Large-scale transit market segmentation with spatial-behavioural features

Transit market segmentation enables transit providers to comprehend the commonalities and heterogeneities among different groups of passengers, so that they can cater for individual transit riders’ mobility needs. The problem has recently been attracting a great interest with the proliferation of automated data collection systems such as Smart Card Automated Fare Collection (AFC), which allow researchers to observe individual travel behaviours over a long time period. However, there is a need for an integrated market segmentation method that incorporating both spatial and behavioural features of individual transit passengers. This algorithm also needs to be efficient for large-scale implementation. This paper proposes a new algorithm named Spatial Affinity Propagation (SAP) based on the classical Affinity Propagation algorithm (AP) to enable large-scale spatial transit market segmentation with spatial-behavioural features. SAP segments transit passengers using spatial geodetic coordinates, where passengers from the same segment are located within immediate walking distance; and using behavioural features mined from AFC data. The comparison with AP and popular algorithms in literature shows that SAP provides nearly as good clustering performance as AP while being 52% more efficient in computation time. This efficient framework would enable transit operators to leverage the availability of AFC data to understand the commonalities and heterogeneities among different groups of passengers.     

Acquisition,efficiency and scale economies: An analysis of the British bus industry

The British Bus industry has undergone considerable transformation since privatization. Five major operators have emerged to dominate the market, a position almost exclusively attained through acquisition. This paper reviews the economies of scale argument commonly cited for this change and gives an overview of the acquisition process. It questions whether this argument gives a complete explanation for this industry development. For 58 individual companies, the level of technical efficiency attributable to firms operating at or near the optimum level of output is examined over 5 years to determine if mergers in practice have resulted in scale economies. Technical efficiency is estimated using data envelopment analysis, under assumptions of constant and variable returns to scale. Efficiency scores are then regressed on a time trend and a merger dummy to test whether acquired firms' efficiency has significantly improved above the average. It was found that over the period, efficiency had improved. This improvement, however, cannot be wholly attributed to the achievement of economies of scale. More specifically, there has been an improvement in the internal efficiency of acquired firms and some scale economies within group companies, the latter of which may have resulted from the eradication of competition.     

Nothing focuses the mind on productivity quite like the fear of liquidation: Changes in airline productivity in the United States, 2000–2004

Using data envelopment analysis and the Malmquist productivity index, this paper examines changes in the productivity of the major United States passenger airlines from 2000 to 2004. The analysis finds that there was a significant improvement in the productivity of the carriers at transforming labor, fuel and passenger seating capacity into available seat-miles during this period. Most of the productivity improvements came about from the efficiency laggards catching up with the efficiency leaders in the industry. To a lesser extent, the adoption of new technologies improved productivity over this period.     

Achieving transport modal split targets at intermodal freight hubs using a model predictive approach

The increase of international freight commerce is creating pressure on the existing transport network. Cooperation between the different transport parties (e.g., terminal managers, forwarders and transport providers) is required to increase the network throughput using the same infrastructure. The intermodal hubs are locations where cargo is stored and can switch transport modality while approaching the final destination. Decisions regarding cargo assignment are based on cargo properties. Cargo properties can be fixed (e.g., destination, volume, weight) or time varying (remaining time until due time or goods expiration date). The intermodal hub manager, with access to certain cargo information, can promote cooperation with and among different transport providers that pick up and deliver cargo at the hub. In this paper, cargo evolution at intermodal hubs is modeled based on a mass balance, taking into account hub cargo inflows and outflows, plus an update of the remaining time until cargo due time. Using this model, written in a state-space representation, we propose a model predictive approach to address the Modal Split Aware – Cargo Assignment Problem (MSA–CAP). The MSA–CAP concerns the cargo assignment to the available transport capacity such that the final destination can be reached on time while taking into consideration the transport modality used. The model predictive approach can anticipate cargo peaks at the hub and assigns cargo in advance, following a push of cargo towards the final destination approach. Through the addition of a modal split constraint it is possible to guide the daily cargo assignment to achieve a transport modal split target over a defined period of time. Numerical experiments illustrate the validity of these statements.     

