Call for Papers

Call for short papers (pdf) 

Emerging digital technologies—ranging from intelligent systems (such as generative AI and learning algorithms) to distributed architectures (such as blockchain, Web3, and decentralized autonomous organizations), and increasingly pervasive datafied environments (including big data infrastructures and digital twins)—continue to reshape organizational and institutional life. These technologies enter organizations not as neutral instruments but as active participants in sociomaterial life: reshaping routines, redistributing expertise, reorganizing authority, and altering the institutional conditions under which action becomes meaningful (Anthony et al., 2023; Bailey et al., 2022; Berente & Seidel, 2022; Faik et al., 2020; Gegenhuber et al., 2022; Hinds & von Krogh, 2024; Hinings et al., 2018). At the same time, they transform how individuals experience work, influencing emotions, identities, power relations, knowledge practices, trust dynamics, and leadership (Karunakaran et al., 2025; Pakarinen & Huising, 2025; Tang et al., 2022; Villani & Phillips, 2021).

Yet it remains far from clear what kinds of organizational, epistemic, and institutional configurations we are collectively co-producing, and what the consequences will be of this ongoing hybridization of humans, machines, code, and infrastructures. These transformations unfold not only in everyday work practices, but also reverberate across fields and institutional orders, reshaping boundaries, jurisdictions, and the architectures of collective action. Intelligent and distributed technologies unsettle relationships between markets, states, professions, and communities, and generate new configurations of institutional interdependence, fragmentation, or hybridity—a shift that calls for integrated theorizing across micro, meso, and macro levels.

What we have begun to understand, however, is that intelligent and distributed technologies rarely evolve in linear, predictable, or deterministic ways. Their diffusion seldom fulfills the tidy promises contained in strategic roadmaps or technological imaginaries. While introduced with expectations of efficiency, transparency, decentralization, or augmentation, their implementation routinely generates friction, contradiction, and paradox (Raisch & Krakowski, 2021; Ramaul et al., 2026). They promise autonomy while expanding algorithmic forms of control; deliver transparency while introducing new layers of opacity; pursue decentralization yet often recentralize infrastructural power; and claim trustlessness while relying on institutional and epistemic foundations (Arora et al., 2023; Davidson et al., 2018; Ellinger et al., 2024; Lumineau et al., 2023; Pakarinen & Huising, 2025; Ungureanu, 2025; Ungureanu et al., 2025). These tensions reverberate at the human level as well, generating emotional ambivalence, unpredictable resistance and acceptance dynamics, and evolving challenges for leadership and coordination (Berente & Seidel, 2022; Farahbakhsh et al., 2024; Knight & Paroutis, 2017).

Although earlier waves of digital technologies also produced tensions, these become more acute and consequential as intelligent and distributed systems increasingly mediate interpersonal, organizational, and institutional processes (Orlikowski & Scott, 2023). These dynamics are observable across multiple technological domains, from specialized and general-purpose AI systems to blockchain-enabled infrastructures—such as DAOs, token governance, and decentralized platforms—that serve as institutional laboratories experimenting with novel models of coordination, authority, and collective action.

To better study these new challenges, we propose a renewed attention to multiplex sociomaterial relations in the digital age: new forms of coordination and collaboration, expanded forms of machine participation, and shifting relationships among humans, algorithms, protocols, and infrastructures (Hinds & von Krogh, 2024; Wang et al., 2025). As these sociomaterial entanglements take hold, they can simultaneously enable and constrain, centralize and decentralize, empower and disempower, illuminate and obscure (Bailey et al., 2022; Gawer & Phillips, 2013; Waardenburg et al., 2022). Their multiplex nature challenges established theories of organizing and institutional change, and invites scholars to examine the complex, hybrid, and often ambiguous dynamics that arise as technologies evolve in everyday settings, and unpack the implications that new relational struggles bring to how individuals interpret, negotiate, and emotionally respond to sociotechnical transformation (Bailey et al., 2022; Faraj & Leonardi, 2022; Lebovitz et al., 2022; Orlikowski & Scott, 2023).

This sub-theme invites scholars to examine how intelligent and distributed technologies generate ambiguous, contested, and hybrid spaces in which organizational and institutional life is reconfigured. Rather than viewing technologies as discrete artifacts or deterministic drivers of change, we encourage contributions that approach them as sociomaterial assemblages, institutional interventions, and sites of negotiation through which new possibilities and constraints are continually produced in the mundane of daily life.

We are especially interested in research that explores:

• Paradoxical dynamics emerging as organizations grapple with coexisting yet contradictory imperatives: automation/autonomy, decentralization/control, speed/delay, experimentation/stabilization, openness/protection.

