A Narrative Review of Critical Realism in Information Systems Research

Document Type : علمی - پژوهشی

Authors

1 Professor, Department of Management, Vali-e-Asr University of Rafsanjan, Kerman, Iran.

2 Ph.D. Student, Department of Information Technology Management, Tarbiat Modares University, Tehran, Iran.

3 Professor, Department of Information Technology Management, Tarbiat Modares University, Tehran, Iran.

Abstract

Introduction and Objective: Research in the field of information systems has undergone significant transformations over the past two decades. These transformations have led to fundamental changes in the methodologies employed in this domain. In this regard, three primary approaches used in information systems studies include positivism, interpretivism, and critical realism, which dictate the theory and methods applied. Each of these approaches has its own specific ontological assumptions along with various strengths and weaknesses. One of the major challenges faced by information systems research is the existence of contradictions between theory and practice within the frameworks of positivism and interpretivism. These contradictions arise from the inconsistencies between the ontological assumptions of researchers and the actual functioning of science, necessitating a reevaluation of the ontological premises of research and practice in information systems. According to the methodology of critical realism, a distinction exists between the "real" and "observable" worlds, with unobservable structures giving rise to observable events. Information systems, characterized by their technical and social nature, can only be understood when the structures that generate events are recognized and comprehended. By emphasizing the importance of philosophical topics, critical realism provides a fruitful context for information systems research, enabling the reinterpretation of scientific activities and the concepts of structures and generative mechanisms. This approach offers greater explanatory power compared to current research methodologies, resolving the contradictions between theory and practice. Thus, this study conducts a systematic review of theoretical foundations using a narrative review approach to develop a comprehensive understanding of practical concepts and specialized perspectives surrounding one of the prominent methods in information systems research, namely critical realism. This study represents a systematic examination of theoretical foundations, presenting findings from a narrative synthesis of previously published information regarding critical realism.
Method: This research employs a systematic narrative review approach aimed at examining the theoretical foundations related to critical realism. For this purpose, the research was conducted in two main steps. In the first step, a search for reputable sources was conducted using two approaches: automated and snowballing, both forward and backward, in recognized databases. Through searching with defined keywords, 137 relevant articles were obtained. In the subsequent phase, these articles were further analyzed using both forward and backward approaches, adding 19 additional valid studies, bringing the total number of articles to 156. Finally, after screening the resources obtained from automated searches, forward and backward methodologies, and eliminating duplicates, 152 sources were found. These sources were assessed based on predefined inclusion and exclusion criteria, resulting in the removal of 103 sources. Ultimately, following a qualitative evaluation of the collected studies, 49 studies were selected for an in-depth review. In the second step, based on the narrative review method and in the context of the SANRA methodological tool guidelines, fundamental concepts related to the methodological framework of critical realism were examined and extracted.
Results: The findings of this study highlight several key points. Firstly, the distinction between the real world and the observable world, which critical realism offers, allows researchers to delve deeper into phenomena and gain a more accurate understanding of the structures influencing information systems. Secondly, by addressing the contradictions between theory and practice, critical realism enables researchers to identify and resolve inconsistencies between theory and practice. Additionally, this research suggests that researchers should utilize dynamic mixed-method approaches that incorporate critical realism in information systems research to enhance the quality and effectiveness of future studies. This is because critical realism provides a realistic position that, while acknowledging criticisms leveled against realism, aligns with the practical realities of information systems as an applied discipline. Overall, this study advises researchers in this field to emphasize critical realism, pursuing a deeper investigation of current issues to achieve genuine and meaningful outcomes in the domain of information systems.
Discussion and Conclusion: The findings of this study underscore the importance of critical realism as an effective approach in information systems research. Critical realism emphasizes that to fully understand information systems, it is insufficient to rely solely on observable structures; it is also necessary to examine the unobservable and hidden structures that underlie observable phenomena. Given that many current research methods in the field of information systems may fail to achieve a comprehensive and valid understanding of reality, critical realism serves as a suitable and effective alternative to address these theoretical and practical contradictions. Furthermore, the analyses conducted in this research indicate that selecting appropriate research methods based on the types of data and research questions can facilitate a better understanding of information systems. Consequently, researchers seeking to generate serious and credible knowledge in this field should leverage the tenets of critical realism. This study emphasizes the importance of establishing a clear and comprehensive theoretical framework for information systems research and demonstrates that critical realism can provide a suitable foundation for a deeper understanding of the complex structures and active mechanisms within this domain. It is anticipated that by relying on this approach, researchers will achieve more reliable results, enhancing their analytical capabilities and understanding of the changes and challenges within information systems research. The narratives and fundamental concepts identified, considering the ontological assumptions as the core of the critical realism methodology, address key epistemological issues such as causality and validity, as well as the explanation of access to reality through the recognition of what exists and the knowledge surrounding it. They also encompass the logic of inference in the research process, primarily through what is recognized as retroductive or abductive reasoning—the use of current information or ideas to infer or explain an event (or past situation)—and the choice of research methodology and strategy as fundamental concepts when conducting research using critical methodology in the field of information systems. The aforementioned narratives are presented and discussed within four categories: (1) Ontological narratives and mechanisms of production and causality, (2) Reality in critical realism, (3) The process of retroductive reasoning in critical realism, and (4) Research design.