Estimation method for railway passengers’ train choice behavior with smart card transaction data

Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused on train choices made by railway passengers. If each passenger’s train choice can be identified over a long period of time, this information would be useful for improving the customer relationship management of the railway company and for improving train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns from smart card transaction data collected over a long time period.     

Why do urban travelers select multimodal travel options: A repertory grid analysis

The increasing number of travelers in urban areas has led to new opportunities for local government and private mobility providers to offer new travel modes besides and in addition to traditional ones. Multimodal travel provides an especially promising opportunity. However, until now the underlying reasons why consumers choose specific alternatives have not been fully understood. Hence, the design of new travel modes is mainly driven by obvious criteria such as environmental friendliness and convenience but might not consider consumers’ real or latent needs. To close this research gap, sixty in-depth interviews with urban travelers were conducted. To identify the perceptual differences of customers among different travel modes, the repertory grid technique as an innovative, structured interview method was applied. Our data show that urban travelers distinguish and select travel alternatives based on 28 perceptual determinants. While some determinants associated with private cars such as privacy, flexibility and autonomy are key indicators of travel mode choice, costs and time efficiency also play a major role. Furthermore, by comparing travel modes to an ideal category, we reveal that some perceptual determinants do not need to be maximized in order to fulfill customer needs optimally. A comparison of consumers’ perceptual assessments of alternative travel modes identifies specific advantages and disadvantages of all alternatives, and provides fruitful implications for government and private mobility providers.     

Yardsticks on the road: Regulatory contracts and cost efficiency in the Norwegian bus industry

In this paper a cost frontier model is estimated for an eleven-year panel of Norwegian bus companies (1136 company-year observations) using the methodology proposed by Battese and Coelli (1995). The main objective of the paper is to investigate to what extent different type of regulatory contracts affect company performance. The panel model proposed by Battese and Coelli (1995) allow for year/company specific efficiency measures to be estimated. Thus, unobservable network or other time invariant characteristic of the operating environment can be controlled for by analyzing the dynamics of measured productivity across time for firms regulated under different types of contracts, rather than relying solely on variations across companies during one time period. Therefore, the paper offers methodological and data advantages over previous work on this subject. The main and robust result of the paper is that the adoption of a more high-powered scheme based on a yardstick type of regulation significantly reduces operating costs. The results contained in this paper thus confirms theoretical predictions regarding the incentive properties of high powered incentive schemes and in particular the dynamic benefits of yardstick competition.     

An empirical analysis of freight transport traffic modes in Brazil, 1996–2012

This paper analyses the performance of freight transportation modes in Brazil – namely air, water, rail and road – from February 1996 to August 2012 by investigating their long memory properties using fractional integration and autoregressive models on monthly tonnage data. Two important features are analysed: the degree of dependence of transportation traffic across time and its seasonal structure over the period. Furthermore, the stability of parameters across the sample period is investigated, incorporating potential structural breaks in the data, which describe discontinuity in freight transportation traffic. Some policy implications are derived.     

Characteristics of household activity and travel patterns in the Mumbai metropolitan region

Activity-based modelling approaches require a typical survey instrument which can collect the finer details of activities of each individual over both time and space. This paper focuses on the design of a new survey instrument called an activity-travel diary; examines its method of administration; and analyses activity-travel behaviour in the context of developing countries. The Mumbai Metropolitan Region in India is selected as the study area. With the aim of understanding the activities of each individual over a period of time, a pilot survey was conducted in a continuous time frame for a period of 15 days, followed by a main survey. The analysis of data collected by the instrument reveals some interesting facts regarding the relationships between socioeconomic attributes, activities and trip making behaviour. Identification of interactions among households and other members were also facilitated by the newly designed diary, which is not a well-versed topic for research in the context of a developing economy like Mumbai's.     

