Call for Papers

Call for short papers (pdf)

Research on teamwork has a long-standing and robust tradition (e.g., Hackman, 1987; Cohen & Bailey, 1997; Stewart, 2006; Bell et al., 2011; Wageman et al., 2012; Koslowski & Chao, 2018; Rapp et al., 2021). However, recent technological advancements and evolving organizational practices challenge many of the foundational assumptions about how teams function. The traditional paradigms that have guided teamwork research are being disrupted by contemporary teams’ dynamic boundaries, the increasing complexity in team membership, and the integration of new technologies. This sub-theme seeks to explore these changes, inviting innovative theoretical and empirical contributions that push the boundaries of what we know about teamwork.
 
First, much of the traditional research on teams assumes that boundaries between a team and its external environment are relatively clear, even if permeable (Dibble & Gibson, 2018; Wimmer et al., 2019). However, contemporary teams often exist in a state of constant flux, with members joining and leaving dynamically (Bushe & Chu, 2011; Mortensen & Haas, 2018). Moreover, the limited opportunities for face-to-face interactions among globally distributed team members, as well as employees in hybrid or remote work arrangements, can lead to varying perceptions and interpretations of who belongs to the “team”, further complicating the definition of team boundaries (e.g., Mortensen, 2014; Mattarelli et al., 2022). How can we reconceptualize team boundaries in light of these shifts?
 
Second, the majority of existing literature focuses on optimizing the effectiveness of a single team in isolation. Yet, team members increasingly participate in multiple teams simultaneously, navigating a variety of team contexts, such as differing tasks, roles, and norms, often alongside low temporal stability in their membership (e.g., O’Leary et al., 2011; Bertolotti et al., 2015; Margolis, 2020; Incerti et al., 2020; Rishani et al., 2024). Research on how such variety influences individual-level outcomes such as exhaustion, turnover, or overall performance (van de Brake et al., 2024) is still in its infancy. At a broader level, the optimization of teamwork must account for the complex web of interdependencies that span across teams (O’Leary et al., 2011; Rishani et al., 2024), which can cause delays in completing team tasks and increase conflicts. How do team members’ overlapping roles and responsibilities, frequent team switches, and low temporal stability impact performance, collaboration, and conflict at both individual, team and organizational levels?
 
Third, emerging technologies, particularly artificial intelligence (AI), are reshaping the way teams collaborate. The very notion of a “team member” is being challenged, with Gen and conversational AI agents now functioning as integral contributors (Larson & DeChurch, 2020; Seeber et al., 2020; Harris-Watsin et al., 2023; Bankins et al., 2024). Additionally, as AI algorithms are increasingly fine-tuned and tailored to the specific needs of various organizational roles and professions, their potential to enhance coordination and productivity continues to grow (e.g., Jarrahi, 2018; Bankins et al., 2024; Anthony et al., 2023). However, these technologies may also introduce unintended consequences. For instance, AI might reduce the necessity for human collaboration, undermining team dynamics, or alternatively, increase expectations and exacerbate conflict. How do these technologies influence team functioning, and what does it mean to be a “team” in this context?
 
Finally, new work arrangements, such as online labor platforms and gig work, challenge the traditional notions of teamwork. Online labor platforms are increasingly providing access to teams of experts to perform complex tasks (Bellesia et al., 2024). Hence, freelancers and gig workers now form and disband "flash teams" at unprecedented speeds, guided by client needs and controlled by algorithms (Retelny et al., 2014; Ai et al., 2023; Kadolkar et al., 2024). What does teamwork look like in these rapidly forming, ephemeral structures? How do trust, collaboration, and coordination evolve in such contexts?
 
These trends collectively challenge four key assumptions that have traditionally underpinned teamwork research:

• that team boundaries are fixed and well-defined and team membership is somehow stable;

• that the effectiveness of a single team can be optimized in isolation;

• that team members are exclusively human;

• that trust and collaboration are prerequisites for effective teamwork.

