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TRACK CHAIRS

Gert-Jan de Vreede

Stevens Institute of Technology
School of Business
1 Castle Point
Hoboken, NJ 07030
GJ@stevens.edu

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
nunamaker@cmi.arizona.edu

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.

Papers from HICSS-57

The 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 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.

The use of advanced technologies in learning environments also invites new questions, applications, and research methodologies: How do technology integration and remote teaching augment how people learn? 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?

This minitrack encourages research contributions that deal with learning theories, teaching tools, 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. 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). However, learning and the Collaboration Systems and Technology settings 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
obscrivn@iu.edu

Maarten de Laat
University of South Australia
Maarten.DeLaat@unisa.edu.au

Andy Nguyen
University of Oulu
andy.nguyen@oulu.fi

James Scrivner
Butler University
jscrivner@butler.edu

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):

  • Adversarial behaviors: Cybermobbing, cyberbullying, digital vigilantism, doxing, hacktivism, human flesh search engine, online extremism, cyberterrorism, fake news, cyber harassment, trolling, hate speech, shaming
  • Adversarial strategies and tactics: Strategic information operations, information warfare, disinformation campaigns, coordinated inauthentic behavior, astroturfing, sockpuppeting
  • Consequences and drivers of adversarial behaviors: Network polarization, echo-chambers, filter bubbles
  • Intervention design: (Algorithmic) content moderation, censorship, deplatforming, content monitoring, policy design, platform governance, platform (self) regulation, privacy protection

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 5.90 in 2022.

Minitrack Co-Chairs:

Christy M.K. Cheung (Primary Contact)
Hong Kong Baptist University
ccheung@hkbu.edu.hk

Marten Risius
University of Applied Sciences Neu-Ulm
marten.risius@hnu.de

Matthew K.O. Lee
City University of Hong Kong
cbmatlee@cityu.edu.hk

Christian Wagner
City University of Hong Kong
c.wagner@cityu.edu.hk

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. Topics of interest include:

  • 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 work-life 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
tdevreede@usf.edu

Xusen Cheng
Renmin University of China
xusen.cheng@ruc.edu.cn

Dominik Siemon
LUT University
Dominik.Siemon@lut.fi

The advent of the Internet, social media, distributed databases, and mobile devices has led to an exponential growth in data, both structured and unstructured. This diverse data holds substantial business value, encompassing customer information, superstore and online transactions, competitive intelligence, labor market insights, and development trends across various industries to name a few. Real-time data from sources like Twitter, Reddit, and Facebook adds an additional layer of complexity, requiring instant processing using Artificial Intelligence (AI), Big Data (BD), machine learning, data streaming technology, and visual analytics.

Despite the potential benefits, many organizations either lack the necessary tools or fail to grasp the full value of their available data. This minitrack seeks to address these challenges by offering a platform for theoretical, conceptual, and applied discussions on the integration of AI and BD. This minitrack will attempt to gain insights into utilizing data to increase sales, identify opportunities, outperform competitors, enhance products and services, recruit talent, improve operations, and make informed forecasts.

The main objective of this minitrack is to provide organizations with a comprehensive understanding of leveraging AI and BD for innovative, collaborative, and sustainable development, ultimately facilitating effective decision-making. As the digital landscape evolves rapidly, the minitrack aims to bridge the gap between the wealth of available data and its practical utilization within organizations.

This minitrack is designed for researchers, professionals, and practitioners interested in maximizing the potential of AI and BD for organizational growth. It attempts to gain valuable insights into theoretical frameworks, practical applications, and collaborative approaches, equipping them to make informed decisions in a dynamic, data-driven environment. The minitrack provides a platform for in-depth discussions on the transformative power of AI and BD in shaping the future of organizations. This minitrack invites original research, case studies, and practical implementations focused on, but not limited to:

  • Theoretical foundations of AI and BD for organizational, collaborative, and sustainable development.
  • Practical applications of AI and BD in enhancing products, services, operations, and collaboration.
  • Collaborative approaches to data-driven decision-making using AI.
  • Historical and real-time data processing using AI, machine learning, and visual analytics.
  • Overcoming challenges in implementing AI and BD for collaborative and sustainable development.
  • Tools and technologies for effective utilization of available data.
  • Supporting organizational creativity, innovation and decision-making using AI.
  • Designing intelligent information systems and build decision support systems.
  • Using AI and BD tools and solutions to achieve innovative, collaborative, and sustainable development of organizations.
  • Challenges and opportunities of applying AI and BD for innovative, collaborative, and sustainable development of organizations.
  • State-of-the-art practical approaches, solutions, methods, and tools including machine and deep learning to foster innovative, collaborative, and sustainable development of organizations by using of AI and BD.
  • Technological and human requirements for effective and efficient AI and BD operations.

