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Look at what Santa dropped when he came down the chimney last night. A bunch of valuable ThisISResearch Best paper Awards! As we do at the end of every year, we look back at the finest information systems scholarship our field has produced this year, and we pick some of our favorite papers that we want to give an award too. Like in previous years, we recognize three different kinds of best papers – a paper that is innovative in its use of research methods, a paper that is a fine example of elegant scholarship, and a paper that is trailblazing in the sense that it starts new conversations in our field. References Pujol Priego, L., & Wareham, J. (2023). From Bits to Atoms: White Rabbit at CERN. MIS Quarterly, 47(2), 639-668. Recker, J., Zeiss, R., & Mueller, M. (2024). iRepair or I Repair? A Dialectical Process Analysis of Control Enactment on the iPhone Repair Aftermarket. MIS Quarterly, 48(1), 321-346. Seidel, S., Frick, C. J., & vom Brocke, J. (2025). Regulating Emerging Technologies: Prospective Sensemaking through Abstraction and Elaboration. MIS Quarterly, 49, . Abbasi, A., Somanchi, S., & Kelley, K. (2025). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, 49, . 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. Kitchens, B., Claggett, J. L., & Abbasi, A. (2024). Timely, Granular, and Actionable: Designing a Social Listening Platform for Public Health 3.0. MIS Quarterly, 48(3), 899-930. Chen, Z., & Chan, J. (2024). Large Language Model in Creative Work: The Role of Collaboration Modality and User Expertise. Management Science, 70(12), 9101-9117. Matherly, T., & Greenwood, B. N. (2024). No News is Bad News: The Internet, Corruption, and the Decline of the Fourth Estate. MIS Quarterly, 48(2), 699-714. Morse, L., Teodorescu, M., Awwad, Y., & Kane, G. C. (2022). Do the Ends Justify the Means? Variation in the Distributive and Procedural Fairness of Machine Learning Algorithms. Journal of Business Ethics, 181(4), 1083-1095. Hansen, S., Berente, N., & Lyytinen, K. (2009). Wikipedia, Critical Social Theory, and the Possibility of Rational Discourse. The Information Society, 25(1), 38-59. Habermas, J. (1984). Theory of Communicative Action, Volume 1: Reason and the Rationalization of Society. Heinemann.
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What do academics have to offer that practitioners do not already have? They have the data academics want. They can analyse it by themselves, sometimes better than academics. They are also not reading our articles. So why would academics bother engaging with them? Why should we even bridge that perceived or existing gap between theory and practice? Because academics need to dip their toes into practice, and they need to mingle with industry to stay relevant. So says Jonny Holmström, director and co-founder of the Swedish Center for Digital Innovation. He has been at the forefront of doing academic research that blends theory and practice, rigor and relevance, and he knows a thing or two about how to do so successfully. His secret? Maximize the gap between academics and practitioners, don’t close it. References Holmström, J., Magnusson, J., & Mähring, M. (2021). Orchestrating Digital Innovation: The Case of the Swedish Center for Digital Innovation. Communications of the Association for Information Systems, 48(31), 248-264. Churchman, C. W. (1972). The Design of Inquiring Systems: Basic Concepts of Systems and Organization. Basic Books. Latour, B. (2005). Reassembling the Social: An Introduction to Actor-Network Theory. Oxford University Press. Holmström, J. (2022). From AI to Digital Transformation: The AI Readiness Framework. Business Horizons, 65(3), 329-339. Recker, J., Bockelmann, T., & Barthel, F. (2024). Growing Online-to-Offline Platform Businesses: How Vytal Became the World-Leading Provider of Smart Reusable Food Packaging. Information Systems Journal, 34(1), 179-200. Abbasi, A., Somanchi, S., & Kelley, K. (2025). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, 49, . Sandberg, J., Holmström, J., & Lyytinen, K. (2020). Digitization and Phase Transitions in Platform Organizing Logics: Evidence from the Process Automation Industry. MIS Quarterly, 44(1), 129-153. Werder, K., Seidel, S., Recker, J., Berente, N., Kundert-Gibbs, J., Abboud, N., & Benzeghadi, Y. (2020). Data-Driven, Data-Informed, Data-Augmented: How Ubisoft’s Ghost Recon Wildlands Live Unit Uses Data for Continuous Product Innovation. California Management Review, 62(3), 86-102. Sting, F. J., Tarakci, M., & Recker, J. (2024). Performance Implications of Digital Disruption in Strategic Competition. MIS Quarterly, 48(3), 1263-1278. Tarakci, M., Sting, F. J., Recker, J., & Kane, G. C. (2024). Three Questions to Ask About Your Digital Strategy. MIT Sloan Management Review, July, . Davenport, T. H. (1993). Process Innovation: Reengineering Work Through Information Technology. Harvard Business School Press. Davenport, T. H. (1998). Putting the Enterprise into the Enterprise System. Harvard Business Review, 76(4), 121-131. Schecter, A., Wowak, K. D., Berente, N., Ye, H., & Mukherjee, U. (2021). A Behavioral Perspective on Service Center Routing: The Role of Inertia. Journal of Operations Management, 67(8), 964-988. Sundberg, L., & Holmström, J. (2024). Innovating by Prompting: How to Facilitate Innovation in the Age of Generative AI. Business Horizons, 67(5), 561-570. Kronblad, C., Essén, A., & Mähring, M. (2024). When Justice is Blind to Algorithms: Multilayered Blackboxing of Algorithmic Decision Making in the Public Sector. MIS Quarterly, 48(4), 1637-1662.
