Gert-Jan de Vreede

University of South Florida
Muma College of Business
4202 E. Fowler Avenue, BSN 210
Tampa, FL 33620
Tel: (813) 974-6768

Portrait image of Jay Nunamaker.

Jay Nunamaker

University of Arizona
Eller School of Business, Rm 430 HH
1130 E. Helen St.
Tucson AZ 85721
Tel: (520) 621-4475
Fax: (520) 621-3918

Groups collaborate to create value that their members cannot create through individual effort. Collaboration, however, engenders economic, interpersonal, social, political, cognitive, emotional, physical, and technical challenges. Groups can improve key outcomes using collaboration technologies, but any technology that can be used well can also be used badly; IS/IT artifacts do not assure successful collaboration. The value of a collaboration technology can only be realized in the larger context of a collaboration system, a combination of actors, hardware, software, knowledge, and work practices to advance groups toward their goals.

Designers of collaboration systems must therefore address many issues when creating a new collaboration system. This track seeks new work from researchers in many disciplines to foster a growing a body of exploratory, theoretical, experimental, and applied research that could inform design and deployment choices for collaboration systems. We seek papers that address individual, group, organizational, and social factors that affect outcomes of interest among people making joint efforts toward a group goal.

We look for papers from the range of epistemological and methodological perspectives. Behavioral science and design science papers are welcome. The track seeks to synthesize broader understandings in the diversity of approaches that contributors bring to the conference.

The Advances in Teaching and Learning Technologies (ATLT) minitrack encourages research contributions that deal with learning theories, teaching tools and their development, supporting infrastructures, user experiences and feedback, learning analytics, and measurable outcomes as they relate to the area of technology and its support of improving teaching and learning. The current increasing demand for hybrid learning, online learning models, and learning in extended realities (VR/AR/MR) have challenged multidisciplinary research for advancing the design, development, and implementation of effective teaching and learning technologies. Furthermore, the recent progress in Artificial Intelligence (AI) and other advanced technologies has shown the potential to disruptively transform learning and teaching in several ways such as providing personalized and adaptive learning experiences, automating certain tasks, and enabling new forms of instruction and assessment. For instance, the release of the ChatGPT language model, a highly advanced generative AI technology, has raised concerns about academic integrity, reduced critical thinking skills due to students’ reliance on AI, the possibility of replacing human teachers, and its other potential impacts on teaching and learning. By combining the capabilities of AI and human intelligence, hybrid intelligence has the potential to overcome some of the threats associated with the use of AI alone such as mitigating the risk of replacing human teachers and reducing critical thinking skills. Nevertheless, It is important to note that this approach also requires research and development of new pedagogy and methodologies to guarantee the best use of such systems.

The use of AI and advanced technologies in learning environments also invites new questions, applications, and research methodologies. How, for example, do technology integration and remote teaching augment how people learn?, and Can we effectively develop agency, trust, analytics, feedback, and interventions to support learning in complex environments where boundaries between human and artificial cognition and knowledge processes become blurred? What new capability and research will this integration bring and how will it advance our current understanding of learning?

We seek to bridge disciplines and research communities between system sciences, AI, computer, and learning sciences, so within this scope, a broad range of research questions, learning settings, and theoretical and methodological traditions will be considered. We are flexible about what constitutes ‘learning’ (e.g., acquisition or co-creation of knowledge or skills, intersubjective meaning-making, advancing community and network learning, collective change) and about the nature of the setting (e.g., face-to-face or online; formal or informal; educational, workplace or leisure and mixtures thereof; with diverse technological media and artificial intelligence mediating networked or community social interaction), but learning and the Collaboration Systems and Technology setting should be considered in relation to each other rather than one without regard for the other.

Papers should make a theoretical and/ or empirical contribution or establish the value of a methodological or design innovation. It is not sufficient to merely document the use of technology in a learning context or apply a well-worn model without new insights.

Papers accepted for presentation in this minitrack will be selected and invited for submitting extended manuscripts to a special issue in Policy Futures in Education. Papers with implications for policies regarding advanced learning technologies (e.g. AI, learning analytics) will be considered and the selected papers will be fast-tracked through the review process for the issue.

Minitrack Co-Chairs:

Olga Scrivner (Primary Contact)
Rose-Hulman Institute of Technology and Indiana University

Maarten de Laat
University of South Australia

Andy Nguyen
University of Oulu

James Scrivner

Collaboration systems have long been used to support individuals to work together to attain their goals. With the widespread popularity of social media technologies, the pervasive expansion of immediate many-to-many connections has introduced new dynamics amongst and between users, companies, and advocates that pertain to all forms of political, economic, and personal life. While these dynamics imply various positive consequences for the civil society (e.g., greatly unrestrained access to sharing and collecting information), they also introduce severe issues of coordinated adversary behaviors (e.g., coordinated inauthentic behavior, cybermobbing, distortion of the public discourse, proliferation of unreliable information, relinquished on- and offline privacy).

The rise of coordinated adversarial behaviors in collaboration and social media systems deserves more scholarly and public attention, because of their devastating consequences to individuals and society. Furthermore, system providers and platform regulators struggle to develop effective means to counteract these undesirable and destructive issues. There is also a need to conduct theory-guided studies to investigate prevention and intervention strategies for coordinated adversary behaviors in collaboration and social media systems. Thus, the aim of this minitrack is to identify, conceptualize, and assess these emergent cutting-edge issues as well as their actual or potential counter mechanisms.

