developments shaping the future of IT.

Potential Topics include (but are not limited to):

1. Contemporary challenges and/or opportunities associated with developmental trends in digital technologies
2. Brain-computer interaction
3. Impact of digitalization on the environment
4. Impact of digitalization on society
5. Digital twin
6. Edge computing
7. Green computing
8. Holographic 3D printing
9. Immersive media (e.g., augmented reality, virtual reality, mixed reality, extended reality)
10. Jitterbug, assistive technology, and gerontechnology
11. Kill chain management
12. Low code technology and development platforms
13. Metaverse and non-fungible tokens (NFTs)
14. Neuro-IS
15. Open-source intelligence
16. Pervasive computing
17. Quantum computing applications
18. Robotic process automation with human-in-the-loop
19. Smart devices, homes, offices, cities, and nations
20. Total or multi-experience
21. Universal authentication
22. Voice and speech recognition for conversational chatbots
23. Wearable and haptic technology
24. Operational challenges for analytics and machine learning

Associate editors

1. Shiqi Bai (Univeristy of Nottingham Ningbo China)
2. Nanyi Bi (National Taiwan University)
3. Fang Cao (Hunan University)
4. Zhengzhi Guan (Beijing Normal-Hong Kong Baptist University)
5. Yanping Guo (Xi’an University of Architecture and Technology)
6. Nizar Hoblos (Macquarie University) 
7. Jian-Ren Hou (National Cheng Kung University)
8. Fangfang Hou (Xi’an Jiaotong Liverpool University)
9. Dedi Inan (University of Papua)
10. Abhishek Kumar Jha (Indian Institute of Management Indore) 
11. Mou Jian (Pusan National University)
12. Didin Kristinawati (Telkom University)
13. Joyce Lee (National Chengchi University)
14. Yi-Ling Lin (National Chengchi University)
15. Teng Ma (Xi’an Jiaotong Liverpool University)
16. Fatwa Ramdhani (University of Tsukuba) 
17. Vipin Saini (National Chung Cheng University)
18. Hsiao-Ting Tseng (National Central University)
19. Tailai Wu (Huazhong University of Science and Technology)
20. Jia Xu (Deakin University) 
21. Mengli Yu (Nankai University)