WAS THE DUTCH RAILWAYS NEW OFF PEAK INFRASTRUCTURE MAINTENANCE EXPERIMENT A SUCCESS? R.A.R.G. Jansen and P. van Beek Department of Research and Development, Goudappel Coffeng bv H.F. Hofker and J.H. de Munnik Department of Marketing Research, Dutch Railways 1. INTRODUCTION In the Netherlands the Dutch organisation Prorail is responsible for the maintenance, renewal and the extension of the Dutch rail infrastructure and its train stations. Prorail regulates daily rail-road traffic, solves disturbances and decides when and who is allowed to use the track. Dutch Railways are a commercial enterprise and are granted a concession to operate most of the rail-roads in the Netherlands. Dutch Railways have a vital role in mobility in the Netherlands. One of its missions is to transport as much as possible passengers in time and in a safe and comfortable way. From the 12th of December 2004 until the 6th of March 2005 Prorail and the Dutch Railways performed an off peak rail-road maintenance experiment on three corridors in the Netherlands. A new maintenance scheme should make it possible to perform small maintenance and inspection activities at a high safety level according to the instructions of new Standards Work Safe 1. In contrast to existing safety requirements future small maintenance and inspection activities are to be performed only in case no trains are in service. These activities can not be performed during night times for two reasons. Firstly, inspection activities require day light. Secondly, night times are already full of large maintenance activities. In the experiment tracks of three corridors (i.e. between the cities of Amersfoort and Enschede, Utrecht and Hilversum and Utrecht and Amersfoort) were closed one day a week at Tuesdays or Wednesdays during off peak hours between 9:30 and 15:30. During these hours only a single track instead of two tracks was available for train services. As a result regular train services reduced by an approximate fifty percent: i.e. instead of two trains an hour only one train was in service. In case the experiment would prove to be a success it was planned to introduce the new maintenance scheme on all rail-road corridors in the Netherlands. 1.1. Problems under Study During the experiment a number of investigations and measurements were performed by organizations such as Prorail, Dutch Railways and Raillon which is the largest rail transport company in the Netherlands. In this paper we focus on the investigations of Dutch Railways. As regards the temporary implementation of the new maintenance scheme by means of the experiment, Dutch Railways had six main questions and a number of related sub questions to be answered. These are stated as follows: 1. Are there any changes in train use on the three corridors and to what extent? 2. What types of changes occur regarding train use?
Which groups alter travel behaviour, and to what extent are these caused by the new maintenance scheme? Are there any differences between groups? To what extent is the maintenance scheme brought to the passengers attention? To what extent does the new maintenance scheme lead to inconveniences for train passengers? 3. What are the consequences of the new maintenance scheme with regard to transport revenues? 4. To what extent do train passengers alter their opinions and attitudes about general service levels of Dutch Railways and of service levels at trains and stations? What is their opinion about the experiment? 5. To what extent did the experiment reduce punctuality of train services? 6. What are the implications of a national introduction of the new off peak maintenance scheme? This paper discusses the following subjects. Section 2 consists of a description of the study. Section 3 describes the results and in the final section the outcomes are discussed. 2. SURVEY DESCRIPTION This section describes the maintenance experiment, the research populations of interest, the repeated measurement design and comparison of the sub-samples. 2.1 Maintenance Experiment Studies of change often involve the application of repeated measurement designs enabling to cover the dynamics of the phenomenon investigated. In the present study we discerned a pre-experimental and an experimental phase. In the first phase regular timetables of train services applied to each of the three corridors under investigation (see Figure 1). pre-experimental phase experimental phase 1st measurement time point 2nd measurement time point 3rd measurement time point 1st cross-section panel-study 2nd cross-section Figure 1: repeated measurement design In the experimental phase, these timetables were replaced by off peak maintenance timetables. For each corridor the maintenance timetable differed from the regular timetable one fixed day a week during off peak hours. During these periods only a
