163 results found
Anupriya, Graham DJ, Carbo JM, et al., 2020, Understanding the costs of urban rail transport operations, Transportation Research Part B: Methodological, Vol: 138, Pages: 292-316, ISSN: 0191-2615
There is considerable variation in the average cost of operations across urban rail transport (or metro) systems. Since metros are typically owned and operated by public authorities, there is a public interest case in understanding the key drivers of their operational costs. This paper estimates short-run cost functions for metro operations using a unique panel dataset from twenty-four metro systems around the world. We use a flexible translog specification and apply dynamic panel generalised method of moments (DPGMM) estimation to control for confounding from observed and unobserved characteristics of metro operations. Our empirical results show that metro systems with a high density of usage are the most cost-efficient. We also find that operational costs fall as metro size increases. These results have important implications for the economic appraisal of metro systems.
Horcher D, Graham DJ, 2020, MaaS economics: Should we fight car ownership with subscriptions to alternative modes?, Economics of Transportation, Vol: 22, ISSN: 2212-0122
Proponents of the Mobility as a Service concept claim that subscriptions to alternative modes can effectively reduce car ownership and the adverse effects of underpriced car use. We test this hypothesis in a microeconomic model with endogenous mode choice as well as car and subscription ownership. The model contains congestible urban rail and car sharing options as substitutes of underpriced private car use. We find that aggregate car ownership is not a reliable proxy for road congestion: subscriptions may reduce car ownership while increasing the vehicle miles travelled by remaining car owners. Subscriptions induce welfare losses for two reasons. First, pass holders overconsume the alternative modes, as the marginal fare they face drops to zero. Second, non-pass holders tend to shift to car use due to the crowding induced by pass holders, causing additional distortions. We illustrate numerically that differentiated pricing is more efficient in achieving the goals of MaaS.
Ouali LAB, Graham DJ, Barron A, et al., 2020, Gender differences in the perception of safety in public transport, Journal of the Royal Statistical Society: Series A (Statistics in Society), Vol: 183, Pages: 737-769, ISSN: 0964-1998
Singh R, Graham DJ, Horcher D, et al., 2020, Decomposing journey time variance on urban metro systems via semiparametric mixed methods, Transportation Research Part C: Emerging Technologies, Vol: 114, Pages: 140-163, ISSN: 0968-090X
The availability of automated data for urban metro systems allows operators to accurately measure journey time reliability. However, there remains limited understanding of the causes of journey time variance and how journey time performance can be improved. In this paper, we present a semiparametric regression modelling framework to determine the underlying drivers of journey time variance in urban metro systems, using the London Underground as a case study. We merge train location and passenger trip data to decompose total journey times into three constituent parts: access times as passengers enter the system, on-train times, and egress times as passengers exit at their destinations. For each journey time component, we estimate non-linear functional relationships which we then use to derive elasticity estimates of journey times with respect to service supply and demand factors, including operational and physical characteristics of metros as well as passenger demand and passenger-specific travel characteristics. We find that the static fixed physical characteristics of stations and routes have the greatest influence on journey time, followed by train speeds, and headways, for which the average elasticities of total journey time are −0.54 and 0.05, respectively. The results of our analysis could inform operators about where potential interventions should be targeted in order to improve journey time performance.
Li H, Zhu M, Graham DJ, et al., 2020, Are multiple speed cameras more effective than a single one? Causal analysis of the safety impacts of multiple speed cameras, Accident Analysis and Prevention, Vol: 139, ISSN: 0001-4575
Most previous studies investigate the safety effects of a single speed camera, ignoring the potential impacts from adjacent speed cameras. The mutual influence between two or even more adjacent speed cameras is a relevant attribute worth taking into account when evaluating the safety impacts of speed cameras. This paper investigates the safety effects of two or more speed cameras observed within a specific radius which are defined as multiple speed cameras. A total of 464 speed cameras at treated sites and 3119 control sites are observed and related to road traffic accident data from 1999 to 2007. The effects of multiple speed cameras are evaluated using pairwise comparisons between treatment units with different doses based on the propensity score methods. The spatial effect of multiple speed cameras is investigated by testing various radii. There are two major findings in this study. First, sites with multiple speed cameras perform better in reducing the absolute number of road accidents than those with a single camera. Second, speed camera sites are found to be most effective with a radius of 200 m. For a radius of 200 m and 300 m, the reduction in the personal injury collisions by multiple speed cameras are 21.4 % and 13.2 % more than a single camera. Our results also suggest that multiple speed cameras are effective within a small radius (200 m and 300 m).