The minitrack intends to inform the respective decision making of regulators and tech companies from an Information Systems standpoint. Researchers are invited to adopt a pessimistic perspective (i.e., the extent to which collaboration and social media systems cause or prolong problems) or an optimistic view (i.e., ways to prevent and mitigate these problems) when addressing coordinated adversarial behaviors in collaboration and social media systems. We also welcome papers examining the synergies of collaboration and social media systems and exploring the potential, social and other impacts of integrated systems. This minitrack is open to all types of research, conceptual, theoretical, and/or empirical. Examples of possible topics of interest include (but are not limited to):

  • Cybermobbing, cyberbullying, cyberharassment, online disinhibition, hate speech, trolling, deceptive communication
  • Digital vigilantism, shaming, doxing, hacktivism, human flesh search engine
  • Violent online extremism and cyberterrorism
  • Fake news, deception, participatory or bot-driven disinformation campaigns
  • Coordinated inauthentic behavior, astroturfing, sockpuppeting
  • Network polarization, echo-chambers, filter bubbles
  • Prevention and intervention mechanisms, (algorithmic) content moderation, balancing the protection of civil liberties and national security, censorship, deplatforming, content monitoring
  • Policy, governance, platform (self) regulation
  • Privacy protection and violations, dark pattern design

High quality and relevant papers from this minitrack will be selected for fast-tracked development towards Internet Research. Selected papers will need to expand in content and length in line with the requirements for standard research articles published in the journal. Although the minitrack co-chairs are committed to guiding the selected papers towards final publication, further reviews may be needed before a final publication decision can be made. Internet Research (IntR) is an international and refereed journal that is indexed and abstracted in major databases (e.g., SSCI, SCI, ABI/INFORM Global), with an impact factor 6.353 in 2021.

Minitrack Co-Chairs:

Christy M.K. Cheung (Primary Contact)
Hong Kong Baptist University

Marten Risius
University of Queensland

Matthew K.O. Lee
City University of Hong Kong

Christian Wagner
City University of Hong Kong

This minitrack focuses on the impact of AI on the various aspects of the workplace as it exists currently as well as how it may evolve in the future. We seek papers that address the social, technical, behavioral, attitudinal, emotional, or managerial aspects of AI in the workplace. The unit of analysis can be individuals, teams, or organizations. All kinds of research are welcome including but not limited to quantitative, qualitative, conceptual, or design-oriented research.

The focus of these papers can range from the impact of AI on work and its related aspects to the design considerations of AI in the workplace. In short, this minitrack seeks to highlight research that may influence the future of work and act as a springboard for new ideas and innovations in AI that will be disruptive to the workplace.

The “AI and the Future of Work” minitrack is especially interested in the following topics:

  • Power shifts between humans and AI
  • AI and employees’ mental and physical wellbeing
  • Shift in social/role identities with the introduction of AI
  • Required skill set for human employees in an era of AI
  • AI and the changing face of leadership
  • Social relationships and AI at the workplace
  • Integration of AI in work practices (knowledge sharing, decision making, etc.)
  • Responsible and Explainable AI
  • Ethical considerations of AI at the workplace
  • Financial and economic implications of AI implementation in the workplace
  • The changing meaning of work or worklife balance in an era of AI
  • AI task appropriateness
  • Designing AI for the workplace
  • AI and changes in work settings
  • Workplace Analytics and AI
  • AI and creativity in the workplace
  • Collaboration with AI
  • AI mimicking human labor (ChatGPT, Next Rembrandt etc.)
Minitrack Co-Chairs:

Triparna de Vreede (Primary Contact)
University of South Florida

Xusen Cheng
Renmin University of China

Dominik Siemon
LUT University

The development of the Internet, social media, distributed databases, and a variety of mobile devices has caused a huge increase in data. Much of this diverse data in unstructured and structured forms has a high business value and, if properly utilized, can become an important organizational asset. It contains various information about customers, transactions at superstores and on the Internet, competition, labor market, and development trends for industries, products and services, social media such as Twitter, Reddit, and Facebook, as well as the public and political mood. Moreover, this data comes in real-time and needs to be processed instantly using data streaming technology. For innovative, collaborative and sustainable development, it is essential for organizations to utilize this data to increase sales, identify future opportunities and new markets, outperform the competition, enhance products and services, recruit talent, improve operations, perform forecasting, protect the brand, and identify areas for improvement to name a few. However, many organizations make a limited use of this valuable data available to them either because they lack necessary tools or do not understand the value of this data.

The main objective of this mini-track is to provide organizations a theoretical, conceptual, and applied grounded discussion of Business Intelligence (BI) and Big Data (BD) to aid in innovative, collaborative, and sustainable development as well as effective decision-making.

This minitrack addresses the following topics:

  • What is the substance (nature) of BI & BD?
  • What is the addedvalue of BI & BD to development of organizations and their decisionmaking process?
  • How to support organizational creativity, innovation and decisionmaking using BI & BD?
  • How to design intelligent information systems and build decision support systems based on BI & BD?
  • How to enhance company level decision making process to integrate external stakeholders in order to develop collaborations?
  • How to use BI & BD tools and solutions to achieve innovative, collaborative, and sustainable development of organizations?

Thus, this minitrack invites papers focused on, but not limited to:

  • Theoretical foundations for BI & BD development
  • BI & BD to improve innovative, collaborative, and sustainable development of organizations
  • Challenges and opportunities of applying BI & BD for innovative, collaborative, and sustainable development of organizations
  • Development of BI & BD analytics capability
  • BI & BD driven strategies
  • BI & BDenabled business transformation
  • Business value of BI & BD
  • BI & BD engineering for business model innovation
  • Stateoftheart practical approaches, solutions, methods, and tools including machine and deep learning to foster innovative, collaborative, and sustainable development of organizations by using of BI & BD
  • Cognitive technologies in organizations
  • Social networks
  • The evolution of BI & BD through wide diffusion of digital technologies and digital platforms
  • Technological and human requirements for effective and efficient BI & BD operations

Minitrack Co-Chairs:

Celina Olszak (Primary Contact)
University of Economics in Katowice

Jozef Zurada
University of Louisville

Dilek Cetindamar
University of Technology Sydney

Pawel Weichbroth
Gdansk University of Technology

Collaboration is increasingly essential for cocreating value across geographic distances and among diverse groups of people within, between, and outside of organizations. With higher demand for remote opportunities and dispersed talent around the world, digital platforms and interconnected systems provide a means for collective engagement among firms and customers in markets. Prior Information Systems research provides important insights into how collaboration systems are designed, developed, and deployed to support collective decision making, group processes, communication, and coordination. However, these technology-based systems are nested within broader, multi-level and multi-sided sociotechnical and economic ecosystems that shape the nature, scope and impact of collaboration.

