IDEAS home Printed from https://ideas.repec.org/a/gam/jpubli/v8y2020i4p45-d434285.html
   My bibliography  Save this article

Assessment of Factors Causing Bias in Marketing- Related Publications

Author

Listed:
  • Mangirdas Morkunas

    (Division of Farms’ and Enterprises’ Economics, Lithuanian Institute of Agrarian Economics, Vivulskio str. 4A, 03220 Vilnius, Lithuania)

  • Elzė Rudienė

    (Business School, Vilnius University, Sauletekio ave. 21, 10222 Vilnius, Lithuania)

  • Lukas Giriūnas

    (Faculty of Public Governance and Business, Mykolas Romeris university, Ateities str. 20, 08303 Vilnius, Lithuania)

  • Laura Daučiūnienė

    (Faculty of Public Governance and Business, Mykolas Romeris university, Ateities str. 20, 08303 Vilnius, Lithuania)

Abstract

The present paper aims at revealing and ranking the factors that most frequently cause bias in marketing-related publications. In order to rank the factors causing bias, the authors employed the Analytic Hierarchy Process method with three different scales representing all scale groups. The data for the study were obtained through expert survey, which involved nine experts both from the academia and scientific publishing community. The findings of the study confirm that factors that most frequently cause bias in marketing related publications are sampling and sample frame errors, failure to specify the inclusion and exclusion criteria for researched subjects and non-responsiveness.

