Some academics go into the office every day; some are rarely ever seen on campus. Is one way better than the other? Who better to ask than the brilliant Ella Hafermalz who spent her career on the topic of remote work and its implications for belonging, community, collaboration, and performance. She points out that academia has always been a distributed and flexible profession. Researchers need flexibility and freedom to figure out their own best way of solving problems and doing their work, some of which may mean sitting at a desk, but maybe also involve lab or field work. On the other hand, pure freedom for individual academics makes a university nothing more than a collection of hired guns without a true community. How do we find the best balance and what is a good balance to begin with? Episode reading list Chang, S. (2025): China's unemployed young adults who are pretending to have jobs. BBC News, 11 August 2025, https://www.bbc.com/news/articles/cdd3ep76g3go. Hafermalz, E., & Riemer, K. (2021). Productive and Connected While Working from Home: What Client-facing Remote Workers can Learn from Telenurses about 'Belonging Through Technology'. European Journal of Information Systems, 30(1), 89-99. Huysman, M. (2025). Studying AI in the Wild: Reflections from the AI@Work Research Group. Journal of Management Studies, https://doi.org/10.1111/joms.70021. The Professor and the Madman. https://www.imdb.com/title/tt5932728/. Hafermalz, E. (2021). Out of the Panopticon and into Exile: Visibility and Control in Distributed New Culture Organizations. Organization Studies, 42(5), 697–717. Rovelli, C. (2022). Helgoland: The Strange and Beautiful Story of Quantum Physics. Penguin Books. Carroll, S. (2019). Something Deeply Hidden: Quantum Worlds and the Emergence of Spacetime. Dutton. Sting, F. J., Tarakci, M., & Recker, J. (2024). Performance Implications of Digital Disruption in Strategic Competition. MIS Quarterly, 48(3), 1263-1278. Archive.org: Philosophy 185 Heidegger: Lectures from the course Philosophy 185 Heidegger by Hubert Dreyfus. https://fourble.co.uk/podcast/philosophy185heidegger. Baudrillard, J. (1981). Simulacra and Simulation. University of Michigan Press. Retkowsky, J., Hafermalz, E., & Huysman, M. (2024). Managing a ChatGPT-empowered Workforce: Understanding its Affordances and Side Effects. Business Horizons, 67(5), 511-523. Haubrich, G. F., Soekijad, M., & Hafermalz, E. (2025). 'What's Up with Work?'Bringing Screens into a Theory of Hybrid Working Situations. Academy of Management Annual Meeting Proceedings, https://doi.org/10.5465/AMPROC.2025.10670abstract. Tekeste, M. (2025). Under Pressure: Becoming the Good Enough Academic. Organization, https://doi.org/10.1177/13505084251383285. LinkedIn Community: The Digital Visibility Group: https://www.linkedin.com/groups/13346086/.

A key problem in empirically oriented research, especially inductive and abductive work, is figuring out which theoretical lens or scaffold to apply to uncover novel insights. In other words, which theory should you use? We discuss a few heuristics scholars can draw on to reach a higher level of scholarly maturity, namely disposition, empirical salience, outcome definition, skepticism, and reflexivity. Episode reading list Recker, J. (2021). Scientific Research in Information Systems: A Beginner's Guide (2nd ed.). Springer. Quine, W. V. O. (1961). Two Dogmas of Empiricism. In W. V. O. Quine (Ed.), From a Logical Point of View (pp. 20-46). Cambridge University Press. Duhem, P. (1998). Physical Theory and Experiment. In M. Curd & J. A. Cover (Eds.), Philosophy of Science: The Central Issues (pp. 257-279). Norton. Popper, K. R. (1959). The Logic of Scientific Discovery. Basic Books. Glikson, E., & Woolley, A. W. (2020). Human Trust in Artificial Intelligence: Review of Empirical Research. Academy of Management Annals, 14(2), 627-660. 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. Kotter, J. P. (1996). Leading Change. Harvard Business School Press. Kerr, N. L. (1998). HARKing: Hypothesizing After the Results are Known. Personality and Social Psychology Review, 2(3), 196-217. 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. Lindberg, A., Berente, N., Gaskin, J., & Lyytinen, K. (2016). Coordinating Interdependencies in Online Communities: A Study of an Open Source Software Project. Information Systems Research, 27(4), 751-772. Chandar, B. (2025): AI and Labor Markets: What We Know and Don't Know. https://digitaleconomy.stanford.edu/news/ai-and-labor-markets-what-we-know-and-dont-know/.

