Track Descriptions
Track 1. Intelligent Systems & Sustainable Supply Chain Management
Track chairs:
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Dr. Guoqing Zhao, School of Management, Swansea University, UK
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Dr. Samuel Fosso Wamba, TBS Education, France
Scope: A supply chain is a complex logistics system consisting of different stakeholders to convert raw materials into finished products and distribute them to end consumers. However, it is difficult to make them sustainable owing to their complexity, environmental concerns, social responsibility, and economic viability. Integrating intelligent systems into supply chains can significantly enhance efficiency and reduce environmental impact, and thereby can be considered as a feasible way to improve overall supply chain sustainability. Intelligent systems such as machine learning and predictive analytics-enabled artificial intelligence (AI) can be used to enhance decision-making processes, internet of things (IoT) can be used to connect physical devices across different stakeholders to achieve real-time data collection and analysis, blockchain provides a decentralized and transparent ledger for tracking transactions and ensuring data integrity, and robotics and automation can be used to reduce human error and increase efficiency. The application of intelligent systems in sustainable supply chain management promises a range of benefits, such as reduced environmental impact, cost savings, improved compliance and reporting, and enhanced customer satisfaction. Thus, this session focuses on papers addressing research and applications that provide insights into intelligent systems & sustainable supply chain management.
Topics of interest include, but are not limited to:
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Resources to be used to apply different intelligent systems to supply chains;
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Enablers/barriers enable/impede the application of intelligent systems to achieve sustainable supply chain management;
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Supply chain efficiency improvement with autonomous robotics;
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Improved decision-making through the application of AI;
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Supply chain transparency enhancement by applying blockchain and IoT;
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Intelligent systems and social, environment and economic dimensions of a supply chain;
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Other potential papers that relevant to the topic.
Track 2. Digital technologies and the future of work, workforce, and workplace
Track chairs:
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Dr. Sian Roderick, School of Management, Swansea University, Wales.
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Dr. Tamilla Triantoro, Quinnipiac University, USA
Scope: The world of work is changing. Digital technologies, digital platforms, and algorithms, and are fundamentally transforming the way we organize and perform work. Some jobs will be lost, many others will be created, and almost all will change. At the same time, the meaning of work, employment and the boundaries between work and personal life is changing rapidly. Such change inevitably brings opportunities, but it also raises concern about the known and unknown consequences of digitised work, workforce and workplace.
We welcome submissions that take a broad perspective addressing digital technologies and the future of work, workforce, and workplace. Submissions are encouraged from all theoretical and methodological perspectives drawing from IS, management, and related disciplines.
Topics of Interest include, but are not limited to:
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New forms of digitally-enabled work arrangements
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AI, metaverse and the augmentation of work
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Digital technologies, information systems, and the future of work
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Leadership and management in a digitised work environment
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Robots, bots, algorithms and human workforce
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Digital platforms, the gig economy and temporary agency workers
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Flexibility, precarity and opportunity in digital workplaces
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Worker wellbeing, human factors, and the gig economy
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Digital competencies, people analytics, and HR.
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Equity, diversity, and inclusion in hybrid, virtual, mobile and remote working
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Technology for people resilience and organisational resilience
Track 3. IS Pedagogy in the Age of Disruption: Leveraging AI Technologies in Higher Education
Track chairs:
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Dr. Surajit Bag, Excelia Business School, France
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Dr. Desiree Cranfield, Swansea University, U.K.
Scope: The age of disruption, driven by rapid advancements in AI technologies like conversational AI, is transforming the landscape of Information Systems (IS) education. Both undergraduate and postgraduate programs face unique challenges in adapting to these changes while maintaining academic rigor and interdisciplinary integration. AI technologies are enabling new ways for students, educators, and learning support teams (e.g., librarians and instructional designers) to communicate and interact, fostering a dynamic and innovative learning environment.