Minitrack Co-Chairs:

Celina Olszak (Primary Contact)
University of Economics in Katowice
celina.olszak@ue.katowice.pl

Jozef Zurada
University of Louisville
jozef.zurada@louisville.edu

Pawel Weichbroth
Gdansk University of Technology
pawel.weichbroth@pg.edu.p

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 actors and variety of resources. This inter- and intra-organizational complexity has the potential to create greater value as it attracts and connects 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. Prior contributors highlighted the role of technology across multiple levels of collaboration, from consumer collectives to manufacturing networks to entrepreneurship ecosystems. We seek a wide variety of 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
  • Collaboration Practices and Capabilities
  • Innovation Diffusion through Collaboration Practices
  • Value Cocreation and 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
  • Institutions and Institutional Arrangements/Logics that Support/Hinder Collaboration
  • Emergence of Collaboration in Market-based Ecosystems
  • (Re)Emergence of Markets via Collaboration
  • Antecedents and Consequences of Collaboration in Markets
  • The Role of Devices and Data in Collaboration

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
melissa.akaka@du.edu

Hope Jensen Schau
University of Arizona
hschau@arizona.edu

Stephen L. Vargo
University of Oklahoma
sv@ou.edu

John Sebesta
University of Denver
john.sebesta@du.edu

Many intelligent agents (e.g., chatbots, social robots, virtual assistants, advice-giving systems leveraging AI) are being incorporated into teams, organizations and daily life. These varied types of AI use text, voice and audio, or other environmental sensors to retrieve information from the user, process it, and respond appropriately. Historically, these agents have helped individuals find directions, assist in ordering goods or services on a website, or recommend relevant sources in an otherwise unmanageable pool of information.

With the technological progress of AI, these agents become smarter and more autonomous. Humans are increasingly using these intelligent agents for creative and collaborative tasks (e.g., create royalty-free music with beatoven.ai, improve programming code with chatGPT, creating summaries of interaction logs with recommendations with Google Bart, etc.). While more autonomous intelligent agents present a potential solution for many information-processing and decision-making problems, it is not fully understood how humans will in fact interact, utilize, and are impacted by them in ways different from traditional human-to-human collaboration. As intelligent agents advance and become more mainstream, social norms will emerge that will offer a diverse user group various benefits. however this might also lead to unintended (negative) consequences. Hence, we need to explore new dimensions of these new forms of human-machine collaboration.

This minitrack will examine the emergence of this new type of collaborating, intelligent, autonomous agents and their implications for individuals, teams, organizations, and crowds. We seek papers that address the social, technical, behavioral, attitudinal, emotional, or managerial aspects of intelligent agents in the workplace, particularly in collaboration settings. The unit of analysis can be individuals, teams, organizations, or crowds. All kinds of research is welcome including but not limited to quantitative, qualitative, conceptual, or design-oriented research. This minitrack focuses on:

  • Human collaboration with artificial agents and intelligent systems in teams, crowds, and with individuals
  • Effects of ChatGPT and/or other generative AI 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
  • 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
  • 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 on phenomena of interest, such as trust, autonomy, control, satisfaction or performance in human-AI teams
  • Design features for automated teammates that improve human collaboration with them
  • Studies of group dynamics and group process when an artificial teammate is on the team
  • Studies on task delegation and/or knowledge augmentation when collaborating with intelligent systems
  • Neurophysiological approaches to assess interactions with intelligent systems including eye-tracking (e.g. pupillometry), galvanic skin response (GSR), and electroencephalogram (EEG)

Selected authors of the minitrack will be invited to participate in a BISE fast-track option. To qualify, authors must extend their manuscripts by approximately 30%, incorporating new analysis, additional theorizing, extended background, and extra data. The revised submissions will undergo a review process with new reviewers, and the minitrack chairs will serve as Associate Editors (AEs). The initial HICSS review will count as the first review round. However, receiving an invitation for the fast-track does not guarantee publication.

