DE / EN

Theory in Information Systems Research

IS 903 for Doctoral program (Center for Doctoral Studies in Business)

General Information

Spring 2022
Lecturer Dr. Monica Fallon
Course Format Seminar
Credit Points 8 ECTS
Language English
Grading Theory Presentation (33%), Class Discussion (33%), Discussion Leader (33%)
Information for Students Registration: CDSB Website
Dr. Monica Fallon

Dr. Monica Fallon

Contact person IS Theories

For further information please contact Monica Fallon.

Course Information

  • Brief Description

    Knowledge creation and dissemination are key objectives of scientific endeavors. However, what constitutes knowledge is a highly contested issue. Certainly, at the core of social science disciplines, knowledge is inseparable from theory. Indeed, to seek theory- guided explanations of real-world phenomenon is what separates scholars from consultants, who seek to change reality without explaining it, and from journalists, who report reality but do not explain it. The pursuit of theory drives us to understand reality—to discover truth—before making recommendations on how to change reality. To pursue theory is to pursue knowledge; to pursue knowledge is to advance humanity. Consequently, many scholars emphasize the centrality of theories for any scientific endeavor—a thought widely reflected in many disciplines from the natural to the social sciences. While attention to theoretical work has been at the heart of the Information Systems (IS) discipline for a long time, the focus on theoretical debates and genuine conceptual contributions has been picking up recently. This is reflected by a number of journal sections and conference tracks dedicated to advancing theory and theorizing in IS research and just as much as in many authors’ experiences during the reviews of their work.

    This course invites participants to join the ongoing discourse on theories and theorizing in IS research. It is designed to help participants build and extend their understanding of the nature and role of theory in IS research. Through discussions and analyses of current theoretical developments in the IS discipline and some of its main reference disciplines, participants will engage with theory and advance their skills of crafting their own theoretical contributions and evaluating those of others.

    Course Objectives

    • To understand the importance and usefulness of theory in research 
    • To learn theorizing strategies 
    • To learn to evaluate theoretical contribution in research 
    • To develop basic theorizing skills 
    • To identify a theory that could be applicable to the participants’ own research programs 
  • Course Structure and Grading

    This course will be driven by discussion and as such students are expected to come prepared for each class, having read and thought about all readings. During the kick-off session, each student will volunteer to lead the discussion on the readings for the seven following sessions.

    The purpose of the classes is to discuss what students have learned from the readings—both assigned and otherwise. My role as instructor will be to help guide the discussion, ensure that the key points have been identified and understood, and move the discussion forward. All students are expected to actively participate in the discussion on all readings by sharing their own thinking, raising questions, and making connections among the readings of this course and beyond.

    Theory Presentation

    Each student will present one theory not covered in the course readings that could be applicable to the students’ own research. The presentations will take place during session eight on May 24th. The presentations will be no more than 15 minutes. The presentations are intended to encourage students to select a theory that is appropriate to explain the phenomenon in their own research. The student should plan to explain the main tenets of the theory, name rival theories, and illustrate reasons why the selected theory is better than rival theories for explaining the phenomenon at hand. The students will distribute the slides among participants and present the slides to the class. The final slides should provide references to the seminal work as well as other references, as needed, to the theory.

    Course Grading

    The grade will be based on class discussion, leading the discussion of some of the articles, and a single individual project.

    • Class Discussion: 1/3
    • Discussion Leader: 1/3
    • Theory Presentation: 1/3
  • Lecture

    Schedule

    Date Time Topic(s) Room
    February 22nd 12:00pm – 1:30pm Kick-Off L 15, 1-6, Room 714
    March 1st 12:00pm – 1:30pm Theory Part 1 L 15, 1-6, Room 714
    March 8th 12:00pm – 1:30pm Theory Part 2 L 15, 1-6, Room 714
    March 15th 12:00pm – 1:30pm Theorizing Part 1 L 15, 1-6, Room 714
    March 22nd 12:00pm – 1:30pm Theorizing Part 2 L 15, 1-6, Room 714
    March 29th 12:00pm – 1:30pm Evaluating Theory Contribution L 15, 1-6, Room 714
    April 5th 12:00pm – 1:30pm Theory Contribution in Different Journals L 15, 1-6, Room 714
    April 26th 12:00pm – 1:30pm Theory Contribution Across Methods L 15, 1-6, Room 714
    May 24th 12:00pm – 1:30pm Student Presentations L 15, 1-6, Room 714
  • Reading List

    Session 1: Theory Part 1

    • Feldman, D. C. (2004). What are we talking about when we talk about theory? Journal of Management, 30(5), 565-567.
    • Gregor, S. (2006). The Nature of Theory in IS Research. MIS Quarterly, 30(3), 611-642.
    • Sutton, R. I. and Staw, B. M. (1995). What theory is not. Administrative Science Quarterly, 40, 371-384.
      • DiMaggio, P. J. (1995). Comments on “What theory is not.” Administrative Science Quarterly, 40, 391-397.
      • Weick, K. E. (1995). What theory is not, theorizing is. Administrative Science Quarterly, 40, 385-390.

