A bus route evaluation model based on GIS and super-efficient data envelopment analysis

When compared to large cities in developed countries, the shares of public transportation in most Chinese cities are low. Increasing the competitiveness of urban public transportation remains an urgent problem. A capable evaluation method for public transportation is required to assist the development of urban transit systems. This paper focuses on the bus system. Being devoid of standard criteria, it is difficult to determine the efficiency of a transit system or any bus line using a single evaluation index. This paper proposes a comparative analysis to evaluate bus lines so as to filter out candidates for further optimization. From the viewpoints of transit planning, operation and quality of service, this paper establishes 10 subordinate evaluation indices and then uses geographical information system tools, global positioning system data and smart card data to assist the index definition and calculation. Super-efficient data envelopment analysis (DEA) method is adopted for the proposed single factor and comprehensive evaluation models. Finally, the bus system in Shenzhen, China is used as a case study. The comparable significant results validate the capability of the proposed model.     

A data envelopment analysis model for evaluating the performance of taxi operators: a case study in Harbin,China

ABSTRACT

This paper measures the performance of taxi operators using data envelopment analysis (DEA) and the improvement of performance based on benchmarks. This includes basic DEA models and a cross efficiency model. In the present work, a sample set of 20 taxi operators are considered, and an evaluation indicator framework is constructed, which mainly involves the identification of decision-making units (DMUs) and the determination of input-output variables. The combined results of multiple DEA models are used to evaluate the performance of taxi operators in a case study of Harbin. The results highlight the significance of the combined application of multiple DEA models, especially a cross-efficiency model that can obtain more objective efficiency values. Finally, the benchmarking method is used to capture the achievements of best-performing operators and provide valuable improvement recommendations for inefficient operators. Conclusions provide a suitable basis for the operation and management of the taxi market.     

Investigating transit production and performance: a programming approach

Although efficiency and productivity are closely related issues, they have been generally examined separately in the transit literature. Using an extensive panel data set, this analysis extends prior research in two directions. First, efficiency rankings and efficient subsets of transit systems are obtained through data envelopment analysis (DEA), a non-parametric linear programming based methodology. Second, based on the results of the DEA analysis, globally efficient frontier production functions, in the context of transit operations in the United States, are built. The results indicate that when jointly considered, there is an improvement on both the theoretical and empirical aspects of examining efficiency and production in transit systems. Further, the results indicate that efficiency and returns to scale findings differ substantially depending on the evaluation methodology used.     

Have Emission Control Areas (ECAs) harmed port efficiency in Europe?

Ports in the European Union and North America have enforced environmental regulations on controlling SO_x and NOx emissions from ships in their coastal areas known as Emission Control Areas (ECAs). This study uses two-stage approaches to examine whether ECA regulations impact the efficiency of ports operating in such areas. First, port efficiencies are estimated using non-radial slacks-based measure (SBM) Data Envelopment Analysis (DEA) models. The efficiency scores estimated by the SBM DEA models are then regressed on explanatory variables, including the ECA factor, and macroeconomic indicators using bootstrapped truncated regression (BTR) models. Panel data is collected on countries in EU ECAs and non-ECAs regarding such input variables as capital and labor, with cargo as an output variable. The results indicate that ECA regulations can harm port efficiency, reflecting concerns of policy-makers and industrial managers: the average efficiency loss from an ECA designation amounts to 0.058–0.066 on a scale of 0–1, accounting for a 15–18% loss from ECA ports’ average efficiency scores.     

A Modeling Framework for Bus Rapid Transit Operations Evaluation and Service Planning

Abstract

In this paper, we present a dynamic traffic assignment-simulation modeling framework (DYNASMART-P) to support the evaluation and planning of Bus Rapid Transit (BRT) services in urban transportation networks. The model represents the different characteristics associated with BRT operations such as: exclusive right-of-way lanes, limited-stop service, signal prioritization at congested intersections, and enhanced bus stops to reduce passenger boarding times. A set of simulation experiments is conducted using the model to study the impact of introducing a hypothetical BRT service in the Knoxville area in the State of Tennessee. In these experiments, the different operational characteristics of BRT are evaluated in terms of potential impact on transit ridership and on the interacting auto traffic. The results illustrate the advantages of BRT for increasing transit ridership and improving overall system performance.     

Efficiency measurement of selected Australian and other international ports using data envelopment analysis

Available studies have not provided a satisfactory answer to the problem of making international comparisons of port efficiency. This study applies data envelopment analysis (DEA) to provide an efficiency measurement for four Australian and twelve other international container ports. While DEA has been applied to a wide number of different situations where efficiency comparisons are required, this technique has not previously been applied to ports. The DEA technique is useful in resolving the measurement of port efficiency because the calculations are non-parametric, can handle more than one output and do not require an explicit a priori determination of relationships between output and inputs, as is required for conventional estimation of efficiency using production functions. The ports of Melbourne, Rotterdam, Yokohama and Osaka are found to be the most inefficient ports in the sample, based on constant and variable returns to scale assumptions, mainly due to the enormous slack in their container berths, terminal area and labor inputs. The study also draws some policy implications for ports and recommends certain areas for future research.     