This track invites educators, researchers, and practitioners to explore the evolving landscape of IS pedagogy in this age of disruption. It seeks insights on leveraging AI technologies to enhance education while addressing the unique challenges they pose. Topics should include innovative teaching strategies, AI-driven pedagogies, and the integration of advanced tools like conversational AI. The track will also tackle pedagogical challenges such as preventing AI-enabled plagiarism, ensuring authentic student work, and rethinking assessments. Participants will discuss how to navigate these opportunities and challenges to create a dynamic, effective learning environment for both UG and PG levels. This track covers a diverse range of topics to encourage rich dialogue and actionable insights, including but not limited to:
Topics of Interest include, but are not limited to:
Innovative Teaching Strategies
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Innovative strategies for leveraging technology to enhance teaching and learning
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Innovative use of teaching techniques in the classroom
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Evaluating the effectiveness of flipped models in IS courses, emphasizing hands-on application during in-person sessions
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Integrating Generative AI tools into IS teaching materials and methodologies
Pedagogical Approaches and Student Engagement
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Approaches and pedagogies to drive student interest and success
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Techniques to foster teamwork and communication in virtual and hybrid learning environments
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Using real-world IS challenges as the foundation for active learning and skill development
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Blending IS with emerging disciplines like data science, behavioral economics, and digital transformation
Research and Case Studies
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Teaching and learning research projects
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Teaching cases for IS curriculum using real-world applications of blockchain, IoT, and cloud computing
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Partnering with organizations to create teaching cases that mirror current industry challenges
Workforce Readiness and Industry Alignment
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Aligning IS education with industry certifications (e.g., AWS, SAP, CISSP) to ensure workforce readiness
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Developing simulations that prepare students for dynamic and uncertain IS environments
Ethical and Security Considerations
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Incorporating topics like ethical AI, digital sovereignty, and quantum computing
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Addressing challenges in preventing AI-enabled plagiarism and ensuring authentic student work
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Addressing concerns about student data security and ethical use of analytics
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Exploring the implications of algorithmic bias in educational technology and assessments
Assessment and Evaluation
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Rethinking assessments to account for the use of Generative AI in problem-solving and ideation
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Managing the increasing complexity of digital teaching while maintaining a focus on student outcomes
Collaboration and Continuous Learning
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Digital collaboration beyond the classroom by building global networks of IS learners and professionals for continuous learning
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The role of instructors is shifting from knowledge providers to learning facilitators in a technology-driven environment
Educator Training and Support
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Training educators to use advanced tools, platforms, and techniques effectively
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Strategies for ensuring all students can participate fully in digitally enhanced education
Track 4. Measuring IS Research Contribution to Sustainable Development Goals
Track chairs:
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Dr. Peter Saba, De Vinci Higher Education, De Vinci Research Center
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Dr. Nicolas Travers, De Vinci Higher Education, De Vinci Research Center
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Prof. Noor Ul-Ain, EMLV, France.
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Prof. Mehwish Waheed, Institut Mines-Télécom Business School, France.
Scope:
The role of Information Systems (IS) in addressing the United Nations Sustainable Development Goals (SDGs) remains underexplored, particularly regarding the visibility and tangible contributions of IS research. This track invites innovative papers that propose concrete methods and frameworks to enhance the measurability, visibility, and impact of IS research contributions to achieving the SDGs. We aim to bridge gaps in current IS literature by encouraging studies that focus on interdisciplinary approaches, practical implementations, and evaluation metrics aligned with SDG targets.
By focusing on the intersection of IS research and sustainable development, this track seeks to catalyze efforts in measuring, scaling, and demonstrating the role of IS in advancing environmental, social, economic, and digital sustainability. We welcome submissions that adopt diverse methodologies and perspectives, contributing to a comprehensive understanding of IS's role in fostering sustainable innovation and addressing global challenges.
Topics of interest include, but are not limited to:
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Frameworks for measuring IS research contributions to specific SDG targets.
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Metrics and indicators for assessing the impact of IS-driven sustainability initiatives.
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Case studies showcasing the tangible benefits of IS in achieving SDGs.
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Digital platforms and systems for monitoring SDG progress.
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The role of emerging technologies (AI, IoT, blockchain) in driving SDG-oriented IS research.
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Strategies for integrating IS research into global SDG policy frameworks.
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Addressing ethical, social, and environmental dimensions of IS in SDGs.
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Interdisciplinary approaches combining IS with fields like environmental science, economics, and social policy to achieve SDGs.
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Methods for enhancing stakeholder engagement in IS-related SDG projects.
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Leveraging IS research to support equitable and inclusive sustainability practices.
Track 5. eHealth and Applications
Track chairs:
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Dr. Roderick Thomas, Swansea University
Dr. Daniel Rees, Swansea University
Scope:
The eHealth Innovations and Applications track at ICTO2025 will explore the transformative role of digital technologies in healthcare delivery, focusing on how innovations such as AI, telemedicine, electronic health records, and wearable devices are reshaping patient care, clinical decision-making, and administrative efficiency.
Topics of interest include, but are not limited to:
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AI and Machine Learning: Advancements in predictive analytics and personalised treatment plans.