Most think that algorithms are the modern root cause of innovations. But Marta Stelmaszak says not only are organizations today powered by data, they innovate through data. With several other colleagues, Marta is bringing data studies back to the forefront of information systems research. She produces workshops, a forthcoming book, and an online bibliography with seminal readings. We talk to Marta about the relationship between data and meaning, representation versus innovation, and whether we all soon live in a hyperreality created through synthetic data that lost all connection to the real-world. Episode reading list Alaimo, C., & Kallinikos, J. (2022). Organizations Decentered: Data Objects, Technology and Knowledge. Organization Science, 33(1), 19-37. Aaltonen, A., Stelmaszak, M., & Xu, D. The Data Studies Bibliography. https://www.datastudiesbibliography.org/. Chen, H., Chiang, R., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impacts. MIS Quarterly, 36(4), 1165-1188. Wand, Y., & Wang, R. Y. (1996). Anchoring Data Quality Dimensions in Ontological Foundations. Communications of the ACM, 39(11), 86-95. Xu, D., Stelmaszak, M., & Aaltonen, A. (2025). What is Changing the Game in Data Research? Insights from the "Innovating in Data-based Reality" Professional Development Workshop. Communications of the Association for Information Systems, 56(8), 194-208. Kent, W. (1978). Data and Reality. North-Holland. Hirschheim, R., Klein, H. K., & Lyytinen, K. (1995). Information Systems Development and Data Modeling: Conceptual and Philosophical Foundations. Cambridge University Press. Goodhue, D. L., Wybo, M. D., & Kirsch, L. J. (1992). The Impact of Data Integration on the Costs and Benefits of Information Systems. MIS Quarterly, 16(3), 239-311. Aaltonen, A., & Stelmaszak, M. (2024). Data Innovation Lens: A New Way to Approach Data Design as Value Creation. SSRN, https://ssrn.com/abstract=4574855. 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. Bowker, G. C., & Star, S. L. (1999). Sorting Things Out: Classification and Its Consequences. MIT Press. Baudrillard, J. (1981). Simulacra and Simulation. University of Michigan Press. Harari, Y. N. (2024). Nexus: A Brief History of Information Networks from the Stone Age to AI. Random House. Wittgenstein, L. (1953). Philosophical Investigations. Basil Blackwell. Stelmaszak, M., Wagner, E., & DuPont, N. N. (2024). Recognition in Personal Data: Data Warping, Recognition Concessions, and Social Justice. MIS Quarterly, 48(4), 1611-1636. Aaltonen, A., Stelmaszak, M., & Lyytinen, K. (Eds.). (2026). Research Handbook on Digital Data: Interdisciplinary Perspectives. Edward Elgar Publishing.