Minitrack Co-Chairs:

Isabella Seeber (Primary Contact)
Grenoble Ecole de Management
isabella.seeber@grenoble-em.com

Joel Elson
University of Nebraska at Omaha
jselson@unomaha.edu

Matthias Söllner
University of Kassel
soellner@uni-kassel.de

Ryan Mullins
Google Research
ryanmullins@google.com

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).

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 build on our successful initial track last year. It will 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 mini-track
Minitrack Co-Chairs:

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

Hsinchun Chen
University of Arizona
hsinchun@email.arizona.edu

Sagar Samtani
Indiana University
ssamtani@iu.edu

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

In the evolving landscape of work environments, collaboration technologies stand at the forefront of innovation, particularly in development. The emergence of low-code platforms and generative AI has ushered in a new era of efficiency and accessibility in application creation, empowering teams to collaborate more effectively and bring solutions to market faster. At the same time, augmented reality (AR) and metaverse technologies are redefining the paradigms of communication and collaboration, offering immersive experiences that enhance understanding and engagement among team members, regardless of their physical locations.

The challenge for researchers and practitioners now extends to designing sustainable processes and systems that not only support collaboration within and between organizations but also leverage the unique capabilities of low-code platforms, generative AI, and immersive communication technologies like AR and the metaverse. This interdisciplinary endeavor traverses technical, behavioral, social, emotional, economic, and political domains, aiming to foster environments where collaboration thrives through innovative technologies. This minitrack seeks contributions that explore:

  • The integration of low-code platforms and generative AI in software development processes, emphasizing how these technologies streamline collaboration, improve productivity, and democratize software creation
  • The role of AR and metaverse technologies in facilitating immersive communication for collaborative software development, enhancing shared understanding, and bridging physical distances between team members.
  • Evaluation methods for collaborative tools and practices in software development that incorporate generative AI and immersive technologies, assessing their impact on team dynamics, project success, and innovation.
  • Design and implementation of automated virtual agents in collaborative platforms, including their application in software development environments enhanced by AR and metaverse technologies.
  • Frameworks for maintaining shared focus and mental models in software development projects, especially when leveraging low-code platforms, generative AI, and immersive communication tools.
  • Strategies for fostering user acceptance and engagement with collaboration systems that integrate AI, low-code solutions, and immersive technologies.
  • Research on the division of labor between humans and AI in the context of development, exploring how task design can be optimized through the capabilities of AI, low-code platforms, and immersive communication technologies.
  • Case studies and theoretical analyses on the use of social signals in enhancing collaboration within software development teams, facilitated by advanced communication technologies like the metaverse and AR.
Minitrack Co-Chairs:

Edona Elshan (Primary Contact)
Vrije Universiteit Amsterdam
e.elshan@vu.nl

Eva Bittner
University of Hamburg
eva.bittner@uni-hamburg.de

Philipp Alexander Ebel
University of St. Gallen
philipp.ebel@unisg.ch

Sarah Oeste-Reiß
University of Kassel
oeste-reiss@uni-kassel.de

Cross-organizational and cross-border collaboration makes firms achieve respectful innovation through their business partners beyond countries. Entrepreneurship and talent management are essential parts of innovative companies. Cases on intelligent collaboration using big-data analytics, AI development, and ChatGPT stories show potential approaches and methods for the firm’s future application development. Digital capabilities and their contributions on firms’ sustainability goals are open to academics and practitioners around the world. Empirical research on digital capabilities with collaboration, and successful case studies on entrepreneurship and new business models are enough for invitation in terms of respectful innovation beyond industries and respectful translation over country boundaries.

Integration of people, processes, and information systems across organizational and national borders enables productive teamwork toward achieving mutual goals. Perception of value, trust, and commitment among participants and stakeholders fosters quality in collaboration. Cross-system integration and intelligent collaboration technologies play crucial roles in 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:

  • Collaborative digital innovation with big-data analytics, AI applications, and Deep Learning
  • Collaboration and digital capabilities on firm’s sustainability goals
  • Digital capabilities, entrepreneurship, talent management on respectful innovation
  • Case studies on global entrepreneurial talent management and respectful translation
  • Eco-friendly or socio-friendly IS/IT 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

Accepted papers will receive an opportunity of fast-track reviews for the Asia Pacific Journal of Information Systems.

