Introduction

  • Leslie P. Willcocks
  • Chris Sauer
  • Mary C. Lacity

Abstract

The field of Information Systems (IS) has long concerned itself with the process of enquiry, that is, what should be researched, the methods that can be properly utilized, and the assessment of the validity of outcomes. Like almost all social scientists, IS scholars have been greatly influenced by methods adopted by the natural sciences, and by the power of quantitative techniques. At the same time IS scholars have come from varied backgrounds, and the research role of qualitative enquiry, what the IS field has come to call ‘interpretive’ and ‘critical’ approaches, have been frequently juxtaposed against ‘positivist’ approaches. There is a case to be made that these are no longer helpful distinctions, if they ever were. Lee and Hubona (2009), for example, show common issues across seemingly different research approaches, namely common scientific basis, the fallacy of affirming the consequent and the issue of summative validity. A strong case has also been made for multi-methods and mixed methodologies (Mingers, 2001), and this approach has been increasingly adopted in recent years.

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References

  1. de Waal, C. (2005) On Pragmatism. Belmont: Wadsworth.Google Scholar
  2. Dewey, J. (2004a) Essays in Experimental Logic. New York: Dover Press.Google Scholar
  3. Dewey, J. (2004b) Reconstruction in Philosophy. New York: Dover Press.Google Scholar
  4. Dewey, J. (1960) The Quest for Certainty: A Study of the Relation of Knowledge to Action. Capricorn, London: Capricorn.Google Scholar
  5. Lee, A. and Baskerville, R. (2003) Generalizing Generalizability in Information Systems Research. Information Systems Research 14(3): 221–243.CrossRefGoogle Scholar
  6. Lee, A. and Baskerville, R. (2012) Conceptualizing Generalizability: New Contributions and a Reply. MIS Quarterly 36(3): 749–761.Google Scholar
  7. Lee, A., and Hubona, G. (2009) A Scientific Basis for Rigor in IS Research. MIS Quarterly 33: 237–262.CrossRefGoogle Scholar
  8. Law, D. (2004) After Method: Mess in Social Science Research. London: Routledge.Google Scholar
  9. Mills, C. Wright (1959) The Sociological Imagination. Oxford: Oxford University Press.Google Scholar
  10. Mingers, J. (2001) Combining Research Methods in IS: Towards a Pluralist Methodology. Information Systems Research 12(3): 240–259.CrossRefGoogle Scholar
  11. Mingers, J. and Willcocks, L. (eds) (2004) Social Theory and Philosophy For Information Systems. Chichester: Wiley.Google Scholar
  12. Peirce, C. (1931–1958) Collected Papers of Charles Sanders Peirce (8 Volumes). Cambridge: Harvard University Press.Google Scholar
  13. Polanyi, M. (1966) The Logic of Tacit Inference. Philosophy 41(155): 1–18CrossRefGoogle Scholar
  14. Popper, K. (1959) The Logic of Scientific Discovery. London: Hutchinson.Google Scholar
  15. Seddon, P. and Scheepers, R. (2012) Drawing General Conclusions from Samples: Towards the Improved Treatment of Generalization of Knowledge Claims in IS Research. European Journal of Information Systems 21: 6–21.CrossRefGoogle Scholar
  16. Tsang, E. and Williams, J. (2012) Generalization and Induction: Misconceptions, Clarifications, and a Classification of Induction. MIS Quarterly 36(3): 729–748.Google Scholar
  17. Willcocks, L. and Lee. A. (2008) Major Currents in the Information Systems Field. Sage, London, six volumes.Google Scholar
  18. Wittgenstein, L. (1969) On Certainty. Oxford: Basil Blackwell.Google Scholar
  19. Wittgenstein, L. (2009) Philosophical Investigations. Chichester: Wiley, 4th edition.Google Scholar

Copyright information

© Leslie P. Willcocks, Chris Sauer and Mary C. Lacity 2016

Authors and Affiliations

  • Leslie P. Willcocks
  • Chris Sauer
  • Mary C. Lacity

There are no affiliations available

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