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Telemedicine and Remote Care: The expansion of virtual platforms to improve accessibility and equity in healthcare.
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Interoperability and Data Integration: Addressing challenges in creating unified healthcare ecosystems.
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Health Informatics and Patient-Centered Care: Empowering patients with real-time health monitoring and self-management tools.
While eHealth technologies offer immense potential, this track also emphasises critical ethical and regulatory considerations, including data privacy, security, and the mitigation of algorithmic biases. By addressing these challenges and leveraging technologies such as augmented intelligence and blockchain, this track aims to inspire innovative solutions for smarter, more inclusive healthcare systems, ultimately contributing to improved societal well-being. Researchers, practitioners, and policymakers are invited to join this vital dialogue to shape the future of healthcare technologies.
Track 6. Human-Centric AI and Hospitality: Optimizing Service Quality Across All Industries
Track chairs:
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Dr. Mario Saba, Higher Hospitality Academy of Switzerland
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Dr. Jeff Joireman, Washington State University
Scope:
The integration of human-centric AI within diverse sectors is continually expanding. This integration is crucial for enhancing service quality across all industries. Substantial investments have underscored the commitment to utilizing Human-Centric AI and Hospitality values to transform operations and improve customer and employee satisfaction.
This track aims to illuminate the relationship between Human-Centric AI and Hospitality, emphasizing their dual benefits in boosting operational efficiencies and enhancing quality experiences. Additionally, the track will showcase how AI can revolutionize service standards, making operations more effective while simultaneously enhancing customer and employee satisfaction.
Topics of interest include, but are not limited to:
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Integration Strategies: Exploring how human-centric AI can be integrated with hospitality values to elevate service delivery.
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Applied Research Cases: Showcasing examples of successful AI applications that have improved service experiences across various industries.
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Operational Improvements: Discussing ways AI enhances both visible operations and behind-the-scenes processes to enhance overall service quality.
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Impact Measurement: Developing methods to assess the effectiveness of integrating Human-Centric AI with hospitality values and practices.
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Customer Engagement: Implementing techniques that use AI to personalize customer interactions, thereby increasing loyalty and satisfaction.
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Efficiency and Sustainability: Analyzing how AI-driven improvements in service processes can reduce costs and foster sustainable practices.
Track 7. Research Methodology in the Era of Data
Track chairs:
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Dr. Imed Ben Nasr, Excelia Business School, France
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Dr. Sabrine Mallek, ICN Business School, France
Scope:
The data era has fundamentally transformed how research is conducted across disciplines. With the exponential growth of data availability, advancements in data analytics, and the integration of artificial intelligence (AI) and machine learning (ML) into research practices, traditional research methodologies are being redefined. Researchers now face both unprecedented opportunities and challenges in designing, conducting, and interpreting studies in this data-driven landscape.
This track aims to explore the evolving methodologies that leverage data-centric approaches to enhance research rigor, reproducibility, and impact. It invites contributions that address the theoretical, methodological, and practical implications of conducting research in the data era. Topics include innovative data collection techniques, the role of big data and AI in research design, ethical considerations in data-driven research, and the integration of interdisciplinary approaches to tackle complex research questions. The track also seeks to discuss how researchers can adapt to the challenges of data quality, bias, and the increasing complexity of analytical tools while ensuring transparency and validity in their work.
We welcome submissions from diverse disciplines and perspectives that contribute to advancing research methodologies in the context of data-driven innovation. This track provides a platform for researchers, practitioners, and educators to share insights, frameworks, and case studies that highlight the transformative potential of data in shaping the future of research.
Topics of interest include, but are not limited to:
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Innovative data collection methods, including IoT, sensors, and digital platforms.
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The integration of AI and ML in research design and analysis.
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Big data analytics and its implications for research methodologies.
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Ethical considerations in data-driven research, including privacy, bias, and transparency.
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Interdisciplinary approaches to solving complex research problems using data.
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Frameworks for ensuring reproducibility and validity in data-centric research.
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The role of data visualization and storytelling in communicating research findings.
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Addressing challenges in data quality, accessibility, and integration.
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Leveraging generative AI tools for hypothesis generation and exploratory research.
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Case studies showcasing innovative applications of data-driven methodologies.
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Training and education in data-centric research methodologies for the next generation of researchers.
