New appraisal values of travel time saving and reliability in Great Britain

Transportation - This paper provides an overview of the study ‘Provision of market research for value of time savings and reliability’ undertaken by the Arup/ITS Leeds/Accent consortium...     

Economic and occupational causes of transit operator absenteeism: a review of research

Transit operator absence from work is a costly and pervasive problem within public transport organizations. This paper reviews over forty international studies in order to document significant factors related to this phenomenon. We begin with a brief assessment of the magnitude and costs of operator absence and isolate two major theories which have been proposed to explain operator absence behaviour: the income‐leisure trade‐off and occupational stress. Case study reports from three U.S. public transport organizations are used to illustrate the range of factors which influence employee absence behaviour. We conclude with suggestions for organizational changes which may serve to reduce operator absence and suggestions for further research.     

Organizational form and performance in urban mass transit

Ownership and management for urban mass transit organizations have taken many forms over the years, with publicly‐owned and managed systems now dominant. In recent years, however, strong economic and political forces have increased pressures for privatizing urban mass transit services. This review analyses 20 studies from three countries (predominantly the U.S.A.) on the relationship between organizational form and fixed‐route bus transit performance. It concludes that previous research has not made a persuasive case for the whole‐scale privatization of either ownership or management of urban mass transit organization. Conclusions here are intended to apply to the U.S.A. as well as other countries with mixed enterprise systems in which choices about organizational form may have some consequence for performance.     

Comparison of data envelopment analysis and deterministic parametric frontier approaches: an application in the Norwegian road construction sector

This paper analyzes efficiency in the Norwegian road sector by using two competing methods. The first is Data Envelopment Analysis (DEA), while the second is Deterministic Frontier Analysis (DFA) with a Cobb‐Douglas kernel specification. Both approaches show similarities with respect to efficiency distribution. The rock‐blasting sectors potential for efficiency improvement is in the range 19–59 percent. Both approaches demonstrate decreasing return to scale properties for the average unit. There is a significant correlation between size and efficiency indicating that larger units perform better than smaller ones. Precautionary blasting mainly performed in densely populated areas is also found to explain much of the variations in efficiency scores. Any policy implication should therefore carefully examine exogenous factors. The main difference between the two approaches, which can be explained by the number of parameters to be determined, concerns level of scores rather than their distribution. However, there are arguments that advocate DEA rather than DFA in the rock‐blasting sector.     

Modeling the effects of traveler information on freeway origin–destination demand prediction

The primary focus of this research is to develop an approach to capture the effect of travel time information on travelers’ route switching behavior in real-time, based on on-line traffic surveillance data. It also presents a freeway Origin–Destination demand prediction algorithm using an adaptive Kalman Filtering technique, where the effect of travel time information on users’ route diversion behavior has been explicitly modeled using a dynamic, aggregate, route diversion model. The inherent dynamic nature of the traffic flow characteristics is captured using a Kalman Filter modeling framework. Changes in drivers’ perceptions, as well as other randomness in the route diversion behavior, have been modeled using an adaptive, aggregate, dynamic linear model where the model parameters are updated on-line using a Bayesian updating approach. The impact of route diversion on freeway Origin–Destination demands has been integrated in the estimation framework. The proposed methodology is evaluated using data obtained from a microscopic traffic simulator, INTEGRATION. Experimental results on a freeway corridor in northwest Indiana establish that significant improvement in Origin–Destination demand prediction can be achieved by explicitly accounting for route diversion behavior.