Using on-board logging devices to study the longer-term impact of an eco-driving course

In this paper the long-term impact of an eco-driving training course is evaluated by monitoring driving behavior and fuel consumption for several months before and after the course. Cars were equipped with an on-board logging device that records the position and speed of the vehicle using GPS tracking as well as real time as electronic engine data extracted from the controller area network. The data includes mileage, number of revolutions per minute, position of the accelerator pedal, and instantaneous fuel consumption. It was gathered over a period of 10 months for 10 drivers during real-life conditions thus enabling an individual drive style analysis. The average fuel consumption four months after the course fell by 5.8%. Most drivers showed an immediate improvement in fuel consumption that was stable over time, but some tended to fall back into their original driving habits.     

The dynamics of household travel time expenditures and car ownership decisions

A dynamic (panel data) structural equations model is developed that links four dependent travel behavior variables at two points in time, one year apart. The four dependent variables are: car ownership, travel time per week by car, travel time by public transit, and travel time by nonmotorized modes. Exogenous variables include 13 household characteristics and variables accounting for period effects over the 1985 to 1987 time frame in the Netherlands. The model treats car ownership as ordered-response probit variables and all travel times as censored (tobit) continuous variables. The model accounts for serially-correlated errors and panel conditioning biases. Results are interpreted in terms of recommendations for forecasting procedures.     

Shipping log data based container ship fuel efficiency modeling

Container shipping lines have been initiating various ship fuel efficiency management programs because bunker fuel costs always dominate the daily operating costs of a container ship. As the basis of these kinds of programs, we develop a viable research methodology for modeling the relationship between the fuel consumption rate of a particular container ship and its determinants, including sailing speed, displacement, sea conditions and weather conditions, by using the shipping log data available in practice. The developed methodology consists of an outlier-score-based data preprocessing procedure to tackle the fuzziness, inaccuracy and limited information of shipping logs, and two regression models for container ship fuel efficiency. Real shipping logs from four container ships (two with 13000 TEUs and two with 5000 TEUs) over a six-month sailing period are used to exhibit the applicability and effectiveness of the proposed methodology. The empirical studies demonstrate the performance of three models for fitting the fuel consumption rate of a ship and the industrial merits of ship fuel efficiency management. In addition, we highlight the potential impacts of the models developed in this study on liner shipping network analysis, as these models can serve as base models for additionally considering the influence of displacement and weather conditions on ship fuel efficiency and exhaust emissions.     

Productivity changes in Taiwan's port industry incorporating environmental regulations on harbor water quality

Abstract

This paper evaluates the productivity changes in Taiwan's port industry for the period 2003–2007. Based on a ‘three-year-window’ data envelopment analysis method, Luenberger productivity indicators are employed to estimate the productivity changes that account for the success of attempts by port agents to control harbor water quality. This is one of the typical environmental concerns in port operations that prior studies on port productivity changes over time have not considered. The results show that the productivity of Taiwan's port industry has experienced growth over the study period, regardless of whether water quality has been considered or not. At a disaggregated level, however, if a port agent has succeeded in controlling water quality, but we do not consider it, the results will misclassify the agent by understating the port's productivity.     

Energy efficiency,technological change and the dieselization of agriculture in the United States

This study focuses on the increase in the relative importance of diesel fuel consumption on farms in the United States over the 1971–1989 period. Four factors are identified as being central to the observed trend. These include the relative efficiency of diesel powered equipment versus gasoline powered equipment, technological changes that have impacted energy efficiency, the trend towards larger farms, and the enhanced energy conservation by farmers as a result of the adoption of reduced tillage practices.     

On a pathway to de-carbonization – A comparison of new passenger car CO2 emission standards and taxation measures in the G20 countries