Minitrack Co-Chairs:

Ilsang Ko (Primary Contact)
Chonnam National University
isko@chonnam.ac.kr

Daniel Beimborn
University of Bamberg
daniel.beimborn@uni-bamberg.de

The development of Artificial Intelligence (AI) has transcended its initial purpose of enhancing human cognitive functions. Especially, the recent progress in digital technology has transformed AI algorithms into social entities that closely emulate human intelligence and even human appearance, which are called “AI-powered digital humans” or simply “digital humans.” This advancement has enabled interactions with AI applications that closely resemble human beings, creating the illusion of conversing with real individuals rather than AI algorithms or digitally-animated characters.

Consisting of a human-like appearance (as their form realism) and intelligence (as their behavioral realism), the AI-powered digital humans are equipped with interactive capabilities that significantly enhance the quality of human-AI encountering processes. This evolution has led to more enriched and personalized experiences for human users in various AI application contexts such as AI chatbots for customer care, AI recommenders for e-commerce, AI consultants for financial investment, and AI doctors.

Among the various industries adopting AI and digital human technologies, the entertainment industry is one of the most rapidly and broadly transforming industries with a variety of AI and digital human applications such as AI-generated celebrities, fashion models, movie characters (both virtual and real), content creators, artists, etc. These emerging phenomena driven by AI and digital humans represent a fundamental shift in the creation, consumption, and user engagement in the entertainment industry. However, what technical, social, and individual factors lead to certain outcomes and how, why, and where these outcomes happen at various levels (e.g., individual, service, firm, and industry levels) is not yet known.

This minitrack aims to explore the convergences of AI and digital human technologies, and their impacts on the entertainment sector, especially in terms of the creation, consumption, and user engagement of AI and digital humans. The specific focus is on exploring the combined potential, challenges, and implications that arise from the intersection. It seeks to:

  • Investigate the impact of digital humans, including but not limited to virtual entertainers, virtual influencers, VTubers (i.e., Virtual YouTubers), avatars, AI-driven characters, etc., on audience engagement metrics like viewership, interaction rates, and emotional responses across various entertainment platforms. This should also encompass the psychological and sociological effects, such as the sense of social presence, parasocial relationships, and the blending of real and virtual identities.
  • Examine how businesses and marketing agencies employ digital humans as brand ambassadors, influencers, and spokespersons in advertising campaigns. Assess the effectiveness of these strategies in reaching and engaging target audiences successfully.
  • Address the ethical and legal issues related to the creation and use of digital human representations in the entertainment industry. This includes exploring concerns related to intellectual property, privacy, the digital rights of creators and stakeholders, manipulation, and potential unexpected outcomes in human-computer interactions.
  • Investigate the cultural and artistic importance of digital human expression by examining the intersections of digital art, performance, and cultural representation. This research should focus on how digital humans are created and depicted in various artistic mediums and their role in shaping contemporary cultural narratives and identities.
  • Investigate the evolving nature of creative collaboration between AI systems and human artists in the production of entertainment content, including music, visual arts, literature, etc.
  • Explore the application of advanced AI algorithms, such as deep learning, reinforcement learning, and natural language processing, in modeling and simulating realistic human behaviors in digital humans. This exploration should span various contexts, including but not limited to gaming, music, fashion, virtual assistants, and AI-driven avatars.
  • Delve into the potential of humans existing as digital inhabitants in virtual worlds and immersive environments, along with their virtual collaborations. This exploration should represent actual individuals in the real world and their interactions in these digital spaces.
  • Delve into the technological advancements and challenges surrounding interactions with AI-driven digital humans. This explores innovative approaches to real-time processing, strategies for handling substantial data volumes, and efficient management of diverse computing resources to enable seamless interactions with AI-driven digital humans.
Minitrack Co-Chairs:

Joonghee Lee (Primary Contact)
Appalachian State University
leej12@appstate.edu

One-Ki Daniel Lee
University of Massachusetts Boston
daniel.lee@umb.edu

Soo Il Shin
Kennesaw State University
sshin12@kennesaw.edu

Jin Sik Kim
University of Tennessee at Chattanooga
jinsik-kim@utc.edu

Transforming nowadays linear economy towards a sustainable and circular one that addresses the current ecological and social challenges as well as global resource scarcities, requires a broad cross-industry and cross-societal approach. The transition process requires not only a deep understanding of the ecological and technical domains, but shows as well the essential necessity of participation concepts and attempts on an ecosystem level. Therefore, stakeholders across different domains must cooperate on different levels to enable the transition from the current linear economy with its “take, make, use and waste” conduction towards more ecological and social practices. Only with a fundamental culture change on an economic, social and governmental level the extension of product life, global waste reduction and environmental sustainability and stability can become reality.