Collaboration ecosystems are sociotechnical structures and networks of relationships that support interactions among interdependent participants within, across and outside of organizations. These interdependent actors operate along different logics that may converge or conflict and often rely on technological platforms for opportunities to engage. Collaboration engagement is guided by social norms that reflect a specific notion of interdependence and mediated by collaboration technologies, which lead to the cocreation of value for individuals, groups and society at large. The importance of this interdependence is evidenced in network effects that increase in complexity through diversity of actors and variety of resources. These inter- and intra-organizational and market-facing collaborations have the potential to create greater value as they attract and connect more participants, including customers or end users, interacting for their mutual benefit; the whole is more than the sum of its parts.

This minitrack centers on the exploration of collaboration ecosystems, or the multi-sided, multi-level sociotechnical systems in which joint efforts to create value and associated collaboration technologies are embedded. We seek papers that investigate the nested nature of collaboration technologies in markets, as well as networks of actors and their dynamic relationships that support collaboration practices, processes, and outcomes. We encourage the submission of both theoretical and empirical papers, and all types of methods (qualitative or quantitative) are welcome.

Topics of interest include, but are not limited to, the following:

  • How Collaboration Ecosystems Support Wellbeing
  • Economic Drivers and Impacts of Collaboration Ecosystems
  • Platform Design for Multi-level, Multi-sided Collaboration Ecosystems
  • Critical Collaboration Capabilities
  • Value Cocreation in Collaboration Ecosystems
  • Innovation in Collaboration Ecosystems
  • Collaboration vs Competition in Value Cocreation
  • Methods for Evaluating Collaboration
  • Dimensions and/or Types of Collaboration
  • Collaboration Practice, Processes and Outcomes
  • Institutional Logics that Support Collaboration
  • Antecedents and Consequences of Collaboration in Markets
  • Collaboration and Market Formation
  • The Role of Devices and Data in Collaboration
  • Adoption of Collaboration Technologies
  • Diffusion of Collaboration Practices

Nascent research on collaboration ecosystems underscores the importance of conceptual and theoretical development. Conceptual articles of the minitrack that are of high scholarly quality and have a good fit with the journal’s aims and scope (the study of markets and marketing), will be considered for fast-tracked publication in AMS Review. Selected authors will be notified about the opportunity to submit their work as a regular submission. However, editor, associate editors, and reviewers will commit to a speedy review process while keeping the quality of the journal in mind. Hence, the invitation to the fast-track does not guarantee publication.

Minitrack Co-Chairs:

Melissa Archpru Akaka (Primary Contact)
University of Denver

Hope Jensen Schau
University of Arizona

Stephen L. Vargo
University of Oklahoma

Online communities consist of individuals who share a common interest and who use the internet to communicate with each other and work together in pursuit of shared interests. Individuals seek out information online for both utilitarian and hedonic reasons. Online forums are one example of a pervasive platform where individuals can submit and receive answers to questions as well as browse the experiences of others. Individuals with questions often turn to these forums, either directly or indirectly (through search engine results), to find answers to problems they face. While research has begun to address utilitarian and hedonic seeking and consumption of information, there is still much left unknown.

This minitrack focuses on research related to understanding information processing and decision making in the context of online communities. The following is a list of sample topics (non-exhaustive) that would be a good fit for this minitrack:

  • How individuals search for, filter, or adopt online information
  • Online decision-making processes
  • Cognitive processing related to consumption of online information
  • Validation of online content
  • AI-generated content
  • Community based cues
  • Evaluation of different cue types (e.g., upvotes, star ratings)
  • Design elements of tools to support online communities
  • Crowdsourced knowledge
  • Approaches to increase contributions/engagement
  • Novel approaches to support online communities
Minitrack Co-Chairs:

Matt Jensen (Primary Contact)
University of Oklahoma

Tom Meservy
Brigham Young University

Kelly Fadel
Utah State University

Humans and machines are collaborating in new ways and organizations are increasingly leveraging human-machine teams. Decision-makers at all levels of organizations interact with information systems that are designed to enable better, faster, and more effective decisions. The problem is that information has reached a critical mass. The sheer volume of data and data sources make it impossible for a human being to capture and process all available and relevant data, facts, figures, etc. The need for collaborative, human-machine decision-making is increasing in importance. However, it remains unclear how to enable these new forms of effective human-machine decision-making and provide organization with leverage.

Machine teammates are technology-based systems that are capable of sensing, information processing, decision-making, and learning to act upon their environment and to interact with humans and other machines in order to achieve a shared task goal with more or less autonomy. These varied types of artificial intelligence (AI) use text clues, vocal cues, or other environmental sensors to retrieve information from the user, process it, and respond appropriately. These intelligent agents help individuals complete everyday tasks such as find directions, ask for help when ordering goods or services on a website, or understand additional information about a topic or idea. Today, most humans use these intelligent agents for simple, utilitarian tasks. However, with the speed of technological progress, humans are likely to soon undertake larger, more creative and knowledge-intensive tasks with these more autonomous, intelligent agents.   As intelligent agents advance and become more mainstream, new use cases (e.g., create royalty-free music with, improve programming code with chatGPT, automated meeting summaries with Microsoft Teams, etc.) will emerge that will offer a diverse user group various benefits, but might also lead to unintended (negative) consequences. It is not fully understood how humans will actually interact with them or if humans utilize intelligent agents in ways different from traditional human-to-human collaboration. Hence, we need to explore new dimensions of these new forms of human-machine collaboration.

This minitrack invites papers that will examine the emergence of this new type of collaboration and its implications for individuals, teams, organizations, and crowds.  It is focused at the intersection of human-machine collaboration.