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You set up an assumption, you have a theory, you analyze your data, and you show that the assumption does not hold. Doing good qualitative research is that simple. Except that it’s not, of course. On the ground, in the research and writing process, these basic rules can be quite tricky to implement. So we discuss some heuristics researchers can use to limit their conversants, settle on suitable theoretical lenses to examine their data, and collecting more data than what they thought was necessary. References Geertz, C. (1973). The Interpretation Of Cultures. Basic Books. Goodall, J. (1986). The Chimpanzees of Gombe: Patterns of Behavior. Harvard University Press. Popper, K. R. (1959). The Logic of Scientific Discovery. Basic Books. Durkheim, E. (1895). The Rules of Sociological Method. Free Press. Giddens, A. (1976). New Rules of Sociological Method. Hutchinson. Barley, S. R. (1986). Technology as an Occasion for Structuring: Evidence from Observations of CT Scanners and the Social Order of Radiology Departments. Administrative Science Quarterly, 31(1), 78-108. Kellogg, K. C. (2022). Local Adaptation Without Work Intensification: Experimentalist Governance of Digital Technology for Mutually Beneficial Role Reconfiguration in Organizations. Organization Science, 33(2), 571-599. https://doi.org/10.1287/orsc.2021.1445 Mertens, W., Recker, J., Kummer, T.-F., Kohlborn, T., & Viaene, S. (2016). Constructive Deviance as a Driver for Performance in Retail. Journal of Retailing and Consumer Services, 30, 193-203. Markus, M. L. (1983). Power, Politics, and MIS Implementation. Communications of the ACM, 26(6), 430-444. Berente, N., Lyytinen, K., Yoo, Y., & King, J. L. (2016). Routines as Shock Absorbers During Organizational Transformation: Integration, Control, and NASA’s Enterprise Information System. Organization Science, 27(3), 551-572. Alashoor, T., Keil, M., Smith, H. J., & McConnell, A. R. (2023). Too Tired and in Too Good of a Mood to Worry about Privacy: Explaining the Privacy Paradox through the Lens of Effort Level in Information Processing. Information Systems Research, 34(4), 1415-1436. Yin, R. K. (2009). Case Study Research: Design and Methods (4th ed.). Sage. Berente, N., Recker, J., & Leonardi, P. (2023). . This IS Research podcast, 13 September 2023. Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013). Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology. Organizational Research Methods, 16(1), 15-31. Lebovitz, S., Levina, N., & Lifshitz-Assaf, H. (2021). Is AI Ground Truth Really “True”? The Dangers of Training and Evaluating AI Tools Based on Experts’ Know-What. MIS Quarterly, 45(3), 1501-1525. Ryle, G. (1949). The Concept of Mind. University of Chicago Press. Langley, A. (1999). Strategies for Theorizing from Process Data. Academy of Management Review, 24(4), 691-711. Miles, M. B., & Huberman, M. (1994). Qualitative Data Analysis (2nd ed.). Sage. Cramton, C. D., & Hinds, P. J. (2014). An Embedded Model of Cultural Adaptation in Global Teams. Organization Science, 25(4), 1056-1081.
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Did you know there is someone who published a MIS Quarterly paper in its inaugural issue in 1977 and has another one forthcoming in 2024? Hard to fathom but has published at least one paper in our top journal in every decade of its existence. Izak has been doing IS scholarship for almost fifty years, which makes him the perfect researcher to talk to about how the field has changed, where it is going, whether we are progressing well, and whether we maintain the optimal balance between social and technical, internal and external views of IS phenomena in our research. References Benbasat, I., & Schroeder, R. G. (1977). An Experimental Investigation of Some MIS Design Variables. MIS Quarterly, 1(1), 37-49. Jussupow, E., Benbasat, I., & Heinzl, A. (2024). An Integrative Perspective on Algorithm Aversion and Appreciation in Decision-Making. MIS Quarterly, . Benbasat, I., & Zmud, R. W. (2003). The Identity Crisis Within The IS Discipline: Defining and Communicating The Discipline's Core Properties. MIS Quarterly, 27(2), 183-194. Gregor, S., & Benbasat, I. (1999). Explanations from Intelligent Systems: Theoretical Foundations and Implications for Practice. MIS Quarterly, 23(4), 497-530. Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450. Lyytinen, K., & King, J. L. (2004). Nothing At The Center? Academic Legitimacy in the Information Systems Field. Journal of the Association for Information Systems, 5(6), 220-246. Sarker, S., Chatterjee, S., Xiao, X., & Elbanna, A. R. (2019). The Sociotechnical Axis of Cohesion for the IS Discipline: Its Historical Legacy and its Continued Relevance. MIS Quarterly, 43(3), 695-719. Wand, Y., & Weber, R. (1995). On the Deep Structure of Information Systems. Information Systems Journal, 5(3), 203-223. Banville, C., & Landry, M. (1989). Can the Field of MIS be Disciplined? Communications of the ACM, 32(1), 48-60. Benbasat, I., & Wang, W. (2005). Trust In and Adoption of Online Recommendation Agents. Journal of the Association for Information Systems, 6(3), 72-101. Benbasat, I., & Barki, H. (2007). Quo Vadis TAM? Journal of the Association for Information Systems, 8(4), 211-218. Toulmin, S. E. (1958). The Uses of Argument. Cambridge University Press. Kim, D., & Benbasat, I. (2006). The Effects of Trust-Assuring Arguments on Consumer Trust in Internet Stores: Application of Toulmin's Model of Argumentation. Information Systems Research, 17(3), 286-300. Qiu, L., & Benbasat, I. (2009). Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems. Journal of Management Information Systems, 25(4), 145-182. Applegate, L., & King, J. L. (1999). Rigor and Relevance: Careers on the Line. MIS Quarterly, 23(1), 17-18. Mason, R. O., Mason, F. M., & Culnan, M. J. (1995). Ethics of Information Management. Sage. Mason, R. O. (2022). On the Evolution to PAPA. Communications of the Association for Information Systems, 51(2), 7-22. Keen, P. G. W., & Scott Morton, M. S. (1978). Decision Support Systems: An Organizational Perspective. Addison-Wesley. Davis, G. B. (1974). Management Information Systems: Conceptual Foundations, Structure and Development. McGraw-Hill. Alaimo, C., & Kallinikos, J. (2024). Data Rules: Reinventing the Market Economy. MIT Press. Burton-Jones, A., Butler, B. S., Scott, S. V., & Xu, S. X. (2021). Next-Generation Information Systems Theorizing: A Call to Action. MIS Quarterly, 45(1), 301-314. Leidner, D. E., & Tona, O. (2021). The CARE Theory of Dignity Amid Personal Data Digitalization. MIS Quarterly, 45(1), 343-370. Parker, G., Van Alstyne, M., & Jiang, X. (2017). Platform Ecosystems: How Developers Invert the Firm. MIS Quarterly, 41(1), 255-266. Pujol Priego, L., & Wareham, J. (2023). From Bits to Atoms: White Rabbit at CERN. MIS Quarterly, 47(2), 639-668. Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research. Information Systems Research, 21(4), 724-735. Moore, G. C., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2(3), 192-222.
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We continue our discussion around theorizing about digital phenomena and publishing conceptual papers. Today, we are joined by , who has published several theoretical articles on digital technology in Academy of Management Review. He is also an AMR editor for a special issue on and he heads the Theory section as senior editor in the Journal of the Association for Information Systems. With Robert, we talk about the AMR publishing process, how it is different from mainstream IS journals and what we need to look out for when we generate theory about new digital phenomena. References Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, H. (2021). The Role of Artificial Intelligence and Data Network Effects for Creating User Value. Academy of Management Review, 46(3), 534-551. Sieber, S., & Gregory, R. W. (2018). Facebook’s Data Debacle in 2018. How to Move on? IESE Teaching Case, Number SI-200-E. Gregory, R. W., Henfridsson, O., Kaganer, E., & Kyriakou, H. (2021). Data Network Effects: Key Conditions, Shared Data, and the Data Value Duality. Academy of Management Review, 47(1), 189-192. Gregory, R. W., & Henfridsson, O. (2021). Bridging Art and Science: Phenomenon-Driven Theorizing. Journal of the Association for Information Systems, 22(6), 1509-1523. Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a Solution to Distant Search. Academy of Management Review, 37(3), 355-375. Fisher, G., Mayer, K. J., & Morris, S. (2021). From the Editors—Phenomenon-Based Theorizing. Academy of Management Review, 46(4), 631-639. Raisch, S., & Fomina, K. (2024). Combining Human and Artificial Intelligence: Hybrid Problem-Solving in Organizations. Academy of Management Review, . Baiyere, A., Berente, N., & Avital, M. (2023). On Digital Theorizing, Clickbait Research, and the Cumulative Tradition. Journal of Information Technology, 38(1), 67-73. Grover, V., & Lyytinen, K. (2023). The Pursuit of Innovative Theory in the Digital Age. Journal of Information Technology, 38(1), 45-59. Gregory, R. W., Beck, R., Henfridsson, O., & Yaraghi, N. (2024). Cooperation Among Strangers: Algorithmic Enforcement of Reciprocal Exchange with Blockchain-Based Smart Contracts. Academy of Management Review, . Bacharach, S. B. (1989). Organizational Theories: Some Criteria for Evaluation. Academy of Management Review, 14(4), 496-515. Rivard, S. (2021). Theory Building is Neither an Art Nor a Science. It is a Craft. Journal of Information Technology, 36(3), 316-328. Leidner, D. E., & Gregory, R. W. (2024). About Theory and Theorizing. Journal of the Association for Information Systems, 25(3), 501-521.