Although the Stakeholders on their own, especially governments and businesses, are major players in the accomplishment of such profound transition processes, a broader and domain overarching engagement is necessary to close the present gap in stakeholder interaction and achieve collaborative and sustainable systems on a new level. Therefore, different stakeholder approaches must interlock to create synergies which are benefitting the economic and social system as a whole. Because of those relations, collaborating systems must take various participating entities into account, which extend the mere view of hard- and software components and address the specific needs and demands. These reach beyond the technological and economic domain and include for example personal and social challenges as well as the cohesion between these influence factors. Lastly, the trade-off of digitized solutions must be considered when designing such systems to achieve the most suitable outcome in a collaborative system in terms of safety and responsibility.

Digital innovations in association with social development can be viewed in this context as key enabler, allowing interconnectedness over system and domain boundaries and enabling technological milestones like smart cyber-physical systems for product lifecycle management and repair/recycling process systems to establish a foothold in the path towards an ethical and fair Circular Economy, which benefits all of its stakeholders. Technological milestones are therefore necessary to open up new collaboration forms and ecosystem designs to achieve a true Circular Economy. Additionally, innovative business models, like Product-as-a-Service (PaaS), pave the way in the direction of sustainable collaboration forms and mindful resource consumption.

The current state of the transition to a Circular Economy shows the great necessity for collaborative systems across domain boarders, in order to reach common goals with regards to shared research and development, economic feasibility of applications, and environmentally and socially acceptable solutions. This minitrack therefore aims for highlighting effective collaborations across various domains and systems to point out challenges and solutions fostering a Circular Economy.

To address the current challenges and advance research in this field, we invite researchers to submit their paper to one of the following research fields:

  • Cooperative cyber-physical systems and digital twins for product monitoring and optimization, control, information transparency and data analytics with emphasis on multi-stakeholder management in the Circular Economy
  • Interdisciplinary, domain overarching sustainable ecosystem design for stakeholder collaborations through digitized solutions
  • Legal and social approaches for safeguarding digitized Circular Economy concepts
  • Collaborative business models for sustainable systems, acceptance & success models for Circular Economy
  • System architectures and platform systems for product sharing, reuse, repair, remanufacture and recycle
  • Artificial Intelligence (AI)-based decision support systems for product lifecycle management, system planning and cross-system collaboration
  • User data privacy protection, data management, transmission protection in sensor systems
  • Automated interconnected collaboration systems for product repair, decomposition and recycling
  • Human/robot cooperation in Circular Economy domains
Minitrack Co-Chairs:

Andreas Rausch (Primary Contact)
TU Clausthal
andreas.rausch@tu-clausthal.de

Carolin Rubner
Siemens AG
carolin.rubner@siemens.com

Agnieszka Szmelter Jarosz
University of Gdańsk
agnieszka.szmelter-jarosz@ug.edu.pl

Marit Briechle-Mathiszig
TU Clausthal
marit.elke.anke.mathiszig@tu-clausthal.de

Human-AI collaborations represent transformative frontiers in today’s technology, where AI systems are designed to work alongside humans and enhance human capabilities. Ranging from computer vision algorithms that can identify patterns in X-rays, to chatbots that provide customer support, to generative AI that can compose music and emails, human-AI collaborations have permeated almost every sector of our society, paving the way for more efficient, innovative, and personalize solutions.

However, the parternership between humans and AI are not only accelerating problem-solving but also raising important ethical considerations on trust, privacy, and security. For instance, holding AI accountable for the misdiagnosis of medical images can be challenging, and chatbots may become toxic when users’ reliance on them reaches a certain threshold. As the field of human-AI collaborations rapidly evolves, it is crucial to identify and address these ethical issues to better leverage the strengths of both humans and AI.