This minitrack provides one of the key international platforms on which the following issues can be discussed:

  • Human collaboration with artificial agents and intelligent systems in teams, crowds, and with individuals
  • Effects of ChatGPT and/or other intelligent technologies on human productivity, collaboration, teams, and decision-making
  • Design and evaluation of smart technology as team members including agent-based support (e.g., robots, chatbots) for decision makers
  • Individual differences that impact collaboration with and acceptance of artificial intelligence
  • Algorithmic management in teams and crowds
  • Collaboration with agents in extended reality environments (e.g., virtual reality, augmented reality, mixed reality)
  • Usability and design research for human collaboration with automated teammates
  • Digitalization and automation of collaborative processes
  • Agent-based support for groups including innovative facilitation methods, techniques, and procedures to improve (a)synchronous collaboration between co-located and/or distributed teams
  • Studies and frameworks that examine trust in, satisfaction with, and expectations of artificial intelligence
  • Design features for automated teammates that improve human collaboration with them
  • Studies of group dynamics when an artificial teammate is on the team
  • Methods and technologies for eliciting and capturing tacit knowledge from experts (i.e., externalization) and sharing / incorporating that knowledge into collaborative efforts with automation
  • Neurophysiological approaches to assessing interactions with intelligent systems including eye-tracking (e.g. pupillometry), galvanic skin response (GSR), and electroencephalogram (EEG)

There are no preferred methodological stances for this mini-track: this mini-track is open to both qualitative and quantitative research, to research from a positivist, interpretivist, or other theoretical perspectives to studies from the lab, from the field, or developmental in nature.

Accepted articles of the minitrack that are of high scholarly quality and have a good fit with the journal’s aims and scope, will be considered for fast-tracked publication in Internet Research. Authors will be notified during or shortly after the HICSS conference about this opportunity. Authors are asked to extend the manuscript by at least 30% with new content and change the paper’s title. This new content could be additional empirical evidence, new analysis, a more refined theorizing, extended background, etc. The authors are expected to submit an improved version of their conference paper to the journal. The invited authors need to declare their invitation to the fast-track in the cover letter to the editor-in-chief (Christy Cheung) and upload their HICSS review table with their extended manuscript. The minitrack chairs will function as (invited) associate editors and invite 2-3 reviewers for each manuscript. These reviewers will not be the same as the reviewers from the HICSS conference. The HICSS review counts as a first review round, which should inform the newly invited reviewers about the merit of the manuscript. The submission will run as a regular submission. However, editor, associate editors, and reviewers will commit to a speedy review process while keeping the quality of the journal in mind. Hence, the invitation to the fast-track is no guarantee for publication.

Minitrack Co-Chairs:

Joel Elson (Primary Contact)
University of Nebraska at Omaha

Douglas Derrick
University of Nebraska at Omaha

Isabella Seeber
Grenoble Ecole de Management

Lena Waizenegger
Auckland University of Technology

This minitrack is dedicated to the employment of collaborative robots (cobots) in emergency situations. Cobots are robots that are built for direct human-robot collaboration (HRC) in a shared environment. It focuses on the idea that collaboration between people and robots must go much farther – rather than viewing robots as tools or mobile sensors, they must be viewed as team members especially in predictable environments such as production lines, towards disaster zones, and in emergency circumstances. In the aftermath of earthquakes, accidents, avalanches, or explosions, cobots can work with human counterparts to reduce the risk to human life and increase the possibility of rescuing people.

Topics of interest include, but are not limited to:

  • Search and Rescue (SAR) collaborative robots (cobots)
  • Human-robot cooperation (HRC) in emergency scenarios
  • Haptics for emergency scenario
  • Robot control algorithms for emergency scenarios
  • Robotic sensors and actuators for emergency scenarios
  • Ethical issues for human-robot cooperation (HRC) in emergency scenarios
  • Machine Learning (ML) and Artificial Intelligence for robotics in emergency scenarios
  • Robotic simulation for emergency scenarios
  • Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), Extended Reality (ER) for robotics in emergency scenarios
Minitrack Co-Chairs:

Filippo Sanfilippo (Primary Contact)
University of Agder

Gionata Salvietti
Università degli Studi di Siena

Conversational AI (CA) is becoming an important means for human-computer collaboration. CA uses massive datasets and Artificial Intelligence (AI) techniques, such as Natural Language Processing (NLP), Machine Learning (ML) and Deep Learning (DL), to mimic human interaction. By translating the meanings of voice and text input, CA performs a wide range of functions, from assisting users in searching web resources, summarizing and translating text, to answering challenging questions based on knowledge obtained from large volumes of data. Such CA not only increases the usability of computer-based services but also brings a radical change to human-computer collaboration. However, despite its exponentially increasing adoption across industries, CA suffers from a variety of technical limitations, calling for more scholarly attention to address them. Further, with its rapid adoption, our society is facing numerous ethical issues which need to be addressed to ensure that CA is safe, secure, trustworthy, and ethically appropriate in various contexts.

This minitrack welcomes theoretical and empirical research addressing a variety of technical, social, and ethical issues relevant to a complex and multifaceted challenge of Conversational AI systems. The topics relevant to this minitrack include, but not limited to:

  • Generative AI: Generative AI has been used to create various types of new content, including text, images, audio, video and synthetic data. The release of powerful generative models, such as ChatGPT, has accelerated the adoption of generative AI, calling for more research to address its various issues, including design methods, development challenges, innovative use cases, and ethical concerns.
  • Natural Language Processing and Text Analytics: A wide variety of ML/DL methods along with NLP have been used to analyze voice and text in conversation. Nonetheless, existing approaches suffers from technical limitations, calling for more research to advance the state-of-the art in voice/text analytics.
  • Transparency and Explainability: Conversational AI systems can be difficult to understand or explain, making it harder for people to trust them. This has led to a growing need for research on methods to increase the transparency and explainability of AI systems.
  • Bias and Fairness: Conversational AI systems can perpetuate and amplify biases present in the data used to train them, which can lead to unfair and discriminatory outcomes. This has led to a growing need for research on methods to increase fairness and reduce bias in Conversational AI systems.
  • Autonomy: As Conversational AI systems become more advanced, there are concerns about their potential to make decisions without human oversight or control. This has led to a growing need for research on methods to ensure the safety and accountability of autonomous AI systems.
  • Privacy and Data Breaches: The use of Conversational AI can raise concerns about the collection, storage, and process of large amounts of personal sensitive data that makes them a target for data breaches and other forms of cybercrime. Methods and implications for protecting individuals’ privacy and data breaches as a result of misuse of AI systems need to be studied.
  • Security and Vulnerabilities: Conversational AI systems can be vulnerable to adversarial attacks (e.g., hacking, malware, and other forms of cyber attack), which can compromise their security and the security of the systems and networks they are connected to. Attackers also manipulate input data or use other techniques to trick the system into making incorrect decisions. This has led to a growing concern about the confidentiality and integrity of Conversational AI systems, which needs research on methods to increase the robustness and security of Conversational AI systems against adversarial attacks.
  • Infringement of Copyrights and Intellectual Property Rights: Conversational AI systems can be used to create and distribute unauthorized copies of copyrighted and trademarked material, making it difficult to enforce and protect such rights. In addition, the models of Conversational AI systems are trained on a large amount of data, are valuable assets, and can be stolen or replicated.
  • Weaponization: AI systems are increasingly being used in weapon systems, which raises ethical questions about the use of Conversational AI in warfare and the possibility of Conversational AI being used to create autonomous weapons.
Minitrack Co-Chairs:

Dan J. Kim (Primary Contact)
University of North Texas

Victoria Yoon
Virginia Commonwealth University

Kiseol Yang
University of North Texas

Manoj Thomas
University of Sydney

Effective Cross-organizational collaboration makes firms to achieve advance innovation through timesaving and cost reduction in the Post-Corona era. ESG management initiates new forms of collaboration across industries and countries while the carbon neutrality goal motivates companies to implement digital cross-border collaboration. New missions and roles of cross-organizational and cross-border collaboration will be defined for 2050 Zero Carbon society. New methods and success stories on eco-friendly and socio-friendly collaboration will contribute to the realization of carbon neutrality.

Information Systems and Information Technology have for a long time played a major role in supporting sustainability goals and a substantial research strand on “green IS/IT” has existed for many years. However, motivated by observing positive side effects caused by the COVID-19 pandemic, such as positive ecolocical effects through less travel and more virtualized collaboration, we believe that there are many more and not yet understood effects IT and IS can have on ecological and social sustainability goals, particularly through the virtualization of communication and collaboration. While there are obvious advantages, there are also downsides and challenges which require research activities to detect, understand, and mitigate those.

Integration of people, processes, and information systems across organizational and national borders enables productive teamwork towards achieving mutual goals. People involved should be motivated to enter into collaborative projects and interactions, which lead to satisfaction and performance. Perception of value, trust, and commitment among participants and stakeholders fosters quality in collaboration. With progress in globalization and AI technology, many of these collaborations are increasing across widely dispersed organizations and national borders. Cross-system integration and intelligent collaboration technologies play crucial roles and often decide about IS project success or failure. Additional complexity and dynamics evolve through digital innovation activities in which collaborators, across organizations, countries, and cultures, work on new digital products, services, and business models – changing the way to shape innovation success. Digital collaboration has been increasing by organizations seeking to gain competitive advantage by lowering costs, increasing knowledge, and reaching new customers. Perceived value serves as a stimulus for further growth.

Possible contributions regarding the cross-organizational and cross-border collaboration may include, but are not limited to the following:

  • Eco-friendly or Socio-friendly collaboration for ESG management
  • Cross-organizational collaboration cases for carbon neutrality
  • Processes of international and inter-organizational collaboration in IS/IT projects and operations
  • Effects of collaboration on IS/IT performance
  • Conceptual frameworks of IS/IT collaboration across organizations and borders
  • Motivating factors for IS/IT collaboration
  • Methodologies for studies of IS/IT collaboration
  • Development and validation of IS/IT collaboration instrument
  • IS/IT collaboration studies at country, industry, firm, project, team or individual level
  • Comparative cross-country research on IT/IS collaboration
  • Industry-specific and organization-specific case studies on IT/IS collaboration
  • Managing IS/IT outsourcing and offshoring/nearshoring relationships
  • Out-tasking and crowdsourcing in IT/IS contexts
  • Cross-organizational and international IS/IT project management
  • Multinational teams and their cultural and leadership factors
  • IT/IS-enabled Open Innovation approaches
  • Cross-organizational innovation approaches and processes
  • Collaboration cases on Big-Data analytics for creating customer value
  • Social collaboration using online social networks across countries
  • Sustainability enabled and facilitated through digital collaboration
  • The role of digital collaboration for impact sourcing and other forms of sustainability-focused outsourcing engagements
  • SME case studies on social innovations and sustainability
Minitrack Co-Chairs:

Ilsang Ko (Primary Contact)
Chonnam National University

Daniel Beimborn
University of Bamberg

Cybersecurity and Artificial Intelligence (AI) are key domains whose intersection gives great promises and poses significant threats. The nature of AI and Cybersecurity encompasses many domains. While some perspectives are narrowly focused (e.g., point solutions inside an organization identifying threats in a network stream), many are very sweeping and are either collaborative or tackle collaborative domains (e.g., identifying intentional or unintentional cybersecurity threats propagating across collaboration platforms). Indeed, enhancing our capabilities in AI for cybersecurity has been noted as a key national priority by significant entities such as the National Science Foundation, the National Science Technology Council, and the National Academies of Science.

Implementing AI and Cybersecurity can also be internal to an organization or broadly collaborative (e.g., organizations working and competing together in adversarial AI research). Conversely, cybersecurity for AI has point solutions internal to organizations and broadly collaborative domains (e.g., collaboratively protecting from adversarial examples in shared data sets or shared models with multi-organizational transfer learning). However, the range and scope of how AI could be used for cybersecurity and how to improve the cybersecurity of AI remain relatively understudied yet critically important areas.