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Editorials are spaces in journals where the key stewards of the field leave advice for others about what type of research the journals they lead are looking to publish. We discuss some of our favorite editorials and dissect the advice to dish out for finding important research problems, theorizing effectively, and writing persuasively. References Rai, A. (2016). Celebrating 40 Years of MIS Quarterly: MISQ’s History and Future Through the Lenses of its Editors-in-Chief. MIS Quarterly, 40(4), iii-xvi. Lee, A. S. (2001). Editor's Comments: Research in Information Systems: What We Haven't Learned. MIS Quarterly, 25(4), v-xv. Saunders, C. (2005). Editor's Comments: Looking for Diamond Cutters. MIS Quarterly, 29(1), iii-viii. Rai, A. (2017). Editor's Comments: Avoiding Type III Errors: Formulating IS Research Problems that Matter. MIS Quarterly, 41(2), iii-vii. Weber, R. (2003). Editor's Comments: The Problem of the Problem. MIS Quarterly, 27(1), iii-ix. Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450. Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015). Understanding Algorithm Aversion: Forecasters Erroneously Avoid Algorithms After Seeing them Err. Journal of Experimental Psychology: General, 144(1), 114-126. Jussupow, E., Benbasat, I., & Heinzl, A. (2024). An Integrative Perspective on Algorithm Aversion and Appreciation in Decision-Making. MIS Quarterly, . 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. Sparrowe, R. T., & Mayer, K. J. (2011). Publishing in AMJ—Part 4: Grounding Hypotheses. Academy of Management Journal, 54(6), 1098-1102. Straub, D. W. (2009). Editor's Comments: Why Top Journals Accept Your Paper. MIS Quarterly, 33(3), iii-x.
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Conceptual papers that offer new theories are hard to write and even harder to publish. You do not have empirical data to back up your arguments, which makes the papers easy to reject in the review cycle. We are also typically not well trained in theorizing, and there isn’t even a clear process to theorizing we could learn or follow. Does that mean that we shouldn’t even try to write theory papers? We ponder these questions, figure out what is so hard in writing conceptual papers – and share a few tricks that might help if you still wanted to write such a paper. References Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450. Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine Publishing Company. Watson, R. T., Boudreau, M.-C., & Chen, A. J. (2010). Information Systems and Environmentally Sustainable Development: Energy Informatics and New Directions for the IS Community. MIS Quarterly, 34(1), 23-38. Lee, A. S., & Baskerville, R. (2003). Generalizing Generalizability in Information Systems Research. Information Systems Research, 14(3), 221-243. Tsang, E. W. K., & Williams, J. N. (2012). Generalization and Induction: Misconceptions, Clarifications, and a Classification of Induction. MIS Quarterly, 36(3), 729-748. Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research. Information Systems Research, 21(4), 724-735. Yoo, Y. (2010). Computing in Everyday Life: A Call for Research on Experiential Computing. MIS Quarterly, 34(2), 213-231. Merleau-Ponty, M. (1962). Phenomenology of Perception Routledge. Baldwin, C. Y., & Clark, K. B. (2000). Design Rules, Volume 1: The Power of Modularity. MIT Press. Weick, K. E. (1989). Theory Construction as Disciplined Imagination. Academy of Management Review, 14(4), 516-531. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75-105. Sætre, A. S., & van de Ven, A. H. (2021). Generating Theory by Abduction. Academy of Management Review, 46(4), 684-701. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291. Farjoun, M. (2010). Beyond Dualism: Stability and Change As a Duality. Academy of Management Review, 35(2), 202-225. Recker, J., & Green, P. (2019). How do Individuals Interpret Multiple Conceptual Models? A Theory of Combined Ontological Completeness and Overlap. Journal of the Association for Information Systems, 20(8), 1210-1241. Jabbari, M., Recker, J., Green, P., & Werder, K. (2022). How Do Individuals Understand Multiple Conceptual Modeling Scripts? Journal of the Association for Information Systems, 23(4), 1037-1070. Cornelissen, J. P. (2017). Editor’s Comments: Developing Propositions, a Process Model, or a Typology? Addressing the Challenges of Writing Theory Without a Boilerplate. Academy of Management Review, 42(1), 1-9. Recker, J., Lukyanenko, R., Jabbari, M., Samuel, B. M., & Castellanos, A. (2021). From Representation to Mediation: A New Agenda for Conceptual Modeling Research in a Digital World. MIS Quarterly, 45(1), 269-300. Haerem, T., Pentland, B. T., & Miller, K. (2015). Task Complexity: Extending a Core Concept. Academy of Management Review, 40(3), 446-460. Kallinikos, J., Aaltonen, A., & Marton, A. (2013). The Ambivalent Ontology of Digital Artifacts. MIS Quarterly, 37(2), 357-370. Ho, S. Y., Recker, J., Tan, C.-W., Vance, A., & Zhang, H. (2023). MISQ Special Issue on Registered Reports. MIS Quarterly, . Simon, H. A. (1990). Bounded Rationality. In J. Eatwell, M. Milgate, & P. Newman (Eds.), Utility and Probability (pp. 15-18). Palgrave Macmillan. James, W. (1890). The Principles of Psychology. Henry Holt and Company. Watson, H. J. (2009). Tutorial: Business Intelligence - Past, Present, and Future. Communications of the Association for Information Systems, 25(39), 487-510. Baird, A., & Maruping, L. M. (2021). The Next Generation of Research on IS Use: A Theoretical Framework of Delegation to and from Agentic IS Artifacts. MIS Quarterly, 45(1), 315-341.
