2016
DOI: 10.1016/j.tranpol.2016.06.008
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Curbside parking pricing in a city centre using a threshold

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Cited by 24 publications
(5 citation statements)
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“…Recent applications of the constrained multinomial logit (CMNL) model span various domains, including the choice of transportation mode [24], school selection [25], urban economy [26,27], parking pricing [28], location modeling [29], renewable energy development [30], and modeling path choices in urban rail transit networks [31]. While the CMNL has been employed in pricing decisions [32,33], primarily analyzing the impact of constraints on the maximum availability of payment to different consumers, none of the models incorporate the influence of exogenous constraints or the system in a dynamic or intertemporal environment of integrated inventory management with pricing.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Recent applications of the constrained multinomial logit (CMNL) model span various domains, including the choice of transportation mode [24], school selection [25], urban economy [26,27], parking pricing [28], location modeling [29], renewable energy development [30], and modeling path choices in urban rail transit networks [31]. While the CMNL has been employed in pricing decisions [32,33], primarily analyzing the impact of constraints on the maximum availability of payment to different consumers, none of the models incorporate the influence of exogenous constraints or the system in a dynamic or intertemporal environment of integrated inventory management with pricing.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Thus, studies of commercial parking offer comprehensive insights into the trade-offs between location, time, and cost that are relevant to charging choices as well. These studies measure how choice of parking location is influenced by cost or fee levels, walk time, search time or the probability of finding a vacant space, time limits or opening hours of a car parking facility, and whether the parking is onstreet or off-street (Zhang and Zhu, 2016;Chaniotakis and Pel, 2015;Ibeas et al, 2014;Simićević et al, 2013;van der Waerden et al, 2011;Hess and Polak, 2009). Millard-Ball et al (2014) measure the relationship between occupancy and the probability of finding a space quickly in order to estimate parking stability, a concept similar to the 'certainty' described in the previous section.…”
Section: Destination Chargingmentioning
confidence: 99%
“…Vehicle safety is yet another consideration, and one study of commercial parking found that car parks were assumed to be more secure than on-street parking, particularly for owners of new cars (Ibeas et al, 2014). Meanwhile, Zhang and Zhu (2016) found that fee thresholds influence the decision of where to park, with users willing to accept a higher maximum cost for on-street parking compared to off-street, although not if the on-street parking came with a long walk to the destination, with older drivers willing to pay more to walk less. Finally, the value of walking time from the parking space to the destination was found by some studies to be dependent upon journey purpose and length of stay, with a desire to walk less for work or weekly shopping trips and more willingness to walk further for infrequent shopping or other longer stays (van der Waerden et al, 2017;Hess and Polak, 2009).…”
Section: Commercial Parkingmentioning
confidence: 99%
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“…Some scholars have observed the influences of various travel factors on travelers' behavior are based on the heterogeneity of travelers, analyzed the utility function of various parking methods, and optimized the price with the ideal parking sharing rate [13][14][15][16]. Others have used marginal cost-benefit analysis to take factors of environmental protection and living standards of surrounding residents [17], set charging threshold [18], and set pricing into consideration in order to maximize social benefits [19]. In recent years, some scholars have combined expected utility and prospect theory with travel mode selection, and used the combination of travel mode sharing logit model and private car traveler satisfaction function to build a price-setting model [20,21].…”
Section: Introductionmentioning
confidence: 99%