Call for Papers

Call for short papers (pdf)

From Representation to Simulation

Contemporary organizations increasingly operate through models of reality rather than through lived, situated experiences. Digitalization, datafication, and AI technologies create worlds where simulations, synthetic data, predictive models, and behavioral proxies become the terrain upon which everyday practices unfold. The result is a growing hyperreal (Baudrillard, 1994) organizational condition, in which data-driven abstractions overtake the social and material practices they once purported to capture (Aaltonen & Stelmaszak, 2023).

This sub-theme invites scholars to explore what happens to organizational practices when simulations of work become more consequential than the underlying reality. We welcome research that investigates this phenomenon both conceptually and empirically, for example by engaging with notions of ontological reversal (Baskerville, et al., 2020), synthetic knowing (Monteiro & Parmiggiani, 2019), gamification, digital twins (Lyytinen et al., 2024), algorithmic management (Möhlmann et al., 2021; Cameron, 2024), the validity of insights derived from representations (Østerlie & Monteiro 2020), the performative nature of data (Jones, 2019), and the politics of representation in organizational life. Whether empirical or conceptual, a reflexive stance is strongly encouraged (Alvesson & Kärreman, 2007; Alvesson & Sköldberg, 2009).

Datafied Work and Instrumentarian Power

Across many organizations, everyday work is becoming increasingly datafied and gamified. Digital platforms assign scores, track behaviors, and provide continuous feedback that nudges how workers act. These systems often resemble games: they reward particular choices, penalize others, and translate complex tasks into sequences of measurable moves.

While such interfaces may appear simple or even playful, they reflect a deeper shift in how organizations guide and shape behavior. As Zuboff (2019) argues, these systems operate through instrumentarian power - a logic of surveillance, data extraction, and behavioral steering or ‘nudging’ that seeks to monitor workers in order to influence their conduct. Consequently, workers, managers, and systems increasingly orient their actions toward models, dashboards, and algorithmic outputs rather than toward the material and social practices these representations claim to capture.

Generational and Cultural Dimensions

This trend is especially significant for younger workers entering organizations under contradictory labor conditions: shortages in some sectors, scarcity and precarity in others, and heightened competition for secure or desirable roles. For these cohorts, algorithmic scoring, gamified performance metrics, and digital nudges are not exceptional—they are normalized as everyday components of work (Mazmanian & Beckman, 2018).

Speculative fiction such as The Hunger Games or Ender’s Game resonates because it depicts competitive environments governed by opaque rules, constant assessment, and simulations with highly consequential outcomes (Tansley, et al., 2014).

Ontological Reversal and the Rise of the Hyperreal

In today’s work environments, the hyperreal is present in mundane models of reality that feed images of work back into organizational systems: HR models, behavioral indicators, dashboards, and digital twins translate work into data. In doing so, simulations function as performative apparatuses (Barad, 2007): they shape what becomes visible, measurable, actionable, all while rendering other aspects of work invisible or irrelevant (Hafermalz, 2021).

Over time, these powerful representations can become “epistemic monsters” (Faraj, Torrents, Mantere, & Bhardwaj, 2025) – more authoritative than the lived, situated practices they simulate. This reflects the condition Baudrillard (1994) describes as simulacra and simulation: the moment when representations detach from their referents and begin to govern reality.

Organizational and Information Systems research echoes this concern through the concept of ontological reversal. Baskerville, Myers, and Yoo (2020) describe a condition in which digital representations take precedence over the physical phenomena they were meant to model. In such cases, algorithmic outputs become the “real”, and organizational actors must adapt themselves to their logic. In hyperreal workplaces, simulations increasingly define what is attended to and valued (Orlikowski & Scott, 2014).

Aim of the Sub-theme

This sub-theme seeks to attract research that examines how the hyperreal emerges at work, how simulations shape organizational experience, and how these developments challenge established theories of work, organizing, relationality, materiality, and power.

We invite contributions that theorize and empirically investigate how datafication, algorithmic systems, and LLMs reshape organizational realities by making simulations central to work and organizing. We are particularly interested in how data, via tools such as dashboards, digital twins, predictive models, and generative systems (e.g., AI “assistants”, copilots, and hyper-personalized interfaces), structure attention and sensemaking in ways that may detach from lived, situated practices (Alaimo & Kallinikos, 2022). Both theoretical and empirical work is welcome, especially qualitative and interpretive studies that foreground the temporal, relational, and material dynamics of hyperreal organizing. Studies from diverse domains including healthcare, logistics, finance, education, platform work, and public administration are encouraged, particularly those that shed light on how workers and professionals adapt to, resist, or reconfigure increasingly simulated work environments (Kellogg, et al., 2020).

Guiding Questions
Papers may address, but are not limited to, the following questions:

• How do dashboards, digital twins, and generative AI systems participate in constructing organizational realities, and in what ways do these become more consequential than the practices they purport to represent (Bailey, et al., 2012; Leonardi & Leavell, 2024)?