single track instead of two tracks were available for train services. As a result regular train services reduced temporally one day a week by an approximate fifty percent. Before and after off peak hours regular timetables still applied and train services were kept on a normal level. 2.2 Research Populations In order to asses the behavioural effects of the experiment the study focussed on train passengers that travelled on one of the three corridors during the periods in which the experimental conditions held. For this reason the research populations consisted of: - train passengers travelling on the corridor between Amersfoort and Enschede and between Utrecht and Hilversum on Tuesdays between 9:30 and 15:30. - train passengers that travelled on the corridor between Utrecht and Amersfoort at Wednesdays between 9:30 and 15:30. The populations were highly dynamic regarding the number of train passengers and over time compositions of these groups. As people move and change jobs new train passengers flow in and existing ones flow out. In addition a number of travellers took a train on occasion and made a trip on one of the three corridors only incidentally. 2.3 Repeated Measurement Survey Design Behavioural change depends on a number of factors. On the one hand part of the train passengers immediately adapt their travel behaviour to changing conditions. For instance when a train drops out a passenger takes the train one half an hour earlier or later. It might, however, take some time for these behavioural adaptations to become permanent. On the other hand part of the train passengers are hardly confronted with changes in train services. The trains they usually take are still in service whereas trains half an hour earlier or later drop out. Because of the high dynamics and suggested long-term behavioural effects of the maintenance experiment a multi-wave panel design was employed consisting of three waves. In the first wave, before the actual start of the experiment 1.639 train passengers were randomly interviewed on the three corridors during off peak hours and on days at which the new maintenance scheme was to be introduced. In the second wave, one month after the start of the experiment, 759 of these respondents were interviewed again. From this group the non-frequent train users, who occasionally travelled on one of these corridors, were excluded. Finally, 591 panel respondents were interviewed a third time in February 2005 a few weeks before the end of the experiment. At the third measurement time point an additional random sample of 385 train passengers was taken on the corridors during off peak hours on a Tuesday and Wednesday. The additional sample allowed to study population dynamics. Several questionnaires were developed. Items consisted of trip characteristics such as origin and destination, departure time, trip purpose, frequency of train use and frequency of the specific 2 trip. Moreover, items involved opinions and attitudes regarding general service levels of Dutch Railways and of service levels at trains and stations. Finally, items consisted of passengers awareness of the experiment and of experienced inconveniences with regard to implementation of the off peak
maintenance scheme. The questionnaires were put in a format allowing a mixedmode approach (i.e. written and telephone questionnaires) of the respondents. At the first measurement respondents were approached in trains. During the introduction of the interview respondents were told that the study would be repeated. The importance of the respondents opinions for the study was stressed also. During the first measurement interviewers held face-to-face interviews. In case time was short, e.g. for short trips or just before arriving at transfer stations, respondents were offered the possibility to complete the questionnaire at a later point in time. They could choose to be (re)called by telephone or were just handed over the questionnaire and a return envelope. A number of respondents filled out and posted the questionnaire themselves. The respondents were also asked to write down there telephone number. Again it was stressed that Dutch Railways were interested in additional information about their travel behaviour in the near future. Noticeably, almost all respondents gave their telephone number. For the second and third measurement time points questionnaires were slightly adapted. Now, all respondents of the first measurement were approached by telephone. Respondents who travelled on one of the three corridors only incidentally, were excluded from these measurements. When calling interviewers referred to the questionnaire that had been taken during their trip at the first measurement. The respondent was promised a small gift in case he or she agreed to be interviewed a third time. It was possible to spent this gift to a charity organization also. For the additional random sample of 385 train passengers the same methods applied as in the first measurement. In addition to the repeated measurements by means of questionnaires the number of train passengers were counted. During the first and third measurements all train passengers of the trains in service during off peak hours on each of the three corridors were counted. Counts were made repeatedly between each pair of stations and used for weighing the sample. 2.3 Comparison of Sub-samples In studying the problems at hand scores of the different sub-samples were compared. For a descriptive analyses of the populations of interest we compared the average scores of the repeated cross-sections, i.e. first measurement of 1.639 respondents (1st cross-section and 1st panel wave) and the additional sample of 385 respondents (2nd cross-section). For the descriptive dynamic analysis, however, we analysed the changes observed at the individual level on the basis of the data of the three-wave panel of 591 respondents. This analysis attempts to capture the dynamics in travel behaviour and of the attitudes of panel respondents as well as its consequences for the revenues of Dutch Railways. For comparison of the different samples we performed table analyses and applied some simple statistics to compare the distributions of the variables of interest. The analyses were performed after weighing the samples. In weighing adjustments were made for unequal sampling probabilities. These weights also corrected for overrepresentation of short-distance trips compared to long-distance trips. As there were no indications that panel attrition correlated with the variables of interest no attrition model was applied. Most of the attrition occurred from the fact that panel