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Did you know that when you spend time on an online platform, you could be experiencing between six to eight different experimental treatments that stem from several hundred A/B tests that run concurrently? That’s how common digital experimentation is today. And while this may be acceptable in industry, large-scale digital experimentation poses some substantial challenges for researchers wanting to evaluate theories and disconfirm hypotheses through randomized controlled trials done on digital platforms. Thankfully, the brilliant has a new paper forthcoming that illuminates the orthogonal testing plane problem and offers some guidelines for sidestepping the issue. So if experiments are your thing, you really need to listen to what is really going on out there. References Abbasi, A., Somanchi, S., & Kelley, K. (2024). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, . Miranda, S. M., Berente, N., Seidel, S., Safadi, H., & Burton-Jones, A. (2022). Computationally Intensive Theory Construction: A Primer for Authors and Reviewers. MIS Quarterly, 46(2), i-xvi. Karahanna, E., Benbasat, I., Bapna, R., & Rai, A. (2018). Editor's Comments: Opportunities and Challenges for Different Types of Online Experiments. MIS Quarterly, 42(4), iii-x. Kohavi, R., & Thomke, S. (2017). The Surprising Power of Online Experiments. Harvard Business Review, 95(5), 74-82. Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. Pienta, D., Vishwamitra, N., Somanchi, S., Berente, N., & Thatcher, J. B. (2024). Do Crowds Validate False Data? Systematic Distortion and Affective Polarization. MIS Quarterly, . Bapna, R., Goes, P. B., Gupta, A., & Jin, Y. (2004). User Heterogeneity and Its Impact on Electronic Auction Market Design: An Empirical Exploration. MIS Quarterly, 28(1), 21-43. Somanchi, S., Abbasi, A., Kelley, K., Dobolyi, D., & Yuan, T. T. (2023). Examining User Heterogeneity in Digital Experiments. ACM Transactions on Information Systems, 41(4), 1-34. Mertens, W., & Recker, J. (2020). New Guidelines for Null Hypothesis Significance Testing in Hypothetico-Deductive IS Research. Journal of the Association for Information Systems, 21(4), 1072-1102. GRADE Working Group. (2004). Grading Quality of Evidence and Strength of Recommendations. British Medical Journal, 328(7454), 1490-1494. Abbasi, A., Parsons, J., Pant, G., Liu Sheng, O. R., & Sarker, S. (2024). Pathways for Design Research on Artificial Intelligence. Information Systems Research, 35(2), 441-459. Abbasi, A., Chiang, R. H. L., & Xu, J. (2023). Data Science for Social Good. Journal of the Association for Information Systems, 24(6), 1439-1458. Babar, Y., Mahdavi Adeli, A., & Burtch, G. (2023). The Effects of Online Social Identity Signals on Retailer Demand. Management Science, 69(12), 7335-7346. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75-105. Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291. Benbasat, I., & Zmud, R. W. (2003). The Identity Crisis Within The IS Discipline: Defining and Communicating The Discipline's Core Properties. MIS Quarterly, 27(2), 183-194. Gregor, S., & Hevner, A. R. (2013). Positioning and Presenting Design Science Research for Maximum Impact. MIS Quarterly, 37(2), 337-355. Rai, A. (2017). Editor's Comments: Avoiding Type III Errors: Formulating IS Research Problems that Matter. MIS Quarterly, 41(2), iii-vii. Burton-Jones, A. (2023). Editor's Comments: Producing Significant Research. MIS Quarterly, 47(1), i-xv. Abbasi, A., Dillon, R., Rao, H. R., & Liu Sheng, O. R. (2024). Preparedness and Response in the Century of Disasters: Overview of Information Systems Research Frontiers. Information Systems Research, 35(2), 460-468.
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We are back with the usual dose of fortnightly folksy academic wisdom sprinkled in with some serious and substantive conversations. We kick this new season off by discussing observations we made at this year’s Academy of Management conference in Chicago. We talk about how to get the most out of doctoral and junior faculty consortia, how to pick which session to go to, how papers get reviewed at conferences, which papers tend to get selected for presentation – and how to use your session as a platform to pitch your work and yourself and finish with a crescendo and a mic drop. References Kallinikos, J., Yoo, Y., Baldwin, C., Van Alstyne, M., Tucci, C. L., & Saar-Tsechansky, M. (2024). Perspectives on Digital Innovation. Academy of Management Annual Meeting Proceedings, . Baskerville, R., Kaul, M., & Storey, V. C. (2017). Establishing Reliability in Design Science Research 38th International Conference on Information Systems, Seoul, Korea, . Aaltonen, A., Stelmaszak, M. (2024). Innovating in Data-based Reality: New Perspectives on Data as a Research Object. Academy of Management Professional Development Workshop, August 9, 2024, Chicago, Illinois. Meurer, M. M., Chalmers, D., Recker, J. (2024). Digital Technologies as Catalysts for Entrepreneurial Activities. Academy of Management Professional Development Workshop, August 9, 2024, Chicago, Illinois. Davidsson, P., Recker, J., & von Briel, F. (2020). External Enablement of New Venture Creation: A Framework. Academy of Management Perspectives, 34(3), 311-332.
