IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v148y2022icp368-377.html

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296322004131
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2022.04.064?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Benjamin Edelman & Micahel Luca, 2014. "Digital Discrimination: The Case of Airbnb.com," Harvard Business School Working Papers 14-054, Harvard Business School.
    10. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiangsheng Dou & Fizza Ishaq, 2025. "Enterprise’s Strategic Agility and Resource Allocation Choice: A Case of SMEs in China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 2229-2248, March.
    2. Feng Ji & Guangyuan Zhao & Lun Meng & Rana Tehseen & Fushuai Wang, 2022. "Cultivating Talents for Reporting Environmental News on China’s Carbon Neutrality Policy," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    3. Mesbahuddin Chowdhury & Md. Aftab Uddin & Shetu Ranjan Biswas & Ashraful Islam Hridoy, 2025. "Promoting Human Resource and Innovative Climate to Foster Organizational Resilience During Pandemic Time: The Mediating Role of Employee Resilience," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 26(1), pages 55-85, March.
    4. Totok Haryanto & Budhi Haryanto, 2025. "How Do YouTube Ads Shape Consumer Decisions? (Empirical Study on Gen-Z)," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 87-106.
    5. Kosmo Karantonis & Oliver Schnittka & Mario Farsky & Henrik Sattler, 2025. "Empirical validation of a new technique (‘select-and-rank’) to measure brand preference," Journal of Brand Management, Palgrave Macmillan, vol. 32(3), pages 227-237, May.
    6. David Throsby & John R. Severn & Katya Petetskaya, 2024. "Preference formation in demand for live theatre," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 48(2), pages 285-310, June.
    7. Chulmin Lim & Seongcheol Kim, 2024. "Examining factors influencing the user’s loyalty on algorithmic news recommendation service," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    8. Tomasz Gajderowicz & Maciej Jakubowski & Sylwia Wrona & Ghadah Alkhadim, 2023. "Is students’ teamwork a dreamwork? A new DCE-based multidimensional approach to preferences towards group work," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    9. Tavana, Madjid & Mina, Hassan & Santos-Arteaga, Francisco J., 2023. "A general Best-Worst method considering interdependency with application to innovation and technology assessment at NASA," Journal of Business Research, Elsevier, vol. 154(C).

    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. John Rose & David Hensher, 2014. "Tollroads are only part of the overall trip: the error of our ways in past willingness to pay studies," Transportation, Springer, vol. 41(4), pages 819-837, July.
    2. Marco Lerro & Giuseppe Marotta & Concetta Nazzaro, 2020. "Measuring consumers’ preferences for craft beer attributes through Best-Worst Scaling," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 8(1), pages 1-13, December.
    3. Simone Mueller & Larry Lockshin & Jordan Louviere, 2010. "What you see may not be what you get: Asking consumers what matters may not reflect what they choose," Marketing Letters, Springer, vol. 21(4), pages 335-350, December.
    4. Erdem, Seda & Rigby, Dan, 2011. "Using Best Worst Scaling To Investigate Perceptions Of Control & Concern Over Food And Non-Food Risks," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108790, Agricultural Economics Society.
    5. Marti, Joachim, 2012. "A best–worst scaling survey of adolescents' level of concern for health and non-health consequences of smoking," Social Science & Medicine, Elsevier, vol. 75(1), pages 87-97.
    6. Rausch, Theresa Maria & Baier, Daniel & Wening, Stefanie, 2021. "Does sustainability really matter to consumers? Assessing the importance of online shop and apparel product attributes," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    7. Jeroen Oskam & Jean-Pierre Rest & Benjamin Telkamp, 2018. "What’s mine is yours—but at what price? Dynamic pricing behavior as an indicator of Airbnb host professionalization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(5), pages 311-328, October.
    8. Hristov, Hristov & Kuhar, Ales, 2013. "Young Urban Adults' Preferences for Wine Attributes: An Exploratory Study of the Republic of Macedonia Wine Market Applying the Best-Worst Scaling," 2013 Conference: Tools for decision support in agriculture and rural development, April 18-19, 2013, Krško, Slovenia 183907, Slovenian Association of Agricultural Economists (DAES).
    9. Christian Wankmüller & Maximilian Kunovjanek & Robert Gennaro Sposato & Gerald Reiner, 2020. "Selecting E-Mobility Transport Solutions for Mountain Rescue Operations," Energies, MDPI, vol. 13(24), pages 1-19, December.
    10. Stephanie Knox & Rosalie Viney & Deborah Street & Marion Haas & Denzil Fiebig & Edith Weisberg & Deborah Bateson, 2012. "What’s Good and Bad About Contraceptive Products?," PharmacoEconomics, Springer, vol. 30(12), pages 1187-1202, December.
    11. Suprehatin, By & Umberger, Wendy J. & Yi, Dale & Stringer, Randy & Minot, Nicholas, 2015. "Can Understanding Indonesian Farmers’ Preferences for Crop Attributes Encourage their Adoption of High Value Crops?," 2015 Conference, August 9-14, 2015, Milan, Italy 212057, International Association of Agricultural Economists.
    12. Muunda, Emmanuel & Mtimet, Nadhem & Schneider, Franziska & Wanyoike, Francis & Dominguez-Salas, Paula & Alonso, Silvia, 2021. "Could the new dairy policy affect milk allocation to infants in Kenya? A best-worst scaling approach," Food Policy, Elsevier, vol. 101(C).
    13. Greiner, Romy, 2014. "Willingness of north Australian pastoralists and graziers to participate in contractual biodiversity conservation," 2014 Conference (58th), February 4-7, 2014, Port Macquarie, Australia 165839, Australian Agricultural and Resource Economics Society.
    14. Soto, José & Escobedo, Francisco & Adams, Damian, 2016. "Public and Private Preferences for Urban Forest Ecosystem Services," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236232, Agricultural and Applied Economics Association.
    15. Kreye, Melissa M. & Adams, Damian C. & Escobedo, Francisco J. & Soto, José R., 2016. "Does policy process influence public values for forest-water resource protection in Florida?," Ecological Economics, Elsevier, vol. 129(C), pages 122-131.
    16. Kas, Judith, 2022. "The effect of online reputation systems on intergroup inequality," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 96(C).
    17. Petrolia, Daniel R., 2016. "Risk preferences, risk perceptions, and risky food," Food Policy, Elsevier, vol. 64(C), pages 37-48.
    18. Louviere, Jordan & Lings, Ian & Islam, Towhidul & Gudergan, Siegfried & Flynn, Terry, 2013. "An introduction to the application of (case 1) best–worst scaling in marketing research," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 292-303.
    19. Shehely Parvin & Paul Wang & Jashim Uddin, 2016. "Using best-worst scaling method to examine consumers’ value preferences: A multidimensional perspective," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1199110-119, December.
    20. Erdem, Seda & Rigby, Dan & Wossink, Ada, 2012. "Using best–worst scaling to explore perceptions of relative responsibility for ensuring food safety," Food Policy, Elsevier, vol. 37(6), pages 661-670.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    Statistics

    Access and download statistics

    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:eee:jbrese:v:148:y:2022:i:c:p:368-377. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.