Ait Bihi Ouali L, Carbo JM, Graham D, 2020, Do changes in air transportation affect productivity? A cross country panel approach, Regional Science Policy and Practice, ISSN: 1757-7802
This paper quantifies the economic impact of air transportation worldwide using two panel data methods to assess the effect of air cargo and air passenger volumes on GDP per employee (aggregate labour productivity). Fixed effects methods and instrumental variables allow us to tackle endogeneity concerns and simultaneity biases. We first use a generalized method of moments specification (GMM) on a World Bank panel dataset containing information for all countries worldwide, separated into 264 areas over the period 1990‐2017. Results show that a 10% increase in air passengers is associated with a 0.6% increase in GDP per employee. Complementary instrumental variables estimates indicate a slight negative bias in this result, yielding an effect of 0.86%. Results are very similar for different parts of the world, with elasticity estimates ranging between 0.01 and 0.04, except in North Africa and Middle Eastern countries, where effects on labour productivity are found to be insignificant. Overall, air passenger traffic has a stronger and more positive effect on GDP per employee than air cargo. We conduct a complementary analysis at the European level using Eurostat data (NUTS2) and perform an analysis on over 300 European sub‐regions. Results indicate that air transport has a positive, stronger and more significant effect on GDP per employee than air cargo, with a 10% increase in air passengers being associated with a labour productivity increase of 3.2%.
Zhang F, Graham DJ, 2020, Air transport and economic growth: a review of the impact mechanism and causal relationships, Transport Reviews, Vol: 40, Pages: 506-528, ISSN: 0144-1647
The impacts of air transport on the economy arise both directly, via activity in the aviation sector; and indirectly, via increased spending and wider economic benefits associated with improved access to resources, markets, technology and economic mass. Economic activity, in turn, supports and generates demand for air transport. Despite its potential importance, the reciprocal nature of the causal relationship between air transport and economic performance has remained somewhat understudied. This paper provides a synthesis review of the channels the aviation sector interacts with regional economy. The review focuses on quantitative studies that contribute to the state-of-the-art understandings of the causality. We find that the reciprocal causal relationship is more likely to prevail in less developed economies. For more developed economies, only one direction of the causality is recognised, which runs from air transport to economic growth. Especially substantial is the effect of airline enplanement on service-related employment. The reverse direction of the relationship is, however, not as significant as believed in a causal sense within the developed world. Therefore, cautions need to be taken when applying income elasticities (such as the elasticity of air passenger demand with respect to GDP) in air travel demand forecasting, which implicitly assumes that economic growth causally leads to air traffic increment. Based on the fundamental links between air transport and economic growth, some typical imperfections and inefficiencies in aviation markets are discussed and promising avenues for future research are proposed.
