Theory and Theory Development in Information Systems

Registration: Email arto.lanamaki@oulu.fi latest on Friday 11. March 2022

Abstract

This intensive course discusses fundamental concepts of Information Systems, but it also useful for Software Engineering, Organizational and Management Research and Human Computer Interaction students and researchers.

The student learns from this intensive course on characteristics of scientific theory, especially by using information systems (IS) examples. The student also learns some strategies on how theories are discovered. The latter is often termed “theorizing” or “theory development” in the information systems as well as Organizational and Management Research literature. Also, after passing the course, the student should know several misunderstandings of the basic philosophy of science concepts in social science and information systems.

Bio



Mikko Siponen is a full professor of Information Systems (IS). His degrees include Doctor of Social Sciences, majoring in Applied Philosophy; M.Sc. in Software Engineering; Lic.Phil. in information systems; and Ph.D. in Information Systems. Siponen has undertaken several managerial positions, including Vice Dean for Research, Head of Department, Vice Head of Research. He has published more than 80 journal articles. His current H-index is 49, and he has been cited more than 13 800 times. Despite there being several prominent Finnish IS scholars (in Finland and outside of Finland), professor Siponen is the only Information Systems professor who has been invited to be a member of the Finnish Academy of Science and Letters. He is also a holder of the Changjiang (Yangtze River) Scholar award. He is an Honorary Professor in the University of Melbourne.

Program

Day 1: Thursday 24.3.2022

• Lecture 1: some basic philosophical concepts and their common misunderstandings in Information Systems literature
  
  Includes: Positivism, anti-positivism, Popper’s falsification, theory-ladenness, underdetermination versus objective tests
• Lecture 2: Theoretical versus Empirical Contribution in IS
  
  2. Theoretical versus Empirical
  
  2.1. Theoretical versus Empirical in Philosophy of Science
  
  2.2. Theoretical versus Empirical in IS
  
  2.3. Problems of Requiring primarily "Theoretical contribution" and the value of "Empirical" contribution in IS
• Exercises on Empirical Contributions
• Students consider how they could progress in this research (area) by making empirical contributions.

Day 2: Friday 25.3.2022

• Lecture 3: Variance, process, and stage

3. Mohr's variance and process theories

3.1. basic ideas and critique

3.2. How "process" or "variance" is different from MBEs

3.3. Stage Theorizing

3.5 what makes a theory a stage theory?

3.6. Is stage an empirical or theoretical?

3.7. stage as idealization

• Lecture 4: Mechanism-based Explanations
  
  4. Mechanism-based explanations (MBEs)
  
  4.1. History of mechanisms-based explanations
  
  4.2. Modern mechanism accounts as alternative to laws-based explanations
  
  4.3. Common misunderstandings of mechanisms in IS.
  
  4.4 why and how explanations and mechanisms
  
  4.5 laws and causal confusions regarding MBEs
  
  4.6 the ontic conception of explanations
  
  4.7 Deliberate misrepresentations in MBEs
  
  4.8 Naturalism versus critical realism in MBEs
• Lecture 5. On developing Theories

5.1. Discovering and testing stage theories

5.2 Hypothetico-deductive method

5.3 "H-D" in IS

5.4. H-D in the philosophy of science

5.5. why H-D in IS is not a H-D method?

5.6. hypothetico-inductive-qualitative method

5.7 hypothetico-inductive-statistical method

5.8 ”Inductive” methods

Pre-seminar task:

Read the four required articles in the reading list. Prepare to discuss these topics in the seminar.

Required reading:

Siponen, M., Klaavuniemi, T., Nathan, M. (2020) Mechanistic Explanations and Deliberate Misrepresentations. Proceedings of the 53nd HICSS conference.

Siponen, M., Klaavuniemi, T. 2021. Demystifying Beliefs about the Natural Sciences in IS. Journal of Information Technology 36(1).

Siponen, M. & Klaavuniemi, T. 2020. Why Is the Hypothetico-Deductive (H-D) Method in Information Systems Not an H-D Method. Information and Organizations, Volume 30, Issue 1.

Williams, J. N., & Tsang, E. W. (2015). Classifying generalization: paradigm war or abuse of terminology. Journal of Information Technology, 30(1): 18-29.

Extended reading list:

Inductive methods, H-D, theory development methods:

Laudan, L. (1980). Why was the logic of discovery abandoned? In Nickles (Ed.). Scientific discovery, logic, and rationality (pp. 173–183). D. Reidel Publishing Company.

Siponen, M., Soliman, W., Holtkamp, P. 2021. Research Perspectives: Reconsidering the Role of Research Method Guidelines for Qualitative, Mixed Methods, and Design. Journal of the Association for Information Systems 22(4), Article 1.

Mechanisms: Hedström, P & Ylikoski, P. (2010) Causal Mechanisms in the Social Sciences. Annual Review of Sociology 36:49-67.

H-D, inductive, deductive:

Salmon, M. (1975). Confirmation and Explanation in Archaeology. American Antiquity, 40(4), 459–464.

Salmon, M. (1976). “Deductive” versus “inductive” archaeology. American Antiquity, 41(3), 376–381.

Theory/theoretical contribution:

Iivari, J. (2020) A critical look at theories in design science research. Journal of the Association for Information Systems 21(3), 502–519.

Siponen, M. & Klaavuniemi, T. (2019). How and Why ‘Theory’ Is Often Misunderstood in Information Systems Literature. Proceedings of the International Conference on Information Systems 2019, München, Germany.

Siponen, M. & Baskerville, R. (2018). Intervention Effect Rates as a Path to Research Relevance: Information Systems Security Example. Journal of the Association for Information Systems 19(4): 247-265.

Siponen, M., & Klaavuniemi, T. (2021). The Primary Scientific Contribution Is Hardly a Theory in Design Science Research. In L. C. Kruse, S. Seidel, & G. I. Hausvik (Eds.), DESRIST 2021: The proceedings of the 16th International Conference on Design Science Research in Information Systems and Technology. The Next Wave of Sociotechnical Design (pp. 137-146). Springer. Lecture Notes in Computer Science, 12807.

Ågerfalk, P.: Insufficient theoretical contribution: a conclusive rationale for rejection? European Journal of Information Systems 23, 593–599 (2014). https://doi.org/10.1007/978-3-030-82405-1_16

Stage models:

Schwarzer, R., 2008. Some burning issues in research on health behavior change. Applied Psychology 57 (1), 84–93.

Tsohou, A., Siponen, M., Newman, M. 2020. How does information technology-based service degradation influence consumers’ use of services? An information technology-based service degradation decision theory. Journal of Information Technology, 35(1): 2-24.

Weinstein, N.D., Rothman, A.J., Sutton, S.R., 1998. Stage theories of health behavior: conceptual and methodological issues. Health Psychology 17 (3), 290–299.

Post-seminar task:

- Choose one topic from the seminar and link it to your own research

- Write a short essay: three pages minimum, five pages maximum.

- Your essay should contain at least five scientific references that you integrate into your own text.

You can use the references on the above reading list, but also other academic sources can be used.

- Deadline two weeks after the seminar: Friday 8 April 2022.