respondents just were not reached by telephone during the second and third measurements. 3. RESULTS In this section we describe the main results of the experiment. We start with a characterization of the populations of interest. Next we focus on answering the research questions stated in section 1.1. 3.1 Descriptive Analyses To characterize the populations of interest, the data of the first (n=1.639) and third measurement (n=385) are compared. Both datasets are independent random samples. A description is given of changes in trip attributes and a some background variables. The figures used, are derived from the sample of 1.639 respondents. 3.1.1 Changes in trip attributes Travelled distance Of all trips 28% had a distance up to 20 kilometres. Half of the trips had a distance between 21 and 40 kilometres and 15% fell into the class of 41-80 kilometres. Only 7% were long distance trips of more than 80 kilometres. In the second cross-section short trips up to 20 kilometres had a somewhat higher share in the population compared to the first measurement. Trip purpose 28% Were home-work trips and 7% had a business purpose. 43% were homeschool/school-home based trips. 18% Of the trips were social and/or recreational in character. In the second cross-section the distribution of trip purpose did not change. Type of ticket 27% Of the passengers were students travelling with public transport cards that can be used in all public transport means during weekdays. 19% Of the passengers bought a one- or two-way ticket with a discount of 40%. 15% Travelled with an annual public transport card and 12% bought a one- or two-way ticket without discount. The distribution of tickets of the first and second measurements are comparable. Frequency of the trip 47% Of the respondents made the specific trip at least 4 times a week and 24% made it 1 to 3 times a week. Non-frequent users had a share of 14%. This group only occasionally made the specific trip or made it for the first time. In the second measurement frequent users had a lower share compared to non-frequent users. Company of others Most of the respondents (81%) travelled alone. 7% Travelled with colleagues or costudents. Here also there appear no clear differences between the two samples. Preparation of the trip 82% Of the train passengers did not prepare the trip. About 9% used the internet to retrieve travel information. The first and second measurements are comparable.
Alternative travel modes In both measurements about three quarters of the passengers responded they could make the same trip by means of another mode also. Bound to departure and arrival time 37% Of the passengers was bound to the arrival time, whereas 25% could take a train earlier. 14% Could take a train at a later point in time. Here also both measurements are comparable. 3.1.2 Background variables In addition to the trip attributes some background variables were measured. 53% Of the respondents were women. The median age was about 25 years. 46% Of the population was a student and 37% had an occupation. Finally, 64% of the respondents had a driving license. The distributions of both measurements were again comparable. To summarize most of the passengers travelled for purposes of work or school. These were frequent users of the corridors, mostly travelling over distances up to 40 kilometres. They travelled alone and mostly used subscription tickets. Furthermore, most passengers turned out to be experienced train users. They were reasonably flexible regarding departure and arrival times. Respondents were also relatively young and were occupied with school or work. Notice that the resemblances of the outcomes of the first and second measurements are quiet striking. 3.2 Descriptive Dynamic Analyses The focus of the analysis now shifts from changes in sample-wide averages to changes observed at the individual level. This analysis attempts to capture the dynamics in travel behaviour and attitudes of the panel respondents and its consequences for the revenues of Dutch Railways. The three-wave panel consisted of 591 respondents. In general the sub-sample showed characteristics that were similar to those of the sub-samples described in section 3.1. Percentage of change In comparing the outcomes of the three waves it turned out that 40% of the panel still made the specific trip two and a half months after the start of the experiment. 46% stopped making this trip before the second (24%) or third wave (22%), whereas 14% did not make the trip between the first and second wave but did so between the second and third wave. The figures indicate high dynamics of travel behaviour regarding the specific trips on the corridors. In fact after two and a half months almost half of the population did not make the same trip anymore on the same day and during the same period of time. Types of change From the group that stopped making the specific trip about half, i.e. 25% of the panel, did not make the trip anymore. From the group that still made the trip, 2% changed travel mode, 8% changed the day, e.g. from Tuesdays to Thursdays, and 11% changed the time period of the trip but still travelled on the same day. To summarize about half of the group that changed really stopped making the trip whereas the rest just adapted their travel behaviour.