Morse L, Trompet M, Barron A, et al., 2020, A benchmarking framework for understanding bus performance in the U.S., Benchmarking: an international journal, Vol: 27, Pages: 1533-1550, ISSN: 1463-5771
Purpose This paper describes a benchmarking framework applied to medium-sized urban public bus agencies in the United States which has overcome the challenges of data quality, comparability and understanding.Design/methodology/approach The benchmarking methodology described in this paper is based on lessons learned through seven years of development of a fixed route key performance indicator (KPI) system for the American Bus Benchmarking Group (ABBG). Founded in 2011, the ABBG is a group of public medium-sized urban bus agencies that compare performance and share best practices with peers throughout the United States. The methodology is adapted from the process used within international benchmarking groups facilitated by Imperial College and consists of four main elements: peer selection, KPI system development, processes to achieve high-quality data, and processes to understand relative performance and change.Findings The four main elements of the ABBG benchmarking methodology consist of eighteen sub-elements, which when applied overcome three main benchmarking challenges; comparability, data quality, and understanding. While serving as examples for the methodology elements, the paper provides specific insights into service characteristics and performance among ABBG agencies.Research limitations/implications The benchmarking approach described in this paper requires time and commitment and thus is most suitably applied to a concise group of agencies. Practical implications This methodology provides transit agencies, authorities and benchmarking practitioners a framework for effective benchmarking. It will lead to high-quality comparable data and a strong understanding of the performance context to serve as a basis for organizational changes, whether for policy, planning, operations, stakeholder communication, or program development. Originality/value The methodology, while consistent with recommendations from literature, is unique in its scale, in-depth validation
Hörcher D, De Borger B, Seifu W, et al., 2020, Public transport provision under agglomeration economies, Regional Science and Urban Economics, Vol: 81, Pages: 1-19, ISSN: 0166-0462
The purpose of this paper is to investigate, using both theoretical and numerical analysis, the impact of agglomeration externalities on short-run policy decisions in public transport, i.e. socially optimal pricing, frequency setting, and subsidisation. We develop a simple two-mode model in which commuters can opt for car or public transport use; car use leads to congestion, and public transport is subject to crowding. Allowing for agglomeration externalities, we show the following results. First, if car use is correctly priced for congestion, agglomeration benefits imply substantially lower public transport fares and higher frequencies. They neutralise to some extent the pressure to increase fares to correct the crowding externality. Second, as a consequence, agglomeration benefits justify low cost recovery ratios in public transport. Assuming an agglomeration elasticity of 1.04, a value well within the range of reported elasticities, numerical implementation of the model finds that cost-recovery ratios are 35.8% lower than in the absence of the productivity externality. Third, interestingly, the effect of agglomeration benefits on fares and frequency is much smaller if road use is exogenously under-priced. In this case, any modal shift induced by lower public transport fares has opposing agglomeration effects on the two modes, since agglomeration benefits are not mode-specific.
Ait Bihi Ouali L, Graham D, Trompet M, et al., 2020, Gender differences in the perception of safety in public transport, Journal of the Royal Statistical Society Series A: Statistics in Society, ISSN: 0964-1998
Concerns over women's safety on public transport systems are commonly reported in the media. In this paper we develop statistical models to test for gender differences in the perception of safety and satisfaction on urban metros and buses using large-scale unique customer satisfaction data for 28 world cities over the period 2009 to 2018. Results indicate a significant gender gap in the perception of safety, with women being 10\% more likely than men to feel unsafe in metros (6% for buses). This gender gap is larger for safety than for overall satisfaction (3% in metros and 2.5% in buses), which is consistent with safety being one dimension of overall satisfaction. Results are stable across specifications and robust to inclusion of city-level and time controls. We find heterogeneous responses by sociodemographic characteristics. Data indicates 45% of women feel secure in trains and metro stations (respectively 55% in buses). Thus the gender gap encompasses more differences in transport perception between men and women rather than an intrinsic network fear. Additional models test for the influence of metro characteristics on perceived safety levels and find that that more acts of violence, larger carriages, and emptier vehicles decrease women's feeling of safety.
Ait Bihi Ouali L, Graham DJ, 2020, The Impact of the MeToo Scandal on Women’s Perceptions of Safety
This paper quantifies the effect of speed cameras on road trafficcollisions using anapproximate Bayesian doubly-robust (DR) causal inference estimation method.Previous empirical work on this topic, which shows a diverse range ofestimatedeffects, is based largely on outcome regression (OR) models using the Empirical Bayesapproach or on simple before and after comparisons. Issues of causality andconfounding have received little formal attention. A causal DR approach combinespropensity score (PS) and OR models to give an average treatmenteffect (ATE)estimator that is consistent and asymptotically normal under correct specification ofeither of the two component models. We develop this approach withina novelapproximate Bayesian framework to derive posterior predictive distributions for theATE of speed cameras on road traffic collisions. Our results for England indicatesignificant reductions in the number of collisions at speed cameras sites (mean ATE =-15%). Our proposed method offers a promising approach for evaluation of transportsafety interventions.
Ait Bihi Ouali L, Graham DJ, Gender Differences in the Perception of Safety in Transport: The case of subways, 8th hEART Conference
Graham D, Gibbons S, 2019, Quantifying wider economic impacts of agglomeration for transport appraisal: existing evidence and future directions, Economics of Transportation, Vol: 19, ISSN: 2212-0122
This paper is concerned with the Wider Economic Impacts (WEIs) of transport improvements that arise via scale economies of agglomeration. It reviews the background theory and empirical evidence on agglomeration, explains the link between transport and agglomeration, and describes a three step procedure to appraise agglomeration impacts in a number of different settings. It includes new analytical work on measures of agglomeration and reports agglomeration-productivity elasticity estimates for the UK not previously published in the academic literature. The paper concludes with a set of recommendations for future empirical work on agglomeration and transport appraisal.
