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Online Survey Data Quality and Its Implication for Willingness-to-Pay: A Cross-Country Comparison

Author

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  • Zhifeng Gao
  • Lisa A. House
  • Jing Xie

Abstract

type="main" xml:lang="fr"> Le recours aux enquêtes en ligne pour caractériser les préférences des consommateurs gagne en popularité en raison de ses nombreux avantages. Les recherches antérieures se sont principalement limitées à comparer les enquêtes en ligne et les autres types d'enquêtes. Peu se sont penchées sur l'utilisation d'outils susceptibles d'améliorer la qualité des données recueillies lors d'enquêtes en ligne destinées à évaluer le consentement à payer des consommateurs. Dans le présent article, nous analysons l'impact lié à l'utilisation d'une méthode comprenant une question de validation dans laquelle on demandait aux répondants de choisir une réponse en particulier pour améliorer la qualité des données d'enquête en ligne dans six pays. Les résultats de notre étude montrent que la qualité des données d'enquête est un problème courant dans les pays à l'étude et que la gravité du problème varie considérablement d'un pays à l'autre. Le fait d'inclure des questions de validation permettrait de déceler les répondants qui sont moins consciencieux lorsqu'ils répondent à des questions d'enquête et qui, par conséquent, fournissent des réponses plus ou moins fiables. Selon notre étude, les modèles économétriques qui utilisent les données de répondants qui ont répondu correctement aux questions de validation donnent de meilleurs résultats que les modèles qui utilisent les données de répondants qui n'y ont pas répondu correctement; l'écart entre les estimations du consentement à payer des deux groupes de répondants varie considérablement. En règle générale, les estimations du consentement à payer des répondants qui ont répondu correctement aux questions de validation présentent de plus faibles variances que celles pour l'ensemble des répondants et pour ceux qui n'ont pas répondu correctement aux questions de validation.

Suggested Citation

  • Zhifeng Gao & Lisa A. House & Jing Xie, 2016. "Online Survey Data Quality and Its Implication for Willingness-to-Pay: A Cross-Country Comparison," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 199-221, June.
    • Handle: RePEc:bla:canjag:v:64:y:2016:i:2:p:199-221
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    1. Nielsen, Jytte Seested, 2011. "Use of the Internet for willingness-to-pay surveys: A comparison of face-to-face and web-based interviews," Resource and Energy Economics, Elsevier, vol. 33(1), pages 119-129, January.
    2. 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.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    4. Maddala,G. S., 1986. "Limited-Dependent and Qualitative Variables in Econometrics," Cambridge Books, Cambridge University Press, number 9780521338257, November.
    5. Auger, Pat & Devinney, Timothy M. & Louviere, Jordan J. & Burke, Paul F., 2010. "The importance of social product attributes in consumer purchasing decisions: A multi-country comparative study," International Business Review, Elsevier, vol. 19(2), pages 140-159, April.
    6. Jones, Michael S. & House, Lisa A. & Gao, Zhifeng, 2014. "Respondent Screening and SARP: Testing Quarantining Methods for Better Data Quality in Web Panel Surveys," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169653, Agricultural and Applied Economics Association.
    7. Jill Windle & John Rolfe, 2011. "Comparing Responses from Internet and Paper-Based Collection Methods in more Complex Stated Preference Environmental Valuation Surveys," Economic Analysis and Policy, Elsevier, vol. 41(1), pages 83-97, March.
    8. Søren Olsen, 2009. "Choosing Between Internet and Mail Survey Modes for Choice Experiment Surveys Considering Non-Market Goods," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 44(4), pages 591-610, December.
    9. Lindhjem, Henrik & Navrud, Ståle, 2011. "Are Internet surveys an alternative to face-to-face interviews in contingent valuation?," Ecological Economics, Elsevier, vol. 70(9), pages 1628-1637, July.
    10. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
    11. Glynn T. Tonsor & Ted C. Schroeder & Joost M. E. Pennings & James Mintert, 2009. "Consumer Valuations of Beef Steak Food Safety Enhancement in Canada, Japan, Mexico, and the United States," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(3), pages 395-416, September.
    12. Gao, Zhifeng & House, Lisa & Bi, Xiang, 2012. "Finding True Consumer Attitudes: Do Validation Questions Help?," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123922, Agricultural and Applied Economics Association.
    13. Scarpa, R. & Thiene, M. & Train, K., 2008. "Appendix to Utility in WTP space: a tool to address confounding random scale effects in destination choice to the Alps," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(4), pages 1-9, January.
    14. Gregory L. Poe & Kelly L. Giraud & John B. Loomis, 2005. "Computational Methods for Measuring the Difference of Empirical Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 353-365.
    15. Garrett Sonnier & Andrew Ainslie & Thomas Otter, 2007. "Heterogeneity distributions of willingness-to-pay in choice models," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 313-331, September.
    16. Marta-Pedroso, Cristina & Freitas, Helena & Domingos, Tiago, 2007. "Testing for the survey mode effect on contingent valuation data quality: A case study of web based versus in-person interviews," Ecological Economics, Elsevier, vol. 62(3-4), pages 388-398, May.
    17. Balcombe, Kelvin & Chalak, Ali & Fraser, Iain, 2009. "Model selection for the mixed logit with Bayesian estimation," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 226-237, March.
    18. Riccardo Scarpa & Mara Thiene & Kenneth Train, 2008. "Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 994-1010.
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