Impacts of built environment and emerging green technologies on daily transportation greenhouse gas emissions in Quebec cities: a disaggregate modeling approach

This paper aims to investigate the impact of the built environment (BE) and emerging transit and car technologies on household transport-related greenhouse gas emissions (GHGs) across three urban regions. Trip-level GHG emissions are first estimated by combining different data sources such as origin–destination (OD) surveys, vehicle fleet fuel consumption rates, and transit ridership data. BE indicators for the different urban regions are generated for each household and the impact of neighborhood typologies is derived based on these indicators. A traditional ordinary least square (OLS) regression approach is then used to investigate the direct association between the BE indicators, socio-demographics, and household GHGs. The effect of neighborhood typologies on GHGs is explored using both OLS and a simultaneous equation modeling approach. Once the best models are determined for each urban region, the potential impact of BE is determined through elasticities and compared with the impact of technological improvements. For this, various fuel efficiency scenarios are formulated and the reductions on household GHGs are determined. Once the potential impact of green transit and car technologies is determined, the results are compared to those related to BE initiatives. Among other results, it is found that BE attributes have a statistically significant effect on GHGs. However, the elasticities are very small, as reported in several previous studies. For instance, a 10 % increase in population density will result in 3.5, 1.5 and 1.4 % reduction in Montreal, Quebec and Sherbrooke, respectively. It is also important to highlight the significant variation of household GHGs among neighborhoods in the same city, variation which is much greater than among cities. In the short term, improvements on the private passenger vehicle fleet are expected to be much more significant than BE and green transit technologies. However, the combined effect of BE strategies and private-motor vehicle technological improvement would result in more significant GHGs reductions in the long term.     

Accounting for systematic heterogeneity across car commuters in response to multiple TDM policies: case study of Tehran

Modeling commuters’ choice behavior in response to transportation demand management (TDM) helps in predicting the consequences of TDM policies. Although research looking at choice behavior has evolved to investigate preference heterogeneity in response to factors influencing mode choice, as far as we know, no study has considered taste variation across commuters in response to multiple TDM policies. This paper investigates the presence of systematic preference heterogeneity across commuters, in response to the TDM policies that can be explained by their socio-economic or commuting-related characteristics. Analysis is based on results of a stated preference survey developed using a Design of Experiments approach. Five policies were assessed in order to study the impact they had on how commuters chose their mode of transportation. These include increasing parking cost, increasing fuel cost, implementing cordon pricing, reducing transit time and improving access to transit facilities. For the sake of assessing both systematic and random preference heterogeneity across car commuters, a form of the Mixed Multinomial Logit (MMNL) model that identifies sources of heterogeneity and consequently makes the choice models less restrictive in considering both systematic and random preference variation across individuals was developed. The sample includes 366 individuals who regularly commute to their workplace in the city center of Tehran, Iran. The likelihood function value of this model shows a significant improvement compared to the base MNL model, using the same variables. The MMNL model shows that taste variation across the studied commuters results in differences in influences estimated for three policies: increasing parking cost, reducing transit time and improving access to transit. The analysis examines several distributions for random parameters to test the impacts of restricting distributions to allow for only normality. The results confirm the potential to improve model fit with alternative distributions.     

A test of inter-modal performance measures for transit investment decisions

Choices among alternative transit capital investments are often complex and politically controversial. There is renewed interest in the use of performance indicators to assist in making rational and defensible choices for the investment of public funds. To improve the evaluation of rail and bus performance and provide more useful information for transit investment decision-makers, it is important to use performance indicators that fairly and efficiently compare different transit modes. This paper proposes a set of inter-modal performance indicators in which service input, service output, and service consumption are measured by total cost, revenue capacity miles/hours, and unlinked passenger trips/miles respectively based on economic principles and evaluation objectives. The proposed improvements involve the inclusion of capital as well as operating costs in such comparisons, and the recognition of the widely varying capacities of transit vehicles for seated and standing passengers. Two California cases, the Los Angeles – Long Beach Corridor and the Market/Judah Corridor in San Francisco, are used for testing their usefulness in the evaluation of the efficiency and effectiveness of rail and bus services. The results show substantial differences between performance indicators in current use and those proposed in this study. The enhanced inter-modal performance indicators are more appropriate for comparing the efficiency and effectiveness of different modes or a combination of transit modes at the corridor and system levels where most major investment decisions are made. This revised version was published online in June 2006 with corrections to the Cover Date.     

