Are pricing policies effective to change car use?

The effectiveness of transport pricing was considered in two studies regarding intended changes in car use if pricing policies were implemented. In the first study, respondents kept a travel diary for four days, noting all their car trips. Next, they indicated to what extent various pricing policies would affect the trips noted in the diary. In the second study, respondents indicated their intention to change their car use for various types of trips if pricing measures were implemented. By using tailored questionnaires, accurate feedback was provided about the financial consequences of pricing for each respondent separately.Results revealed that under pricing policies most people did not intend to change their car use. Pricing policies were relatively more effective when prices increased significantly. Especially visiting and shopping trips were affected, while commuting trips were hardly affected. Moreover, respondents were most likely to reduce their car use for short trips, which are an important source of CO2 emissions and local air pollution

A multi-modal network approach to model public transport accessibility impacts of bicycle-train integration policies

In the Netherlands, the bicycle plays an important in station access and, to a lesser extent, in station egress. There is however fairly little knowledge in the potential effects of bicycle-train integration policies. The aim of this paper is to examine the impacts of bicycle-train integration policies on train ridership and job accessibility for public transport users.MethodsWe extended the Dutch National Transport Model (NVM) by implementing a detailed bicycle network linked to the public transport network, access/egress mode combinations and station specific access and egress penalties by mode and station type derived from a stated choice survey. Furthermore, the effects of several bicycletrain integration policy scenarios were examined for a case study for Randstad South, in the Netherlands, comprising a dense train network with 54 train stations.ConclusionsOur analysis shows that improving the quality of bicycle routes and parking can substantially increase train ridership and potential job accessibility for train users. Large and medium stations are more sensitive to improvements in bicycle-train integration policies, while small stations are more sensitive to improvements in the train level of service

Implementation of toll collection at the Kiltunnel 1990-1991

The survey was held in order to study the effects of toll collection in the central part of the Netherlands (Randstad). Especially on making detours in order to avoid paying toll. Trips through tunnels / frequency of trips / possibilities of alternative transport (public transport) / reasons for travelling / refunding of travelling expenses / preferences for hypothetical transportation possibilities / data on car / commuting / car-pooling. Background variables: basic characteristics/ household characteristics/ occupation/employment/ consumption of durable

Parking in periferal work areas in the Randstad 1988

Investigation of effectiveness and negative side-effects of parking-measures, aimed at reducing rush-hour traffic and car use in general. The study investigates secondary and tertiary effects of policy-measures with regard to parking. Secondary effects relate to choice between transportation alternatives, tertiary effects to location behaviour of both employees and firms. The study consists of five sub studies: 1. P1024A: Screening of car-drivers to single out commuters, working in nine selected peripheral working areas ( Amsterdam Sloterdijk, Amsterdam Zuid, Amsterdam Zuidoost, Den Haag Bezuidenhout, Schiphol, Rotterdam Noordoost, Den Haag Laakhavens, Rijswijk Plaspoelpolders, Hoofddorp Beukenhorst ). Data on: commuting-time / choice of alternative way of transport if not by car.( N=1124 ) 2. P1024B: Stated preference questionnaire filled out by screened respondents. Data on: preferred transportation alternatives / parking: search-time, costs, walking distance / will parking measures make respondent change job? /car-allowance / job requires use of car? ( N=596 ) 3. P1024C: Tertiary effects of parking measures on employees who recently changed job. Comparison of commuting data of current and former job: distance / means of transportation / parking / parking costs / car allowance / relative importance of factors influencing choice of job / relative importance of commuting factors in choice of current job. ( N=153 ) 4. P1024D: Tertiary effects of parking measures on newly employed. Commuting situation / relative importance of commuting factors in accepting this job / moving / car ownership. ( N=74 ) 5. P1024E: Tertiary effects of parking measures on firms. Parking situation / number of car-commuters employed / public transport connections / will parking measures lead to relocation of the firm? ( N=201 ) Background variables: basic characteristics/ residence/ place of work/ income/capital assets/ educatio

Government policy regarding public transport 1989

The survey aimed at estimating the effects of policy measures on the use of public transport. By means of the stated preference technique, respondent evaluated the effects of changes in pricing, level of service, transport-time, waiting-time, car costs on their travelling behaviour. The data contain no background variables nor a key to link them to the LVO-data. Drivers licence / car ownership / trips made last ( 2 ) months: means of transportation, purpose, distance / bicycle theft / alternative ways of transport / crowdedness / waiting time / feelings of unsafety / preference regarding (hypothetical) alternative ways of travelling. Background variables: basic characteristics/ consumption of durable

Longitudinal transportation survey, wave 10, 1989 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the tenth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Preceding waves are stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries were used for describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. Moving to another home and factors influencing this. Use of train in preceding week, month, half year and year. Change in place of work last three years and factors influencing this. Parking facilities near place of work, use of public transportation in commuting, attitude regarding public transport and ownership and use of Pas 65 ( reduction card for the aged ). This wave proper consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ), and commuting data ( G=raw data ) respectively. It contains two extra cumulative files. One contains the most relevant variables from all March-waves of all respondents ever participating ( P1015H ). The second ( P1045J ) uses cars owned by panel-members as units of analysis and contains car-related variables and costs analysis. Moreover this wave contains two general SPSS-setup files, to be used for analyzing the week- matrices and commuting-data files of all waves ( P1045K and P1045L ). General hard-copy documentation relevant to all preceding waves is also stored under this number. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable

Longitudinal transportation survey, wave 7, 1987 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the seventh wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries had to be filled out, describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. This wave consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ), and commuting data ( G=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable

Longitudinal transportation survey, wave 4, 1985 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the fourth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. The diaries, describing all mobility during one week, were not use in this wave. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. This wave was held for administrative purposes only and in order to keep panel-attrition down. It contains far less information than the normal waves. It consists of four files, containing family-data( A=SPSS-file, C=raw data ) and family member-data ( B=SPSS-file, D=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable

Longitudinal transportation survey, wave 5, 1986 - LVO

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the fifth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Subsequent waves will be stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries, describing all mobility during one week, were used. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. This wave consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ) and commuting-data( G=raw data ) respectively. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durable