We invite scholars to challenge and expand our understanding of teamwork and to rethink the fundamental principles of teamwork in response to the changing technological and organizational landscape. This sub-theme aims to stimulate dialogue and innovation, fostering a deeper understanding of the evolving nature of teamwork in today’s organizations. Through rigorous exploration, we hope to uncover new insights that will advance both theory and practice in this vital area of research.
 
Both theoretical and empirical contributions are welcome. Potential questions and topics include, but are not limited to:

• How do individuals navigate and negotiate fluid team boundaries?

• How can we address the empirical challenges of studying teams with fluid boundaries?

• How do hybrid work arrangements affect how team members perceive their teammates and teamwork dynamics?

• What frameworks can address the interdependencies of multiple team memberships?

• How do individuals who are members of multiple teams simultaneously make sense of their memberships?

• How do individuals navigate the context variety of the teams they belong to?

• How can organizations optimize teamwork and promote wellbeing when employees are members of multiple teams simultaneously?

• What are the implications of AI and other technologies on team structure, processes, and outcomes?

• What does being a team member mean in the age of AI?

• What are the supporting or hindering factors in considering AI as a team member?

• How are AI and other technologies integrated in a team’s activities?

• How does the use of AI affect team dynamics?

• How do ephemeral “flash teams” impact our understanding of trust and collaboration in online labor platforms?

• How do gig workers interact with algorithms to form temporary teams? When are teams likely to turn into stable teams?

• What novel methodologies can be used to study these emergent phenomena?

