Ex ante evaluation - Area of Waldviertel- Deliverable 6.2

Institute for Transport Studies, University of Natural Resources and Life Sciences, Vienna

Roman Klementschitz • Oliver Roider • Nora Spiegel

December 2015

Contract N°: IEE/12/970/S12.670555

Table of contents

1 Introduction 3 1.1 Background 3 1.2 The SmartMove project 3 1.3 Content of this Deliverable 5

2 Data collection 6 2.1 Data collection – profile of implementation area 6 2.2 Data collection - situation before 6

3 Profile of implementation area 8

4 The situation before the implementation 13 4.1 Participants of the campaign 13 4.2 Persons who did not participating in the campaign 19

5 Summary and conclusion 20

6 References 21

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1 Introduction 1.1 Background The SmartMove project addresses key action on energy-efficient transport of the Intelligent Energy Europe programme (STEER). In line with the Transport White Paper it focuses on passenger transport and gives particular emphasis to the reduction of transport energy use.

1.2 The SmartMove project The delivery of public transport (PT) services in rural areas is faced with tremendous challenges: On the one hand the demographic dynamics of ageing and shrinking societies have particular impacts on the PT revenues depending on the (decreasing) transport demand. On the other hand, PT stops density and the level of service frequency are often of insufficient quality. Thus, there is a need for the development of effective feeder systems to PT stops and for the adaptation of the scarce PT resources to user needs. For the SmartMove project, feeder systems are the different ways of linking a specific region with the back bone PT system, usually a bus or train network or a combination of both. This can be done by improving the walking and cycling facilities to and around the stations, by implementing flexible bus systems or by promoting carpooling or car sharing etc.. However, even if sufficient rural PT systems are available, large parts of the population face diverse subjective barriers to use PT. This is even more relevant for PT feeder systems: in many cases citizens are not even aware of their existence or, if they are aware of them, there exist subjective barriers to their use.

These problems are addressed within SmartMove by implementing “Active Mobility Consultancy” (AMC) campaigns for PT lines and their feeder systems in eight rural and peripheral areas. The objective of the AMC campaigns within the project aims at promoting the use of PT via personalised travel marketing approach. The word ‘active’ in the term “active mobility consultancy” has a twofold meaning. On the one hand, it refers to the active process of informing people on PT: it is not PT users, who have to inform themselves about PT services; rather the PT operators that have to inform their (current and potential) customers according to their individual needs. For this purpose, current and potential PT users are contacted to provide them with demand based information via different communication channels. The second meaning refers to several active measures aimed at decreasing subjective barriers such as overestimating prize and travel time whereas underestimating the supply and options to the use of rural PT systems.

The AMC campaigns are more than purely the provision of information: active measures will be offered in addition to the written information and the consultancy talks that are usually applied in similar campaigns. This might include actions like practical traveller training, citizen participation in planning or guided tours for PT feeder schemes. Additionally, information and feedback on user needs can be

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collected within the AMC campaign. This supports the adjustment of PT offers in line with users’ requirements.

The AMC concept used in SmartMove builds on existing approaches, which will be further developed through SmartMove based on the exchange of experience and mutual learning. In particular, we will develop existing AMC approaches along 4 lines: (i) the adaptation of the existing approach to recent developments, (ii) the consideration and inclusion of feeder systems into the AMC campaign, (iii) the development and application of a common monitoring and evaluation method and, (iv) the adaptation of the AMC concept to specific requirements of the implementing regions. The result is an easy to use AMC concept that can be applied by PT operators all over Europe. The aim is to solve the specific, significant challenges of PT schemes in rural areas.

A main pillar of the concept is the extension of the AMC concept to PT feeder systems as they are crucial factors for rural PT systems. Better knowledge gained on this subject helps to improve public transport in rural areas. From a scientific point of view, the information attained about a feeder system based AMC campaign makes an important contribution to the further development of personalized travel marketing approaches. Even more important, by implementing a large range of dissemination activities, such as webinars and take-up seminars, not only the SmartMove partners, but also a broad range of stakeholders are informed about the manifold possibilities and advantages of an AMC campaign.

Eight rural and peripheral regions in Europe prepare, implement and evaluate a local Active Mobility Consultancy campaign. PT operators achieve insight into the demands of both current PT users and those who do not currently use PT systems, by applying the AMC campaign. If the non-use of PT is caused by hard facts – e.g. the location of the PT stops or schedule organization – PT operators can adapt their services to the demand of potential users. This will increase opportunities to make PT systems attractive for new passengers. Each of the AMC campaigns to be conducted through SmartMove will be based on a shared methodological approach which will then be tuned in practice to the needs of the local specific situation. These include the specific target groups, the specific cultural barriers, barriers and enablers, the type of PT feeder system (a possibility to reach PT stops by individual or public means), the spatial aspect (e.g. compactness vs spread, topography and geography, environment), the socio political aspects at the appropriate decision making level, the administrative aspects, the economic aspect and the planning aspects. Within each region, we have defined targets of several hundreds of households to be contacted. As a result, we expect a substantial mode shift to public transport, which in turn will lead to a substantial increase on energy efficiency, a decrease of resources consumed and a reduction of the greenhouse gas emissions caused by road traffic.