Groups of change Further analyses of the data show that a relatively high percentage of the respondents that changed travel behaviour consisted of low-frequency users with regard to the specific trip. The specific trips of this group mostly had a social and/or recreational purpose. They travelled over relatively long distances such as on the corridor of Amersfoort and Enschede. Finally, these group more often used one- or two-way tickets compared to the group that more often made the specific trip. Reported causes of change As stated above changes result from a number of factors. The question is to what extent these changes actually resulted from the off peak maintenance scheme. Some of the reasons of change related to the off peak maintenance scheme, others were personal in nature. 54% Of the panel reported they had not changed their travel behaviour regarding the specific trip. 44% did change but reported that it occurred for personal reasons which had nothing to do with the off peak maintenance scheme. Only 2.1% of the respondents reported that behavioural change regarding the specific trip resulted from the introduction of the off peak maintenance scheme. This also implied that the behavioural changes on the three corridors had only a limited effect on the revenues of Dutch Railways. Further analysis of the data points out that changes resulting from the maintenance scheme more often involved groups that travelled with a one- or two-way ticket, had an average trip frequency, did not make the trip for purposes of work and school, and finally, made relatively short trips (up to 20 kilometres) especially on the corridor of Amersfoort and Enschede. On the one hand it was noticed that respondents who changed travel behaviour, had a relatively high share in long trips such as on the corridor of Amersfoort and Enschede. On the other hand short trips appeared to suffer more from the implementation of the off peak maintenance scheme. Indeed one can expect the off peak maintenance scheme to have a relatively high influence on short trips on a long-distance corridor like Amersfoort and Enschede, compared to long trips on the same corridor. Awareness and inconvenience During the second measurement 62% of the respondents confirmed they noticed changes regarding the specific trips on the corridors. 88% noted there were less trains in service, 17% noted that departure times of trains had changed. Most of the respondents (44%) became aware of the changes by means of announcements of public address systems at stations. 14% noticed changes by reading timetables at stations. A number of other communication means were noted also, e.g. advertisements in newspapers (13%), the internet (13%), employees of Dutch Railways at stations (11%) and electric light boards at stations (10%). Moreover respondents were asked if they had experienced any inconveniences because of the experiment. 41% Confirmed these experiences, such as long delays (40%), cancelled trains (34%), different departure times (12%) and fuzzy timetables (9%). 3.3 Change in Revenues Results indicate high dynamics in travel behaviour, but also suggest that the off peak maintenance scheme hardly influenced these dynamics. Most of the changes had a personal reason related to work, study and other activities. In fact, experimental related loss of revenues added up to only 0.3% of the respondents. Typically these
losses appeared within the group of users that use subscription tickets. As persons who travelled only occasionally on one of the corridors were excluded from the panel, it was not known how this group was influenced by the off peak maintenance scheme. The same applied to groups of new train passengers that flew in into the populations of interest during the experiment. These groups are not captured by the panel. Therefore one can reasonably assume a higher loss of total revenues than predicted by the panel. 3.4 Change in attitudes Respondents were also repeatedly asked to express their opinions about general service levels of Dutch Railways and of service levels in trains and at stations? Again the panel (n=591) was analyzed to study change at the individual level. Change was also assessed by means of comparing average scores of the first measurement (n=1.639) and the second cross-section (n=385). 