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A comparison of Best-Worst Scaling and Likert Scale methods on peer-to-peer accommodation attributes

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  • Heo, Cindy Yoonjoung
  • Kim, Bona
  • Park, Kwangsoo
  • Back, Robin M.

Abstract

Surveys based on Likert scales continue to dominate market research practice despite their limitations. Several researchers have suggested adopting different types of scales and a unique alternative for rating the importance level of several attributes is Best − Worst Scaling (BWS). The purpose of this study is to compare two scaling approaches, the Best-Worst Scale (BWS) and the Likert Scale to explore their advantages and disadvantages. This study tried to identify the relative importance of Peer-to-Peer (P2P) accommodation attributes using the aforementioned two scaling approaches. A comparison of the results found that the BWS approach helps to validate priorities from a customer perspective by achieving better discrimination among attributes, while the Likert scale approach is useful for comparing group differences such as gender differences.

Suggested Citation

  • Heo, Cindy Yoonjoung & Kim, Bona & Park, Kwangsoo & Back, Robin M., 2022. "A comparison of Best-Worst Scaling and Likert Scale methods on peer-to-peer accommodation attributes," Journal of Business Research, Elsevier, vol. 148(C), pages 368-377.
    • Handle: RePEc:eee:jbrese:v:148:y:2022:i:c:p:368-377
    DOI: 10.1016/j.jbusres.2022.04.064
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    References listed on IDEAS

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    1. Louviere, Jordan J. & Islam, Towhidul, 2008. "A comparison of importance weights and willingness-to-pay measures derived from choice-based conjoint, constant sum scales and best-worst scaling," Journal of Business Research, Elsevier, vol. 61(9), pages 903-911, September.
    2. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    3. Pat Auger & Timothy Devinney & Jordan Louviere, 2007. "Using Best–Worst Scaling Methodology to Investigate Consumer Ethical Beliefs Across Countries," Journal of Business Ethics, Springer, vol. 70(3), pages 299-326, February.
    4. Gibson, Clark C. & Ostrom, Elinor & Ahn, T. K., 2000. "The concept of scale and the human dimensions of global change: a survey," Ecological Economics, Elsevier, vol. 32(2), pages 217-239, February.
    5. Benjamin Edelman & Micahel Luca, 2014. "Digital Discrimination: The Case of Airbnb.com," Harvard Business School Working Papers 14-054, Harvard Business School.
    6. T.N. Flynn & A.A.J. Marley, 2014. "Best-worst scaling: theory and methods," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 8, pages 178-201, Edward Elgar Publishing.
    7. Ert, Eyal & Fleischer, Aliza & Magen, Nathan, 2016. "Trust and reputation in the sharing economy: The role of personal photos in Airbnb," Tourism Management, Elsevier, vol. 55(C), pages 62-73.
    8. Kevin Arceneaux, 2012. "Cognitive Biases and the Strength of Political Arguments," American Journal of Political Science, John Wiley & Sons, vol. 56(2), pages 271-285, April.
    9. Adam J. Berinsky & Michele F. Margolis & Michael W. Sances, 2014. "Separating the Shirkers from the Workers? Making Sure Respondents Pay Attention on Self‐Administered Surveys," American Journal of Political Science, John Wiley & Sons, vol. 58(3), pages 739-753, July.
    10. Andrew Healy & Gabriel S. Lenz, 2014. "Substituting the End for the Whole: Why Voters Respond Primarily to the Election‐Year Economy," American Journal of Political Science, John Wiley & Sons, vol. 58(1), pages 31-47, January.
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