This minitrack is organized to draw attention to a wide variety of ethical issues relevant to human-AI collaborations and to encourage more intensive research on this emergent topic. It welcomes theoretical and empirical research addressing a variety of technical, social, and ethical issues relevant to complex and multifaceted challenges of AI systems. The topics relevant to this minitrack include, but are not limited to:

  • Trust in AI Systems: As AI becomes increasingly capable of performing a wide range of tasks, both user engagement and perceived reliability of AI systems have seen significant growth, thereby amplifying their influence on human decisions and actions. However, given that AI optimization can progress rapidly and in unforeseen ways, ensuring that AI’s objectives and behaviors are consistent with human values and goals poses a considerable challenge. Consequently, it is crucial to conduct thorough research to ascertain when, where, and to what extent human users should place their trust in AI systems and integrate their outputs into decision-making processes.
  • Unintended Consequences of Human-AI Collaborations: Unintended consequences can emerge from the complex interplay between human users and AI. Recognizing these unintended consequences is crucial in guiding the development AI systems toward more equitable, responsible, and beneficial outcomes for society.
  • Transparency and Explainability: AI systems, which are commonly characterized as a “black box”, can be difficult to understand or explain, making it harder to earn human users’ trust. The opacity of AI systems has led to a growing need for research on methods to increase the transparency and explainability of AI systems.
  • Bias and Fairness: AI systems can perpetuate and amplify biases present in the data and the computation architecture 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 AI systems.
  • Autonomy: As 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 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: 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 AI systems that directly interact with human users, which needs research on methods to increase the robustness and security of AI systems against adversarial attacks.
  • Copyrights and Intellectual Property Rights: 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 AI systems are trained on a large amount of data, which are valuable assets and can be stolen or replicated. Furthermore, in a co-creative system, the role of AI can be complex and substantial, making it difficult to answer “who owns the product in a human-AI co-creation?”  These questions need to be investigated.
  • Weaponization: AI systems are increasingly being used in autonomous weapon systems, which raises ethical questions about human-AI collaborations in warfare and the possibility of AI being used to create autonomous weapons.
  • Generative AI and Large Language Models: The last few years have witnessed remarkable signs of progress in Generative AI (GAI) technologies, such as ChatGPT and Stable Diffusion. These advancements have tremendously enhanced AI systems and accelerated their adoption. Concurrently, the new technology integration calls for more research to address its various issues, including design methodologies, development challenges, innovative applications, and ethical concerns.
  • Multimodal Human-AI Collaboration: The rapid integration of large pre-trained foundation AI models, such as GPT-4, Whisper, and DALL·E, has been equipped with multimodal input and output capabilities. These advancements unlock fresh user experiences and pave the way for more adaptive human-AI collaborations. However, the wide-ranging implications of multimodal applications, along with the potential for misuse – particularly through the generation of highly expressive and convincing multimodal content – highlight the urgent need for careful consideration of how multimodal AIs communicate with users.
  • 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 suffer from technical limitations, calling for more research to advance the state-of-the art in voice/text analytics.
  • Job Displacement: While AI creates new job opportunities in the IT sector, they have rendered some jobs obsolete, profoundly influencing the skills and competencies required for future employment. Does AI replace human laborers, potentially exacerbating economic inequality, or does it aid in preparing job candidates for more productive roles, and thereby promoting occupational well-being? The potential impact of human-AI collaborations on human employment should be carefully examined.
  • AI for Vulnerable Population: (mental disorder sufferers, disabled, minor, etc.): While affording universal accessibility, AI’s interaction with vulnerable groups, such as those suffering from mental disorders and disabilities, may raise concerns due to inadequate design or data contamination. Communication generated by AI for the general population may appear insensitive or inappropriate for these vulnerable groups. Therefore, it is essential to explore design principles for AI systems that specifically accommodate the needs of vulnerable populations.
Minitrack Co-Chairs:

Dan J. Kim (Primary Contact)
University of North Texas
dan.kim@unt.edu

Victoria Yoon
Virginia Commonwealth University
vyyoon@vcu.edu

Xunyu Chen
Virginia Commonwealth University
chenx@vcu.edu

Humans are inherently social beings who communicate through multi-modal means spanning audio, visual and physical forms. This social nature heavily impacts how people work together in a team of equals to collaborate on a shared goal, and the effectiveness of their combined efforts in reaching their goal. Robots intended for collaborative work with humans embody physical systems that share a space with their human counterparts. It is no surprise that the nature of how humans work collaboratively with other humans, has a heavy influence on how humans collaborate with embodied robots, using similar forms of multimodal (audio, visual and physical) communication. Therefore, the design of multimodal human-machine interfaces is critical to the successful design of a collaborative robot. The ultimate pursuit being a robot that is accepted by its human collaborators and acts as an equal member of a mixed human/robot team in pursuit of a shared goal.

