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Common Biases in Business Research

  • Sulaiman Mouselli
  • Hiba Massoud
Chapter
Part of the Progress in IS book series (PROIS)

Abstract

Bias occurs in research when an error is committed in sampling or testing which results in choosing or favoring one outcome, conclusion or result over others. Bias can happen at any stage of research, including study design, methodology selection, collection of data and stating conclusions (Pannucci and Wilkins in Plast Reconstr Surg 126:619–625, 2011 [1]). Given the significant threats of these biases on the reliability and validity of research conclusions, understanding different types of biases, their consequences and treatment methods, is the corner stone in avoiding such biases and an important step in critically evaluating research. This chapter discusses biases that are common in quantitative research, biases associated with qualitative research and biases that usually occur in quantitative research using qualitative data. It will focus on introducing business researchers to their definitions and sources. The chapter also suggests methods to uncover those biases and provides remedies and ways to deal with such biases.

References

  1. 1.
    C.J. Pannucci, E.G. Wilkins, Identifying and avoiding bias in research. Plast. Reconstr. Surg. 126(2), 619–625 (2011)CrossRefGoogle Scholar
  2. 2.
    B. Shajani, 11th Hour Guide for 2015 Level I CFA, vol. 1. (Wiley, 2015)Google Scholar
  3. 3.
    A. Lo, A. MacKinlay, Data-snooping biases in tests of financial asset pricing models. Rev. Financ. Stud. 3(3), 431–467 (1990)Google Scholar
  4. 4.
    E. Fama, K. French, Common risk factors in the returns on stocks and bonds. J. Financ. Econ. 33(1), 3–56 (1993)Google Scholar
  5. 5.
    C. Brooks, Introductory Econometrics for Finance, vol. 1, Third edn. (Cambridge University Press, New York, 2014)Google Scholar
  6. 6.
    R. Sullivan, A. Timmermann, H. White, Data-snooping, technical trading rule performance, and the bootstrap. J. Finance 54(5), 1647–1691 (1999)Google Scholar
  7. 7.
    H. White, A reality check for data snooping. Econometrica 68(5), 1097–1126 (2000)Google Scholar
  8. 8.
    D.L. Olson, D. Delen, Advanced Data Mining Techniques‏ (Springer Science & Business Media‏, Berlin, 2008)Google Scholar
  9. 9.
    J. Heckman, Sample selection bias as specification error. Econometrica 47(1), 153–162 (1979)CrossRefGoogle Scholar
  10. 10.
    E. Gilbert, D. Strugnell, Does survivorship bias really matter? An empirical investigation into its effects on the mean reversion of share returns on the JSE (1984–2007). Invest. Anal. J. 39(72), 31–42 (2010)Google Scholar
  11. 11.
    G. Daniel, D. Sornette, P. Woehrmann, Look-ahead benchmark bias in portfolio performance evaluation. J. Portfolio Manag. 36(1), 121–130 (2009)CrossRefGoogle Scholar
  12. 12.
    F.J. Fowler, Survey Research Methods, 2nd edn. (Sage, London, 2002)Google Scholar
  13. 13.
    L. Cohen, L. Manion, K. Morrison, Research Methods in Education, 5th edn. (Routledgeflamer, New York, 2003)Google Scholar
  14. 14.
    M. Easterby-Smith, R. Thorpe, A. Lowe, Management Research: An Introduction, 1st edn. (Sage, London, 2002)Google Scholar
  15. 15.
    J.F. Hair, R.E. Anderson, R.L. Tatham, W.C. Black, Multivariate Data Analysis, 5th edn. (Prentice Hall, USA, 1998)Google Scholar
  16. 16.
    A. Oppenheim, Questionnaire Design, Interviewing and Attitude Measurement (Pinter, London, 1992)Google Scholar
  17. 17.
    S. Lucas, Beyond the existence proof: ontological conditions, epistemological implications, and in-depth interview research. Qual. Quant. (2014)Google Scholar
  18. 18.
    S. Berg, Snowball sampling–I, in Encyclopedia of Statistical Sciences, ed. by B.V. Samuel Kotz, C. Read, N. Balakrishnan, Vol 15, 2nd edn. (Wiley, Hoboken, NJ, 2005), pp. 7817–7821Google Scholar
  19. 19.
    M. Saunders, P. Lewis, A. Thornhill, Research Methods for Business Students (Financial Times, USA, 2007)Google Scholar
  20. 20.
    G.L. Patzer, Using Secondary Data in Marketing Research: United States and World-Wide (Quorum Books, Westport, CT, 1995) Google Scholar
  21. 21.
    S. Sreejesh, S. Mohapatra, M. Anusree, Business Research Methods (Springer International Publishing AG, Switzerland, 2014)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Finance, Faculty of Business AdministrationArab International University (AIU)DamascusSyria
  2. 2.School of Economics, Finance and AccountingCoventry UniversityCoventryUK

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