Li H, Graham DJ, Ding H, et al., 2019, Comparison of empirical Bayes and propensity score methods for road safety evaluation: a simulation study, Accident Analysis and Prevention, Vol: 129, Pages: 148-155, ISSN: 0001-4575
Statistical evaluation of road safety interventions can be undertaken using a variety of different approaches, typically requiring different assumptions to obtain causal identification. In this paper, we conduct a simulation study to compare the performance of empirical Bayes (EB) and propensity score (PS) based methods, which have featured prominently in the recent literature, in settings with and without violation of key assumptions. The estimators considered include EB, inverse probability weighting (IPW), and Doubly Robust (DR) estimation. We find that while the EB approach has good finite sample properties when model assumptions are met, the consistency of this estimator is substantially diminished when the reference and treated sites follow different functions. The IPW estimator performs well in large samples, but requires a correctly specified PS model with sufficient overlap in covariate distributions between treated and control units. The DR estimator allows for violation of assumptions in either the regression or PS model, but not both. We find that this added level of robustness affords overall better performance than attained via EB or IPW estimation.
Singh R, Graham DJ, Anderson RJ, 2019, Characterizing journey time performance on urban metro systems under varying operating conditions, Transportation Research Record, Vol: 2673, Pages: 516-528, ISSN: 0361-1981
Automated fare collection (AFC) data provide opportunities for improved measurement of public transport service quality from the passenger perspective. In this paper, AFC data from the London Underground are used to measure service quality through an analysis of journey time performance under regular and incident-affected operating conditions. The analysis involves two parts: (i) parametrically defining the shape of journey time distributions, and (ii) defining three performance metrics based on the moments of the distributions to measure the mean and variance of journey times. The metrics show that mean journey times are longest during the afternoon peak across all lines analyzed, and are more variable during the afternoon and off-peak periods depending on the line. Under incident conditions, mean journey times range from 8% to 39% longer compared with regular conditions, depending on the line. Overall, the main application of this work is that the metrics presented here can be directly applied by operators to quantify customer journey time performance, and can be further extended for industry-wide application to compare performance across metro networks.There has been increasing recognition in the transport industry of the need for performance metrics that capture journey time reliability from a passenger perspective as opposed to the traditional operator-oriented indicators. In a report for the Organisation for Economic Co-operation and Development (OECD) on service quality metrics used by metro operators, it is noted that the three most commonly reported metrics relating to journey time are train delay, wait times, and passenger journeys on-time (1). The first two metrics capture train performance from a schedule and headway adherence point of view. The third attempts to capture the experience of the user; however, it is recognized that operator-oriented indicators are rarely able to measure the true impact of passenger delay (2).The journey time distribution on
Anupriya A, Graham D, Horcher D, Existence of Hypercongestion in Highways: A truth or a fallacy?, ITEA Annual Conference on Transportation Economics
Canavan S, Barron A, Cohen J, et al., 2019, Best Practices in Operating High Frequency Metro Services, Transportation Research Record, ISSN: 0361-1981
© National Academy of Sciences: Transportation Research Board 2019. Most metro rail systems worldwide are facing increasing demand and the need to deliver additional capacity in key corridors. Although total capacity reflects the combination of train capacity and frequency, increasing frequency is the primary strategy to increase capacity on existing lines where infrastructure is fixed. Higher frequencies also increase efficiency, by attracting more passengers and making existing journeys faster, thereby making better use of expensive rail infrastructure and increasing both metro revenues and wider economics benefits to the cities they serve. This paper is based on a study conducted for the Community of Metros, a worldwide group of metro systems, which surveyed 17 high frequency lines. The paper first documents the characteristics of high frequency lines [with 25 trains per hour (tph) or more defined as “high frequency” and 30 tph or more as “very high frequency”] and presents the various constraints to higher frequency operations, including how they interact and the various possible solutions. Five main categories of constraints were identified, relating to signaling and train control, station and train crowding, fleet, terminal turnarounds, and service complexity. To achieve the highest frequencies, it is essential for metro systems to take a holistic approach and identify not only the immediate constraints but also secondary and tertiary constraints that may prevent the full benefits of improvements from being realized. This paper provides guidance to those operating, funding, planning, and designing metro systems in how to maximize frequency and thereby deliver greater benefits to riders, transit agencies, and stakeholders.