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Many people think of summer as the best time to read. On the beach, on the airplane to a vacation, in between semesters… Sounds like a perfect time to do a literature review. But there are many ways to do a literature review, and in all honesty, we think most people choose the wrong type of review – the “systematic” literature review where they select papers about a phenomenon, do a supposedly structured but not exhaustive search across IS journals, and then criticize the knowledge others have created. We discuss a few alternatives that we think hold more promise: qualitative and quantitative meta analyses, or narrative and integrative reviews. We also point to a few papers that have helped us organize the conversations we read about in the literature – which really, is what literature reviewing is all about. References Berente, N., Lyytinen, K., Yoo, Y., & Maurer, C. (2019). Institutional Logics and Pluralistic Responses to Enterprise System Implementation: A Qualitative Meta-Analysis. MIS Quarterly, 43(3), 873-902. Noblit, G. W., & Hare, R. D. (1988). Meta-Ethnography: Synthesising Qualitative Studies. Sage. King, W. R., & He, J. (2006). A Meta-analysis of the Technology Acceptance Model. Information & Management, 43(6), 740-755. Zaza, S., Joseph, D., & Armstrong, D. J. (2023). Are IT Professionals Unique? A Second-Order Meta-Analytic Comparison of Turnover Intentions Across Occupations. MIS Quarterly, 47(3), 1213-1238. Trang, S., Kraemer, T., Trenz, M., & Weiger, W. H. (2024). Deeper Down the Rabbit Hole: How Technology Conspiracy Beliefs Emerge and Foster a Conspiracy Mindset. Information Systems Research, . 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. Skinner, R. J., Nelson, R. R., & Chin, W. (2022). Synthesizing Qualitative Evidence: A Roadmap for Information Systems Research. Journal of the Association for Information Systems, 23(3), 639-677. vom Brocke, J., Simons, A., Niehaves, B., Riemer, K., Plattfault, R., & Cleven, A. (2009). Reconstructing the Giant: On the Importance of Rigour in Documenting the Literature Search Process. 17th European Conference on Information Systems, Verona, Italy. vom Brocke, J., Simons, A., Riemer, K., Niehaves, B., Plattfault, R., & Cleven, A. (2015). Standing on the Shoulders of Giants: Challenges and Recommendations of Literature Search in Information Systems Research. Communications of the Association for Information Systems, 37(9), 205-224. Bunge, M. A. (1977). Treatise on Basic Philosophy Volume 3: Ontology I - The Furniture of the World. Kluwer Academic Publishers. Burton-Jones, A., Recker, J., Indulska, M., Green, P., & Weber, R. (2017). Assessing Representation Theory with a Framework for Pursuing Success and Failure. MIS Quarterly, 41(4), 1307-1333. Recker, J., Indulska, M., Green, P., Burton-Jones, A., & Weber, R. (2019). Information Systems as Representations: A Review of the Theory and Evidence. Journal of the Association for Information Systems, 20(6), 735-786. Saghafi, A., & Wand, Y. (2020). A Meta-Analysis of Ontological Guidance and Users' Understanding of Conceptual Models. Journal of Database Management, 31(4), 46-68. Leonardi, P. M., & Vaast, E. (2017). Social Media and their Affordances for Organizing: A Review and Agenda for Research. Academy of Management Annals, 11(1), 150-188. Orlikowski, W. J., & Scott, S. V. (2008). Sociomateriality: Challenging the Separation of Technology, Work and Organization. Academy of Management Annals, 2(1), 433-474. Felin, T., Foss, N. J., & Ployhart, R. E. (2015). The Microfoundations Movement in Strategy and Organization Theory. Academy of Management Annals, 9(1), 575-632. Cronin, M. A., & George, E. (2023). The Why and How of the Integrative Review. Organizational Research Methods, 26(1), 168-192. Paré, G., Trudel, M.-C., Jaana, M., & Kitsiou, S. (2015). Synthesizing Information Systems Knowledge: A Typology of Literature Reviews. Information & Management, 52(2), 183-199. Rivard, S. (2014). Editor's Comments: The Ions of Theory Construction. MIS Quarterly, 32(2), iii-xiii. Leidner, D., Berente, N., & Recker, J. (2023). What’s been done, what’s been found, and what it means. This IS research podcast, . Webster, J., & Watson, R. T. (2002). Analyzing the Past to Prepare for the Future: Writing a Literature Review. MIS Quarterly, 26(2), xiii-xxiii. Grisot, M., & Modol, J. R. (2024). Special Section Introduction: Reflecting and Celebrating Ole Hanseth’s Contribution to the IS Community. Scandinavian Journal of Information Systems, 36(1), 39-40. Association for Information Systems (2023. History of AIS. .