When we discuss artificial intelligence, what metaphors do we use to illustrate what we mean? Is artificial intelligence some sort of robot—like Ultron—or is it an organism—like a beehive? What happens to our expectations, our thinking, and our conclusions when we change these metaphors, say, from an entitative metaphor (say, an agent) to a relational metaphor (say, belonging to our work network)? We discuss these points with Angelos Kostis and Paavo Ritala who wrote a very interesting paper on how management scholars think about artificial intelligence. Episode reading list Ramaul, L., Ritala, P., Kostis, A., & Aaltonen, P. (2025). Rethinking How We Theorize AI in Organization and Management: A Problematizing Review of Rationality and Anthropomorphism. Journal of Management Studies, https://doi.org/10.1111/joms.13246. Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing Artificial Intelligence. MIS Quarterly, 45(3), 1433-1450. Alvesson, M., & Sandberg, J. (2020). The Problematizing Review: A Counterpoint to Elsbach and Van Knippenberg's Argument for Integrative Reviews. Journal of Management Studies, 57(6), 1290-1304. Berente, N. (2020). Agile Development as the Root Metaphor for Strategy in Digital Innovation. In S. Nambisan, K. Lyytinen, & Y. Yoo (Eds.), Handbook of Digital Innovation (pp. 83-96). Edward Elgar. Pepper, S. C. (1942). World Hypotheses: A Study in Evidence. University of California Press. Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at Work. The Quarterly Journal of Economics, 140(2), 889-942. Russell, S. J., & Norvig, P. (2010). Artificial Intelligence: A Modern Approach (3rd ed.). Prentice Hall. Jarrahi, M. H., & Ritala, P. (2025). Rethinking AI Agents: A Principal-Agent Perspective. California Management Review Insights, https://cmr.berkeley.edu/2025/07/rethinking-ai-agents-a-principal-agent-perspective/. Boxenbaum, E., & Pedersen, J. S. (2009). Scandinavian Institutionalism – a Case of Institutional Work. In T. B. Lawrence, R. Suddaby, & B. Leca (Eds.), Institutional Work: Actors and Agency in Institutional Studies of Organizations (pp. 178-204). Cambridge University Press. Iivari, J., & Lyytinen, K. (1998). Research on Information Systems Development in Scandinavia-Unity in Plurality. Scandinavian Journal of Information Systems, 10(1), 135-186. Alvesson, M., & Sandberg, J. (2024). The Art of Phenomena Construction: A Framework for Coming Up with Research Phenomena beyond 'the Usual Suspects'. Journal of Management Studies, 61(5), 1737-1765. Brunsson, N. (2003). The Organization of Hypocrisy: Talk, Decisions, and Actions in Organizations. Copenhagen Business School Press. Floyd, C., Mehl, W.-M., Reisin, F.-M., Schmidt, G., & Wolf, G. (1989). Out of Scandinavia: Alternative Approaches to Software Design and System Development. Human-Computer Interaction, 4(4), 253-350. Grisold, T., Berente, N., & Seidel, S. (2025). Guardrails for Human-AI Ecologies: A Design Theory for Managing Norm-Based Coordination. MIS Quarterly, 49, https://doi.org/10.25300/MISQ/2025/18058. Forster, E. M. (1909). The Machine Stops. The Oxford and Cambridge Review, November 1909, https://www.cs.ucdavis.edu/~koehl/Teaching/ECS188/PDF_files/Machine_stops.pdf.

We are together in South Bend and teach a class to PhD students in the Mendoza College of Business at the University of Notre Dame. Our joint teaching experience makes us wonder: What should all doctoral students learn or what should we all teach the next generation of IS students? We come up with Nick's rules for a good PhD education: First, understand what knowledge and inferences are. Second, learn different methods and then deep dive into a primary method. Third, pick a domain and learn its foundations and history. Fourth, develop a mindset of mastery to become the world's expert on your topic. And finally, develop and hone your writing skills. Episode reading list Bacon, F. (1620/2019). Novum Organum. Anodos. Hume, D. (1748/1998). An Enquiry Concerning Human Understanding. In J. Perry & M. E. Bratman (Eds.), Introduction to Philosophy: Classical and Contemporary Readings (3rd ed., pp. 190-220). Oxford University Press. Popper, K. R. (1959). The Logic of Scientific Discovery. Basic Books. Yin, R. K. (2009). Case Study Research: Design and Methods (4th ed.). Sage Publications. Berente, N., Ivanov, D., & Vandenbosch, B. (2007). Process Compliance and Enterprise Systems Implementation. In: Proceedings of the 40th Annual Hawaii International Conference on System Sciences. Waikoloa, Hawaii, pp. 222-231. Castelo, N., Bos, M. W., & Lehmann, D. R. (2019). Task-Dependent Algorithmic Aversion. Journal of Marketing Research, 56(5), 809-825. Recker, J. (2021). Scientific Research in Information Systems: A Beginner's Guide (2nd ed.). Springer. Mackie, J. L. (1965). Causes and Conditions. American Philosophical Quarterly, 2(4), 245-264. Gable, G. G. (1994). Integrating Case Study and Survey Research Methods: An Example in Information Systems. European Journal of Information Systems, 3(2), 112-126. Chalmers, A. F. (2013). What Is This Thing Called Science? (4th ed.). Hackett. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2001). Experimental and Quasi-Experimental Designs for Generalized Causal Inference (2nd ed.). Houghton Mifflin. Taylor, F. W. (1911). The Principles of Scientific Management. Harper and Bros. March, J. G., & Simon, H. A. (1958). Organizations. John Wiley & Sons. Nelson, R. R., & Winter, S. G. (1982). An Evolutionary Theory of Economic Change. Harvard University Press.