Keywords


  1. Archer, M., Bhaskar, R., Collier, A., Lawson, T., & Norrie, A. (Eds.). (1998). Critical Realism: Essential Readings (1st ed.).

https://doi.org/10.4324/9781315008592

  1. Backhouse, R. E. (1994). New directions in economic methodology. Routledge.
  2. Benbasat, I., & Weber, R. (1996). Research commentary: Rethinking “diversity” in information systems research. Information Systems Research, 7(4), 389-
  3. Benz, C. R., Ridenour, C. S., & Newman, I. (2008). Mixed methods research: Exploring the interactive continuum. SIU Press.
  4. Bhaskar, R. (1978). A Realist Theory of Science (Vol. null).
  5. Bhaskar, R. (1979). The possibility of naturalism: a philosophical critique of the contemporary human sciences / by Roy Bhaskar. Harvester Press.
  6. Bhaskar, R. (1989). Reclaiming Reality: A Critical Introduction to Contemporary Philosophy (Vol. 55). Verso.
  7. Bhaskar, R. (2013a). The possibility of naturalism: A philosophical critique of the contemporary human sciences. Routledge.
  8. Bhaskar, R. (2013b). A realist theory of science. Routledge.
  9. Blaikie, N., & Priest, J. (2017). Social research: Paradigms in action. John Wiley & Sons.
  10. Bygstad, B., Munkvold, B. E., & Volkoff, O. (2016). Identifying generative mechanisms through affordances: a framework for critical realist data analysis. Journal of Information Technology, 31, 83-
  11. Carlsson, S. (2003). Advancing information systems evaluation (research): a critical realist approach. Electronic Journal of Information Systems Evaluation, 6(2), 11-
  12. Creswell, J. W. (2011). Designing and conducting mixed methods research / John W. Creswell, Vicki L. Plano Clark. SAGE Publications.
  13. Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
  14. Danermark, B., Ekström, M., & Karlsson, J. C. (2019). Explaining society: Critical realism in the social sciences. Routledge.
  15. Dobson, P. J. (2001). The philosophy of critical realism—an opportunity for information systems research. Information systems frontiers, 3(2), 199-
  16. Downward, P., & Mearman, A. (2002). Critical realism and econometrics: constructive dialogue with Post Keynesian economics. Metroeconomica, 53(4), 391-
  17. Downward, P., & Mearman, A. (2007). Retroduction as mixed-methods triangulation in economic research: reorienting economics into social science. Cambridge Journal of Economics, 31(1), 77-
  18. Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D., Elbanna, A., Ravishankar, M., & Srivastava, S. C. (2015). Research on information systems failures and successes: Status update and future directions. Information Systems Frontiers, 17, 143-
  19. Fleetwood, S. (1998). Situating critical realism in economics. In Critical realism in economics (pp. 141-150). Routledge.
  20. Fox, S. (2009). Applying critical realism to information and communication technologies: a case study. Construction management and economics, 27(5), 465-
  21. Imran, H. (2024). Pragmatic critical realism and Mixed methods in Inter-disciplinary Research—Management and Information systems. Valley International Journal Digital Library, 5953-
  22. Johnston, R., & Smith, S. P. (2010). How critical realism clarifies validity issues in theory-testing research: analysis and case. Information systems foundations: The role of design science, 21-
  23. Landry, M., & Banville, C. (1992). A disciplined methodological pluralism for MIS research. Accounting, management and information technologies, 2(2), 77-
  24. Lawson, T. (1997). Economics and reality. Routledge.
  25. Lee, A. S. (1999). Rigor and relevance in MIS research: Beyond the approach of positivism alone. MIS quarterly, 29-
  26. Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14(3), 221-
  27. Lee, A. S., & Hubona, G. S. (2009). A scientific basis for rigor in information systems research. MIS quarterly, 237-
  28. Markus, M. L., Steinfield, C. W., & Wigand, R. T. (2006). Industry-wide information systems standardization as collective action: the case of the US residential mortgage industry. MIS quarterly, 439-
  29. Maxwell, J. (1992). Understanding and validity in qualitative research. Harvard educational review, 62(3), 279-
  30. McEvoy, P., & Richards, D. (2006). A critical realist rationale for using a combination of quantitative and qualitative methods. Journal of research in nursing, 11(1), 66-
  31. Mingers, J. (2000). The contribution of critical realism as an underpinning philosophy for OR/MS and systems. Journal of the Operational Research Society, 51(11), 1256-
  32. Mingers, J. (2001). Combining IS research methods: towards a pluralist methodology. Information Systems Research, 12(3), 240-
  33. Mingers, J. (2003). The paucity of multimethod research: a review of the information systems literature. Information systems journal, 13(3), 233-
  34. Mingers, J. (2004). Real-izing information systems: critical realism as an underpinning philosophy for information systems. Information and Organization, 14(2), 87-
  35. Mingers, J. (2006). A critique of statistical modelling in management science from a critical realist perspective: its role within multimethodology. Journal of the Operational Research Society, 57(2), 202-