References

• Ai, W., Chen, Y., Mei, Q., Ye, J., & Zhang, L. (2023): “Putting teams into the gig economy: A field experiment at a ride-sharing platform.” Management Science, 69 (9), 5336–5353.
• Anthony, C., Bechky, B.A., & Fayard, A.-L. (2023): “’Collaborating’ with AI: Taking a System View to Explore the Future of Work.” Organization Science, 34 (5), 1672–1694.
• Bankins, S., Ocampo, A.C., Marrone, M., Restubog, S.L.D., & Woo, S.E. (2024): “A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice.” Journal of Organizational Behavior, 45 (2), 159–182.
• Bell, S.T., Villado, A.J., Lukasik, M.A., Belau, L., & Briggs, A.L. (2011): “Getting specific about demographic diversity variable and team performance relationships: A meta-analysis.” Journal of Management, 37 (3), 709–743.
• Bellesia, F., Mattarelli, E., Bertolotti, F., & Sobrero, M. (2024): “Algorithmic Embeddedness and the ‘Gig’ Characteristics Model: Examining the Interplay between Technology and Work Design in Crowdwork.” Journal of Management Studies, first published online on August 2, 2024, https://doi.org/10.1111/joms.13130.
• Bertolotti, F., Mattarelli, E., Vignoli, M., & Macrì, D.M. (2015): “Exploring the relationship between multiple team membership and team performance: The role of social networks and collaborative technology.” Research Policy, 44 (4), 911–924.
• Bushe, G.R., & Chu, A. (2011): “Fluid teams: solutions to the problems of unstable team membership.” Organizational Dynamics, 40 (3), 181–188.
• Cohen, S.G., & Bailey, D.E. (1997): “What makes teams work: Group effectiveness research from the shop floor to the executive suite.” Journal of Management, 23 (3), 239–290.
• Dibble, R., & Gibson, C.B. (2018): “Crossing team boundaries: A theoretical model of team boundary permeability and a discussion of why it matters.” Human Relations, 71 (7), 925–950.
• Hackman, J.R. (1987): “The design of work teams.” In: J. Lorsch (ed.): Handbook of Organizational Behavior. New York: Prentice-Hall, 315–342.
• Harris-Watson, A.M., Larson, L.E., Lauharatanahirun, N., DeChurch, L.A., & Contractor, N.S. (2023): “Social perception in Human-AI teams: Warmth and competence predict receptivity to AI teammates.” Computers in Human Behavior, 145, https://doi.org/10.1016/j.chb.2023.107765.
• Incerti, V., Bellesia, F., Bertolotti, F., Chudoba, K., Fadel, K.J., Mattarelli, E., & Ungureanu, P. (2020): “Working in the Era of Multiple Virtual Team Membership. A Study on the Effects of Variety of Communication Rules on Individual Management of Knowledge Resources.” Proceedings of ICIS 2020 Conference in India: Making Digital Inclusive: Blending the Local and the Global, December 13–16, 2020, https://aisel.aisnet.org/icis2020/is_workplace_fow/is_workplace_fow/2/.
• Jarrahi, M.H. (2018): “Artificial intelligence and the future of work: Human AI symbiosis in organizational decision making.” Business Horizons, 61 (4), 577–586.
• Kadolkar, I., Kepes, S., & Subramony, M. (2024): “Algorithmic management in the gig economy: A systematic review and research integration.” Journal of Organizational Behavior, first published on September 5, 2024, https://doi.org/10.1002/job.2831.
• Kozlowski, S.W., & Chao, G.T. (2018): “Unpacking team process dynamics and emergent phenomena: Challenges, conceptual advances, and innovative methods.” American Psychologist, 73 (4), 576–592.
• Larson, L., & DeChurch, L.A. (2020): “Leading teams in the digital age: Four perspectives on technology and what they mean for leading teams.” The Leadership Quarterly, 31 (1), https://doi.org/10.1016/j.leaqua.2019.101377
• Margolis, J. (2020): “Multiple team membership: An integrative review.” Small Group Research, 51 (1), 48–86.
• Mattarelli, E., Bertolotti, F., Prencipe, A., & Gupta, A. (2022): “The effect of role-based product representations on individual and team coordination practices: A field study of a globally distributed new product development team.” Organization Science, 33 (4), 1423–1451.
• Mortensen, M. (2014): “Constructing the team: The antecedents and effects of membership model divergence.” Organization Science, 25 (3), 909–931.
• Mortensen, M., & Haas, M.R. (2018): “Perspective–Rethinking teams: From bounded membership to dynamic participation.” Organization Science, 29 (2), 341–355.
• O’Leary, M.B., Mortensen, M., & Williams Woolley, A. (2011): “Multiple team membership: A theoretical model of its effects on productivity and learning for individuals and teams.” Academy of Management Review, 36 (3), 461–478.
• Rapp, T., Maynard, T., Domingo, M., & Klock, E. (2021): “Team Emergent States: What Has Emerged in the Literature Over 20 Years.” Small Group Research, 52 (1), 68–102.
• Retelny, D., Robaszkiewicz, S., To, A., Lasecki, W.S., Patel, J., Rahmati, N., Tulsee Doshi, T., Valentine, M., & Bernstein, M.S. (2014): “Expert crowdsourcing with flash teams.” In: UIST ’14: Proceedings of the 27th annual ACM Symposium on User Interface Software and Technology, 75–85, https://doi.org/10.1145/2642918.2647409.
• Rishani, M., Schouten, M.E., & Hoever, I.J. (2024): “Navigating multiple team membership: A review and redirection of its influence on effectiveness outcomes.” Social and Personality Psychology Compass, 18 (1), https://doi.org/10.1111/spc3.12899.
• Seeber, I., Bittner, E., Briggs, R.O., de Vreede, T., de Vreede, G.-J., Elkins, A., Maier, R., Merz, A.B., Oeste-Reiß, Randrup, S.N., Schwabe, G., & Söllner, M. (2020): “Machines as teammates: A research agenda on AI in team collaboration.” Information & Management, 57 (2), https://doi.org/10.1016/j.im.2019.103174
• Stewart, G.L. (2006): “A meta-analytic review of relationships between team design features and team performance.” Journal of Management, 32 (1), 29–55.
• van de Brake, H.J., van der Vegt, G.S., & Essens, P.J.M.D. (2024): “More than just a number: Different conceptualizations of multiple team membership and their relationships with emotional exhaustion and turnover.” Journal of Applied Psychology, 109 (5), 714–729.
• Wageman, R., Gardner, H., & Mortensen, M. (2012): “The changing ecology of teams: New directions for teams research.” Journal of organizational Behavior, 33 (3), 301–315.
• Wimmer, J., Backmann, J., & Hoegl, M. (2019):” In or out? Exploring the inconsistency and permeability of team boundaries.” Small Group Research, 50 (6), 699–727.