Achurra-Gonzalez PE, Angeloudis P, Goldbeck N, et al., Evaluation of port disruption impacts in the global liner shipping network, Journal of Shipping and Trade, ISSN: 2364-4575
The global container shipping network is vital to international trade. Current techniques for its vulnerability assessment are constrained due to the lack of historical disruption data and computational limitations due to typical network sizes. We address these modelling challenges by developing a new framework, composed by a game-theoretic attacker-defender model and a cost-based container assignment model that can identify systemic vulnerabilities in the network. Given its focus on logic and structure, the proposed framework has minimal input data requirements and does not rely on the presence of extensive historical disruption data. Numerical implementations are carried in a global-scale liner network where disruptions occur in Europe’s main container ports. Model outputs are used to establish performance baselines for the network and illus-trate the differences in regional vulnerability levels and port criticality rankings with different disruption magnitudes and flow diversion strategies. Sensitivity analysis of these outputs identifies network compo-nents that are more susceptible to lower levels of disruption which are more common in practice and to assess the effectiveness of component-level interventions seeking to increase the resilience of the system.
Collins DJ, Graham DJ, 2019, Use of open data to assess cyclist safety in London, Transportation Research Record, Vol: 267, Pages: 27-35, ISSN: 0361-1981
This study develops a predictive model for cycling collisions in London. Specifically, the effects of bus lanes, parking or loading facilities, and multilane roads on the risk of cycling collisions are considered. To the best of the authors’ knowledge, this is the first such predictive collision model that develops covariates to measure the characteristics of different types of road infrastructure within zones. A kernel density estimator is used to identify 90 collision hotspots. Each hotspot is populated with information regarding the highway infrastructure within it. A multiple linear regression model tests for the statistical significance of the infrastructure variables. Bus lanes, multilane roads, and 30-mph speed limits are found to affect cycle collision counts, whereas junction density has the largest impact on collision density. Speed limits of 20 mph affect collision counts to a lesser degree than 30 mph, indicating potential safety improvement from reducing speed limits. One-way roads are found to reduce the risk of collisions, along with the provision of priority junctions. This infers that other junction types, such as roundabouts and signalized junctions, present a higher collision risk. The models produce conflicting results on parking or loading provision. The models are expanded to include sociodemographic variables, such as population and employment. The combined model offers no performance improvement over the infrastructure-only model, although a potential link between public transport provision and reducing cycle collisions warrants further investigation.
Pogonyi CG, Graham DJ, M Carbo J, 2019, Metros, Agglomeration and Firm Productivity. Evidence from London
Achurra-Gonzalez PE, Novati M, Foulser-Piggott R, et al., 2019, Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application, Accident Analysis & Prevention, Vol: 123, Pages: 399-410
Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity.
Carbo Martinez J, Graham D, Anupriya A, et al., 2018, Evaluating the causal economic impacts of transport investments: evidence from the Madrid-Barcelona high speed rail corridor, Journal of Applied Statistics, Vol: 46, Pages: 1714-1723, ISSN: 0266-4763
This paper evaluates economic impacts arising from the introduction of high-speed rail (HSR) between Madrid and Barcelona. Using difference-in-differences estimation we estimate an average treatment effect for provinces with stops on the HSR line of 2.4% for economic output, 3.3% for numbers of firms, and 1.1% for labour productivity. We complement our DID results with a synthetic control analysis for Lleida and Tarragona, two provinces that we argue were assigned HSR stations largely due to their incidental location. We find that both the number of firms and labour productivity are substantially higher in these provinces than in their synthetic counterparts.