Suggested Citation

  • Mangirdas Morkunas & Elzė Rudienė & Lukas Giriūnas & Laura Daučiūnienė, 2020. "Assessment of Factors Causing Bias in Marketing- Related Publications," Publications, MDPI, vol. 8(4), pages 1-16, October.
    • Handle: RePEc:gam:jpubli:v:8:y:2020:i:4:p:45-:d:434285
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2304-6775/8/4/45/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2304-6775/8/4/45/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alrik Thiem & Lusine Mkrtchyan & Tim Haesebrouck & David Sanchez, 2020. "Algorithmic bias in social research: A meta-analysis," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
    2. Michelle Greenwood, 2016. "Approving or Improving Research Ethics in Management Journals," Journal of Business Ethics, Springer, vol. 137(3), pages 507-520, September.
    3. John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
    4. Nicola Lacetera & Lorenzo Zirulia, 2011. "The Economics of Scientific Misconduct," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 27(3), pages 568-603.
    5. Pflaumer, Peter, 1992. "Forecasting US population totals with the Box-Jenkins approach," International Journal of Forecasting, Elsevier, vol. 8(3), pages 329-338, November.
    6. R. Benedetti & M. S. Andreano & F. Piersimoni, 2019. "Sample selection when a multivariate set of size measures is available," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 1-25, March.
    7. S. Trevis Certo & John R. Busenbark & Hyun‐soo Woo & Matthew Semadeni, 2016. "Sample selection bias and Heckman models in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 37(13), pages 2639-2657, December.
    8. Sartori, Anne E., 2003. "An Estimator for Some Binary-Outcome Selection Models Without Exclusion Restrictions," Political Analysis, Cambridge University Press, vol. 11(2), pages 111-138, April.
    9. Iwasaki, Ichiro & Ma, Xinxin & Mizobata, Satoshi, 2020. "Corporate ownership and managerial turnover in China and Eastern Europe: A comparative meta-analysis," Journal of Economics and Business, Elsevier, vol. 111(C).
    10. Kerry Dwan & Douglas G Altman & Juan A Arnaiz & Jill Bloom & An-Wen Chan & Eugenia Cronin & Evelyne Decullier & Philippa J Easterbrook & Erik Von Elm & Carrol Gamble & Davina Ghersi & John P A Ioannid, 2008. "Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-31, August.
    11. Jane Qiu, 2010. "Publish or perish in China," Nature, Nature, vol. 463(7278), pages 142-142, January.
    12. Jonathan Schooler, 2011. "Unpublished results hide the decline effect," Nature, Nature, vol. 470(7335), pages 437-437, February.
    13. A Ishizaka & D Balkenborg & T Kaplan, 2011. "Influence of aggregation and measurement scale on ranking a compromise alternative in AHP," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 700-710, April.
    14. Patrick T. Harker & Luis G. Vargas, 1987. "The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process," Management Science, INFORMS, vol. 33(11), pages 1383-1403, November.
    15. Seunghwan Myeong & Yuseok Jung & Eunuk Lee, 2018. "A Study on Determinant Factors in Smart City Development: An Analytic Hierarchy Process Analysis," Sustainability, MDPI, vol. 10(8), pages 1-17, July.
    16. Neal S Young, 2008. "Why Current Publication May Distort Science," Working Papers id:1757, eSocialSciences.
    17. Neal S Young & John P A Ioannidis & Omar Al-Ubaydli, 2008. "Why Current Publication Practices May Distort Science," PLOS Medicine, Public Library of Science, vol. 5(10), pages 1-5, October.
    18. Nico Keilman & Dinh Quang Pham & Arve Hetland, 2002. "Why population forecasts should be probabilistic - illustrated by the case of Norway," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(15), pages 409-454.
    19. MacKenzie, Scott B. & Podsakoff, Philip M., 2012. "Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies," Journal of Retailing, Elsevier, vol. 88(4), pages 542-555.
    20. Dena K. Plemmons & Erica N. Baranski & Kyle Harp & David D. Lo & Courtney K. Soderberg & Timothy M. Errington & Brian A. Nosek & Kevin M. Esterling, 2020. "A randomized trial of a lab-embedded discourse intervention to improve research ethics," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(3), pages 1389-1394, January.
    21. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    22. Eisend, Martin & Tarrahi, Farid, 2014. "Meta-analysis selection bias in marketing research," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 317-326.
    23. Priti Mulimani, 2019. "Publication bias towards Western populations harms humanity," Nature Human Behaviour, Nature, vol. 3(10), pages 1026-1027, October.
    24. Abimbola A Ayorinde & Iestyn Williams & Russell Mannion & Fujian Song & Magdalena Skrybant & Richard J Lilford & Yen-Fu Chen, 2020. "Assessment of publication bias and outcome reporting bias in systematic reviews of health services and delivery research: A meta-epidemiological study," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-17, January.
    25. Stefan Rayer & Stanley Smith, 2014. "Population Projections by Age for Florida and its Counties: Assessing Accuracy and the Impact of Adjustments," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(5), pages 747-770, October.
    26. Robbie C M van Aert & Jelte M Wicherts & Marcel A L M van Assen, 2019. "Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-32, April.