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1.3 Content of this Deliverable The impacts of the AMC campaigns are evaluated in a process- and output evaluation. Output evaluation refers to the measurement of the direct quantitative effects of the campaigns, e.g. mode shift or the number of additional public transport passengers. This information is used as input to calculate secondary effects of the campaigns, e. g. the reduction of CO2 emissions. Based on this, a cost-benefit analysis and a cost-effectiveness analysis are calculated. Statistical figures of the process are collected at each stage of the campaign, e. g. number of people contacted, response rate, figures about materials ordered etc., in order to identify factors of success or failure of the AMC campaigns (process evaluation). Interviews with current and potential public transport users give additionally information to public transport operators about customer satisfaction and the needs of improvement.

The aim of this deliverable is to present and evaluate key figures that had been collected before the AMC campaigns were conducted. The profile of the implementation area contains relevant information on socio demographic factors and the existing mobility behaviour of the inhabitants and participants. These framework conditions may help to explain divergent campaign impacts amongst the different implementation areas in the later stages of the project. The variables describing the characteristics of the participants of the campaign are the core elements of evaluation. Furthermore this deliverable presents the participants’ diverse motivations to use or not to use public transport services as well as the responses obtained from the people who chose not to participate prior to the campaign.

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2 Data collection 2.1 Data collection – profile of implementation area

A literature review was carried out to obtain the relevant information for the profile of the implementation area. The sociodemographic figures have been retrieved from the Statistics website, in particular from the publication “Blick auf die Gemeinde” (View on the Municipality), which offers most of the required data for the implementation area. The national travel survey “Österreich Unterwegs” (mobile Austria), which was funded by the Austrian ministry of transport together with some Austrian provinces and carried out in the years 2013/2014 provided the data for the evaluation of the inhabitants’ mobility pattern of the implementation area.

2.2 Data collection - situation before

MS-excel based data sheets have been prepared for all local implementation partners to be filled in for each person. The structure of the excel file includes the name of the variable; a short description and the format (open text, integer, date, pre- defined answers to be selected by a drop down button). Data are collected for each person individually, i. e. data of a person are entered individually in one row of the data base.

The data collection is structured as follows:  General information (address and names of target persons, dates of contacts, information if the person is a public transport user or not etc.)  Information concerning the questionnaire to be carried out before the campaign (modes used last week, knowledge about the particular line, rating of the performance of the particular line, suggestion for improvements etc.)

Alternatively to the MS Excel based data sheets, a MS Access based database has been developed to enable the data collection in the same way and structure as described above. Figure 2-1 shows the MS Access input form which was used for the implementation area of Waldviertel-Wachau.

The information was collected from the participants primarily by personal interviews by phone. If no telephone numbers were available, paper and pencil questionnaires were distributed among the participants together with the order form. The obtained information was either simultaneously or afterwards entered into the MS Access input form.

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Figure 2-1: Screenshot of the MS Access based database used in the implementation area of Waldviertel-Wachau

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3 Profile of implementation area

The implementation area Waldviertel-Wachau is located in the North-West of the Austrian province of . The SmartMove project is only implemented in a part of the Austrian geographical area of Waldviertel-Wachau. The implementation area consists of several regions and municipalities of the two administrative districts Melk and -Land. The SmartMove implementation area covers a total area of 570 km2 and has a combined population of 58 889 inhabitants [NOE Statistik 2014]. Most of the larger towns in the area are situated along the river , as are Melk and Krems. However the river also imposes the biggest restriction on mobility. There are two ferries crossing the river that carry vehicles and additional seasonal ferries for pedestrians and cyclists only. Bridges are only located at Melk and Krems, the most Eastern and Western municipalities of the implementation area in a distance of approximately 35 km. Small hills and mountains influence the population’s mobility as well. Therefore most motorised movements are limited to a small number of roads in narrow valleys, connecting the smaller villages along and aside the river. The gross regional product for the province Lower Austria is 31.100€ per capita [Statistik Austria 2014]. There is no specific data available for the districts or municipalities within Melk and Krems-Land but due to their geographical constraints amongst other factors the regional product is estimated to be lower than that of the whole province.

