MAJOR PREMISE, MINOR PREMISE, CONCLUSION. SIMPLE. (18 November 2026)

Description

Nick figured out what he thinks is the best formula for theorizing. It’s syllogisms, baby! He explains how you can turn to one body of literature to identify the major premise, turn to a different body of literature to problematize that premise through a minor premise to then theorize new propositions or hypotheses as a conclusion. Simple, right? But like so many other things in academia, saying what to do is one thing, doing it is another. So we go through several papers that operate with such a formula to understand how we can apply this idea to our research. We end up agreeing that academics need to become stewards of deep knowledge in the age of AI.

Episode Reading List

  • Tuckman, B. W. (1965). Developmental Sequence in Small Groups. Psychological Bulletin, 63(6), 384–399.
  • Bacharach, S. B. (1989). Organizational Theories: Some Criteria for Evaluation. Academy of Management Review, 14(4), 496–515.
  • Archer, M. (1995). Realist Social Theory: The Morphogenetic Approach. Cambridge University Press.
  • Bostrom, R. P., & Heinen, J. S. (1977). MIS Problems and Failures: A Socio-Technical Perspective, Part I: The Causes. MIS Quarterly, 1(1), 17–32.
  • Weber, R. (1997). Ontological Foundations of Information Systems. Coopers & Lybrand and the Accounting Association of Australia and New Zealand.
  • Giddens, A. (1984). The Constitution of Society: Outline of the Theory of Structuration. University of California Press.
  • Pentland, B. T., Kremser, W., & Goh, K. T. (2025). Path Nets: Concurrence and Recurrence in the Dynamics of Organizing. Academy of Management Review, 50(1), 114–137.
  • Berente, N., Hansen, S., Rosenkranz, C., & Tumbas, S. (2026). Translating Agile Development in Different Institutional Contexts: Dynamism, Pluralism, and Ratcheting over Time. Information Systems Research,https://doi.org/10.1287/isre.2021.0352.
  • Lindberg, A., Berente, N., Howison, J., & Lyytinen, K. (2024). Discursive Modulation in Open Source Software: How Communities Shape Novelty and Complexity. MIS Quarterly, 48(4), 1395–1422.
  • Tripp, J., & Armstrong, D. J. (2018). Agile Methodologies: Organizational Adoption Motives, Tailoring, and Performance. Journal of Computer Information Systems, 58(2), 170–179.
  • 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.
  • Smiley, T. J. (1973). What Is a Syllogism? Journal of Philosophical Logic, 2(1), 136–154.
  • Angst, C. M., Wowak, K. D., Handley, S. M., & Kelley, K. (2017). Antecedents of Information Systems Sourcing Strategies in U.S. Hospitals: A Longitudinal Study. MIS Quarterly, 41(4), 1129–1152.
  • Leonardi, P. M. (2011). When Flexible Routines Meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies. MIS Quarterly, 35(1), 147–167.
  • Leonardi, P. M. (2023). Affordances and Agency: Toward the Clarification and Integration of Fractured Concepts. MIS Quarterly, 47(4), ix–xx.
  • Recker, J. (2021). Scientific Research in Information Systems: A Beginner’s Guide (2nd ed.). Springer.
  • Charmaz, K. C. (2014). Constructing Grounded Theory: A Practical Guide through Qualitative Analysis (2nd ed.). Sage.
  • Recker, J., Grashoff, I., & Mayer, T. (2026). Build-your-own GPT: Field Lessons about Configuring a Proprietary Generative AI Solution. Information and Organization, 36(4), 100648.
  • Simon, H. A. (1973). The Structure of Ill-Structured Problems. Artificial Intelligence, 4(3-4), 181–201.
  • Lindberg, A., Schecter, A., Berente, N., Hennel, P., & Lyytinen, K. (2024). The Entrainment of Task Allocation and Release Cycles in Open Source Software Development. MIS Quarterly, 48(1), 67–94.
  • Dell’Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F., & Lakhani, K. R. (2026). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality. Organization Science, 37(2), 403–423.

The Home Page of Professor Jan Recker