Could Value-based Pricing Improve Economic Sustainability of Bikeshare?
Keywords:decoy pricing, value-based pricing, behavioural economics, bikeshare, capital bikeshare, pricing, micromobility, shared mobility, revenue, ridership
We scrutinize the reactions of casual users of bikesharing services to fare menu, product pricing, and promotion. We hypothesize that by introducing value-based pricing into the fare-option mix, revenues can be increased and therefore enhance the economic sustainability of the bikesharing system. We conducted a controlled experimental survey of 157 current and potential bikeshare users across six cities in the United States. The survey registered the respondents’ choice of fare options in two groups: one with a binary choice set (control group) and the other with an additional value-priced choice (experimental group). Evidence points to users’ perception of value in bikeshare fare options would contribute to variations in revenues for the same ridership levels. Revenue projections and statistical tests showed that the introduction of value-based pricing options could lead to significant revenue increases. Furthermore, how the fare options are presented to the user would have an impact on users’ reception to the value-based pricing options in the product mix. The study results could be useful for numerous bikeshare systems in re-examining their product mixes and how they are presented to the users on websites, mobile apps and kiosk locations.
Venigalla, M.M., T. Brennan, S. Rayaprolu, & S. Kaviti. (2020a). Increasing Bikeshare Revenue through Value-Based Pricing: Lessons from Behavioral Economics. 99th Annual Meeting of the Transportation Research Board. National Research Council. Washington DC. (Jan 12-15, 2020).
Venigalla, M.M., Kaviti, S., & Brennan, T. (2020b). Impact of bikesharing pricing policies on usage and revenue: An evaluation through curation of large datasets from revenue transactions and trips. Journal of Big Data Analytics in Transportation (in print).
Pucher, J., Dill, J., & Handy, S. (2010). Infrastructure, programs, and policies to increase bicycling: An international review. Preventive Medicine, 50, S106–S125. https://doi.org/10.1016/J.YPMED.2009.07.028
de Nazelle, A., Nieuwenhuijsen, M. J., Antó, J. M., Brauer, M., Briggs, D., Braun-Fahrlander, C., … Lebret, E. (2011). Improving health through policies that promote active travel: A review of evidence to support integrated health impact assessment. Environment International, 37(4), 766–777. https://doi.org/10.1016/J.ENVINT.2011.02.003
Kaviti, S., Venigalla, M. M., Zhu, S., Lucas, K., & Brodie, S. (2018). Impact of pricing and transit disruptions on bikeshare ridership and revenue. Transportation, 1–22. https://doi.org/10.1007/s11116-018-9904-5
Kaviti, S., & Venigalla, M. M. (2019). Assessing service and price sensitivities, and pivot elasticities of public bikeshare system users through monadic design and ordered logit regression. Transportation Research Interdisciplinary Perspectives, 1(1), 100015. https://doi.org/10.1016/J.TRIP.2019.100015
Kaviti, S., Venigalla, M. M., & Lucas, K. (2019). Travel behavior and price preferences of bikesharing members and casual users: A Capital Bikeshare perspective. Travel Behaviour and Society, 15, 133–145. https://doi.org/10.1016/J.TBS.2019.02.004
Venigalla, M.M., Kaviti, S., Pierce, W. and Zhu, S. (2018). Analysis of Single-trip fare data for Capital Bikeshare. District Department of Transportation (DDOT), Final Report.
McCarthy, E.J., Shapiro, S.J., & Perrealt, W.D. (1979). Basic marketing. (pp. 29-33). Irwin-Dorsey.
Citi Bike (2019b). December 2018 Monthly Report. Retrieved August 8, 2019 from http://citibikenyc.com/system-data/operating-reports
McFadden, D. (1974), Conditional logit analysis of qualitative choice behavior. In P. Zarembka, ed., Frontiers in Econometrics, Academic Press, New York, pp. 105– 142.
Lovelock, C.H. (1975). "Researching and Modeling Consumer Choice Behavior in Urban Transportation", in NA - Advances in Consumer Research Volume 02, eds. M.J Schlinger and A. Abor, MI: Association for Consumer Research, Pages: 851-862.
Hinterhuber, A. (2008). Customer value-based pricing strategies: why companies resist. Journal of business strategy, 29(4), 41-50.
Venigalla, M., Kaviti, S., & Brennan, T. (2020). Impact of Bikesharing Pricing Policies on Usage and Revenue: An Evaluation Through Curation of Large Datasets from Revenue Transactions and Trips. Journal of Big Data Analytics in Transportation, 1-16.
Bay Wheels (2020). Bay Wheels Pricing. Retrieved January 30, 2020 from http://lyft.com/bikes/bay-wheels/pricing
Blue Bikes (2020). Choose Your Plan. Retrieved January 30, 2020 from http://bluebikes.com/pricing
Capital Bikeshare (2020). Choose Your Plan. January 30, 2020 from http://capitalbikeshare.com/pricing
Citi Bike (2020). Choose Your Plan. Retrieved January 30, 2020 from http://citibikenyc.com/pricing
Divvy (2019). Choose Your Plan. Retrieved August 8, 2019 from http://divvybikes.com/pricing
Metro Bikeshare (2020). Pricing. Retrieved January 30, 2020 from http://bikeshare.metro.net/pricing/
Nice Ride (2020) Choose Your Plan. Retrieved January 30, 2020 from http://niceridemn.com/pricing
Boz, H., Arslan, A., & Koc, E. (2017). Neuromarketing aspect of tourısm pricing psychology. Tourism Management Perspectives, 23, 119–128. https://doi.org/10.1016/J.TMP.2017.06.002
Gonzalez-Prieto, D., Sallan, J. M., Simo, P., & Carrion, R. (2013). Effects of the addition of simple and double decoys on the purchasing process of airline tickets. Journal of Air Transport Management, 29, 39–45. https://doi.org/10.1016/J.JAIRTRAMAN.2013.02.002
Huber, J., Payne, J. W., & Puto, C. (1982). Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis. Journal of Consumer Research, 9(1), 90. https://doi.org/10.1086/208899
Heide, M., White, C., Gr⊘nhaug, K., & Østrem, T. M. (2008). Pricing Strategies in the Restaurant Industry. Scandinavian Journal of Hospitality and Tourism, 8(3), 251–269. https://doi.org/10.1080/15022250802451065
Kasavana, M. L., Smith, D. I., & Schmidgall, R. S. (1990). Menu engineering : a practical guide to menu analysis. Retrieved from http://agris.fao.org/agris-search/search.do?recordID=US19920039139
McFadden, D., Machina, M. J., & Baron, J. (1999). Rationality for Economists? In Elicitation of Preferences (pp. 73–110). https://doi.org/10.1007/978-94-017-1406-8_4
Ariely, D. (2008). Predictably irrational: the hidden forces that shape our decisions. Retrieved from https://search.proquest.com/docview/235821459?pq-origsite=gscholar
Rayaprolu, R., & Venigalla, M.M. (2020). Motivations and Mode-choice Behavior of Micromobility Users in Washington, DC. Journal of Modern Mobility Systems, 1, (pp. 110-118).
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