One of the big topics at the AOM 2025 conference this summer was the use of large language models in the research process, especially in qualitative studies. We expand this discussion by asking: can qualitative research be automated—or augmented? Yes and no. Some of the advantages LLMs bring to the table are hard to ignore. LLMs can act as critical reviewers, as a consistency checker, as a provider of alternative perspectives on unstructured data, or to break path dependencies in the process of data analysis. They can also help find interesting outcomes that qualitative insights could explain. At the same time, the use of LLMs comes with thorny pitfalls. We know they are unreliable and hallucinate. And the output they create is… average at best. So if you use LLMs, make sure you are not using it for automation—do not lose touch with your craft or your data. Whatever tool you use, make sure you remain a virtuous scholar. Episode reading list Noblit, G. W., & Hare, R. D. (1988). Meta-Ethnography: Synthesising Qualitative Studies. Sage. Recker, J. (2021). Improving the State-Tracking Ability of Corona Dashboards. European Journal of Information Systems, 30(5), 476-495. Rynes, S., & Gephart Jr., R. P. (2004). Qualitative Research and the "Academy of Management Journal". Academy of Management Journal, 47(4), 454-462. Geertz, C. (1973). The Interpretation Of Cultures. Basic Books. Boland, R. J. (2001). The Tyranny of Space in Organizational Analysis. Information and Organization, 11(1), 3-23. Weber, R. (2004). Editor's Comments: The Rhetoric of Positivism Versus Interpretivism: A Personal View. MIS Quarterly, 28(1), iii-xii. Lehmann, J., Hukal, P., Recker, J., & Tumbas, S. (2025). Layering the Architecture of Digital Product Innovations: Firmware and Adapter Layers. Journal of the Association for Information Systems, 26, https://doi.org/10.17705/1jais.00956. 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. Ragin, C. C. (1987). The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. University of California Press. Goodhue, D. L., Lewis, W., & Thompson, R. L. (2012). Comparing PLS to Regression and LISREL: A Response to Marcoulides, Chin, and Saunders. MIS Quarterly, 36(3), 703-716. Goodhue, D. L., Lewis, W., & Thompson, R. L. (2007). Statistical Power in Analyzing Interaction Effects: Questioning the Advantage of PLS With Product Indicators. Information Systems Research, 18(2), 211-227.

