Competition for and in the passenger rail market: Comparing open access versus franchised train operators' costs and reliability in Britain

Stead, Alexander D.; Wheat, Phill; Smith, Andrew; Ojeda-Cabral, Manuel

doi:10.1016/j.jrtpm.2019.100142

Cited by 8 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These effects offset the lower economies of density with respect to franchised operators. Using more data, Stead et al (2019) clarify that openaccess operators, in the UK, focus on lower-cost and lower-quality services.…”

Section: European Casesmentioning

confidence: 98%

A Difference-In-Difference Approach to Estimate the Price Effect of Market Entry in High-Speed Rail

Beria

Tolentino

Shtele

et al. 2022

Competition and Regulation in Network Industries

View full text Add to dashboard Cite

The effect of competition on prices in the passenger transport sector can be difficult to estimate because of many influencing factors such as state regulation, demand, seasonality, and reactions of indirect competitors. A case of great interest in the rail sector is Italy, where on-track competition in the high-speed segment has been in place for nearly ten years. The paper aims at answering the question whether—and how much—incumbent’s prices are affected when competition starts on a route previously in monopoly. The case is the start of operations on the Turin–Milan–Venice route, where Italo entered in May 2018. Adopting a difference-in-difference approach, we check if Trenitalia changed the price strategy on the route before and after the entry, with respect to two control groups. The addition of placebo tests allows us to understand the ranges of significance of the results and to estimate the noise level of the estimates. Our findings suggest that the start of competition led to lower prices in the short-medium period. In the specific case, the Milano–Venezia route saw Trenitalia’s prices reduced by 21–26% (±2–5%) in a time span of 84–140 days after Italo’s entry and for advanced bookings from 2 to 10 days. Last-day prices remain unchanged, while early bookings are reduced by just 9%. This price reduction does not remain stable in the longer term, when other effects add up and blur the effect of the entry. Nevertheless, we keep observing a smaller, ∼15%, but still negative prices change.

show abstract

Section: European Casesmentioning

confidence: 98%

A Difference-In-Difference Approach to Estimate the Price Effect of Market Entry in High-Speed Rail

Beria

Tolentino

Shtele

et al. 2022

Competition and Regulation in Network Industries

View full text Add to dashboard Cite

show abstract

“…Canca et al, 2017 [1] Line planning O Yan et al, 2019 [2] MILP Hickish et al, 2020 [3] Network optimization GA Schlechte et al, 2011 [4] NH Weik et al, 2020 [5] Nodes (location, classification) NH Ahmed et al, 2020 [6] Station location GA Dong et al, 2020 [7] O Qiannan et al, 2022 [8] NH Binder et al, 2021 [9] Timetable creation and rescheduling SA Jamili and Pourseyed Aghaee, 2015 [10] SA Shang et al, 2018 [11] NH Wang et al, 2018 [12] MILP Jensen et al, 2016 [13] NH Yin et al, 2021 [14] O Zhang et al, 2018 [15] O Zhang et al, 2019a [16] MILP Zhang et al, 2019b [17] NH Zhang et al, 2022 [18] O Zhao et al, 2021 [19] MILP Whitbrook et al, 2018 [20] MS Zheng et al, 2014 [21] BBO Satoshi et al, 2011 [22] Operations (delay management, train routing) TS Sama et al, 2017 [23] SI Oneto et al, 2017 [24] O Xiao et al, 2018 [25] Demand side of the transport system NH Shen et al, 2016 [26] O Wu et al, 2013 [27] O Liu et al, 2019 [28] ANN Hansson et al, 2021 [30] Bus systems and networks NH Wei et al, 2021 [31] NH Ngo et al, 2021 [32] Ride-hailing services NH Behrends, 2017 [33] Nodes, coordination NH Stead et al, 2019 [34] NH Yang et al, 2020 [35] GA Lianhua and Xingfang, 2022 [36] SA Chen et al, 2020 [37] Autonomous Vehicles O Lopez and Farooq, 2020 [39] Smart mobility data-markets BC Xavier and Xavier, 2016 [44] Not related to transport systems O Martinelli and Teng, 1996…”

Section: Source Problem Toolmentioning

confidence: 99%

“…The number of input parameters in Dong et al [7] is 21 and includes, inter alia: the number of passengers arriving at the station, the number of trains, etc. A specific parameter is "passenger satisfaction" or "dissatisfaction" (Hickish et al [3], Satoshi et al [22], Stead et al [34], Shen et al [26]). Shen et al [26] formulate nine elements creating passenger satisfaction: direction and guidance, cleanliness and comfort, speediness and convenience, safety and security, ticket service, equipment and facilities, staff service, information distribution, and convenient facilities for passengers.…”

Section: Sourcementioning

confidence: 99%

“…It is worth noting that [29], discussed below, does not exist in the table because of its review character. In [30][31][32][33][34][35][36][37], researchers address the problems of integration in a suburban transport system. Sources [38,39] show directions for future research, and sources [40][41][42][43] contain important definitions (they were not added to the table).…”

Section: Introduction With the Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

NOAH as an Innovative Tool for Modeling the Use of Suburban Railways

Kruszyna

2022

Sustainability

View full text Add to dashboard Cite

The paper presents an innovative method called the “Nest of Apes Heuristic” (NOAH) for modeling specific problems by combining technical aspects of transport systems with human decision-making. The method is inspired by nature. At the beginning of the paper, potential problems related to modeling a suburban rail system were presented. The literature review is supplemented with a short description of known heuristics. The basic terminology, procedures, and algorithm are then introduced in detail. The factors of the suburban rail system turn into “Monkeys”. Monkeys change their position in the nest, creating leaders and followers. This allows for the comparison of the factor sets in a real system. The case study area covers the vicinity of Wroclaw, the fourth largest city in Poland. Two experiments were conducted. The first takes into account the average values of the factors in order to observe the algorithm’s work and formulate the stopping criteria. The second is based on the current values of the factors. The purpose of this work was to evaluate these values and to assess the possibilities of changing them. The obtained results show that the new tool may be useful for modeling and analyzing such problems.

show abstract

Organisational restructuring of Indian Railways

Dutta¹

2022

Case Studies on Transport Policy

View full text Add to dashboard Cite

Competition for and in the passenger rail market: Comparing open access versus franchised train operators' costs and reliability in Britain

Cited by 8 publications

References 13 publications

A Difference-In-Difference Approach to Estimate the Price Effect of Market Entry in High-Speed Rail

A Difference-In-Difference Approach to Estimate the Price Effect of Market Entry in High-Speed Rail

NOAH as an Innovative Tool for Modeling the Use of Suburban Railways

Organisational restructuring of Indian Railways

Contact Info

Product

Resources

About