• Institutional and field-level reconfigurations, including how intelligent and distributed technologies unsettle boundaries between markets and states, professions and platforms, communities and corporations.

• Hybrid constellations of agency, where humans, algorithms, protocols, and infrastructures interact in ways that challenge established understandings of expertise, responsibility, and accountability.

• Human–technology interactions, including how actors domesticate, repurpose, appropriate, or disrupt technological infrastructures—and their impact on emotions, trust, identity, and perceptions of fairness in organizational life.

• Evaluative and epistemic uncertainty of emerging technologies, from the difficulty of verifying algorithmic outputs to disputes over what counts as legitimate, reliable, ethical, or fair technological action.

• Politics, contestation, and resistance, including translation struggles, collective mobilizations, and frictional encounters among competing logics, values, and knowledge regimes.

• Leadership, coordination, and social influence dynamics, particularly how leaders navigate algorithmic mediation, manage emotional climates, or foster psychological safety in technologically augmented environments.

• Temporalities of technological change, including drift, latency, recursive cycles, breakdowns, failures, and stalled or abandoned projects that reveal the fragility and contingency of digital transformations.

• Trajectories of digital transformation, examining conditions under which transformations become successful, partial, stalled, or reversed as technological promises meet limits, breakdowns, and unintended consequences.

• Organizational and institutional hybridization, including cross-sector, cross-field, and cross-logic entanglements, as emerging technologies bridge markets, states, professions, communities, and scientific domains.

We welcome conceptual, empirical, and methodological diversity—including institutional theory, sociomateriality, science and technology studies, paradox theory, practice theory, organizational sociology, innovation and entrepreneurship research, and the full range of methodological approaches from quantitative analysis to ethnography, process research, and historical inquiry. Our aim is to create an inclusive home for scholars exploring AI, blockchain, data infrastructures, digital ecosystems, platform architectures, immersive technologies, and other emerging digital fields as drivers of organizational transformation and new collaborative arrangements across sectors, and as forces that affect the experiences and behavior of individuals at work. Although these technologies differ in their technical properties, they share underlying dynamics of organizational experimentation, institutional reordering, and sociotechnical transformation, which this sub-theme aims to foreground and connect. The emphasis is on examining the complex, uncertain, and paradox-laden realities through which intelligent and distributed technologies become embedded in organizational and institutional life.

If your work speaks to any of these themes, we warmly welcome your contribution to our sub-theme and look forward to lively, insightful, and field-shaping conversations.
 