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Time to reflect a bit. After our conversations with three excellent but very different IS researchers, we sit down and ponder the lessons we learnt from the three previous podcasts with , , and . So did we learn anything? You betcha. We talk about the balancing humble scholarship with the need to popularize important new insights, the difference between rigor and importance of research, and the different career pathways in industry and academia. References Miranda, S. M., Berente, N., Seidel, S., Safadi, H., & Burton-Jones, A. (2022). Computationally Intensive Theory Construction: A Primer for Authors and Reviewers. MIS Quarterly, 46(2), i-xvi. Alaimo, C., & Kallinikos, J. (2024). Data Rules: Reinventing the Market Economy. MIT Press. Miranda, S. M., Wang, D., & Tian, C. (2022). Discursive Fields and the Diversity-Coherence Paradox: An Ecological Perspective on the Blockchain Community Discourse. MIS Quarterly, 46(3), 1421-1452. Miranda, S. M., Kim, I., & Summers, J. D. (2015). Jamming with Social Media: How Cognitive Structuring of Organizing Vision Facets Affects IT Innovation Diffusion. MIS Quarterly, 39(3), 591-614. Watson, R. T., Boudreau, M.-C., & Chen, A. J. (2010). Information Systems and Environmentally Sustainable Development: Energy Informatics and New Directions for the IS Community. MIS Quarterly, 34(1), 23-38. Malhotra, A., Melville, N. P., & Watson, R. T. (2013). Spurring Impactful Research on Information Systems for Environmental Sustainability. MIS Quarterly, 37(4), 1265-1274. Sein, M. K., Henfridsson, O., Purao, S., Rossi, M., & Lindgren, R. (2011). Action Design Research. MIS Quarterly, 35(2), 37-56. Gregor, S., Chandra Kruse, L., & Seidel, S. (2020). The Anatomy of a Design Principle. Journal of the Association for Information Systems, 21(6), 1622-1652. Lukyanenko, R., Parsons, J., Wiersma, Y. F., & Maddah, M. (2019). Expecting the Unexpected: Effects of Data Collection Design Choices on the Quality of Crowdsourced User-generated Content. MIS Quarterly, 43(2), 623-647. Recker, J., Lukyanenko, R., Jabbari, M., Samuel, B. M., & Castellanos, A. (2021). From Representation to Mediation: A New Agenda for Conceptual Modeling Research in a Digital World. MIS Quarterly, 45(1), 269-300. Abbasi, A., Dobolyi, D., Vance, A., & Zahedi, F. M. (2021). The Phishing Funnel Model: A Design Artifact to Predict User Susceptibility to Phishing Websites. Information Systems Research, 32(2), 410-436. vom Brocke, J., Simons, A., Riemer, K., Niehaves, B., Plattfault, R., & Cleven, A. (2015). Standing on the Shoulders of Giants: Challenges and Recommendations of Literature Search in Information Systems Research. Communications of the Association for Information Systems, 37(9), 205-224.
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Behavioral research is alive and well ... online Some time ago, we wondered whether survey research is dead. Today, we speak with , who argues the exact opposite. He gives us plenty of advice on how to design online experiments, sample rigorously on platforms like Prolific, build reliable psychometric measurements, and embed surveys in robust research designs. And because Jason is not only a prolific scholar and senior editor in our field but also very active on LinkedIn, we also talk about reviewing practices and how social media can help communities address topics that need to be spoken about. .
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is with us today. She has done some amazing theory construct research using computational methods before this was really an accepted thing. We discuss which work she built her research around to give it legitimacy, what good stopping rules are for authors or reviewers to know when enough is enough, and how we can engage in humble generalizations of interesting and general regularities. References Miranda, S. M., Kim, I., & Summers, J. D. (2015). Jamming with Social Media: How Cognitive Structuring of Organizing Vision Facets Affects IT Innovation Diffusion. MIS Quarterly, 39(3), 591-614. Walsh, I., Holton, J. A., Bailyn, L., Fernandez, W. D., Levina, N., & Glaser, B. G. (2015). What Grounded Theory Is ... A Critically Reflective Conversation Among Scholars. Organizational Research Methods, 18(4), 581-599. Levina, N., & Vaast, E. (2015). Leveraging Archival Data from Online Communities for Grounded Process Theorizing. In K. D. Elsbach & R. M. Kramer (Eds.), Handbook of Qualitative Organizational Research: Innovative Pathways and Methods (pp. 215-224). Routledge. Berente, N., Seidel, S., & Safadi, H. (2019). Data-Driven Computationally-Intensive Theory Development. Information Systems Research, 30(1), 50-64. Miranda, S. M., Wang, D., & Tian, C. (2022). Discursive Fields and the Diversity-Coherence Paradox: An Ecological Perspective on the Blockchain Community Discourse. MIS Quarterly, 46(3), 1421-1452. Fügener, A., Grahl, J., Gupta, A., & Ketter, W. (2021). Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI. MIS Quarterly, 45(3), 1527-1556. 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. Sahaym, A., Vithayathil, J., Sarker, S., Sarker, S., & Bjørn-Andersen, N. (2023). Value Destruction in Information Technology Ecosystems: A Mixed-Method Investigation with Interpretive Case Study and Analytical Modeling. Information Systems Research, 34(2), 508-531. Miranda, S. M., Berente, N., Seidel, S., Safadi, H., & Burton-Jones, A. (2022). Computationally Intensive Theory Construction: A Primer for Authors and Reviewers. MIS Quarterly, 46(2), i-xvi. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75-105. Adamic, L. A., & Glance, N. (2005). The Political Blogosphere and the 2004 U.S. Election: Divided They Blog. Paper presented at the 3rd International Workshop on Link Discovery, Chicago, Illinois. Pentland, B. T., Vaast, E., & Ryan Wolf, J. (2021). Theorizing Process Dynamics with Directed Graphs: A Diachronic Analysis of Digital Trace Data. MIS Quarterly, 45(2), 967-984. Sarker, S., Xiao, X., Beaulieu, T., & Lee, A. S. (2018). Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2). Journal of the Association for Information Systems, 19(8), 752-774. Lee, A. S., & Baskerville, R. (2003). Generalizing Generalizability in Information Systems Research. Information Systems Research, 14(3), 221-243. Tsang, E. W. K., & Williams, J. N. (2012). Generalization and Induction: Misconceptions, Clarifications, and a Classification of Induction. MIS Quarterly, 36(3), 729-748. Hume, D. (1748/1998). An Enquiry Concerning Human Understanding [Reprint]. In J. Perry & M. E. Bratman (Eds.), Introduction to Philosophy: Classical and Contemporary Readings (3rd ed., pp. 190-220). Oxford University Press. Exemplar Computationally-intensive Theory Construction Papers Bachura, E., Valecha, R., Chen, R., & Rao, H. R. (2022). The OPM Data Breach: An Investigation of Shared Emotional Reactions on Twitter. MIS Quarterly, 46(2), 881-910. Gal, U., Berente, N., & Chasin, F. (2022). Technology Lifecycles and Digital Innovation: Patterns of Discourse Across Levels of Abstraction: A Study of Wikipedia Articles. Journal of the Association for Information Systems, 23(5), 1102-1149. Hahn, J., & Lee, G. (2021). The Complex Effects of Cross-Domain Knowledge on IS Development: A Simulation-Based Theory Development. MIS Quarterly, 45(4), 2023-2054. Indulska, M., Hovorka, D. S., & Recker, J. (2012). Quantitative Approaches to Content Analysis: Identifying Conceptual Drift Across Publication Outlets. European Journal of Information Systems, 21(1), 49-69. Lindberg, A., Majchrzak, A., & Malhotra, A. (2022). How Information Contributed After an Idea Shapes New High-Quality Ideas in Online Ideation Contests. MIS Quarterly, 46(2), 1195-1208. Nan, N. (2011). Capturing Bottom-Up Information Technology Use Processes: A Complex Adaptive Systems Model. MIS Quarterly, 35(2), 505-532. Pentland, B. T., Recker, J., Ryan Wolf, J., & Wyner, G. (2020). Bringing Context Inside Process Research With Digital Trace Data. Journal of the Association for Information Systems, 21(5), 1214-1236. Vaast, E., Safadi, H., Lapointe, L., & Negoita, B. (2017). Social Media Affordances for Connective Action: An Examination of Microblogging Use During the Gulf of Mexico Oil Spill. MIS Quarterly, 41(4), 1179-1205.
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According to the internet, Elon Musk is often praised for his visionary mindset, innovation, risk-taking attitude, and energy. is just like that, we think. With the positivity he brings into every project and meeting, Jan has been right at the center of many seminal developments in our field over the past twenty years, from the rise of design science to the inception of NeuroIS, the development of literature reviews, and more recently the creation of process science. We take the opportunity to reflect with him on his work, the way he builds and steers highly successful research groups, and how he manages to do research that is both impactful and engaging to many different audiences. As usual, the references to readings we mention are listed on .
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In science, citations are used to give credit to sources that are relevant to the topic that is being discussed where the citation appears. They are a key vehicle through which we establish a cumulative knowledge tradition – we use them to acknowledge material that informs our arguments. But citations are much more than that. They have become a key metric of academic success in their own right, providing a quantifiable basis to measure a scholar’s impact, reputation, and fame. And as any metrics-based systems, also the citation system can be gamed, and is being gamed. Time to unpack the role that citations play and discuss which citations are legit – and which may just be a bit flunky. As usual, the references to readings we mention are listed on .
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Research is a conversation. Every scholar must become a professional writer. But how do we learn these things? Most graduate school programs do not include a writing course and books on how to write are read even less than other types of books. Is good writing maybe all either genetics or just experience? Or does it depend on how we approach research, either phenomena- or theory-driven? We think both things matter – but there are also some practical steps people can take to get their writing going and maintain the flow of writing. As usual, the references to readings we mention are listed on .
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The thing is, special issues are special. Hence the name. But what is it that makes them special? We look at some of the hottest special issues out there for information systems researchers and we discuss three key aspects of special issues – topical fit, competition, and process – that provide both advantages and disadvantages to researchers thinking about submitting to them. And for some weird reason we end up discussing our experiences at doctoral and junior faculty consortia and why everyone should attend them, always. As usual, the references to readings we mention are listed on .
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Jan has a boy crush on IS Econ researchers while Nick thinks they reduce all phenomena to regressions. Time to put both myths – and a few others – to rest. We brought on the inimitable and wonderful and to talk about everything you ever wanted to know about economics, econometrics, difference-in-difference designs, mechanism identifications, analytical modeling, and forbidden comparisons. At the end of it all, Jan’s boy crush has subsided a little bit – which is probably good – and Nick’s theory that every study is just a case study is, well, still a theory. But Gordon and Brad share a wealth of insights and tricks about how to do good econometric research in IS and how to get it published. As usual, the references to readings we mention are listed on . Also, just to be clear – the 2024 SIG DITE paper development workshop keynote speakers are not yet confirmed, but it will definitely be worthwhile to attend. In case you are interested, follow .
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Generative AI is the biggest tech issue of our time. We might be witnessing history in the making. At least, so says , who is not only but also has been studying AI and innovation for years and who is part of an inter-disciplinary team that explores the impact of generative AI on professional practices. Together, we decipher what is new and what is not, what is different and what is the same, before and after tools such as ChatGPT and Midjourney entered society at large. As usual, the references to readings we mention are listed on .
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Trivia question: which information systems scholar was a division one tennis professional and has an award-winning MIS Quarterly paper to her name? Of course, it can only be . She joins us today to talk about bots and cyborgs, how to deal with publishing pressures, and how to find a perfect co-author. Our solution is to build a Tinder platform that allows finding the perfect co-author match for your next project. And we agree that you should never put your name on a paper where you do not agree with every single sentence. As usual, the references to readings we mention are listed on .
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