This minitrack aims at exploring the cutting edge of Human-Robot Interaction (HRI) and the evolution towards seamless Human-Robot Collaboration (HRC). It intends to examine how multimodal communication, including audio, visual, and physical interactions, plays a pivotal role in fostering meaningful connections. The goal is to provide insights into the innovative design of collaborative robots that coexist harmoniously with humans, sharing spaces and objectives. 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
  • The role of individual differences (robot and/or human) in human–robot interactions.
Minitrack Co-Chairs:

Filippo Sanfilippo (Primary Contact)
University of Agder
Filippo.Sanfilippo@uia.no

Lionel Robert
University of Michigan
lprobert@umich.edu

Sangseok You
Sungkyunkwan University
sangyou@skku.edu

Connor Esterwood
University of Michigan
cte@umich.edu

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 technology trends like Metaverse, AIGC, provide new 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 will focus on a wide range of topics including but not limited to:

  • IT enabled collaboration in emerging context (e.g. Metaverse) in developing regions
  • Opportunities and challenges in AI generated and participated collaboration
  • Metaverse and its influence for digital collaboration
  • Digital collaboration technology diffusion case studies in education, business, government, and healthcare organizations in developing regions
  • Global, virtual, distributed, blended, and face-to-face IT enabled collaboration for development at the team and organizational level
  • New generation of digital technology for cross-cultural collaboration
  • Group decision making, negotiation, facilitation, and communication technologies for development
  • Trust, privacy, security issues in digital technology enabled collaboration
  • Social, behavioral, psychological, economic 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
xusen.cheng@ruc.edu.cn

Xiangbin Yan
Guangdong University of Foreign Studies
xbyan@ustb.edu.cn

Deepinder Bajwa
Western Washington University
Deepinder.bajwa@wwu.edu

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

The minitrack on Responsible Innovation in Collaborative, Connected, and Intelligent Systems provides a scholarly venue for researchers and practitioners to present their work and engage in discussions on the responsible design, development, implementation, management, and use of AI-enabled collaborative and connected systems. The focus on human-machine collaboration highlights the importance of considering the effects of AI and other intelligent technologies on work, employment, and society and addressing the challenges and opportunities posed by these systems. This minitrack will serve as a platform for exchanging ideas, exploring challenges, and promoting interdisciplinary research and development in this critical area. We welcome submissions of high-quality research papers that address the current knowledge gaps and provide insights into the responsible design, development, implementation, management, and use of 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 5.90 in 2022.

Minitrack Co-Chairs:

Bo Sophia Xiao (Primary Contact)
University of Hawaii at Manoa
boxiao@hawaii.edu

Chee-Wee Tan
Copenhagen Business School
cta.itm@cbs.dk

Kaveh Abhari
San Diego State University
kabhari@sdsu.edu

Technological advancements are reshaping the landscape of digital collaboration. It is also important for digital collaboration to harness emerging technologies. In particular, generative AI and large language models, which have witnessed tremendous growth in recent years, empower next-generation digital collaboration and transform the dynamics and ways of it. For instance, large language models are widely adopted by businesses to assist users in a diverse range of open-ended tasks, offering novel ways to enhance the productivity and creativity in digital collaboration. However, generative AI and large language models are also facing their own set of challenges such as hallucination. Therefore, there is a strong need to both effectively leverage and continuously advance these technologies to enhance digital collaboration.

