Francesca Pagliara

The Intention to Move and Residential Location Choice Behaviour

This paper aims to quantify the extent to which transport and other factors impact on residential decisions using Oxfordshire, UK, as a case study. It investigates the impacts of the current dwelling, household characteristics and alternative properties on the probability of moving. It also highlights the trade-off between access, space and other attributes in residential location choice. Particular emphasis is placed on assessing the impact of transport and location-embedded amenities. A nested logit model is applied to estimate the indirect random utility functions of the intention to move and residential location choice based on stated preference data. The estimation results of the intentions to move model illustrate the impact of housing and household characteristics on the probability of moving. The estimation results of the residential location choice model quantify the trade-offs between transport, amenities and other factors.

Residential Location Choice

This chapter provides an overview of the history of modelling residential location choice. Models of residential mobility typically have developed for illuminating the nature of location choice at different territorial scales or as part of an integrated model of land-use and transport. The latter tend to be more comprehensive in nature, though certain other investigations do consider interactions of location choice with other key decisions, such as work location. Models presented in this book are described here briefly and are presented here according to three dimensions: theory and method, i.e. the modelling approach at the root of the model; categorisation of residential decision makers; and treatment of space, i.e. continuous, zoning or cells.

High-Speed Rail Versus Air Transportation: Case Study of Madrid–Barcelona, Spain.

Travel time savings, better quality of supplied services, greater comfort for users, and improved accessibility are the main factors of success for high-speed rail (HSR) links. In this paper, results are presented from a revealed and stated preference survey concerning HSR and air transport users in the Madrid–Barcelona, Spain, corridor. The data gathered from the stated preference survey were used to calibrate a modal choice model aimed at explaining competition between HSR and air transportation in the corridor. The major findings of the paper describe the demand response to different policy scenarios considering improvements in the level of transport services. From the model, prices and service frequency were found to be among the most important variables in competing with the other mode. In addition, it was found that check-in and security controls at the airport are a crucial variable for users in making their modal choices. Other policies, such as the improvement of parking facilities at train stations, play a secondary role.

The State-of-the-Art in Building Residential Location Models

This chapter provides an overview of the history of modelling residential location choice. Models of residential mobility typically have developed for illuminating the nature of location choice at different territorial scales or as part of an integrated model of land-use and transport. The latter tend to be more comprehensive in nature, though certain other investigations do consider interactions of location choice with other key decisions, such as work location.

AN ANALYSIS OF RESIDENTIAL LOCATION CHOICE BEHAVIOUR IN OXFORDSHIRE, UK: A COMBINED STATED PREFERENCE APPROACH

This paper proposes and applies a combined stated preference approach in order to estimate residential location choice behaviour in Oxfordshire, UK. The estimation results demonstrate the potentials for the combined estimation of two stated preference experiments. Our findings show that the transport related attributes have significant impacts on residential location choice. The estimated monetary values of one minute of commuting time and one pence of commuting cost are equivalent to £6,339 and £883 with regard to house price, while the estimated value of time is 7.18 pence per minute. Higher quality of school has a significantly positive effect, while higher density and central city location have a significantly negative impact on residential location choice. The simulation results based on the model estimates suggest that the best location for new housing development varies with commuting patterns, spatial job distribution, and the changes of attributes influencing residential location choice.

Transport policy impact on residential location

This study investigates the impacts of transport factors on residential location decisions to assess the extent to which transport policy decisions (road user charging, changes to fuel duties, and the provision of a new public transport system) affect housing markets. This was achieved by undertaking stated preference experiments in the Greater Oxford area in UK. The forecasts of the impact of transport improvements on house prices suggest road user charging might reduce house prices on average by around 2%. A 10% change in fuel duty leads to an average change in house prices of around 3%, but with the direction of change being uniform throughout the study area. It was also found that introducing a new public transport might increase house prices by around 3% on average, with the greatest increases in central Oxford.