This minitrack seeks to focus on AI and Cybersecurity that works in broader domains, collaborative inter- organizational realms, shared collaborative domains, or with collaborative technologies. The threats being addressed with and/or to AI are intended to be sweeping in nature and of significant societal impact. Broadly, the topics and research areas include, but are not limited to:

  • Novel applications of Artificial Intelligence, Machine Learning, and Deep Learning in Cybersecurity as it pertains to multi-user/multi-organizational collaborative domains and/or systems
  • Adversarial AI/Machine Learning Applications in Cybersecurity that collaboratively span organizations or apply to collaborative systems (i.e., malware, phishing, or any applicable threat/identification domain)
  • Protecting AI that is used collaboratively (i.e., shared data sets, shared models, shared applications) or spans collaborative domains from cybersecurity threats (i.e., adversarial examples, trojans, model inversion)
  • Using AI to protect AI in any appropriate wide-reaching setting
  • Novel Collaboration approaches to leveraging and protecting AI in the cybersecurity domain
  • Sharing/disseminating tools, techniques, and applications of AI in Cybersecurity and Cybersecurity for AI that applies to the overarching theme of this minitrack
Minitrack Co-Chairs:

Mark Patton (Primary Contact)
University of Arizona

Hsinchun Chen
University of Arizona

Sagar Samtani
Indiana University

Hongyi Zhu
University of Texas at San Antonio

Collaboration technologies are a fundamental cornerstone of modern work environments and hold many promising avenues for further development. The pace of change looks only to accelerate as the metaverse, and extended reality technology promise new possibilities for both in person and remote collaboration. However, successful collaboration is often difficult. Groups and teams often need to overcome both physical and metaphorical distance. Other challenges include groupthink, dominance, lack of efficiency, lack of focus, overwhelming information, differing motivations, and uncertainty.

The challenge for researchers and practitioners alike is to design sustainable processes and systems within and between organizations that allow people, groups, teams and machines to collaborate successfully. This challenge has many dimensions that cross technical, behavioral, social, emotional, economic, and political boundaries. This mini-track invites papers that address the theory, design, development, deployment, and evaluation of collaboration processes and systems within and between organizations, groups, teams, and machines.

Topics to be discussed in this minitrack include, but are not limited to:

  • Evaluations and empirical studies involving extended reality technologies (augmented reality, virtual reality, mixed reality) and their use for collaboration
  • Theoretical foundations and design methodologies for collaborative work practices and technologies
  • Processes and tools for establishing and maintaining shared focus and shared mental models over time and when working in remote environments
  • Processes, technologies, and theoretical breakthroughs to improve and speed up shared sense-making
  • Facilitation methods, techniques, patterns, and procedures to improve (a)synchronous collaboration between co-located and distributed people, teams, or groups
  • Assessment models and methods for team collaboration and performance
  • Design, codification and reuse of work practices and pattern languages for group collaboration
  • Design and building of automated virtual agents to participate in online collaborations (e.g., ChatOps)
  • Exemplary use cases in various fields of application that refer to collaborative work practices
  • Approaches for a new division of labor (including hand-offs) in reference to the task design and capabilities of AI and humans
  • Approaches for increasing user acceptance of collaboration systems with AI components
  • Usage of Low-code approaches for developing collaboration technologies
  • Approaches for detecting and using social signals in different modalities (e.g., voice, language, vison) for the design of technologies to support collaboration
  • Usage of generative AI collaboration technologies
Minitrack Co-Chairs:

Philipp Alexander Ebel (Primary Contact)
University of St. Gallen

Eva Bittner
University of Hamburg

Sarah Oeste-Reiß
University of Kassel

Edona Elshan
University of St.Gallen

Robots are increasingly being adopted in private and public spaces, leading to a proliferation of human-robot interactions in the home, workplace, and other public settings. Robot interactions with humans across an array of roles and settings pose interesting questions to scholars in various fields such as information systems, robotics, psychology, and sociology. Interaction with robots is distinct from that with other artificial intelligence (AI)-enabled technologies in that robots have a physical body that allows them to manifest physical actions. This distinguishes interactions with robots from interactions with disembodied AI agents, such as voice agents like Siri by Apple and Alexa by Amazon. Thus, research on human-robot interaction can differ significantly from that of human interaction with disembodied AI agents.

This minitrack welcomes research papers that explore human‒robot interaction and robot design at any level (i.e. individual, team, organizational, and societal). This minitrack would also cover human‒robot interaction as much as possible beyond the notion of “robots as teammates.” Thus, we would encourage submissions that examine many facets of interactions in any context (e.g., homes, work, and public services) and role (e.g., companion, co- worker, boss, and adversary).

Topics of interest include, but are not limited to, the following:

  • Promoting cooperative and collaborative interaction with robots
  • Examining uncooperative and adversarial human interactions with robots
  • The role of adoption and appropriation in human-robot interactions
  • Empirical studies examining the cognitive, psychological, emotional, and social aspects of human‒robot interactions
  • The impact of haptic feedback and touch on human‒robot interaction
  • The role of robot attractiveness on human‒robot interaction
  • Ethics on human‒robot interactions
  • Social-emotional models of human‒robot interaction
  • Theoretical frameworks for human‒robot interaction
  • Case studies of human‒robot interaction
  • Design implications for robot interactions at home, work and public spaces
  • Human-oriented practices that promote human‒robot interactions
  • New methodological approaches to studying human‒robot interactions
Minitrack Co-Chairs:

Sangseok You (Primary Contact)
Sungkyunkwan University

Lionel Robert
University of Michigan

Diffusion (adoption, implementation, and utilization) of collaboration technologies has been investigated in many countries and regions around the globe. While many of the research initiatives have been undertaken in Western Europe and North America, they have been scarce in developing regions like Eastern Europe, Asia, Africa, and Latin America. The diffusion of collaboration technologies in these regions is on the rise as globalization drives inter and intra-country collaboration intensity within and across organizations. In many developing countries, synchronous and asynchronous computer support for team members (co-located or virtual) is being enhanced by handheld mobile devices in communities of practice and social media environments. Moreover, the use of digital technology enabled tools for collaboration and communication, has become more popular in the age of new technologies. Emerging trends like Metaverse, provide opportunities to further enhance IT enabled collaboration for development.

