(1) The Digital Phenomenon (Abayomi Baiyere)
Overall Focus
Digital is emerging as an oft used conceptual label to characterize age-long phenomena in the Information Systems discipline that hitherto have been described by the IT label. This has taken a formulaic approach, which has been described as Digital “X” – where “X” can be infrastructure, strategy, innovation, capability, etc. Yet, there is a sense in the community that digital and IT are not mere synonyms, but there is something fundamentally different being signaled when the digital label is invoked. This session is focused on tracing the intellectual roots, and ontological foundations of the growing use of digital as a conceptual label in information systems as well as the implications that it holds for future IS scholarship. Participants should expect an interactive hands-on workshop, and are thus, encouraged to engage dutifully with the provided readings and videos prior to the session.
Required readings
Ross, J.W., Beath, C. and Sebastian, I. (2017) Digitized ≠Digital MIT Sloan CISR Briefing 17(10) (4 pages)
Wessel, L., Baiyere, A., Ologeanu-Taddei, R., Cha, J., & Jensen, T. (2020). Unpacking the difference between digital transformation and IT-enabled organizational transformation. Journal of Association of Information Systems
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: toward a next generation of insights. MIS Quarterly, 471-482.
Baiyere, A., Salmela, H., & Tapanainen, T. (2020). Digital transformation and the new logics of business process management. European Journal of Information Systems, 1-22
Baskerville, R. L., Myers, M. D., & Yoo, Y. (2020). Digital first: The ontological reversal and new challenges for is research. MIS Quarterly, 44 (2).
Faulkner, P., & Runde, J. (2019). Theorizing the Digital Object. MIS Quarterly, 43(4).
Recommended readings (Workshop materials)
Baiyere, A., Grover, V., Lyytinen, K., Woerner, S., and Gupta, A. (tbd) Digital X: Charting a path for digital themed research.
Baiyere, A., Zimmer, M., Staykova, K., and Jöhnk, J (tbd) Digital vs IT: An empirical unpacking
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary—the new organizing logic of digital innovation: an agenda for information systems research. Information systems research, 21(4), 724-735.
(2) IS Strategy (Stefan Henningsson)
Overall Focus
The IS strategy literature addresses how the IT organization and its leadership can contribute to an organization reaches its strategic objectives. Over time, as the nature of corporate strategy and use of digital technology haves evolved, so has the role of IS strategy. In this session we explore the evolving role of IS strategy in organizations and the refinement of research approaches to adequately account for the phenomenon.
Required readings
Drnevich, P. L., & Croson, D. C. (2013). Information technology and business-level strategy: toward an integrated theoretical perspective. MIS quarterly, 483-509.
Reynolds, P., & Yetton, P. (2015). Aligning business and IT strategies in multi-business organizations. Journal of Information Technology, 30(2), 101-118.
Törmer et al. (Forthcomming) Architecting Innovation-enabling IS Architectures: A configurational perspective
Williams, J. A., Torres, H. G., & Carte, T. (2019). A Review of IS Strategy Literature: Current Trends and Future Opportunities. Journal of Computer Information Systems, 1-11
Recommended readings
Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 66-77.
El Sawy, O. A. (2003). The IS Core IX: The 3 Faces of IS identity: connection, immersion, and fusion. Communications of the Association for Information Systems, 12(1), 39.
Kohli, R., & Grover, V. (2008). Business value of IT: An essay on expanding research directions to keep up with the times. Journal of the association for information systems, 9(1), 1.
Park, Y., Fiss, P. C., & El Sawy, O. A. (2020). Theorizing the Multiplicity of Digital Phenomena: The Ecology of Configurations, Causal Recipes, and Guidelines for Applying QCA. MIS Quarterly.
Wade, M., & Hulland, J. (2004). The resource-based view and information systems research: Review, extension, and suggestions for future research. MIS quarterly, 28(1), 107-142.
(3) Human-Computer Interaction (Chee-Wee Tan)
Human-Computer Interaction (HCI) is a multidisciplinary field of study centering on the design of information technology for human consumption, especially with regards to the interaction between humans (as users) and technological systems. Over time, research into HCI has not only evolved from inquiries of humans’ supraliminal cognitive perceptions to include probes into their metacognitive insensitivite mental activities, but its arsenal of data collection and analytical techniques has also expanded from more conventional methods like experiments and surveys to involve more advanced ones such as Deep Learning, Eye Tracking, and fRMI. In this session, we revisit the evolution in HCI research to discover the latest trends in the field and identify opportunities for future work.
Required readings
Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., and Inkpen, K. (2019) "Guidelines for Human-AI Interaction," Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems: ACM.
Gerlach, J. H., and Kuo, F.-Y. (1991) "Understanding Human-Computer Interaction for Information Systems Design," MIS Quarterly (15:4), pp. 527-549.
Zhang, P., Li, N., Scialdone, M., and Carey, J. (2009) "The Intellectual Advancement of Human-Computer Interaction Research: A Critical Assessment of the MIS Literature (1990-2008)," AIS Transactions on Human-Computer Interaction (1:3), pp. 55-107.
Recommended readings
Cyr, D., Head, M., Larios, H., and Pan, B. (2009) "Exploring Human Images in Website Design: A Multi-Method Approach," MIS Quarterly (33:3), pp. 539-566.
Dimoka, A. (2010) "What Does The Brain Tell Us About Trust and Distrust? Evidence From A Functional Neuroimaging Study." MIS Quarterly (34:2), pp. 373-396.
Jiang, Z., & Benbasat, I. (2007) “The Effects of Presentation Formats and Task Complexity on Online Consumers' Product Understanding,” MIS Quarterly (31:3), pp. 475-500.
