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Using discrete choice experiments to estimate willingness-to-pay intervals

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  • Christian Schlereth
  • Christine Eckert
  • Bernd Skiera

Abstract

Willingness-to-pay has always been conceptualized as a point estimate, frequently as the price that makes the consumer indifferent between buying and not buying the product. In contrast, this article estimates willingness-to-pay (WTP) as an interval based on discrete choice experiments and a scale-adjusted latent-class model. The middle value of this interval corresponds to the traditional WTP point estimate and depends on the deterministic utility; the range of the interval depends on price sensitivity and the utility’s error variance (scale). With this conceptualization of WTP, we propose a new measure, the attractiveness index, which serves to identify attractive consumers by combining knowledge about their price sensitivities and error variances. An empirical study demonstrates that the attractiveness index identifies the most attractive consumers, who do not necessarily have the largest WTP point estimates. Furthermore, consumers with comparable preferences can differ in their purchase probability by an average of 16%, as reflected in differences in their WTP intervals, which yields implications for more customized target marketing. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Christian Schlereth & Christine Eckert & Bernd Skiera, 2012. "Using discrete choice experiments to estimate willingness-to-pay intervals," Marketing Letters, Springer, vol. 23(3), pages 761-776, September.
  • Handle: RePEc:kap:mktlet:v:23:y:2012:i:3:p:761-776
    DOI: 10.1007/s11002-012-9177-2
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    2. Andreas Pondorfer & Katrin Rehdanz, 2018. "Eliciting Preferences for Public Goods in Nonmonetized Communities: Accounting for Preference Uncertainty," Land Economics, University of Wisconsin Press, vol. 94(1), pages 73-86.
    3. Dost, Florian & Wilken, Robert & Eisenbeiss, Maik & Skiera, Bernd, 2014. "On the Edge of Buying: A Targeting Approach for Indecisive Buyers Based on Willingness-to-Pay Ranges," Journal of Retailing, Elsevier, vol. 90(3), pages 393-407.
    4. Christian Schlereth & Fabian Schulz, 2014. "Schnelle und einfache Messung von Bedeutungsgewichten mit der Restricted-Click-Stream Analyse: Ein Vergleich mit etablierten Präferenzmessmethoden," Schmalenbach Journal of Business Research, Springer, vol. 66(8), pages 630-657, December.
    5. Erik Maier & Robert Wilken & Florian Dost, 2015. "The double benefits of consumer certainty: combining risk and range effects," Marketing Letters, Springer, vol. 26(4), pages 473-488, December.
    6. Dost, Florian & Geiger, Ingmar, 2017. "Value-based pricing in competitive situations with the help of multi-product price response maps," Journal of Business Research, Elsevier, vol. 76(C), pages 219-236.
    7. 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.
    8. Jianqing Fisher Wu & Banafsheh Behzad, 2023. "Optimal three-part tariff pricing with Spence-Mirrlees reservation prices," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 97(2), pages 233-258, April.
    9. Jella Pfeiffer & Michael Scholz, 2013. "A Low-Effort Recommendation System with High Accuracy," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(6), pages 397-408, December.
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    11. Tuo Wang & Michael Y. Hu, 2019. "Differential pricing with consumers’ valuation uncertainty by a monopoly," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(3), pages 247-255, June.
    12. Schlereth, Christian & Eckert, Christine & Schaaf, René & Skiera, Bernd, 2014. "Measurement of preferences with self-explicated approaches: A classification and merge of trade-off- and non-trade-off-based evaluation types," European Journal of Operational Research, Elsevier, vol. 238(1), pages 185-198.

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