Jason Thatcher is back on the show and he is bringing decades of experiences as a journal editor. So we decided we play a game of round robin where each of us is giving rules of what to do (or not to do) as an editor. How long can we sit on papers before we make decisions? On what basis should we offer revise and resubmit decisions? When is it okay to desk reject a paper? How many reviews are enough? So if you want to learn more about the different editorial superhuman powers and supervillain powers – this is your episode.

Episode reading list

Recker, J. (2020). Reflections of a Retiring Editor-in-Chief. Communications of the Association for Information Systems, 46(32), 751-761.

Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450.

Li, J., Li, M., Wang, X., & Thatcher, J. B. (2021). Strategic Directions for AI: The Role of CIOs and Boards of Directors. MIS Quarterly, 45(3), 1603-1643.

Grisold, T., Berente, N., & Seidel, S. (2025). Guardrails for Human-AI Ecologies: A Design Theory for Managing Norm-Based Coordination. MIS Quarterly, 45, forthcoming.

Davis, J. L. (2020). How Artifacts Afford: The Power and Politics of Everyday Things. MIT Press.

Majchrzak, A., & Malhotra, A. (2019). Unleashing the Crowd: Collaborative Solutions to Wicked Business and Societal Problems. Springer.

Gaskin, J., Berente, N., Lyytinen, K., & Yoo, Y. (2014). Toward Generalizable Sociomaterial Inquiry: A Computational Approach for Zooming In and Out of Sociomaterial Routines. MIS Quarterly, 38(3), 849-871.

Teodorescu, M., Morse, L., Awwad, Y., & Kane, G. C. (2021). Failures of Fairness in Automation Require a Deeper Understanding of Human–ML Augmentation. MIS Quarterly, 45(3), 1483-1499.

Lee, J., & Berente, N. (2012). Digital Innovation and the Division of Innovative Labor: Digital Controls in the Automotive Industry. Organization Science, 23(5), 1428-1447.

Berente, N., Salge, C. A. D. L., Mallampalli, V. K. T., & Park, K. (2022). Rethinking Project Escalation: An Institutional Perspective on the Persistence of Failing Large-Scale Information System Projects. Journal of Management Information Systems, 39(3), 640-672.

Is it okay to use large language models in the research process? For what task, exactly, and to automate the task or to augment the researcher? In this episode, we try to explore whether and how LLMs could be used in five aspects of the research process - for paper writing, reviewing, data analysis, as a subject of research, or as a surrogate for research subjects. We also discuss whether they should be used at all, and what some long-term consequences could be of such a choice, and we develop a number of heuristic rules to help researcher make decisions about using LLMs for research.

Episode reading list

Kankanhalli, A. (2024). Peer Review in the Age of Generative AI. Journal of the Association for Information Systems, 25(1), 76-84.

Yang, Y., Duan, H., Liu, J., & Tam, K. Y. (2024). LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research. arXiv preprint, https://arxiv.org/abs/2504.02234v1.

Li, J., Larsen, K. R. T., & Abbasi, A. (2020). TheoryOn: A Design Framework and System for Unlocking Behavioral Knowledge Through Ontology Learning. MIS Quarterly, 44(4), 1733-1772.

Larsen, K. R., Yan, S., & Lukyanenko, R. (2024). LLMs and Psychometrics: Global Construct Validity Integrating LLMs and Psychometrics. 45th International Conference on Information Systems, Bangkok, Thailand.

Anthis, J. R., Liu, R., Richardson, S. M., Kozlowski, A. C., Koch, B., Evans, J., Brynjolfsson, E., & Bernstein, M. (2025). LLM Social Simulations Are a Promising Research Method. arXiv preprint, https://arxiv.org/abs/2504.02234.

Abbasi, A., Somanchi, S., & Kelley, K. (2025). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, 49(1), 1-28.

Is there a formula for doing and publishing research on digital phenomena? And if so, it is the same formula as the scripts for IS papers of the past, or has it changed? We discuss how our field has historically worked with reference theories from other disciplines and how we have moved beyond this one way of doing and publishing research to a variety of ways in which we can build theory about digital phenomena. We suggest that reference theories should not be viewed as immutable sacred cows but rather as a tentative basis of received wisdom, which we must problematize and adapt to move knowledge forward. Doing so requires us to find puzzles in the real world that point to things being different instead of new.

Episode reading list

Truex, D. P., Holmström, J., & Keil, M. (2006). Theorizing in Information Systems Research: A Reflexive Analysis of the Adaptation of Theory in Information Systems Research. Journal of the Association for Information Systems, 7(12), 797-821.

Grover, V., & Lyytinen, K. (2015). New State of Play in Information Systems Research: The Push to the Edges. MIS Quarterly, 39(2), 271-296.

Ba, S., & Pavlou, P. A. (2002). Evidence of the Effect of Trust Building Technology in Electronic Markets: Price Premiums and Buyer Behavior. MIS Quarterly, 26(3), 243-268.

Jiang, L., Hou, J., Ma, X., & Pavlou, P. A. (2025). Punished for Success? A Natural Experiment of Displaying Clinical Hospital Quality on Review Platforms. Information Systems Research, https://doi.org/10.1287/isre.2021.0630.

Grover, V., & Lyytinen, K. (2023). The Pursuit of Innovative Theory in the Digital Age. Journal of Information Technology, 38(1), 45-59.

Baiyere, A., Berente, N., & Avital, M. (2023). On Digital Theorizing, Clickbait Research, and the Cumulative Tradition. Journal of Information Technology, 38(1), 67-73.

Grisold, T., Kremser, W., Mendling, J., Recker, J., vom Brocke, J., & Wurm, B. (2023). Keeping Pace with the Digital Age: Envisioning Information Systems Research as a Platform. Journal of Information Technology, 38(1), 60-66.

Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450.

Dell'Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. Harvard Business School Technology & Operations Mgt. Unit Working Paper 24-013.

Fisher, G., Mayer, K. J., & Morris, S. (2021). From the Editors—Phenomenon-Based Theorizing. Academy of Management Review, 46(4), 631-639.

Gregory, R. W., & Henfridsson, O. (2021). Bridging Art and Science: Phenomenon-Driven Theorizing. Journal of the Association for Information Systems, 22(6), 1509-1523.

Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). Free Press.

Salge, C. A. D. L., & Karahanna, E. (2018). Protesting Corruption on Twitter: Is It a Bot or Is It a Person. Academy of Management Discoveries, 4(1), 32-49.

Abramova, O., Recker, J., Schemm, U., & Barwitzki, L.-D. (2025). Inclusion of Autistic IT Workforce in Action: An Auticon Approach. Information Systems Journal, https://doi.org/10.1111/isj.12588.

Grisold, T., Seidel, S., Heck, M., & Berente, N. (2024). Digital Surveillance in Organizations. Business & Information Systems Engineering, 66(3), 401-410.

Dwivedi, Y. K., Kshetri, N., ... Wright, R. T. (2023). “So what if ChatGPT wrote it?” Multidisciplinary Perspectives on Opportunities, Challenges and Implications of Generative Conversational AI for Research, Practice and Policy. International Journal of Information Management, 71, 102642.