Track 8. AI Partnership in Industry 5.0:
Redefining Collaboration, Interaction, and Innovation
Track chairs:
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Dr. Ina Kayser, IST-Hochschule für Management/IST University of Applied Sciences, Dusseldorf, Germany
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Dr. Antoine Harfouche, Université Paris Nanterre, Frane
Scope:
The paradigm shift toward Industry 5.0 emphasizes a human-centric approach that integrates advanced technologies, particularly Artificial Intelligence (AI), with the goal of enhancing collaboration between humans and machines. This transformation is characterized by a focus on behavioral, social, and technological dimensions, which are crucial for understanding how individuals and organizations adopt and interact with intelligent systems to create value in a collaborative environment. This track therefore explores the intersection of human behavior, AI, and advanced systems within the transformative framework of Industry 5.0. As Industry 5.0 evolves from its predecessor, it emphasizes the harmonious collaboration of humans and intelligent technologies, fostering innovation while prioritizing human-centric, sustainable, and resilient practices (Barata & Kayser, 2023).
With the growing integration of digital twins and AI, this track delves into their role in bridging physical-digital gaps, redefining human-computer interactions, and shaping decision-making processes in sociotechnical systems (Barata & Kayser, 2024). Moreover, understanding the factors driving technology acceptance, as outlined in frameworks like TAM and UTAUT2, is pivotal for designing effective, user-friendly systems (Kayser & Gradtke, 2024).
Recent literature highlights the importance of a human-centric framework in the transition to Industry 5.0 (Barata & Kayser, 2023). Bakator (2024) presents a comprehensive model that integrates AI and digitalization into manufacturing processes, emphasizing sustainability and flexibility while placing humans at the core of innovation. This aligns with the findings emphasizing the integration of advanced technologies like AI and the Internet of Things (IoT) to create a more human-centric industrial landscape. This underscores the necessity of collaboration between humans and machines to optimize production processes, which is a fundamental aspect of Industry 5.0.
Moreover, the dynamics of human-computer interaction (HCI) are critical in this context. Law (2023) explores user-centric designs in human-robot interaction, demonstrating how various methodologies can enhance the user experience in smart cities. Such insights are vital for developing intelligent systems that not only function effectively but also resonate with human users, thereby fostering greater acceptance and collaboration.
The integration of AI into workplace environments also raises important considerations regarding biases and ethical implications. Harfouche et al. (2023) discuss the design of human-centric AI applications aimed at mitigating biases through collaborative frameworks. This is essential for ensuring that AI systems are not only effective but also equitable and inclusive, aligning with the overarching goals of sustainable innovation in Industry 5.0.
In summary, the transition to Industry 5.0 requires a comprehensive approach that combines advanced technologies with a deep understanding of human behavior and interaction. The literature emphasizes the significance of human-centric frameworks, ethical considerations, and the integration of AI in creating value through augmented collaboration. Hence, interdisciplinary research is vital for advancing sustainable and inclusive innovation in the evolving industrial landscape.
Topics of interest include, but are not limited to:
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Human Behavior and IS Acceptance:
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Models and frameworks for IS acceptance in Industry 5.0
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Behavioral insights into the adoption of AI-enabled systems in workplace and social contexts
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Individual and organizational resistance to AI and intelligent system integration
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Human-Computer Interaction and Collaboration
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Enhancing user experience (UX) in AI-driven systems
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The evolution of HCI design principles for human-centric AI technologies
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Accessibility and inclusivity in HCI design for intelligent systems
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Dynamics of human-AI collaboration in decision-making and problem-solving
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Human-in-the-loop systems and ethical considerations in shared autonomies
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Role of trust, transparency, and explainability in human-computer collaboration
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AI and Society:
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Social and ethical implications of AI-driven innovations in Industry 5.0
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Balancing automation with meaningful human roles in digitalized industries
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Psychological and emotional responses to AI integration in daily life and work
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Industry 5.0 Applications:
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Case studies of successful human-AI collaborations in manufacturing, healthcare, education, and service industries
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Industry-specific challenges in deploying intelligent systems
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Intelligent systems for sustainable and green innovation in Industry 5.0
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Future Directions in HCI and IS:
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Emerging trends in human-computer interaction and behavioral research
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Collaborative AI for personal development and lifelong learning
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Gamification, augmented reality (AR), and virtual reality (VR) in HCI design
References:
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Bakator, M. (2024). Transition to industry 5.0 with ai and digilitalization of production systems. JEM, 2(1). https://doi.org/10.7251/jem2402008b
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Barata, J., & Kayser, I. (2023). Industry 5.0 – Past, Present, and Near Future. Procedia Computer Science, 219, 778–788. https://doi.org/10.1016/j.procs.2023.01.351
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Barata, J., & Kayser, I. (2024). How will the digital twin shape the future of industry 5.0? Technovation, 134, 103025. https://doi.org/10.1016/j.technovation.2024.103025
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Harfouche, A., Quinio, B., & Bugiotti, F. (2023). Human-Centric AI to Mitigate AI Biases: The Advent of Augmented Intelligence. Journal of Global Information Management (JGIM), 31(5), 1-23. https://doi.org/10.4018/JGIM.331755
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Kayser, I., & Gradtke, M. (2024). Unlocking AI acceptance: an integration of NCA and PLS-SEM to analyse the acceptance of ChatGPT. Journal of Decision Systems, 1–29. https://doi.org/10.1080/12460125.2024.2443231
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Law, W. (2023). Applied design and methodology of delivery robots based on human–robot interaction in smart cities. EAI Endorsed Transactions on Smart Cities, 7(2). https://doi.org/10.4108/eetsc.2649
Track 9 (French). Diffusion des technologies digitales au sein des organisations : de leur appropriation à la création de valeur pour les parties prenantes
Track chairs:
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Dr. Marc Bidan, Université de Nantes, France
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Dr. Pauline de Pechpeyrou, Université Paris-Est Créteil
Scope:
La digitalisation à l’œuvre depuis deux décennies au sein des organisations privées s’est généralisée plus récemment au secteur public, qu’il s’agisse des lieux culturels (expériences muséales immersives, …), des services publics (Plan Action Publique 2022) ou encore de l’enseignement supérieur (place de l’IA dans les formations). Si les recherches ont consacré la pertinence du modèle d’acceptation de la technologie sous sa forme initiale (TAM) ou étendue (C-TAM), il paraît nécessaire d’aller au-delà de l’acceptation de ces dispositifs et d’investiguer plus en profondeur leur appropriation par les utilisateurs, qu’il s’agisse de collaborateurs, de clients ou d’usagers et leur contribution à la création de valeur pour l’ensemble des parties prenantes.
Ce track accueillera des papiers et des présentations proposés en Français. Il est destiné aux auteurs qui désirent partager leur recherche, en cours ou complète, notamment autour des thématiques liées aux sciences des organisations au sens large et au pilotage des technologies de l'information en particulier. Ce tract sera notamment attentif aux travaux liés aux impacts des systèmes d'intelligence artificielle générative notamment dans leurs contributions aux modifications des pratiques de travail, de vente et de mise en marché, de production de contenus et de démarches à vocation inclusives et éthiques. Les démarches originales et inventives seront appréciées notamment en termes de supports théoriques, de diversité de terrains et de cas et de recommandations managériales.
Les thèmes d’intérêt incluent :
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Appropriation des technologies digitales dans les organisations.
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Impact de l'IA générative sur les pratiques professionnelles et managériales.
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Création de valeur pour les parties prenantes grâce aux outils numériques.
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Transformation digitale dans le secteur public.
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Innovations théoriques et méthodologiques en sciences des organisations et technologies digitales.
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Inclusion et éthique dans l'adoption des technologies digitales.
Track 10. AI, Emerging Technologies, and Digital Transformation in MENA
Track chairs:
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Dr. Abbas Tarhini, Lebanese American University, Lebanon
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Dr. Abdullah Albizri, Montclair State University, USA
Scope:
The MENA region is experiencing a profound digital transformation driven by artificial intelligence (AI), emerging technologies, and innovative digital infrastructures. As nations and industries embrace AI-powered solutions, challenges related to governance, ethics, infrastructure, and inclusion must be addressed to ensure sustainable growth and equitable technological progress.
This track explores how AI, Artificial General Intelligence (AGI), blockchain, Internet of Things (IoT), and FinTech are reshaping key sectors such as healthcare, education, financial services, and smart cities. We seek contributions that critically examine the socio-economic impact of digital transformation, address ethical considerations of AI governance in emerging economies, and highlight case studies of successful digital transformation initiatives across the public and private sectors.
Particularly, we invite studies that delve into the role of data analytics and AI-driven decision-making, assess the impact of digital infrastructures on regional development, and explore how technology can promote social inclusion, gender empowerment, and sustainability. By fostering interdisciplinary dialogue, this track aims to bridge the gap between technological advancements and regional challenges, paving the way for an inclusive and resilient digital future in MENA.