High-speed trains and tourists: what is the link? Evidence from the French and Spanish capitals

The objective of this paper is to analyse the factors influencing tourists’ choice of a destination and the role of High Speed Rail (HSR) systems in this choice. The methodology proposed consists in analysing two capitals in Europe, i.e. Paris and Madrid where HSR services are important, to investigate the factors influencing holidaymakers in choosing these cities, and the role of HSR in this choice. The main outcome of this paper is to show that several factors influence the choice of a tourist, like the presence of architectural sites, the quality of promotion of the destination itself, the presence of events, and also HSR services. However we found that the HSR system has affected the choice of Paris and Madrid in a different way. Concerning the French case study, HSR is considered a real transport mode alternative among tourists, therefore HSR is chosen to reach Paris as well as for revisiting it. On the other hand, Madrid is chosen by tourists irrespective on the presence of HSR, while HSR is chosen for reaching cities close to Madrid. Data collected from the two surveys have been used for a further quantitative analysis. Models have been specified and calibrated to identify the factors influencing holidaymakers to revisit Paris and Madrid and the role of HSR in this choice has been highlighted.

High-speed rail systems and tourists’ destination choice: The case studies of Paris and Madrid

The analysis of how tourists select their holiday destinations along with the factors determining their choices is very important for promoting tourism. In particular, transportation is supposed to have a great influence on the tourists’ decisions. The aim of this paper is to investigate the role of High Speed Rail (HSR) systems with respect to a destination choice. Two key tourist destinations in Europe namely Paris, and Madrid, have been chosen to identify the factors influencing this choice. On the basis of two surveys to obtain information from tourists, it has been found that the presence of architectural sites, the quality of promotion of the destination itself, and cultural and social events have an impact while make a choice. However the availability of the HSR systems affects the choice of Paris and Madrid as tourist destinations in a different way. For Paris, TGV is considered a real transport mode alternative among tourists. On the other hand, Madrid is chosen by tourists irrespective of the presence of an efficient HSR network. Data collected from the two surveys have been used for a further quantitative analysis. Regression models have been specified and parameters have been calibrated to identify the factors influencing holidaymakers to revisit Paris and Madrid and visit other tourist places accessible by HSR from these capitals.

The Impact of Transport Policy on Residential Location

The objectives of this chapter are to assess the extent to which transport impacts on residential location decisions and hence on housing occupancy rates and house prices and to assess the extent to which transport policy decisions (such as road user charging, changes to fuel duties or the provision of light rapid transit systems) affect housing markets. This was achieved by undertaking two Stated Preference (SP) experiments in the Greater Oxford area. The aim of these experiments was to determine the key transport and location factors that householders take into account when determining their residential location. These surveys suggested that householders place high values on transport times and costs but also value low density developments, access to high quality schools, low noise levels and developments in small towns/rural areas. Stated Preference data was used to develop a hedonic pricing (HP) model which suggested much lower impacts of travel time to work, housing density and school quality on house prices than the SP choice model. Nonetheless, validation tests indicated that the HP model provided more reliable forecasts of house prices than the SP model. The HP model was used to provide preliminary forecasts of the impact of transport improvements on house prices in the Greater Oxford area.

The evolution and planning of hierarchical transport networks

The continuing growth of urban regions coupled with their strong interactions with transportation systems places great emphasis on the coevolution of these systems. In this paper we introduce three developments. First, as a preliminary, the dynamic model of the evolution of retail structure is extended to show how hierarchies emerge. Secondly, these ideas are applied to a model of the evolution in transport networks. Thirdly, it is shown that such a model can be translated into a planning context and the notion of an explicitly hierarchical dynamic model is introduced. An example of the use of such a model of evolution within a network planning context is presented. This explores the planning of network evolution in a case study of Naples arising from a new harbour which is under construction. The model provides a new method for transport system planning through combining the insights from dynamic modelling, particularly with respect to the sequencing of investment, with the practicalities of budget constraints.