• What happens to organizational knowledge and decision-making when they increasingly rely on synthetic data, and how do actors assess the validity or trustworthiness of such insights?

• In what ways do AI tools contribute to ontological reversal (Baskerville et al., 2020), where algorithmic outputs define what is taken as real or relevant (Introna, 2016)?

• How are decisions about data collection, model design, and AI deployment made, and how do these decisions lead to or (re)configure hyperreal work environments?

• How do organizational actors make sense of and respond to AI-generated simulations (e.g., risk scores, predicted trajectories, scenario models) in everyday work?

• How do gamified interfaces, scoring systems, and continuous feedback mechanisms enact instrumentarian power, and what forms of compliance, coping, or resistance emerge?

• How do hyperreal and gamified forms of organizing differentially affect workers across age, gender, race, class, contract type, or occupational status?

• How do cultural imaginaries of simulation and competition inform the design, justification, and lived experience of hyperreal workplaces?

• How does the introduction of generative AI and simulation-based systems reconfigure professional expertise (Tyskbo & Sergeeva, 2022), identities, and human–machine boundaries?

• How do organizational actors negotiate tensions between simulation-driven guidance and situated judgment, care, and discretion in high-stakes settings?

• What ethical, epistemic, or legitimacy challenges arise when organizational knowledge increasingly relies on synthetic data, generated content, and opaque models?

• What methodological innovations are needed to study hyperreal organizing, including ethnographies of models, interfaces, and simulations?

• Aaltonen, A., & Stelmaszak, M. (2023). The performative production of trace data in knowledge work. Information Systems Research. Advance online publication.
• Alaimo, C., & Kallinikos, J. (2022). Organizations decentered: Data objects, technology and knowledge. Organization Science, 33(1), 19–37.
• Alvesson, M., & Kärreman, D. (2007). Constructing mystery: Empirical matters in theory development. Academy of Management Review, 32(4), 1265–1281.
• Alvesson, M., & Sköldberg, K. (2009). Reflexive methodology: New vistas for qualitative research (2nd ed.). SAGE.
• Bailey, D. E., Leonardi, P. M., & Barley, S. R. (2012). The lure of the virtual. Organization Science, 23(5), 1485–1504. https://doi.org/10.1287/orsc.1110.0703
• Barad, K. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press.
• Baskerville, R. L., Myers, M. D., & Yoo, Y. (2020). Digital first: The ontological reversal and new challenges for information systems research. MIS Quarterly, 44(2), 509–524.
• Baudrillard, J. (1994). Simulacra and simulation (S. F. Glaser, Trans.). University of Michigan Press. (Original work published 1981)
• Cameron, L. D. (2024). The making of the “good bad” job: How algorithmic management manufactures consent through constant and confined choices. Administrative Science Quarterly, 69(2), 458–514.
• Faraj, S., Torrents, J. P., Mantere, S., & Bhardwaj, A. (2025). A time for monsters: Organizational knowing after LLMs [Preprint]. arXiv. https://arxiv.org/abs/2511.15762
• Hafermalz, E. (2021). Out of the Panopticon and into exile: Visibility and control in distributed new culture organizations. Organization Studies, 42(5), 697–717.
• Introna, L. D. (2016). Algorithms, governance, and governmentality: On governing academic writing. Science, Technology, & Human Values, 41(1), 17–49.
• Jones, M. (2019). What we talk about when we talk about (big) data. The Journal of Strategic Information Systems, 28(1), 3–16.
• Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410.
• Leonardi, P. M., & Leavell, V. (2024). How the map becomes the territory: Prediction, performativity and the process of taking digital twins for granted. Journal of Organization Design, 13(3), 101–112.
• Lyytinen, K., Weber, B., Becker, M. C., & Pentland, B. T. (2024). Digital twins of organization: Implications for organization design. Journal of Organization Design, 13(3), 77–93.
• Mazmanian, M., & Beckman, C. M. (2018). “Making” your numbers: Engendering organizational control through a ritual of quantification. Organization Science, 29(3), 357–379.
• Möhlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021). Algorithmic management of work on online labor platforms: When matching meets control. MIS Quarterly, 45(4), 1999–2022.
• Monteiro, E., & Parmiggiani, E. (2019). Synthetic knowing. MIS Quarterly, 43(1), 167–184.
• Orlikowski, W. J., & Scott, S. V. (2014). What happens when evaluation goes online? Exploring apparatuses of valuation in the travel sector. Organization Science, 25(3), 868–891.
• Østerlie, T., & Monteiro, E. (2020). Digital sand: The becoming of digital representations. Information and Organization, 30(1), Article 100275.
• Tansley, C., Hafermalz, E., & Dery, K. (2014). ‘Ender’s Game’: Learning to survive in the limens of an e-HRM gamification talent selection assessment centre [Paper presentation]. 5th International E-HRM Conference, New York.
• Tyskbo, D., & Sergeeva, A. (2022). Brains exposed: How new imaging technology reconfigures expertise coordination in neurosurgery. Social Science & Medicine, 292, Article 114618.
• Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.