Considering the role of transport for a 1.5 Degree stabilization pathway and the importance of light-duty vehicle fuel efficiency within that, it is important to understand the key elements of a policy package to shape the energy efficiency of the vehicle fleet. This paper presents an analysis focusing on three types of policy measures: (1) CO₂ emission standards for new vehicles, (2) vehicle taxation directly and indirectly based on CO₂ emission levels, and (3) fuel taxation. The paper compares the policies in the G20 economies and estimates the financial impact of those policies using the example of a Ford Focus vehicle model. This analysis is a contribution to the assessment of the role of the transport sector in global decarbonisation efforts. The findings of this paper show that only an integrated approach of regulatory and fiscal policy measures can yield substantial efficiency gains in the vehicle fleet and can curb vehicle kilometres travelled by individual motorised transport. Using the illustrative example of one vehicle model, the case study analysis shows that isolated measures, e.g. fuel efficiency regulation without corresponding fuel and vehicle taxes only have minor CO₂ emission reduction effects and that policy measures need to be combined in order to achieve substantial emission reduction gains over time. The analysis shows that the highest level of impact is achieved by a combination regulatory and fiscal policies rather than only one policy even if this policy is more aggressive. When estimating the quantitative effect of fuel efficiency standards, vehicle and fuel tax, the analysis shows that substantial gains with regard to CO₂ emission are only achieved at a financial impact level above 500 Euros over a four year period.     

Evaluating parking reservation policy in urban areas: An environmental perspective

This paper investigates a parking reservation mechanism to reduce car cruising to find parking. To consider the benefits for drivers and parking facility providers, we charge drivers for making reservations in addition to parking fees, by introducing a reservation pricing model that makes reservation prices equivalent to the value of saved search time. By modeling the number of vacant spaces as a stochastic variable, and applying binomial pricing methods, parking reservation prices are obtained. Numerical examples based on the data for two parking facilities in Taiwan are given.     

A technical analysis of model year 2011 US automobile efficiency

This paper investigates the new 2011 automobile fleet to quantify the variation in models’ efficiency and underlying technology attributes. This involves analysis of test data to quantify the aerodynamic, rolling resistance, and powertrain efficiency characteristics of each model, as well as analysis to understand relationships between these and vehicle fuel consumption. The findings indicate that while vehicles are about 14% efficient on average, there is wide variation and direct evidence of dramatically improved powertrain efficiency within existing models. Existing gasoline and diesel models demonstrate improved powertrain efficiency by over 25%, hybrid gasoline-electric powertrains by over 50%, fuel cells by a factor of three, and all-electric by a factor of four as compared to the average 2011 vehicle. Advanced aerodynamic and tire rolling resistance technologies are also in evidence.     

Efficiency measurement in public transport: Are findings specification sensitive?

The need to measure transit system performance along with its various dimensions such as efficiency and effectiveness has led to the development of a wide array of approaches and vast literature. However, depending upon the specific approach used to examine performance, different conclusions are oftentimes reached. Using data from 15 European transit systems for a ten year time period (1990-2000), this paper discusses three important transit performance questions; (i) Do different efficiency assessment methodologies produce similar results? (ii) How are the two basic dimensions of transit performance, namely efficiency and effectiveness, related? and (iii) Are findings regarding organizational regimes (public operations, contracting and so on) sensitive to the methodological specifications employed? Results clearly indicate that efficiency scores and associated recommendations are sensitive to the models used, while efficiency and effectiveness are - albeit weakly - negatively related; these two findings can have far reaching policy implications.     

A recursive, cell processing model for predicting freeway travel times

Travel time information influences driver behaviour and can contribute to reducing congestion and improving network efficiency. Consequently many road authorities disseminate travel time information on road side signs, web sites and radio traffic broadcasts. Operational systems commonly rely on speed data obtained from inductive loop detectors and estimate travel times using simple algorithms that are known to provide poor predictions particularly on either side of the peak period. This paper presents a new macroscopic model for predicting freeway travel times which overcomes the limitations of operational ‘instantaneous’ speed models by drawing on queuing theory to model the processing of vehicles in sections or cells of the freeway. The model draws on real-time speed, flow and occupancy data and is formulated to accommodate varying geometric conditions, the relative distribution of vehicles along the freeway, variations in speed limits, the impact of ramp flows and fixed or transient bottlenecks. Field validation of the new algorithm was undertaken using data from two operational freeways in Melbourne, Australia. Consistent with the results of simulation testing, the validation confirmed that the recursive model provided a substantial improvement in travel time predictions when compared to the model currently used to provide real-time travel time information to motorists in Melbourne.