Assessing the technical efficiency, service effectiveness, and technical effectiveness of the world’s railways through NDEA analysis

This paper presents an approach to include both the unstorable feature of transportation service and the technological differences within railway companies in efficiency and effectiveness measurements. We explore efficiency and effectiveness for a group of 40 global railways in the year 2002, using traditional data development analysis (TDEA) and network data development analysis (NDEA). Comparing the results obtained from the NDEA model with those from the TDEA indicate that performance measures are quite different in terms of the magnitude, and even using different DEA type models to evaluate railway system performance does not distort the ranking of their performance. We also analyze the inter-related effects among three performance measures, finding that transportation service characteristics have positive effects on the evaluation of performance. Generally speaking, the NDEA model provides deeper insight regarding the sources of inefficiency and process-specific guidance to railway managers so as to help them improve their railway’s performance.     

Transit technology investment and selection under urban population volatility: A real option perspective

This paper addresses transit technology investment issues under urban population volatility using a real option approach. Two important problems are investigated: which transit technology should be selected and when should it be introduced. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for shifting from a transit technology to another are explored analytically. Comparative static analyses of the urban system and transit technology investment are also carried out. It was found that (i) transit technology investment can induce urban sprawl; (ii) ignoring the effects of transit technology investment on urban spatial equilibrium can lead to a late investment; and (iii) there is a significant difference in the trigger population thresholds for transit technology shift estimated by the net present value approach and the real option approach.     

Evaluating efficiency in the Norwegian bus industry using data envelopment analysis

This paper focuses on the performance of Norwegian bus companies subsidized by the government. The performance is evaluated from a productive efficiency point of view. The framework is that of a deterministic non-parametric Data Envelopment Analysis (DEA) approach to efficiency measurement. In this context several important issues are addressed: efficiency rankings, distribution and scale properties in the bus industry, potentials for efficiency improvements in the sector, the impact of ownership, area of operation and scope, and ways of improving efficiency in the sector. The findings show that the average bus company exhibits increasing return to scale in production of its services. The extent of such returns however vary, with size and is more prevalent among smaller companies. The average bus company is found to have a considerable input saving potential of about 28 percent. Neither economies of scope nor company ownership are found to have an influence on company performance. It is suggested that geographical factors need a closer attention in future research. The implications of DEA results are discussed and concluding remarks offered.     

Comparative performance analysis of European airports by means of extended data envelopment analysis

Data envelopment analysis (DEA) has become an established approach for analyzing and comparing efficiency results of corporate organizations or economic agents. It has also found wide application in comparative studies on airport efficiency. The standard DEA approach to comparative airport efficiency analysis has two feeble elements, viz. a methodological weakness and a substantive weakness. The methodological weakness originates from the choice of uniform efficiency improvement assessment, whereas the substantive weakness in airport efficiency analysis concerns the insufficient attention for short‐term and long‐term adjustment possibilities in the production inputs determining airport efficiency. The present paper aims to address both flaws by doing the following: (i) designing a data‐instigated distance friction minimization (DFM) model as a generalization of the standard Banker–Charnes–Cooper model with a view to the development of a more appropriate efficiency improvement projection model in the Banker–Charnes–Cooper version of DEA and (ii) including as factor inputs also lumpy or rigid factors that are characterized by short‐term indivisibility or inertia (and hence not suitable for short‐run flexible adjustment in new efficiency stages), as is the case for runways of airports. This so‐called fixed factor case will be included in the DFM submodel of the DEA. This extended DEA—with a DFM and a fixed factor component—will be applied to a comparative performance analysis of several major airports in Europe. Finally, our comparative study on airport efficiency analysis will be extended by incorporating also the added value of the presence of shopping facilities at airports for their relative economic performance. Copyright © 2012 John Wiley & Sons, Ltd.     

An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India

By using the directional distance function (DDF) of data envelopment analysis (DEA), this study measures the technical efficiency of 37 Indian state road transport undertakings (SRTUs) for the year 2012–13. We employ the DDF as a tool for analyzing a joint production function with both desirable and undesirable outputs (i.e., the number of accidents). A comparison between the results with and without accidents shows that several SRTUs have experienced significant changes in their efficiency scores as well as in their rankings after accounting for the undesirable output. This indicates the importance of including the number of accidents – a safety standard – as representative of the undesirable output in computing the efficiency scores of SRTUs. The results of the Tobit model indicate that SRTUs with greater vehicle productivity are more efficient under both conventional DEA and DDF approaches. We also employed zero-truncated negative binomial model to assess the factors influencing the number of road accident experienced by the Indian SRTUs and found that the accident count was significantly influenced by fleet utilization and vehicle productivity.     