We would like to invite the authors to submit their research from theoretical, technological, social, psychological, behavioral, and design science perspectives. Research deploying different theoretical lenses could focus on process and system design, methods, modeling, and techniques in addressing various aspects of IT enabled collaboration for development.

The minitrack focuses on a wide range of topics including but not limited to:

  • IT enabled collaboration in emerging context (e.g. Metaverse) in developing regions
  • Collaboration technology diffusion case studies in education, business, government, and healthcare organizations in developing regions
  • IT enabled cross-cultural and intra and/or inter-organizational collaboration in developing regions
  • Global, virtual, distributed, blended, and face-to-face IT enabled collaboration for development at the team and organizational level
  • Emerging issues in collaboration technology diffusion for development
  • Deployment of mobile technologies for collaboration in developing regions
  • Group decision making, negotiation, facilitation, and communication technologies for development
  • Trust, privacy, security issues in IT enabled collaboration for development
  • Social, behavioral, psychological, and technical factors influencing IT enabled collaboration for development
  • Information systems, technologies, theories, processes, methods, or models that could be transferred and applied from developed regions to developing regions
Minitrack Co-Chairs:

Xusen Cheng (Primary Contact)
Renmin University of China

Xiangbin Yan
University of Science and Technology Beijing

Deepinder Bajwa
Western Washington University

Scientists have started to adopt more open approaches to their research projects, which has seen open science (OS) growing in prominence in recent years, and is challenging this traditional scientific process used in information systems (IS) research. OS refers to making scientific knowledge freely available to the public, where open practices are becoming a requirement to be eligible for funding from most competitive funding schemes.

OS consists of different concepts such as open access (making published research articles freely available under an open access licence); open data (requiring researchers to make research data publicly available with their submitted papers); open methodology (sharing methodological details, such as data collection and analysis processes); open artefact(s) (making artefacts accessible online for free, with an open license to use,modify and reuse); and open peer review (where researchers and reviewers know each others identities). The impact of OS can be seen through the use of registered reports (RR), which facilitate a form of peer review that breaks studies into two stages: (i) study pre-registration – authors identify a relevant problem and detail their research design, which is submitted for (open) peer review and feedback, (ii) improved research execution – the study is completed with the improved design.

The objective of this minitrack is to give researchers the opportunity to present novel and innovative ways that they are conducting research using OS concepts outlined above. In doing so we aim to push the boundary of how IS research is conducted and communicated to the community. Indeed, OS should be more transparent, with greater potential to verify, replicate, and freely share the results. Such openness should also provide a platform for creating research that demonstrates proof-of-use as the community strives to become more relevant to practice. We therefore suggest that the community should strongly engage with OS, and in order to do so, we are looking for both conceptual and empirical papers that either further our understanding of OS in IS research, or studies that practice it.

Thus, we invite papers that focus on, but is not limited to, any of the following topics around open science in IS research:

  • Philosophical considerations
  • Ethical implications
  • Methodological considerations
  • Policies of open science
  • Papers that practice one (or more) concepts of open science in their study
  • Registered reports in IS research (can be either stage 1 or stage 2)
  • Understanding of different platforms/tools/technologies for practicing open science
  • Success/Failure cases that have arisen while practicing open science
  • How we can improve or innovate open science practices
  • Benefits of practicing open science
  • Challenges and/or problems with practicing open science
Minitrack Co-Chairs:

Cathal Doyle (Primary Contact)
Victoria University of Wellington

Yi-Te Chiu
Victoria University of Wellington

Tadhg Nagle
University College Cork

Markus Luczak-Roesch
Victoria University of Wellington

The proliferation of collaborative and connected systems, including digital tools and platforms that facilitate collaboration, information sharing, and communication among multiple users, has dramatically transformed how we interact, work, and live. Integrating Artificial Intelligence (AI) and other intelligent technologies have brought about new levels of automation and intelligence, resulting in the emergence of AI-enabled collaborative and connected systems. This integration has opened new possibilities for human-machine collaboration, yet it has also raised important ethical, legal, and societal concerns, which necessitate the responsible design, development, and use of these systems.

The primary objective of this minitrack is to provide a forum for scholars and practitioners to present their research and engage in discussions on the responsible design, development, implementation, management, and use of AI-enabled collaborative and connected systems. The minitrack aims to address the current knowledge gaps and challenges posed by integrating AI and other intelligent technologies in collaborative and connected systems, particularly in the context of human-machine collaboration.

The scope of this minitrack encompasses, but is not limited to, the following areas of inquiry:

  • Assessment of the social, ethical, and societal impacts of AI-enabled collaborative and connected systems
  • Privacy and security considerations in the design and development of AI-enabled collaborative and connected systems
  • Human-centered design principles for the development of AI-enabled collaborative and connected systems
  • The impact of AI on human-machine collaboration and its implications for work and employment
  • Explainability and transparency in AI-enabled collaborative and connected systems
  • The role of responsible governance in the use and regulation of AI-enabled collaborative and connected systems
  • Responsible AI and machine learning in the development of AI-enabled collaborative and connected systems
  • Addressing bias and fairness in AI-enabled collaborative and connected systems
  • Cross-cultural considerations in the design and deployment of AI-enabled collaborative and connected systems
  • The potential impact of AI-enabled collaborative and connected systems on the future of work and innovation
  • The role of AI-enabled collaborative and connected systems in promoting social good and sustainability in a digital age
  • Ethical and legal considerations in responsible innovation in AI-enabled collaborative and connected systems
  • Best practices in responsible innovation in human-machine collaboration
  • Approaches to measuring and evaluating the effectiveness of responsible innovation in AI-enabled collaborative and connected systems.