• 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. https://doi.org/10.1287/orsc.2022.1651
• Arora, A., Barrett, M., Lee, E., Oborn, E., & Prince, K. (2023). Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization. Information and Organization, 33(3), 100478. https://doi.org/10.1016/j.infoandorg.2023.100478
• Bailey, D. E., Faraj, S., Hinds, P. J., Leonardi, P. M., & von Krogh, G. (2022). We are all theorists of technology now: A relational perspective on emerging technology and organizing. Organization Science, 33(1), 1–18. https://doi.org/10.1287/orsc.2021.1562
• Berente, N., & Seidel, S. (2022). Digital technologies: Carrier or trigger for institutional change in digital transformation. In T. Gegenhuber, D. Logue, C. R. Hinings, & M. Barrett (Eds.), Digital transformation and institutional theory (Research in the Sociology of Organizations, Vol. 83, pp. 197–209). Emerald Publishing Limited. https://doi.org/10.1108/S0733-558X20220000083008
• Charlwood, A., & Guenole, N. (2022). Can HR adapt to the paradoxes of artificial intelligence? Human Resource Management Journal, 32(4), 729–742. https://doi.org/10.1111/1748-8583.12433
• Davidson, S., De Filippi, P., & Potts, J. (2018). Blockchains and the economic institutions of capitalism. Journal of Institutional Economics, 14(4), 639–658. https://doi.org/10.1017/S1744137417000200
• Ellinger, E. W., Gregory, R. W., Mini, T., Widjaja, T., & Henfridsson, O. (2024). Skin in the game: The transformational potential of decentralized autonomous organizations. MIS Quarterly, 48(1), 245–272. https://doi.org/10.25300/MISQ/2023/17690
• Faik, I., Barrett, M., & Oborn, E. (2020). How information technology matters in societal change: An affordance-based institutional logics perspective. MIS Quarterly, 44(3), 1359–1390. https://doi.org/10.25300/MISQ/2020/14193
• Farahbakhsh, S., Villani, E., Linder, C., & Salge, T. O. (2024). How paradoxes shape members and the member–organization relationship: An identity threat perspective. Organization Science, 35(5), 1721–1744. https://doi.org/10.1287/orsc.2020.14630
• Faraj, S., & Leonardi, P. M. (2022). Strategic organization in the digital age: Rethinking the concept of technology. Strategic Organization, 20(4), 771–785. https://doi.org/10.1177/14761270221130253
• Gawer, A., & Phillips, N. (2013). Institutional work as logics shift: The case of Intel's transformation to platform leader. Organization Studies, 34(8), 1035–1071. https://doi.org/10.1177/0170840613492071
• Gegenhuber, T., Logue, D., Hinings, C. R., & Barrett, M. (2022). Institutional perspectives on digital transformation. In T. Gegenhuber, D. Logue, C. R. Hinings, & M. Barrett (Eds.), Digital transformation and institutional theory (Research in the Sociology of Organizations, Vol. 83, pp. 1–32). Emerald Publishing Limited. https://doi.org/10.1108/S0733-558X20220000083001
• Hinds, P., & von Krogh, G. (2024). Generative AI, emerging technology, and organizing: Towards a theory of progressive encapsulation. Organization Theory, 5(4). https://doi.org/10.1177/26317877241293478
• Hinings, B., Gegenhuber, T., & Greenwood, R. (2018). Digital innovation and transformation: An institutional perspective. Information and Organization, 28(1), 52–61. https://doi.org/10.1016/j.infoandorg.2018.02.004
• Karunakaran, A., Lebovitz, S., Narayanan, D., & Rahman, H. A. (2025). Artificial intelligence at work: An integrative perspective on the impact of AI on workplace inequality. Academy of Management Annals, 19(2), 693–735. https://doi.org/10.5465/annals.2023.0230
• Knight, E., & Paroutis, S. (2017). Becoming salient: The TMT leader’s role in shaping the interpretive context of paradoxical tensions. Organization Studies, 38(3–4), 403–432. https://doi.org/10.1177/0170840616640844
• Lebovitz, S., Lifshitz-Assaf, H., & Levina, N. (2022). To engage or not to engage with AI for critical judgments: How professionals deal with opacity when using AI for medical diagnosis. Organization Science, 33(1), 126–148. https://doi.org/10.1287/orsc.2021.1549
• Lumineau, F., Schilke, O., & Wang, W. (2023). Organizational trust in the age of the fourth industrial revolution: Shifts in the form, production, and targets of trust. Journal of Management Inquiry, 32(1), 21–34. https://doi.org/10.1177/10564926221127852
• Orlikowski, W. J., & Scott, S. V. (2023). The digital undertow and institutional displacement: A sociomaterial approach. Organization Theory, 4(2). https://doi.org/10.1177/26317877231180898
• Pakarinen, P., & Huising, R. (2025). Relational expertise: What machines can’t know. Journal of Management Studies, 62(5), 2053–2082. https://doi.org/10.1111/joms.12915
• Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
• Ramaul, L., Ritala, P., Kostis, A., & Aaltonen, P. (2026). Rethinking how we theorize AI in organization and management: A problematizing review of rationality and anthropomorphism. Journal of Management Studies, 63(2), 761–807. https://doi.org/10.1111/joms.13246
• Tang, P., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., ... Ng, C. T. S. (2022). When conscientious employees meet intelligent machines: An integrative approach inspired by complementarity theory and role theory. Academy of Management Journal, 65(3), 1019–1054. https://doi.org/10.5465/amj.2020.1516
• Ungureanu, P., Bellesia, F., & Cochis, C. (2025). Dealing with blame in digital ecosystems: The DAO failure in the Ethereum blockchain. Technological Forecasting and Social Change, 215, 124096. https://doi.org/10.1016/j.techfore.2025.124096
• Ungureanu, P. (2025). Running code or better code? Expertise de/centralization tensions in the Ethereum blockchain ecosystem. In K. T. Elmholdt, R. Huising, & E. I. Mäkinen (Eds.), Expertise in and around organizations: The changing constitution and ecology of expertise (Research in the Sociology of Organizations, Vol. 97, pp. 165–192). Emerald Publishing Limited. https://doi.org/10.1108/S0733-558X20250000097008
• Villani, E., & Phillips, N. (2021). Formal organizations and interstitial spaces: Catalysts, complexity, and the initiation of cross-field collaboration. Strategic Organization, 19(1), 5–36. https://doi.org/10.1177/1476127019897235
• Wang, S., Schlagwein, D., & Seymour, M. (2025). Socio-technical phenomena involving blockchain use: Literature review, conceptual framework, and research agenda. The Journal of Strategic Information Systems, 34(2), 101901. https://doi.org/10.1016/j.jsis.2025.101901
• Waardenburg, L., Huysman, M., & Sergeeva, A. V. (2022). In the land of the blind, the one-eyed man is king: Knowledge brokerage in the age of learning algorithms. Organization Science, 33(1), 59–82. https://doi.org/10.1287/orsc.2021.1544