Topics of interest include, but are not limited to:
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AGI and Advanced Analytics in healthcare, education, and public services
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AI-driven decision-making in manufacturing, construction, and governance
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Governance frameworks for AGI in emerging economies
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Ethical AI, privacy, and data protection in a digitally evolving MENA
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AI and big data analytics for regional economic development
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Industry-specific business analytics for strategic decision-making in MENA
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Blockchain & IoT applications beyond finance (e.g., supply chain, healthcare, energy)
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The rise of FinTech and its impact on financial inclusion and economic growth
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Lessons from successful digital transformation in public and private sectors
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The role of emerging technologies and cultural adaptation in accelerating digital transformation
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Bridging the digital divide through improved digital infrastructure and internet access
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Information systems for social inclusion and economic resilience
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Gender and digital inclusion: Empowering women through technology-driven initiatives
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Circular economy and AI for sustainable development
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Smart cities and sustainability strategies for urban transformation
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AI-driven urban planning and smart governance solutions
Track 11. Ethics and Artificial Intelligence: Challenges and Opportunities in Responsible AI Development
Track chairs:
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Dr. Nuno Guimaraes Da Costa, Excelia Business School, France
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Dr. Antoine Harfouche, Université Paris Nanterre, France
Scope:
The rapid development and adoption of Artificial Intelligence (AI) technologies have brought transformative opportunities across various domains, but they also raise critical ethical concerns. As AI systems increasingly influence decision-making processes, societal norms, and individual behaviors, addressing ethical challenges such as bias, transparency, accountability, and privacy has become paramount. This track explores the intersection of ethics and AI, focusing on how researchers, practitioners, and policymakers can ensure AI technologies' responsible development and deployment.
This track invites innovative papers that address the ethical implications of AI, propose frameworks for responsible AI governance, and explore the societal impact of AI systems. We aim to foster interdisciplinary dialogue and collaboration to develop actionable strategies for mitigating risks while maximizing the benefits of AI. By focusing on ethical considerations, this track seeks to contribute to developing AI systems that are fair, inclusive, and aligned with societal values.
Topics of interest include, but are not limited to:
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Frameworks for ethical AI development and governance.
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Addressing algorithmic bias, fairness, and transparency in AI systems.
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Privacy and data protection in AI-driven applications.
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The role of AI in promoting or hindering equity and inclusion.
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Ethical implications of AI in decision-making processes (e.g., healthcare, education, hiring).
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Case studies on the societal impact of AI technologies.
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Strategies for integrating ethical principles into AI design and deployment.
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The role of interdisciplinary AND TRANSDISCIPLINARY approaches in addressing AI ethics (e.g., combining AI with law, philosophy, and social sciences, INVOLVING BOTH ACADEMIA AND PRACTICE).
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Ethical challenges in using emerging AI technologies (e.g., generative AI, autonomous systems, and deep learning).
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Policy and regulatory frameworks for ensuring responsible AI use.
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Stakeholder engagement in the ethical development and deployment of AI.
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Preparing organizations and individuals for the ethical challenges of AI adoption.
This track aims to provide a platform for researchers, practitioners, and policymakers to share insights, frameworks, and best practices for addressing the ethical challenges of AI. By fostering collaboration and dialogue, this track seeks to advance the development of responsible AI systems that align with societal values and contribute to sustainable innovation.
Track 12. Co-production and co-creation of public services: the role of emerging technologies
Track chairs:
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Dr. Marco De Marco - International Telematic University UNINETTUNO, Italy
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Dr. Maddalena Sorrentino - University of Milan, Italy
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Dr. Danila Scarozza - Link Campus University, Italy
Scope:
Service management principles, particularly those centred on public value creation and co-production, emphasise the importance of actively involving the different groups of stakeholders in a collaborative production process in order to enhance both users satisfaction, and quality and sustainability of public services. This approach recognises that value is co-created through the dynamic interaction between service providers, users, and their broader social context, ensuring more personalised and effective outcomes.
In the last decade a large number of scholars have focused on the analysis of the evolving role of co-production in public services, highlighting its transition from traditional face-to-face collaboration to innovative, technology-enabled models. Some studies evidence that the main groups of technologies reshape how public services are designed, delivered, and assessed: 1) sensing technologies such as IoT devices and wearable sensors enable real-time data collection and monitoring for adaptive service delivery; 2) communication technologies like social media and online platforms facilitate interaction and collaboration between citizens and public organisations; 3) processing technologies involving big data analytics, machine learning, and cloud computing allow for the analysis of vast datasets to inform decision-making and design personalised services; 4) actuation technologies such as robotics and automation provide independent or semi-independent mechanisms for public service delivery.