A new season of podcast episodes is starting and what better place to kick it off as the world's largest business and management conference. We are recording this episode at AOM 2025 in beautiful Copenhagen, made possible through a generous invite from Attila Marton from CBS who organized a recording studio for us. Being here amid symposia, professional development workshops, panels, and paper presentations makes us wonder: what does it take to produce great, stimulating, and productive academic discourse? Does it depend on the people that get invited to speak, is it about their ideas, or what else? We sit down with our friend Philip Hukal with whom we share some stories from the events we've attended at AOM and we distil a few rules that characterize good intellectual debate: let there be cognitive conflict about the merit of ideas, be bold enough to propose new ideas, show humility for the craft and work of others, and be respectful to your colleagues. Episode reading list Kulkarni, M., Mantere, S., Vaara, E., van den Broek, E., Pachidi, S., Glaser, V. L., Gehman, J., Petriglieri, G., Lindebaum, D., Cameron, L. D., Rahman, H. A., Islam, G., & Greenwood, M. (2024). The Future of Research in an Artificial Intelligence-Driven World. Journal of Management Inquiry, 33(3), 207-229. Brynjolfsson, E., Collis, A., Diewert, W. E., Eggers, F., & Fox, K. J. (2025). GDP-B: Accounting for the Value of New and Free Goods. American Economic Journal: Macroeconomics, https://doi.org/10.1257/mac.20210319. Stelmaszak, M., Wagner, E., & DuPont, N. N. (2024). Recognition in Personal Data: Data Warping, Recognition Concessions, and Social Justice. MIS Quarterly, 48(4), 1611-1636. Habermas, J. (1984). Theory of Communicative Action, Volume 1: Reason and the Rationalization of Society. Heinemann. Lehmann, J., Hukal, P., Recker, J., & Tumbas, S. (2025). Layering the Architecture of Digital Product Innovations: Firmware and Adapter Layers. Journal of the Association for Information Systems, 26, https://doi.org/10.17705/1jais.00956.

Is there collusion in our field? Do we have elites running wild, making sure that their work gets published whilst the rest of us struggles to find room to publish our own work? And are we handling conflicts of interest that may exist between authors and the editors who are charged with making decisions about their work? These are serious questions. They target the core of our field, they have the potential to undermine – or bolster – the legitimacy of all our scholarship, and they pose serious material consequences for all scholars, their careers and ultimately their lives. We came across a new paper that reports an analysis of the potential conflict of interest issues in academic publishing, and we use this paper to reflect on our experiences as both authors and editors. We try to draw a few conclusions and recommendations about how we can raise awareness and build institutional trust to minimize if not avoid any questionable or outright unethical practices in publishing. Episode reading list Association for Information Systems. AIS Podcast Library, https://aisnet.org/page/aispodcast. Mindel, V., & Ciriello, R. (2025). Safeguarding Academic Legitimacy: Editorial Conflicts of Interest as a Principal-Agent Problem in Elite Business Journals. SSRN, https://ssrn.com/abstract=5315585. Recker, J., Rosemann, M., Green, P., & Indulska, M. (2011). Do Ontological Deficiencies in Modeling Grammars Matter? MIS Quarterly, 35(1), 57-79. 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. Kane, G. C., Young, A., Majchrzak, A., & Ransbotham, S. (2021). Avoiding an Oppressive Future of Machine Learning: A Design Theory for Emancipatory Assistants. MIS Quarterly, 45(1), 371-396. Grisold, T., Berente, N., & Seidel, S. (2025). Guardrails for Human-AI Ecologies: A Design Theory for Managing Norm-Based Coordination. MIS Quarterly, https://doi.org/10.25300/MISQ/2025/18058. Boh, W., Melville, N. P., Baptista, J., Chasin, F., Horita, F., Ixmeier, A., Johnson, S. L., Ketter, W., Kranz, J., Miranda, S. M., Nan, N., Pentland, B. T., Recker, J., Sadeghi, S., Sarker, S., Sarker, S., Sutanto, J., Wang, P., & Wilopo, W. (2025). Digital Resilience for the Climate Crisis: Theoretical Perspectives and Ideas for Future Information Systems Research. MIS Quarterly, forthcoming. Merton, R. K. (1968). The Matthew Effect in Science. Science, 159(3810), 56-63. Tiwana, A., & Safadi, H. (2025). Silence Inside Systems: Roots and Generativity Consequences. Information Systems Research, https://doi.org/10.1287/isre.2022.0586. 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. Pienta, D., Vishwamitra, N., Somanchi, S., Berente, N., & Thatcher, J. B. (2025). Do Crowds Validate False Data? Systematic Distortion and Affective Polarization. MIS Quarterly, 49(1), 347-366.

