Investigating demand models with more flexible elasticity functions: empirical insights from rail demand analysis

IF 3.5 2区 工程技术 Q1 ENGINEERING, CIVIL
Mark Wardman
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引用次数: 0

Abstract

Models of rail travel demand take one of three generic functional forms: the generalised cost (GC) function where price and the various time variables are combined into a composite term through the use of appropriate values of time; the generalised journey time and fare (GJT-Fare) approach, where the time-related variables are combined into a single term and fare remains separate; and the specification of separate elasticities for all terms, termed the separate components (SC) approach. This research extends that reported by Wardman and Toner (Transportation 47:75–108, 10.1007/s11116-017-9850-7, 2020) in exploring more flexible functional forms where appropriate parameterisation of the standard GC, GJT and SC models allows them to have more general elasticity properties. Whilst the aforementioned study discounted the standard GC approach on the grounds of inferior fit and undesirable elasticity properties, the analysis reported here, based on large datasets, finds best-fitting more flexible models to have elasticity properties that resemble those of the GC approach. Indeed, the preferred functions can deliver elasticities that are somewhat different from those of the GJT-Fare approach that has long provided the basis of official rail demand forecasts in Great Britain. In addition, the study adds to the existing evidence base by providing credible and precise elasticities for GJT and fare, and importantly for the rarely estimated GC and SC elasticities, reaffirms the need of GC models to directly estimate demand consistent values of time, and indicates that the weights currently attached to headway and interchange in formulating GJT are in need of significant amendment. Although the context is rail in Great Britain, the results have relevance to demand analysis of other modes and in other countries as well as to other transport modelling approaches.

研究弹性函数更灵活的需求模型:铁路需求分析的经验启示
铁路旅行需求模型采用三种通用函数形式之一:广义成本(GC)函数,通过使用适当的时间值,将价格和各种时间变量合并为一个综合项;广义旅行时间和票价(GJT-Fare)方法,将与时间相关的变量合并为一个单一项,票价保持独立;以及为所有项指定独立弹性,称为独立组件(SC)方法。这项研究扩展了 Wardman 和 Toner(《交通》,47:75-108, 10.1007/s11116-017-9850-7,2020 年)的研究,探索了更灵活的函数形式,对标准 GC、GJT 和 SC 模型进行适当参数化,使其具有更普遍的弹性特性。上述研究以拟合度较低和弹性特性不理想为由否定了标准 GC 方法,而本报告基于大型数据集的分析发现,拟合度最佳的更灵活模型具有与 GC 方法相似的弹性特性。事实上,优选函数所提供的弹性与 GJT-Fare 方法的弹性有些不同,而 GJT-Fare 方法长期以来一直是英国官方铁路需求预测的基础。此外,该研究还为 GJT 和票价提供了可信而精确的弹性系数,从而为现有的证据基础增添了新的内容。重要的是,对于很少估算的 GC 和 SC 弹性系数而言,该研究重申了 GC 模型直接估算与需求一致的时间值的必要性,并表明目前在制定 GJT 时对班次和换乘所附加的权重需要进行重大修改。虽然研究的背景是英国的铁路,但研究结果对其他国家其他模式的需求分析以及其他交通建模方法也有借鉴意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transportation
Transportation 工程技术-工程:土木
CiteScore
10.70
自引率
4.70%
发文量
94
审稿时长
6-12 weeks
期刊介绍: In our first issue, published in 1972, we explained that this Journal is intended to promote the free and vigorous exchange of ideas and experience among the worldwide community actively concerned with transportation policy, planning and practice. That continues to be our mission, with a clear focus on topics concerned with research and practice in transportation policy and planning, around the world. These four words, policy and planning, research and practice are our key words. While we have a particular focus on transportation policy analysis and travel behaviour in the context of ground transportation, we willingly consider all good quality papers that are highly relevant to transportation policy, planning and practice with a clear focus on innovation, on extending the international pool of knowledge and understanding. Our interest is not only with transportation policies - and systems and services – but also with their social, economic and environmental impacts, However, papers about the application of established procedures to, or the development of plans or policies for, specific locations are unlikely to prove acceptable unless they report experience which will be of real benefit those working elsewhere. Papers concerned with the engineering, safety and operational management of transportation systems are outside our scope.
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