Anupriya A, Graham D, Anderson R, et al., Cost Function for Urban Rail Transport Systems, Transportation Research Board 98th Annual Meeting
Zhang N, Graham DJ, Carbo Martinez JM, Using smart card data to analyse the disruption impact on urban metro systems, Transportation Research Board 98th Annual Meeting
Canavan S, Graham D, Anderson R, et al., 2018, Urban metro rail demand: evidence from dynamic generalised method of moments (GMM) estimates using panel data, Transportation Research Record, Vol: 2672, Pages: 288-296, ISSN: 0361-1981
This paper estimates elasticities of demand for metro service with respect to fares, income, quality of service, population and network length. Data for 32 world metro systems covering the period from 1996 to 2015 are analysed within a dynamic panel data specification. Three key contributions are made. First, we collate a database for estimation that is more extensive than that used in previous studies. Second, the quality of the data we have available allows us to more accurately represent quality of service than has been possible previously. And lastly, we estimate and compare two different measures of demand. Our analysis finds a statistically significant negative fare elasticity of -0.25 in the long run for a passenger km specified model and -0.4 in the long run for a passenger journeys specified model, and a positive long run income elasticity of 0.17 and 0.18 for the passenger km and passenger journey models respectively. Regarding quality of service we find positive long run elasticities of 0.56 and 0.47 for the passenger km and passenger journey models respectively. Income levels, population and the size of the network are also found to be statistically significant and positive in nature. The results suggest passenger km and passenger journeys will increase more in response to changes in service (here represented by increased capacity) than to changes in fares, with the difference in elasticities of service and fares being more pronounced for passenger km.
Zhang F, Graham DJ, Wong M, 2018, Quantifying the substitutability and complementarity between high-speed rail and air transport, Transportation Research Part A: Policy and Practice, Vol: 118, Pages: 191-215, ISSN: 0965-8564
This paper quantifies the substitution and complementary effects of high-speed rail (HSR) on air travel demand in terms of both route traffic and airport enplanement. Employing the difference-in-differences (DID) method, the first part of the analysis measures the effect of new HSR routes on parallel air route traffic with a focus on East Asian regions (Mainland China, Japan, South Korea, and Taiwan). The second part examines the effect of air-HSR integration on passenger enplanement at East Asian airports and compares with that in the Central European market. We find that in general the airport’s access cost (reflected by the distance from central city) has a negative impact on the air traffic. The substitution effects of HSR are the most significant on short- and medium-haul (below 1000 km) air routes while introducing HSR services has encouraged long distance (over 1000 km) air travels in Mainland China. The complementary effect is investigated in the context of air-HSR integration, which has significantly positive impacts on airport enplanement at primary hub airports when fitted with on-site HSR links. The benefit is limited at secondary hubs and regional airports possibly by locations and HSR service frequencies.
Han K, Graham D, Ochleng W, 2018, Border delays could cause congestion, Food Science and Technology (London), Vol: 32, Pages: 14-15, ISSN: 1475-3324
Pogonyi CG, Graham DJ, M Carbo J, 2018, Growth or Displacement? A Metro Line's Causal Impact on the Spatial Distribution of Business Units and Employment: Evidence from London
Trompet M, Anderson RJ, Graham DJ, 2018, Improved understanding of the relative quality of bus public transit using a balanced approach to performance data normalization, Transportation Research Part A: Policy and Practice, Vol: 114, Pages: 13-23, ISSN: 0965-8564
In order for bus operators and/or their respective authorities to understand where service quality can improve, it is useful to systematically compare performance with organizations displaying similarities in types of services offered, operational characteristics and density of the service area. These similar characteristics enable peer organizations to benchmark performance once their operational data are normalized for differences in scale of operations. The most commonly used normalization factors for the demand side output are passenger boardings and passenger kilometres. For the supply side output these are vehicle kilometres and vehicle hours. Through twelve years of experience in the International Bus Benchmarking Group (IBBG) a better understanding of differences in service characteristics between ‘similar’ peers has been achieved, which highlight a challenge for the interpretation of normalized performance. It became clear that relative performance should often not be concluded from performance indicators normalized in a single dimension. Variety between peers in commercial speed, trip length, vehicle planning capacity, vehicle weight and network efficiency result in the need for a bi-dimensional or balanced approach to data normalization. This paper quantifies the variety within these operational characteristics and provides examples of the interpretation bias this may lead to. A framework is provided for use by bus organization management, policymakers and benchmarking practitioners that suggests applicable combinations of denominators for a balanced normalization process, leading to improved understanding of relative performance.
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