3.4.1 General service levels Table 1 shows to what extent attitudes about general service levels of Dutch Railways changed over time. On average hardly any change was noticed in the group of respondents. Only for three items differences of the first and third measurement were statistically significant. The cross-sectional comparisons also showed very slight differences between measurements. judgement (report mark) measure measure measure Signific ment 1 ment 2 ment 3 ance general judgment about travelling by 6.9 7.0 7.0 a) train prize of train services in relation to 5.8 5.6 5.7 quality riding of trains in time 6.4 6.5 6.6 a) connections to other trains 6.7 6.7 6.6 trains frequency 6.9 7.0 6.9 available information at home 7.5 7.3 7.4 a) n=591 n=591 n=591 a) significance paired t-test between measurement 1 and 3 (p=0.05) Table 1: mean development in opinions of general service levels The attitudes towards travelling by train in general and about the travel information at home were slightly more positive in the third measurement. Cross-sectional comparisons showed slight decreases of the average scores regarding the relation between price versus quality and the frequency of train services. Differences between subgroups were also limited and even converged over time. Subgroups did not really change their attitudes after the start of the experiment. 3.4.2 Service levels in trains and at stations Table 2 shows the developments of attitudes regarding aspects of trains and stations. Here also hardly any changes appeared to have taken place. Opinions about the quality of announcements in trains became slightly less positive, whereas one was a
bit more positive about transfers to buses and the information on the timetables at stations. Again the stability on average was high. judgement (report mark) measure ment 1 measure ment 2 measure ment 3 at trains availability of seats in this train 6.6 6.6 6.7 audibility of announcements public 6.6 6.5 6.5 address system in this train announcements in this train subject to 6.8 6.7 6.5 delays announcements in this train arriving at 7.0 6.8 6.7 a) and leaving from stations possibility to address ticket collector 6.3 6.2 6.3 kindness/helpfulness of ticket collector 7.2 7.0 7.1 connections to buses 6.8 6.6 6.7 a) at stations n=364 n=364 n=364 b) information at timetables at stations 7.5 7.2 7.3 a) announcements at stations for trains arriving/leaving announcements at stations in case of delays and/or in case of platform departure changes a) significance paired t-test between measurement 1 and 3 (p=0.05) b) sub-sample of panel respondents who kept making the specific trip 6.9 6.8 6.9 6.8 6.8 6.8 n=364 n=364 n=364 b) signific ance Table 2: mean development in opinions of service levels at trains and stations Additional analyses on the individual level of the panel data again showed high stability of the opinions. About 70 to 90% of the respondents did not alter their opinions whatsoever. Almost all report marks have a value between 6 and 7. Opinions about the experiment itself showed that there was much support and understanding for the experiment and the maintenance activities. Respondents, however, were less satisfied about timeliness of the information. Only half of the respondents reported at the second measurement they had been informed in time about the new maintenance scheme. At the third measurement this figure went up to more than 60%. When respondents were asked whether it would bother them in case the new maintenance scheme would become permanent, 59% disagreed and only 29% agreed. Although train passengers had a relatively positive attitude towards the maintenance experiment, more than half of them did not agree with permanent changes of regular timetables. 3.5 Reduction of Punctuality In addition to surveys performed in this study Dutch Railways also monitored the punctuality of the trains that performed services during the experimental period.