Which research methods are better, quantitative or qualitative? What is more important, getting a richer picture of what goes on in organizations, or seeking generalizable insights about causality? This debate has raged at the very least since Glaser and Strauss popularized the grounded theory method in the mid twentieth century. In 2025, we want to put this debate to rest. We asked one of the best econometric scholars we know (Brad Greenwood) and one of the best qualitative scholars we know (Youngjin Yoo) to fight this debate on air and come up with their very own end-of-all arguments. The result? It may surprise you: We all ought to get mad. Episode reading list Chang, H. (2008). Inventing Temperature: Measurement and Scientific Progress. Oxford University Press. Burtch, G., Carnahan, S., & Greenwood, B. N. (2018). Can You Gig It? An Empirical Examination of the Gig Economy and Entrepreneurial Activity. Management Science, 64(12), 5497-5520. Greenwood, B. N., Kobayashi, B. H., & Starr, E. P. (2025). Can You Keep a Secret? Banning Noncompetes Does Not Increase Trade Secret Litigation. SSRN, https://ssrn.com/abstract=4771171. Kraemer, K. L., Dickhoven, S., Tierney, S. F., & King, J. L. (1987). Datawars: The Politics of Modeling in Federal Policymaking. Columbia University Press. Roth, J., Sant'Anna, P. H. C., Bilinski, A., & Poe, J. (2023). What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature. Journal of Econometrics, 235(2), 2218-2244. 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. Levitt, S. D., & Dubner, S. J. (2005). Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. William Morrow. Greenwood, B. N., & Wattal, S. (2017). Show Me the Way to Go Home: An Empirical Investigation of Ride-Sharing and Alcohol Related Motor Vehicle Fatalities. MIS Quarterly, 41(1), 163-187. King, A. A. (2025). Does Corporate Social Responsibility Increase Access to Finance? A Commentary on Cheng, Ioannou, and Serafeim (2014). Strategic Management Journal, forthcoming. https://doi.org/10.2139/ssrn.4647425. Seidel, S., Frick, C. J., & vom Brocke, J. (2025). Regulating Emerging Technologies: Prospective Sensemaking through Abstraction and Elaboration. MIS Quarterly, 49(1), 179-204. Pentland, B. T. (1999). Building Process Theory with Narrative: From Description to Explanation. Academy of Management Review, 24(4), 711-725. Lee, J., & Berente, N. (2013). The Era of Incremental Change in the Technology Innovation Life Cycle: An Analysis of the Automotive Emission Control Industry. Research Policy, 42(8), 1469-1481. Anderson, P., & Tushman, M. L. (1998). Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change. Administrative Science Quarterly, 35(4), 604-633. Brynjolfsson, E., & Hitt, L. M. (1996). Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending. Management Science, 42(4), 541-558. Noe, R. (2025). Moral Incoherence During Category Emergence: The Contentious Case of Connected Toys. Harvard Business School Working Paper, 24-071, https://www.hbs.edu/faculty/Pages/item.aspx?num=65988.

We continue with our special "Ask us anything" episode to celebrate the centenary of the This IS Research podcast. This time, we handle questions such as "do we have to worry about ontology?" - No; "should we engage in community building?" Yes; and "what have you learned from the podcast?" A whole lot - and we hope you have learned a thing or two along the way as well. Episode reading list Meyer, J. W., & Rowan, B. (1977). Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology, 83(2), 340-363. James, W. (1907). Pragmatism: A New Name for Some Old Ways of Thinking. Hackett Publishing. 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. Faik, I., Barrett, M., & Oborn, E. (2020). How Information Technology Matters in Societal Change: An Affordance-Based Institutional Perspective. MIS Quarterly, 44(3), 1359-1390. Leonardi, P. M. (2010). Digital Materiality? How Artifacts Without Matter, Matter. First Monday, 15(6), https://doi.org/10.5210/fm.v15i6.3036. Goebeler, L., Hukal, P., & Xiao, X. (2024). Four Roles of Physicality in Digital Innovation: A Theoretical Review. Journal of Strategic Information Systems, 33(4), 101862. Faulkner, P., & Runde, J. (2019). Theorizing the Digital Object. MIS Quarterly, 43(4), 1279-1302. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., . . . 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.