    27. Marcus R. Munafò & Brian A. Nosek & Dorothy V. M. Bishop & Katherine S. Button & Christopher D. Chambers & Nathalie Percie du Sert & Uri Simonsohn & Eric-Jan Wagenmakers & Jennifer J. Ware & John P. A, 2017. "A manifesto for reproducible science," Nature Human Behaviour, Nature, vol. 1(1), pages 1-9, January.
    28. Maimouna Diouf & Choonjong Kwak, 2018. "Fuzzy AHP, DEA, and Managerial Analysis for Supplier Selection and Development; From the Perspective of Open Innovation," Sustainability, MDPI, vol. 10(10), pages 1-17, October.
    29. Julie A. Nelson, 2014. "The power of stereotyping and confirmation bias to overwhelm accurate assessment: the case of economics, gender, and risk aversion," Journal of Economic Methodology, Taylor & Francis Journals, vol. 21(3), pages 211-231, September.
    30. Thomas L. Saaty & Luis G. Vargas, 2012. "Models, Methods, Concepts & Applications of the Analytic Hierarchy Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-3597-6, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Omar Al-Ubaydli & John A. List, 2015. "Do Natural Field Experiments Afford Researchers More or Less Control than Laboratory Experiments? A Simple Model," NBER Working Papers 20877, National Bureau of Economic Research, Inc.
    2. Daniele Fanelli, 2012. "Negative results are disappearing from most disciplines and countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 891-904, March.
    3. Klaus D. Goepel, 2019. "Comparison of Judgment Scales of the Analytical Hierarchy Process — A New Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 445-463, March.
    4. Mark D Lindner & Richard K Nakamura, 2015. "Examining the Predictive Validity of NIH Peer Review Scores," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    5. Salandra, Rossella & Criscuolo, Paola & Salter, Ammon, 2021. "Directing scientists away from potentially biased publications: the role of systematic reviews in health care," Research Policy, Elsevier, vol. 50(1).
    6. Salandra, Rossella, 2018. "Knowledge dissemination in clinical trials: Exploring influences of institutional support and type of innovation on selective reporting," Research Policy, Elsevier, vol. 47(7), pages 1215-1228.
    7. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    8. Omar Al-Ubaydli & John List & Claire Mackevicius & Min Sok Lee & Dana Suskind, 2019. "How Can Experiments Play a Greater Role in Public Policy? 12 Proposals from an Economic Model of Scaling," Artefactual Field Experiments 00679, The Field Experiments Website.
    9. Hadani, Michael & Doh, Jonathan P. & Schneider, Marguerite, 2019. "Social movements and corporate political activity: Managerial responses to socially oriented shareholder activism," Journal of Business Research, Elsevier, vol. 95(C), pages 156-170.
    10. Kirmayer, Laurence J., 2012. "Cultural competence and evidence-based practice in mental health: Epistemic communities and the politics of pluralism," Social Science & Medicine, Elsevier, vol. 75(2), pages 249-256.
    11. Siraj, Sajid & Mikhailov, Ludmil & Keane, John A., 2015. "Contribution of individual judgments toward inconsistency in pairwise comparisons," European Journal of Operational Research, Elsevier, vol. 242(2), pages 557-567.
    12. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    13. Oliver Braganza, 2020. "A simple model suggesting economically rational sample-size choice drives irreproducibility," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
    14. Adam Altmejd & Anna Dreber & Eskil Forsell & Juergen Huber & Taisuke Imai & Magnus Johannesson & Michael Kirchler & Gideon Nave & Colin Camerer, 2019. "Predicting the replicability of social science lab experiments," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-18, December.
    15. Zsuzsanna Katalin Szabo & Zsombor Szádoczki & Sándor Bozóki & Gabriela C. Stănciulescu & Dalma Szabo, 2021. "An Analytic Hierarchy Process Approach for Prioritisation of Strategic Objectives of Sustainable Development," Sustainability, MDPI, vol. 13(4), pages 1-26, February.
    16. Chris Doucouliagos & T.D. Stanley, 2013. "Are All Economic Facts Greatly Exaggerated? Theory Competition And Selectivity," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 316-339, April.
    17. Anderson, Brian S. & Wennberg, Karl & McMullen, Jeffery S., 2019. "Editorial: Enhancing quantitative theory-testing entrepreneurship research," Journal of Business Venturing, Elsevier, vol. 34(5), pages 1-1.
    18. Mueller-Langer, Frank & Fecher, Benedikt & Harhoff, Dietmar & Wagner, Gert G., 2019. "Replication studies in economics—How many and which papers are chosen for replication, and why?," Research Policy, Elsevier, vol. 48(1), pages 62-83.
    19. Matthew L. Wallace & Ismael Rafols, 2016. "Shaping the Agenda of a Grand Challenge: Institutional Mediation of Priorities in Avian Influenza Research," SPRU Working Paper Series 2016-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
    20. Wennberg, Karl & Anderson, Brian S. & McMullen, Jeffrey, 2019. "2 Editorial: Enhancing Quantitative Theory-Testing Entrepreneurship Research," Ratio Working Papers 323, The Ratio Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jpubli:v:8:y:2020:i:4:p:45-:d:434285. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.