Assessing service and price sensitivities, and pivot elasticities of public bikeshare system users through monadic design and ordered logit regression

Abstract

Pricing is one of the major factors that affects ridership and revenue of the bikeshare systems. This paper examines bikeshare users' sensitivity to changes in price and preferences on service by conducting an intercept survey at Capital Bikeshare (CaBi) stations. Monadic price testing approach was used to design survey questions and elicit responses on sensitivity of users to price changes in fare products. Ordered logit regression results indicated that higher household income groups and ‘White’ users are less sensitive to price compared to other income groups and other races/ethnicities, respectively. An illustrative application of the demand curves is presented, which showed that low-income groups are more sensitive to price than the middle and high-income groups. White users were found to be approximately 20% less price sensitive than other races for both casual users purchasing single-trips and annual members. The price elasticities revealed that females are about 30% and 10% more price sensitive than males for single-trip fare (STF) and annual membership, respectively. Also, sightseeing trips are 30% less price sensitive than work trips for STF purchasers. An illustrative application of income-based elasticities indicated that reducing the STF to $1.50 from the current $2.00 per trip and annual membership to $73.00 (from $85 per year) were found to improve both ridership and revenue. It is expected that the contributions from this study would provide insights and guidance on evaluating future pricing policy changes at various bikeshare systems.

Keywords

• Bikeshare
• Monadic price test
• Monadic design
• Price sensitivity
• Service sensitivity
• Elasticities