Punctuality is a measure that represents the percentage of trains arriving in time in accordance with the timetable. It is an important measure for the Dutch state uses it as a key performance indicator of the company. In fact, Dutch Railways and the state have an agreement about the minimum value of punctuality. Figure 2 shows that on the corridor Amersfoort - Enschede punctuality decreased dramatically. On average punctuality showed a ten percent decrease leading to a substantial amount of customers delays. 100 95 90 85 punctuality score 80 75 70 65 60 55 50 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 1 2 3 4 5 6 7 8 9 10 11 12 13 14 weeknumbers non-experimental period experimental period Figure 2: Punctuality of trains on the corridor Amersfoort - Enschede before, during and after the off peak maintenance experiment (source: Dutch Railways) 3.6 National Introduction of New Maintenance Scheme Train passengers had a relatively positive attitude towards the maintenance experiment. At the third measurement 77% of the panel respondents showed support and understanding for the maintenance activities and its consequences regarding their specific trip. On the other hand 59 percent stated they would be bothered in case the maintenance scheme would become permanent. Based on this it is hypothesized that a national introduction of the new maintenance scheme would lead customers opinions to become less positive. Combined with an expected nationwide decrease of punctuality this eventually could have a negative impact on total revenues of Dutch Railways. 4. CONCLUSION AND DISCUSSION The study shows high dynamics of travel behaviour regarding the specific trips. About half of the group that changed did not make the specific trip anymore. The other half shifted its trip to another day or time period. Change of mode and route was very limited. The group that changed consisted of low-frequency users not making the specific trip for the purpose of work or school and merely using one- or two-way tickets and, finally, travelling over relatively long distances. Only 2.1% of the
respondents reported they changed travel behaviour for reasons of the off peak maintenance scheme, but only for 0.3% it meant a loss of revenues for Dutch Railways. Changes in opinions about service levels of Dutch Railways were limited. Scores showed high stability over time even at the individual level of respondents. On the one hand results indicate there was much support and understanding for the experiment and maintenance activities during off peak hours. Respondents knew that if the experiment would force them to change travel patterns it would do so only temporarily. They were aware that the experiment was due to maintenance activities of rail-infrastructure. On the other hand, punctuality decreased significantly and many train passengers experienced inconveniences such as long delays and cancelled trains. Also new timetables were rather complex and puzzled at least part of the train passengers. It should be pointed out also that after two and a half months the composition of the train passengers on the corridors had changed. The percentage of frequent trains users decreased compared to the group of non-frequent users. Note that frequent users often have subscription tickets travelling for the purpose of work or school. Finally, more than half of the respondents opposed the off peak maintenance scheme to become permanent. Based on these results, we expect acceptance of the off peak maintenance scheme to deteriorate in the long term. A permanent introduction could eventually result in much more behavioural and enduring change especially within the group of frequent train users. It would be an unfavourable development for Dutch Railways. It potentially has negative impacts on opinions of service levels and on total revenues of the company. A national introduction is expected to even have worse consequences especially as regards punctuality. For Dutch Railways a decrease of national punctuality is not acceptable. End of February 2005 Prorail, Dutch Railways and Raillion decided the new off peak infrastructure maintenance experiment to stop at the 6th of March. Prorail and Dutch Railways are continuously challenged to develop and implement ways to perform small maintenance and inspection activities at a high safety level. In January 2005 they announced to hold a competition. The main question is: How to maintain the track with much less troubles? There were 63 contributions from which 6 have been selected. In November 2005 a prize for the best contribution is distributed.
Notes 1 The safety requirements are part of the instructions of the Normenkader Veilig Werken which is translated as Standards Work Safe. 2 Notice that specific trip refers to the trip investigated, i.e. it refers to trips of the respondent by train with the same origin and destination on a Tuesday or a Wednesday during the off peak hours. Bibliography Prorail Spoorontwikkeling (2005). Hoe kan het spoor worden onderhouden met veel minder hinder? De Longe, Dordrecht. Kampinga, R. (2005). Eindrapportage Experiment Onderhoudsrooster; op het traject Utrecht Enschede. Unpublished document. Modderman, M. (2005). Eindrapportage Experiment Onderhoudsrooster; op het traject Utrecht Enschede. Unpublished document.