    Session 2: Theory Part 2

    • Avison, D. and Malaurent, J. (2014). Is theory king? Questioning the theory fetish in Information Systems. Journal of Information Technology, 29, 327-336.
      • Lee, A. (2014). Theory is king? But first, what is theory? Journal of Information Technology, 29, 350-352.
      • Silverman, D. (2014). Taking theory too far? A commentary on Avison and Malaurent. Journal of Information Technology, 29, 353-355.
      • Gregor, S. (2014). Theory – still king but needing a revolution! Journal of Information Technology, 29, 337-340.
      • Markus, M. L. (2014). Maybe not the king, but an invaluable subordinate: A commentary on Avison and Malaurent’s advocacy of ‘theory light’ IS research. Journal of Information Technology, 29, 341-345.

    Session 3: Theorizing Part 1

    • Colquitt, J. and Zapata-Phelan, C. (2007). Trends in theory building and theory testing: A five-decade study of the Academy of Management Journal. Academy of Management Journal, 50(6), 1281-1303.
    • Alvesson, M. and Sandberg, J. (2011). Generating research questions through problematization. Academy of Management Review, 36(2), 247-271.
    • Poole, M. S. and van de Ven, A. H. (1989). Using paradox to build management and organization theories. Academy of Management Review, 14(4), 562-678.

    Session 4: Theorizing Part 2

    • Shepherd, D. and Sutcliffe, K. M. (2011). Inductive top-down theorizing: A source of new theories of organization. Academy of Management Review, 26(2), 361-380.
    • Oswick, C., Fleming, P., and Hanlon, G. (2011). From borrowing to blending: Rethinking the processes of organizational theory building. Academy of Management Review, 36(2), 318-327.
    • Hong, W., Chan, F., Thong, J. Chasalow, L., and Dhillon, G. (2014). A framework and guidelines for context-specific theorizing in Information Systems research. Information Systems Research, 24(1), 111-136.

    Session 5: Evaluating Theory Contribution

    • Whetten, D. (1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), 490-495.
    • Corley, K. G. and Gioia, D. A. (2011). Building theory about theory: What constitutes a theoretical contribution. Academy of Management Review, 36(10), 12-32.
    • Bacharach, S. B. (1989). Organizational theories: Some criteria for evaluation. Academy of Management Review, 14(4), 496-515.
    • Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14(3), 221-243.
    • Agerfalk, P. J. (2014). Insufficient theoretical contribution: A conclusive rationale for rejection? European Journal of Information Systems, 23, 593-599.

    Session 6:Theory Contribution Examples from Different IS Journals

    • Seeger, A. M., Pfeiffer, J., & Heinzl, A. (2021). Texting with humanlike conversational agents: Designing for anthropomorphism. Journal of the Association for Information Systems, 22(4), 931–967.
    • 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.
    • Spohrer, K., Fallon, M., Hoehle, H., & Heinzl, A. (2021). Designing effective mobile health apps: Does combining behavior change techniques really create synergies? Journal of Management Information Systems, 38(2), 517–545.
    • 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): 1179–1206.

    Session 7: Theory Contribution Across Methods (holding journal constant)

    • Mixed-Methods: Jussupow, E., Spohrer, K., Heinzl, A., & Gawlitza, J. (2021). Augmenting medical diagnosis decisions? An investigation into physicians’ decision-making process with artificial intelligence. Information Systems Research, 32(3), 713–735.
    • Survey: Kude, T., Mithas, S., Schmidt, C. T., & Heinzl, A. (2019). How Pair Programming Influences Team Performance: The Role of Backup Behavior, Shared Mental Models, and Task Novelty. Information Systems Research, 30(4), 1145–1163.
    • Panel Data: Chen, H., De, P., and Hu, Y. H. (2015). IT-enabled broadcasting in social media: an empirical study of artists’ activities and music sales. Information Systems Research, 26(3), 513-531.
    • Experiment: Adomavicius, G., Bockstedt, J. C., Curley, S. P., and Zhang, J. (2013). Do recommender systems manipulate consumer preferences? A study of anchoring effects. Information Systems Research, 24(4), 956-975.