This minitrack explores advanced technologies in enterprise collaboration, social networking, and human-computer interaction, with a specific focus on prompt engineering, Parameter Efficient Fine Tuning (PEFT), RAG, and other relevant techniques. These advancements bring benefits to efficiency, productivity, creativity, emotional support, and even human well-being and organizational competitiveness. This showcases the seamless integration of human collaboration with generative AI, emphasizing transparency and interpretability across digital environments. We welcome technical discussions of the advancement, development, and adaptation of such techniques to enhance the quality, productivity, creativity, user satisfaction, and cost efficiency in terms of digital collaboration. Topics of interest include, but are not limited to:

  • Generative AI Interaction with Prompt Engineering
  • Zero-shot and Few-shots Learning and Prompt Engineering
  • PEFT Applications for Digital Collaboration
  • Effective instruction fine tuning
  • Large Language Models (LLM) on social media contents
  • Generative AI and Natural Language Processing (NLP)
  • RAG and Prompt Engineering
  • Human Feedback for Model Improvement
  • Social and human factors in Prompt Engineering and RLHF
  • LoRA of Generative AI and LLM
  • Ethical Considerations in human-AI collaboration
  • Privacy and security considerations in Parameter-Efficient Fine Tuning
  • Collaborative frameworks with consideration of LLM
  • Lifecycle and strategies for generative AI and LLM projects
Minitrack Co-Chairs:

Jie Tao (Primary Contact)
Fairfield University
jtao@fairfield.edu

Lina Zhou
University of North Carolina at Charlotte
lzhou8@uncc.edu

Xing Fang
Illinois State University
xfang13@ilstu.edu

While geographically distributed collaboration has been a subject of academic research for decades, the aftermath of the COVID-19 pandemic and the continuous growth in companies’ digitalization efforts have 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. The remote work trend has substantially altered organizational practices of employees, contractors, and network members who collaborate across multiple spatial, temporal, and digital boundaries in complex configurations. These distributed collaborations are often comprised of virtual teams or multi-team systems with complex dependency relationships, commonly spanning organizational boundaries. Coordinating task work and teamwork over a web of communication, information sharing, and knowledge relationships continues to serve as an important locus for research opportunities with important theoretical and practical implications. Today, research on virtual work does not only need to account for the general characteristics of virtual work, including technology, distance, and cultural differences, but also a shift in employees’ mindsets post-pandemic. Today, employees increasingly demand more workplace flexibility, which introduces new challenges to leadership, coordination and knowledge-sharing, organizational learning, innovation, as well as organizational culture. 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, and technological perspectives.

Contemporary collaborative work can rarely be studied from the perspective of isolated teams because work units are often commingled into larger organizational networks embedded in multi-team internal and external systems, operating in multiple locations across diverse functions. Moreover, these complex configurations frequently change and evolve to adapt to new unfamiliar situations and technological constellations. Teams are thus increasingly fluid as collaborators often come and go from one project to the next and from one team to another. This calls for research on attention and engagement. In addition, research considering the context, taking multi-level and network approaches can be especially interesting. Team diversity is another issue that needs more research as virtual collaborators often do not have the same first language or national culture. They also work in different time zones, may be employed by different organizations, and enter collaborations with different expectations for group processes. The question of generational differences and expectations for distributed collaboration has also been accentuated post-COVID.

To move the field forward, we encourage submissions that inform research and practice in the area of distributed collaboration and networks through a variety of academic lenses and research approaches, as well as those that highlight methodological challenges for adequately studying virtual collaboration, 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:

  • The impact of spatial, temporal, and technological properties on collaboration
  • Team knowledge networks and coordination in virtual work
  • Influence of technology, social structure, and culture on hybrid work
  • Antecedents of employee workplace- and technological- presence or absence
  • Surveillance and power in virtual collaborations
  • Impacts and consequences of telework and hybrid work on team, organizational, or network outcomes
  • Team dynamics and well-being in hybrid or virtual work
  • Impact of cultural differences, including language, on virtual collaboration
  • Diversity and inclusion management in multicultural virtual teams
  • e-leadership, including leading remote work and virtual teams
  • Emotion and relationship-building in virtual work
  • Loneliness and social connection in virtual collaboration
  • Communication processes in virtual teams and networks
  • Multi-team systems and fast-track expert teams
  • Knowledge collaboration and organizing dynamics in online and open-source communities
  • Social network theory and analysis applied to the context of virtual collaboration, organizations or networks
  • Multi-level dynamics between virtual teams, organizations, or networks
Minitrack Co-Chairs:

Emma S. Nordbäck (Primary Contact)
Hanken School of Economics
emma.nordback@hanken.fi

Kirsimarja Blomqvist
LUT University
kirsimarja.blomqvist@lut.fi

Assia Lasfer
Université Laval
Assia.lasfer@fsa.ulaval.ca

Riitta Hekkala
Aalto University
Riitta.hekkala@aalto.fi

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