Li, Y., Lim, E. T. K., Liu, H., and Liu, Y. (2019) "Seizing Your Market Share: Deciphering the Role of Visual Branding with Deep Residual Networks," in: The 40th International Conference on Information Systems (ICIS 2019), Munich, German.
Zhang, P., Li, N., Scialdone, M., and Carey, J. 2009. "The Intellectual Advancement of Human-Computer Interaction Research: A Critical Assessment of the MIS Literature (1990-2008)," AIS Transactions on Human-Computer Interaction (1:3), pp. 55-107.
(4) Machine Learning and Text Analytics (Raghava Mukkamala)
Overall Focus
Along with the development of machine-learning techniques, automated content analysis or analyzing text using machine-learning techniques, has evolved during the last two decades. However, studying natural language is quite complicated as it is sometimes difficult even for humans to understand the implicit meaning of the texts. On the other hand, advances in machine learning and natural language processing have opened many vast opportunities for analyzing large volumes of text, without which it would not have been possible to analyze them manually. However, one should remember that these methods are to augment Humans, not to replace them. In this topic, a wide range of text analytics methods will be discussed, provide guidance on how to validate the output of the models, and clarify misconceptions and errors.
Required readings
Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political analysis, 21(3), 267-297.
Abbasi, A., & Chen, H. (2008). CyberGate: a design framework and system for text analysis of computer-mediated communication. MIS Quarterly, 811-837.
Kinra, A., Hald, K. S., Mukkamala, R. R., & Vatrapu, R. (2020). An unstructured big data approach for country logistics performance assessment in global supply chains. International Journal of Operations & Production Management.
Recommended readings
Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In Mining text data (pp. 415-463). Springer, Boston, MA.
Abbas, A., Zhou, Y., Deng, S., & Zhang, P. (2018). Text analytics to support sense-making in social media: A language-action perspective. MIS Quarterly, 42(2).
Rizk, A., & Elragal, A. (2020). Data science: developing theoretical contributions in information systems via text analytics. Journal of Big Data, 7(1), 1-26.
(5) Computers, Communication and Collaboration (Mads Bødker)
Overall Focus
The computer has transformed both writing and oral cultures in the past decades. Particularly with the introduction of personal computers in the mid 1980’s, digitalization has profoundly impacted everyday human interaction. In this seminar we will discuss theoretical and conceptual contributions to the understanding of computers in mediating human communication and collaboration practices. Drawing on both foundational historical as well as recent work in the field of communications and medium theory, CSCW, IS and philosophy.
Required readings
Lickliders & Taylor (1968) The Computer as a Communication Device
Winograd & Flores (1986) Understanding Computers and Cognition (excerpts)
Bødker, M., Gimpel, G., & Hedman, J. (2014). Time-out/Time-in: The Dynamics of Everyday Experiential Computing Devices. Information Systems Journal, 24(2), 143-166
Bowers et. al. (1995). Workflow From Within and Without: Technology and Cooperative Work on the Print Industry Shopfloor. Proceedings of ECSCW, 1995.
Murthy, D. (2008). Digital Ethnography: An Examination of the Use of New Technologies for Social Research. Sociology 42 (5).
Recommended readings
Grudin, J. (2005) Three Faces of Human–Computer Interaction, IEEE Annals of the History of Computing
Benford, S. et al. (2012) Supporting Traditional Music-Making: Designing for Situated Discretion, CSCW’12
Hall, S. (1973). Encoding and Decoding in the Television Discourse. University of Birmingham.
Dourish, P. (2006). Implications for Design. ACM CHI’06
(6) Sociomateriality (Ulrike Schultze)
Overall Focus
Sociomateriality is a philosophical stance that explores alternatives to the IS field’s taken-for-granted assumptions around the human-technology relationship. Essential ontological separations between agential subjects (e.g., humans) and passive objects (e.g., technology) are challenged and replaced with notions of relationality, inseparability, performativity, practices, and materiality. Established epistemologies, i.e., positivist, interpretive, and critical modes of constructing knowledge, are seen as insufficient in light of this relational ontology. Methodological practices of data generation, analysis, and re-presentation aligned with sociomateriality tend to rely on material-discursive practices as the unit of analysis and seek ways of preserving the entanglement, performativity, and materiality of phenomena. In order to appreciate the significance of IS’s turn towards sociomaterial theorizing, this session will explore some of the ways in which the relationship between the social (e.g., individuals, organizations) and the material (e.g., technology, data) has previously been conceived.
Required readings
Barley, S. (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. doi:10.2307/2392767
Orlikowski, W. J. (2000). Using technology and constituting structures: A practice lens for studying technology in organizations. Organization Science, 11(4), 404-428.
Sarker, S., Chatterjee, S., Xiao, X., and Elbanna, A. (2019). The sociotechnical axis of cohesion for the is discipline: Its historical legacy and its continued relevance. MIS Quarterly, 43(3), 695-719.
Jones, M. (2014). A Matter of Life and Death: Exploring Conceptualizations of Sociomateriality in the Context of Critical Care. MIS Quarterly, 38(3), 895-925.
Recommended readings
Orlikowski, W. J., & Scott, S. V. (2008). Sociomateriality: Challenging the Separation of Technology, Work and Organization. Annals of the Academy of Management, 2(1), 433-474.
Leonardi, P. (2011). When Flexible Routines Meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies. MIS Quarterly, 35(1), 147-167.
Gosain, S. (2005) Enterprise Information Systems as Objects and Carriers of Institutional Forces: The New Iron Cage? J. Assoc. Inf. Syst., 5(4): 6.
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