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Best-worst scaling: theory and methods

In: Handbook of Choice Modelling

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  • T.N. Flynn
  • A.A.J. Marley

Abstract

Choice modelling is an increasingly important technique for forecasting and valuation, with applications in fields such as transportation, health and environmental economics. For this reason it has attracted attention from leading academics and practitioners and methods have advanced substantially in recent years. This Handbook, composed of contributions from senior figures in the field, summarises the essential analytical techniques and discusses the key current research issues. It will be of interest to academics, students and practitioners in a wide range of areas.

Suggested Citation

  • 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.
    • Handle: RePEc:elg:eechap:14820_8
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    File URL: https://www.elgaronline.com/view/9781781003145.00014.xml
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    References listed on IDEAS

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    1. Jörg Rieskamp & Jerome R. Busemeyer & Barbara A. Mellers, 2006. "Extending the Bounds of Rationality: Evidence and Theories of Preferential Choice," Journal of Economic Literature, American Economic Association, vol. 44(3), pages 631-661, September.
    2. Flynn, Terry Nicholas & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2010. "Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters," Social Science & Medicine, Elsevier, vol. 70(12), pages 1957-1965, June.
    3. 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.
    4. 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.
    5. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    7. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    8. Office of Health Economics, 2007. "The Economics of Health Care," For School 001490, Office of Health Economics.
    9. Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
    10. Rosalie Viney & Elizabeth Savage & Jordan Louviere, 2005. "Empirical investigation of experimental design properties of discrete choice experiments in health care," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 349-362, April.
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    Cited by:

    1. Yang, J. & Chen, F., 2021. "How are social-psychological factors related to consumer preferences for plug-in electric vehicles? Case studies from two cities in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Delle Site, Paolo & Kilani, Karim & Gatta, Valerio & Marcucci, Edoardo & de Palma, André, 2019. "Estimation of consistent Logit and Probit models using best, worst and best–worst choices," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 87-106.
    3. Pedersen, Line Bjørnskov & Hess, Stephane & Kjær, Trine, 2016. "Asymmetric information and user orientation in general practice: Exploring the agency relationship in a best–worst scaling study," Journal of Health Economics, Elsevier, vol. 50(C), pages 115-130.
    4. Davis, Katrina J & Burton, Michael & Kragt, Marit E, 2016. "Discrete choice models: scale heterogeneity and why it matters," Working Papers 235373, University of Western Australia, School of Agricultural and Resource Economics.
    5. Petrolia, Daniel R., 2016. "Risk preferences, risk perceptions, and risky food," Food Policy, Elsevier, vol. 64(C), pages 37-48.
    6. Beck, Matthew J. & Rose, John M., 2016. "The best of times and the worst of times: A new best–worst measure of attitudes toward public transport experiences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 108-123.
    7. Perolia, Daniel R. & Collart, Alba J. & Yehouenou, Lauriane, 2016. "Consumer Preferences for Delacata Catfish: A Choice Experiment with Tasting," Journal of Food Distribution Research, Food Distribution Research Society, vol. 47(3), pages 1-17, November.
    8. Yangui, Ahmed & Akaichi, Faical & Costa-Font, Montserrat & Gil, Jose Maria, 2019. "Comparing results of ranking conjoint analyses, best–worst scaling and discrete choice experiments in a nonhypothetical context," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(2), April.
    9. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).
    10. 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.
    11. Soekhai, V. & Donkers, B. & Levitan, B. & de Bekker-Grob, E.W., 2021. "Case 2 best-worst scaling: For good or for bad but not for both," Journal of choice modelling, Elsevier, vol. 41(C).
    12. 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).

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