Technology-enabled co-production of public services enhance efficiency, efficacy and reduce costs, enabling governments to deliver improved public value despite budget constraints. Digital tools facilitate broader citizen participation by overcoming physical, geographical and temporal barriers. Furthermore, they foster innovation, improve transparency and trust between service providers and citizens, empowering users to engage meaningfully in public service creation and delivery, and enhancing interaction, motivation, resource sharing and decision making. The paradigm of customer- centred approach provides new perspectives for recognising how the set of interactions and relationships within a “virtual team” of co-productors can bring to higher levels of knowledge transfer, organisational learning and innovation spreading. In fact, the benefits include tailored services, empowered stakeholders, and enhanced community outcomes, but success demands robust governance, adaptable leadership, and inclusive strategies (Sorrentino et al., 2021). Moreover, a particular focus was made on the analysis of the AI usage for the co-production process in order to bring communities, policy-makers, and scientists together to solve community issues. While some studies have made advancements on the methodological question of “how to bring communities into the loop," it was stressed that technologies may not be sufficient to address the socio-spatial disparities in co-production without human-machine collaboration. Along with the positive benefits and aspects identified by several scholars, there are also some critical issues in the co-production and co-creation of public services through emerging digital tools. Public organisations face hurdles in sustaining engagement, overcoming resistance, and building capacity to leverage co-production effectively. On the structural side, issues such as financial constraints, limited technical expertise among staff, and complex regulatory frameworks often hinder effective implementation. Cultural barriers, including resistance from public servants who perceive technologies as intrusive or a threat to their roles, further complicate adoption. Moreover, the digital divide, particularly among older or less technically skilled people, exacerbates inequities in access and participation.
Despite a growing number of studies, analysing the role of digital technologies in public service co-production, in the literature there are significant concerns, such as i) terminological conflation: the distinction between co- production, co-creation, and other forms of participation remains unclear, leading to conceptual and practical misunderstandings; ii) techno-optimism: overemphasis on the benefits of technologies often ignores their risks, potential dark sides; iii) empirical gaps: current research is dominated by isolated case studies, with limited systematic evidence on the long-term impacts of technologies in different contexts.
To advance understanding and address these gaps, this call for papers invites contributions that critically examine the role of emerging technologies in co-production and co-creation of public services. Submissions may include theoretical explorations, empirical studies, or practical case analyses that analyse the transformative potential, challenges, and future pathways for technology-enabled public service delivery.
Topics of interest include, but are not limited to:
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Generation of public value through digital co-production and co-creation;
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Evaluation of barriers and enablers of co-production of public services through emerging technologies;
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Evaluation of the role of artificial intelligence for public service co
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Analysis of various demographic, technical, and cultural factors influencing technology-enabled co-production;
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Exploration of institutional and organisational frameworks to support co-production through emerging technologies;
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Examination of power dynamics in the development and implementation of digital tools
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Dynamics and implications of technology implementation, policy, and professionalism within government settings, especially during times of crisis;
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Mitigation of the risks arising from the implementation of digital technologies in the entire public service cycle;
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Development of comparative frameworks for the evaluation of technology effects across diverse contexts and various types of public organisations;
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Investigation of social inclusion in digital co-production, with an emphasis on the role of technologies in bridging or exacerbating inequalities;
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Analysis of the role of emerging technologies for public service production and delivery to people with disabilities in different sectors (education, healthcare, security, social care etc.)
Track 13. Sustainable and human-centred approach to HRM: Discovering the role of emerging technologies
Track chairs:
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Dr. Isabella Bonacci - Universitas Mercatorum, Italy
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Dr. Cinzia Dal Zotto - University of Neuchâtel, Switzerland
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Dr. Eleonora Veglianti - Kedge Business School, France
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Dr. Maria Menshikova - Universitas Mercatorum, Italy
Scope:
Human Resource Management (HRM) literature widely agrees that to attract and retain talent effectively, the organisations have to transit from a model where human resources are merely consumed to one where they are developed and sustained. In response to the shifting demands of the labour market, evolving employment relations, and broader societal changes, the concept of Sustainable HRM has emerged. Key attributes of sustainable HRM include a long-term orientation, employee care, environmental consciousness, participation and social dialogue, flexibility, compliance beyond regulatory requirements, as well as fairness and equality. Furthermore, the Industry 4.0 paradigm has underscored the importance of HRM practices in navigating technological disruptions and promoting sustainable behaviours in the organisation. In this context the HR function has the task of integrating new technologies and sustainable practices to meet changing organisational needs in order to enhance efficiency, improve decision-making, and foster collaboration between humans and machines in a human-centred approach. The technology advancements need to be aligned with the sustainable goals of organisations, ensuring ethical and responsible deployment of emerging technologies. AI-driven HRM practices have led to innovations in recruitment, employee training, and performance management, facilitating personalised learning experiences, optimising talent acquisition processes, and providing predictive insights to improve workforce planning. However, concerns related to job displacement, bias in AI-driven decision-making, and ethical implications remain significant challenges.