High quality and relevant papers from this minitrack will be selected for fast-tracked development towards Internet Research. Selected papers will need to expand in content and length in line with the requirements for standard research articles published in the journal. Although the minitrack co-chairs are committed to guiding the selected papers towards final publication, further reviews may be needed before a final publication decision can be made. Internet Research (IntR) is an international and refereed journal that is indexed and abstracted in major databases (e.g., SSCI, SCI, ABI/INFORM Global), with an impact factor 6.353 in 2021.

Minitrack Co-Chairs:

Bo Sophia Xiao (Primary Contact)
University of Hawaii at Manoa

Chee-Wee Tan
Copenhagen Business School

Kaveh Abhari
San Diego State University

There are new advances in technology on an almost daily basis. For example, we are currently seeing an explosion in the use of chatbots. These developments in AI and robotics technology are having a huge impact on social robots, as these agents evolve from automated devices to highly autonomous partners. These social robots are ready to enter office and service environments such as hotels, retail and banking, where they can interact with customers. The potential of social robots has always been great, but groundbreaking technological developments and the combination with AI multiply this potential. As a result, their integration is rapidly changing the landscape of business and services.

In contrast to other forms of technology, social robots have what is known as automated social presence, which is why customers tend to treat them as social entities rather than as machines. In addition, social robots are increasingly developing social skills that enable them to recognize human emotions and to behave in human-like ways. The wide range of benefits that social robots can offer may be the reason why they have attracted so much and growing interest from the research community.

We welcome exciting contributions that extend our understanding of social human- robot interaction by addressing issues that sharpen and guide our view of the future. Business and service environments are of particular interest. With these findings, we aim not only to advance theoretical knowledge on the topic but also to help practitioners and organizations. The following questions may be addressed by researchers, but are not exhaustive:

Topics of interest include, but are not limited to:

  • How will the role of social and service robots evolve in an era of breakthrough innovations in the field of AI?
  • How can new theories and constructs help to understand the implications of introducing service robots in business and service environments (such as task sharing between social robots and humans)?
  • What are innovative methods in social human-robot interaction research?
  • How can social robot technology and AI-based applications be fruitfully integrated into human-robot interaction (for example, speech or emotion recognition)?
  • How can service robots have an impact on businesses and service industries through improvements in efficiency and effectiveness?
  • What are innovative approaches to social robot applications in business and service contexts?
  • How can we address the dark side of social robots (such as blame attribution or security breaches)?
  • How can we understand privacy and protective mechanisms in human-robot interaction?
  • What are ethical and moral considerations involved in human-robot interaction?
  • How can emotional engagement with social robots be promoted, for example through individualized design approaches?
  • What are sustainable applications for service robots?
Minitrack Co-Chairs:

Ruth Stock-Homburg (Primary Contact)
Technical University Darmstadt

Lea Heitlinger
Technical University Darmstadt

While geographically distributed collaboration has been the subject of academic research for decades, the entire world coping with the aftermath of the COVID-19 pandemic has accelerated interest in this critically important area of research and practice. Today, virtual work, as well as hybrid work which combines remote and onsite work, with different blends of synchronous and asynchronous work, is the new norm. Employees commonly demand by default more workplace flexibility, which introduces new challenges in relation to leadership, coordination and knowledge-sharing, organizational learning and innovation, as well as organizational culture.

Today, research on virtual work does not only need to account for the general characteristics of virtual work, including technology, distance, and commonly cultural differences, but also a shift in employees’ mindsets resulting from the pandemic.  More work is needed to inform both theory and practice on how to navigate this new arena of virtual and hybrid work. The implications are profound from every perspective – including, economic, environmental, social, efficiencies. Research on virtual teams, distributed collaboration, telework, hybrid work, organizations and networks of relationships is necessarily multi-disciplinary to address the key challenges collaborators face, while accounting for the complex context in which such collaborations occur.

Thus, we encourage submissions that may inform practice and research in distributed collaboration and telework through a variety of academic lenses and research that highlight methodological issues and innovation in the study of virtual teams, organizations, and networks. This minitrack invites papers that offer direct and indirect insights into the operation of virtual teams, distributed collaboration, telework and hybrid work, organizations, and networks, including research in the vein of computer supported collaborative work (CSCW), computer supported collaborative learning (CSCW), human computer interaction (HCI), and social, organizational and knowledge networks. The topics for this minitrack include but are not limited to:

  • Spatial and temporal separation and its effects on collaboration
  • Coordination in collaboration across multiple boundaries
  • Team knowledge networks quantitative and visual analysis
  • Influence of technology and social structure on hybrid work
  • Antecedents of employee workplace presence and organizational commitment in hybrid work
  • Impacts and consequences of telework and hybrid work on organizational and network outcomes
  • Team dynamics and distributed leadership in hybrid work
  • Cultural differences in perception of time
  • Conflict management across cultures
  • Project management styles and differences across cultures
  • Differences in language understanding and its effects on collaboration
  • Power distance and its effects on collaboration
  • Uncertainty (risk) avoidance and its effects on collaboration
  • Diversity, equity, inclusion and sustainability management in multicultural (virtual) teams
  • eLeadership, including leading remote work and virtual teams
  • Multiteam systems
  • Social loafing in virtual teams
  • Personality and its role in telework or virtual teams
  • Crosscultural training
  • Virtual team collaboration and innovation
  • Emotion in virtual teams
  • Relationship building in virtual teams or hybrid work
  • Collaboration and communication processes and tools
  • Differences between academic and nonacademic virtual teams
  • Social Network Theory and Analysis
  • Methodological advances on network science and graph analytics
  • Coordination and dependency networks
  • Identifying multilevel influences on virtual teams, organizations, and networks
  • Science of team science, virtual collaboration in scientific teams

A fast track publication opportunity with Data & Policy published by Cambridge University Press has been secured for selected papers accepted to this minitrack. Data & Policy is a peer-reviewed, open access journal dedicated to data science and governance.

Minitrack Co-Chairs:

Derrick Cogburn (Primary Contact)
American University

J. Alberto Espinosa
American University

Mark Clark
American University

Emma Nordback
Hanken School of Economics