https://doi.org/10.1057/palgrave.jors.2601980

  1. Mingers, J., Mutch, A., & Willcocks, L. (2013). Critical Realism: Basic Concepts. Mis Quarterly, 37(3), 795-
  2. Mingers, J., & Standing, C. (2017). Why things happen–Developing the critical realist view of causal mechanisms. Information and Organization, 27(3), 171-
  3. Modell, S. (2009). In defence of triangulation: a critical realist approach to mixed methods research in management accounting. Management Accounting Research, 20(3), 208-
  4. Morton, P. (2006). Using critical realism to explain strategic information systems planning. Journal of Information Technology Theory and Application (JITTA), 8(1), 3.
  5. Myers, M. D., & Avison, D. (2002). Qualitative research in information systems: a reader. Sage.
  6. Outhwaite, W. (1976a). [A Realist Theory of Science, Roy Bhaskar]. Social Studies of Science, 6(1), 123-

http://www.jstor.org/stable/284790

  1. Outhwaite, W. (1976b). Reviews: Roy Bhaskar, A Realist Theory of Science (Leeds: Leeds Books, 1975), 260 pp.,£ 5.95 hardback,£ 2.25 paperback. ISBN. 085952 0137 (cloth) 085952 0145 (paperback). Social Studies of Science, 6(1), 123-
  2. Robey, D. (1996). Research commentary: diversity in information systems research: threat, promise, and responsibility. Information Systems Research, 7(4), 400-
  3. Runde, J. (1998). Assessing causal economic explanations. Oxford Economic Papers, 50(2), 151-
  4. Runde, J., & de Rond, M. (2010). Evaluating causal explanations of specific events. Organization Studies, 31(4), 431-
  5. Sayer, A. (1999). Realism and social science. Sage.
  6. Sayer, R. A. (1992). Method in social science: A realist approach. Psychology Press.
  7. Shotter, J. (1990). Roy Bhaskar, Reclaiming Reality: a Critical Introduction to Contemporary Philosophy, London: Verso, 1989, £24.95, paper £8.95, ix + 218 pp. History of the Human Sciences, 3(3), 443-

https://doi.org/10.1177/095269519000300309

  1. Spagnoletti, P., Ceci, F., & Bygstad, B. (2022). Online black-markets: An investigation of a digital infrastructure in the dark. Information Systems Frontiers, 1-
  2. Strong, D. M., & Volkoff, O. (2010). Understanding Organization—Enterprise system fit: A path to theorizing the information technology artifact. MIS quarterly, 731-
  3. Tashakkori, A., & Teddlie, C. (2010). Sage handbook of mixed methods in social and behavioral research. SAGE publications.
  4. Tashakkori, A., Teddlie, C., & Teddlie, C. B. (1998). Mixed methodology: Combining qualitative and quantitative approaches (Vol. 46). sage.
  5. Tsoukas, H. (1989). The validity of idiographic research explanations. Academy of management review, 14(4), 551-
  6. Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS quarterly, 21-
  7. Volkoff, O., Strong, D. M., & Elmes, M. B. (2007). Technological embeddedness and organizational change. Organization Science, 18(5), 832-
  8. Vukojević, B. (2016). Creswell JW: Research design: Qualitative, quantitative, and mixed methods approaches, London: Sage publications, 2009. Politeia, 6(12), 191-
  9. Walsham, G. (1995). Interpretive case studies in IS research: nature and method. European Journal of Information Systems, 4(2), 74-
  10. Wheaton, J., & Kreps, D. (2023). Towards a critical realist approach to the dark side of digital transformation. Frontiers in Human Dynamics, 5, 1252458.
  11. Williams, C. K., & Karahanna, E. (2013). Causal explanation in the coordinating process: A critical realist case study of federated IT governance structures. Mis Quarterly, 933-
  12. Wisker, G. (2007). The postgraduate research handbook: Succeed with your MA, MPhil, EdD and PhD. Macmillan International Higher Education.
  13. Wynn Jr, D., & Williams, C. K. (2012). Principles for conducting critical realist case study research in information systems. MIS quarterly, 787-
  14. Zachariadis, M., Scott, S., & Barrett, M. (2013). Methodological implications of critical realism for mixed-methods research. Mis Quarterly, 855-