Moreover, the metaverse is emerging as a transformative force in HRM by enabling virtual workplaces and remote collaboration. Immersive technologies facilitate employee engagement, enhancing virtual onboarding experiences, and providing innovative learning and development solutions. These technologies also support sustainable HRM practices by reducing the need for physical workspaces, lowering carbon footprints, and fostering inclusive work environments. However, issues related to privacy, security, and digital inclusivity must be addressed to ensure responsible implementation. As HRM adapts to technological changes, it is crucial to adopt a human-centred approach that prioritises employee well-being and sustainable work practices. AI and robotics should complement human capabilities rather than replace them. Sustainable HRM strategies should be able to integrate employee participation, ethical governance of the emerging technologies, and policies that promote diversity, inclusion, and work-life balance.
Previous research has begun to analyse the impact of emerging technologies such as AI, machine learning, mixed reality, smart robots, virtual assistants, and robotic process automation on various stages of the HR lifecycle. However, there remains a significant gap in empirical research across different sectors and contextual settings.
This track aims to attract contributions that explore the intersection of emerging technologies and sustainable HRM practices at all the stages of the HR lifecycle, addressing existing gaps in the literature.
Topics of interest include, but are not limited to:
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The role of AI in enhancing HRM practices;
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Ethical considerations in AI-driven HRM practices, including bias mitigation and transparency;
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The integration of metaverse technologies in HRM functions;
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The influence of AI and metaverse applications on recruitment, training, and performance management;
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HR strategies for developing digital skills and competencies required for Industry 4.0;
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The implementation of sustainable HRM practices within technology-driven environments;
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The impact of intelligent automation technologies on the transformation of HRM strategies and human-machine collaboration;
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The challenges of digital inclusion, privacy, and ethical governance in technology-enabled HRM environments.
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The evolution of HR specialists’ profile (role, tasks, and skills) in technology-enabled environments.
We encourage submissions that bridge theory and practice, providing insights into how organisations can navigate digital transformations while maintaining a human-centred and sustainable approach to HRM
Track 14. AI-Driven Decision Making & Explainable AI in Business and Society
Track chairs:
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Pr. Taleb Nora, Computer science department, Badji-Mokhtar University, Annaba, ALGERIA
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Dr. Bouslah Ayoub, Computer science department, Badji-Mokhtar University, Annaba, ALGERIA
Scope:
Artificial Intelligence is playing an increasingly central role in decision-making across business and society. From automating complex processes to optimizing strategic choices, AI-driven systems are reshaping industries. However, one of the major challenges remains the transparency and explainability of these systems. Without clear insights into how AI models reach their conclusions, trust, adoption, and ethical concerns become critical issues. This track explores the intersection of AI-powered decision-making and Explainable AI (XAI), focusing on how organizations can leverage AI while ensuring interpretability, accountability, and fairness. We invite contributions that address methodological advancements in XAI, practical applications across various industries, and the ethical and regulatory challenges associated with AI-driven decisions. Whether through case studies, novel frameworks, or interdisciplinary approaches, this track aims to foster discussions on making AI more transparent, responsible, and effective in real-world contexts.
Topics of Interest include, but are not limited to:
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Advancements in Explainable AI (XAI) – Techniques and methodologies to improve AI interpretability and transparency.
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AI in Business Decision-Making – How companies are using AI to optimize operations, risk management, and strategic planning.
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Human-AI Collaboration – The role of AI as a decision-support tool and its interaction with human expertise.
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Bias and Fairness in AI Models – Identifying, mitigating, and addressing bias in AI-driven decision processes.
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Ethical and Regulatory Challenges of AI – Exploring governance frameworks, compliance issues, and ethical concerns.
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Real-World Applications of AI in Different Sectors – Case studies from finance, healthcare, industry, and government.
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Building Trust in AI Systems – The role of explainability in user acceptance and responsible AI deployment.