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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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One of the biggest cases of academic misconduct in recent times has been the case involving Francesca Gino, Dan Ariely, and Max Bazerman. Is there anything we can learn from this case and how it was handled? Nick and Jan are back from the winter break and dig straight into questionable research practices, whistleblowers, senior co-authors and what we as a field should be doing to prevent fraud to undermine our research contributions. As usual, the references to readings we mention are listed on .
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As the year draws to a close, it is time for us to revisit some of the best IS scholarship that got published this year. Yes, time for the 3rd annual thisISresearch podcast awards. This year, it was particularly tough to choose so we just invented a new award! Tune in to find out who won the trailblazing research award, the innovative method award, and our brand-new elegant scholarship award! As usual, the references to readings we mention are listed on .
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What is so special about digital technology? Is digital innovation about architecture or is it about data? We talk with the enigmatic – truly one of the great thinkers in our field. Our conversation covers the ambivalence of digital objects, the role of data as records in organizations, the role of books in expressing broader ideas in scholarship, and whether information systems can or should delve into metaphysics at all. As usual, the references to readings we mention are listed on .
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Nick and Jan venture into new publishing territory. We talk with the fabulous , one of the information systems department editors at , about journal procedures, reviewer expectations, and innovations in the review process. We discuss how our field nurtures multiple communities that all share the aim of advancing information systems knowledge and scholarship. And it’s fair to say that both Nick and Jan now have Management Science more on the radar screen as an information systems outlet than before we produced this episode. As usual, the references to readings we mention are listed on .
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ChatGPT is back in our podcast one more time. Last time we talked about its impact on the academic enterprise. But ChatGPT is also the key digital technology issue of our time. It should be researched, of course, and we information systems researchers should jump on the opportunity to learn more about it. What are some of the questions that surround ChatGPT and similar forms of generative artificial intelligence? We look at a few research ideas at the individual, collective, firm, and economic level. And we conclude that whatever topic people are researching, their key challenge will be to theorize about what’s different with generative artificial intelligence and what is not. As usual, the references to readings we mention are listed on .
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Or maybe it did not. Who knows? ChatGPT is here for the world to see and not even our podcast can avoid talking about it. All the firms we know have long started exploring ChatGPT and other generative AI technologies. Will generative AI also change the academic enterprise? Some suggest it already has. We think we are at the cusp of changes, both in degree and in kind. ChatGPT may help people get started and may even alleviate some of the laborious research tasks but at the end of the day, the academic profession is a person-centric profession built around individual expertise, trust, and honesty of knowledgeable academics. You cannot automate that. As usual, the references to readings we mention are listed on .
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IS as a field has the same problem that IT departments have in organizations - we think those other people should come to us with their questions about digitalization and benefit from our decades of wisdom! But we argue that this is not going to happen. It is our job (as it is the IT manager's job) to make the case for how we can help. OK, so that's a portion of what we talk about today. We actually meander a bit. We jump across a whole lot of topics, from IS' status as a reference discipline, the quarrels of IT departments with other business divisions, what our favorite conferences are, how to engage with conversations occurring in other fields, and what is so special about Taylor Swift. So it’s all over the place. But the good news is we laugh a lot and future episodes will be more focused again, we promise. As usual, the references to readings we mention are listed on .
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