Changes in multi-mode bus transit efficiency, 1988–1992

This paper examines the claim that US bus transit productivity has declined in recent years. It does so with reference to a piecewise-linear best-practice (DEA) production frontier, computed for multi-modal bus transit between 1988 and 1992. Efficiency is measured both by a Russell (static) and Malmquist (dynamic) measure of productivity change. The principal finding is that, overall, bus transit efficiency has improved slightly over the period.     

Equity-oriented skip-stopping schedule optimization in an oversaturated urban rail transit network

In this study, we focus on improving system-wide equity performance in an oversaturated urban rail transit network based on multi-commodity flow formulation. From the system perspective, an urban rail transit network is a distributed system, where a set of resources (i.e., train capacity) is shared by a number of users (i.e., passengers), and equitable individuals and groups should receive equal shares of resources. However, when oversaturation occurs in an urban rail transit network during peak hours, passengers waiting at different stations may receive varying shares of train capacity leading to the inequity problem under train all-stopping pattern. Train skip-stopping pattern is an effective operational approach, which holds back some passengers at stations and re-routes their journeys in the time dimension based on the available capacity of each train. In this study, the inequity problem in an oversaturated urban rail transit network is analyzed using a multi-commodity flow modeling framework. In detail, first, discretized states, corresponding to the number of missed trains for passengers, are constructed in a space-time-state three-dimensional network, so that the system-wide equity performance can be viewed as a distribution of all passengers in different states. Different from existing flow-based optimization models, we formulate individual passenger and train stopping pattern as commodity and network structure in the multi-commodity flow-modeling framework, respectively. Then, we aim to find an optimal commodity flow and well-designed network structure through the proposed multi-commodity flow model and simultaneously achieve the equitable distribution of all passengers and the optimal train skip-stopping pattern. To quickly solve the proposed model and find an optimal train skip-stopping pattern with preferable system-wide equity performance, the proposed linear programming model can be effectively decomposed to a least-cost sub-problem with positive arc costs for each individual passenger and a least-cost sub-problem with negative arc costs for each individual train under a Lagrangian relaxation framework. For application and implementation, the proposed train skip-stopping optimization model is applied to a simple case and a real-world case based on Batong Line in the Beijing Subway Network. The simple case demonstrates that our proposed Lagrangian relaxation framework can obtain the approximate optimal solution with a small-gap lower bound and a lot of computing time saved compared with CPLEX solver. The real-world case based on Batong Line in the Beijing Subway Network compares the equity and efficiency indices under the operational approach of train skip-stopping pattern with those under the train all-stopping pattern to state the advantage of the train skip-stopping operational approach.     

Emissions of demand responsive services as an alternative to conventional transit systems

The environmental performance of public transport plays a key role in improving air quality in urban areas. An important way of improving existing transit services is to use innovative propulsive systems; however, this needs considerable financial resources that are not always available. Here we assess how the organizational form of the transit system may impact the environment relying on a new methodology that permits comparisons in terms of distance traveled between a traditional fixed-route and a demand responsive transit service. We apply an emission model to find the least polluting transit system under a broad range of scenarios with different road networks, service quality levels and demand densities. Results indicate that demand responsive transit services minimize emissions for high quality service level and low demand density scenarios. Furthermore, the possibility of employing smaller vans with lower emission factors guarantees additional substantial benefits in terms of atmospheric pollution for demand responsive transit services, thereby giving them a competitive advantage in virtually every case.     

Efficiency evaluation and PM emission reallocation of China ports based on improved DEA models

The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research.     

Economic impact of a supply change in mass transit in urban areas: A Canadian example

This paper aims at estimating the economic impact of a supply change in the bus transit service in a Canadian city of medium size. By using a quasi-experiment approach and a difference-in-differences (DID) estimator, it evaluates the impact of the introduction of a rapid bus transit (RBT) in Quebec City (Canada) through a spatio-temporal analysis of house price variations. The hedonic price model shows that the new service generates an increase in house price ranging from 6.9% to 2.9%, for those properties located close to the service corridor where the population is quite dense and where the service was offered initially. Using sales transaction data and municipal assessment records from 1997, the effect on price is translated into an economic impact for the whole region. The paper shows that the improvement in public transit supply generates, for Quebec City, a significant fiscal impact estimated to $6 M and a plus-value for properties owners close to $35 M over 12 years. Finally, the implications of this kind of analysis for urban planning and development are discussed.     

Measuring supply chain efficiency based on a hybrid approach

Supply chain management has a tremendous impact on the success of a company. One of the critical issues for gaining competitive advantages for companies is improving supply chain performance. Most studies about the application of Data Envelopment Analysis (DEA) Supply chain models do not identify the benchmarking units for inefficient supply chains. On the other, measuring the short run and long run of the supply chain efficiency is another challenge for decision makers in supply chain management. Hence, we propose a methodology of DEA for measuring of the supply chain. We integrated two approaches as special cases of the hybrid model and compare the short and long run strategies of supply chain and can be identified benchmarking.