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Table 3-1: Profile of the implementation area Waldviertel-Wachau (population and transport demand) [NOE Statistik 2014, Statistik Austria 2015, Österreich Unterwegs 2015]

Category Variable name Variable label [Unit]

Implementation 570 [km²] Area Area total Area Inhabitants total 58 889 [number] Population Population change over the last decade +2.81 [%] men 48 [% of total number] Gender women 52 [% of total number] age class (< 18 years old) 18 [% of total number] Age age class (18 - 64 years old) 61 [% of total number] Population age class (> 64 years old) 21 [% of total number] employed 47 [% of total number] Professional unemployed / home duties 36 [% of total number] status (incl. pensioners) in school / training 17 [% of total number] primary education 26 [% of total number] Educational secondary education 61 [% of total number] status higher education 13 [% of total number]

Car incl. motorcycle drivers 1) 58 [%] Motorcycle riders (available only in n.a [%] combination with car) Modal split Car or motorcycle passengers 1) 16 [%] Transport (n=521 demand persons) Public transport 7 [%] Cycling 4 [%] Walking 15 [%] Trip rate Number of trips per workday and person 2.50 [trips/day]

1) Users of motorcycles contributes with a very small amount only

Table 3-1 presents the sociodemographic figures of the implementation area. Relating these data to the Austrian average, it is noticeable that the population increase of only 2,81% over the last decade is below the national average of 4,6% [Statistik Austria 2014]. This difference can be explained by the high level of migration from this area to the cities. The gender ratio matches the Austrian-wide figures while the age distribution of the implementation area shows a slight shift towards an older population. 18% of the population are under 18 years and 61% are between 18 and 64 years in the implementation area, which is below the national average of 19% and 63%, respectively [Statistik Austria 2014]. In the implementation area, 21% are over 64, compared to 18% nationwide. The figures in the category

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‘professional status’ of the population of the implementation area reveal that the percentage of people ‘in school or training’ (17%) exceeds the national average of only 14% [Statistik Austria 2014]. The Waldviertel-Wachau figures in the categories ‘employed’ and ‘unemployed’ are slightly below the national average. Within the implementation area 47% of the population are employed and 36% are unemployed, whereas nationwide 48% are employed and 38% are unemployed [ibid.]. Looking at the figures for ‘transport demand’, it is noticeable that a clear majority of almost 3 out of 4 times the private car is used. Motorised private transport is used with a share of 74% (58% as a driver and 16% as a passenger). A modal split for the province of Lower Austria shows slightly lower numbers, with 53% of the trips made by car as a driver and only 11% as a passenger [BMVIT 2011]. The share of the implementation area of 7% for public transport use differs greatly from the 13% from the province-wide survey. This can be attributed to the specific geographical factors and the bus services provided in the implementation area. Considering the figures for ‘cycling’, it is apparent that the modal share for the province (7%) exceeds the 4% of the implementation area [BMVIT 2011]. The percentage of ‘walking’, however, is almost the same, 15% for the particular implementation area and 16% for the province-wide modal split [ibid.]. In comparison, the modal split for the easternmost political districts of Austria, including Vienna, shows a distinctly lower percentage of motorised private transport use (33% as a driver and 8% as a passenger) [BRAWISIMO 2015]. The percentage of public transport use is 33%, 3%of the trips are made by bicycle and the modal share for walking is 23% [ibid.]. Vienna and its surrounding districts are responsible for these variations, which show the difference between an urban and the rather rural setting of the implementation area. This mode distribution of the implementation area within the district of Melk and Krems-Land can also be seen in figure 3-1 below. The mean number of trips per person and workday of the implementation area is 2.5 whereas the figure for Lower Austria is 2.9 [NÖ Landesakademie 2008]. In contrast, the average trip rate of mobile inhabitants in Austria is 3.4 trips per day [BRAWISIMO 2015].

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Figure 3-1: Modal Split of modes used in the implementation area [Österreich Unterwegs 2015]

15% Car driver Car passenger 4% Public Transport Cycling 7% Walking

58%

16%

Table 3-2: Profile of the implementation area Waldviertel-Wachau (public transport) [NOE Statistik 2014, Statistik Austria 2015, Österreich Unterwegs 2015]

Category Variable name Variable label [Unit]

Number of bus-lines in the area 4 [number] Number of connections per line, direction 8 [number/day] and workday - WA50 Number of connections per line, direction 6 [number/day] and workday - WA51 Number of connections per line, direction 19 [number/day] and workday - WL1 Number of connections per line, direction 11 [number/day] and workday - WL2 Number of connections per line, direction Public 0 [number/day] transport and Sat, Sun, public holiday - WA50 Number of connections per line, direction 0 [number/day] and Sat, Sun, public holiday – WA51 Number of connections per line, direction 14 [number/day] and Sat, Sun, public holiday – WL1 Number of connections per line, direction 7 [number/day] and Sat, Sun, public holiday - WL2 Number of seat km per workday in the 99,494 [seat km per area workday] Average trip length of PT-users 37 [km] [Österreich Unterwegs 2015]

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Table 3-2 shows the public transport figures of the implementation area. The four bus services WA50, WA51, WL1 and WL2 operate across the implementation area Waldviertel-Wachau. They have different numbers of connections per direction and workday, ranging from 6 connections to 19. The bus lines W50 and WA51 do not operate on public holidays or weekends and the other two lines have a reduced number of connections of 7 and 14 per direction and day. These four bus lines have combined seat kilometres of 99 292 per workday. The average trip length of public transport users in the implementation area is 37 km. This distance exceeds the average trip length of Lower Austria significantly, which is only 31.9 km [BMVIT 2011].

Table 3-3: Profile of the implementation area Waldviertel-Wachau (private car) [TREMOVE 2009, Statistik Austria 2015, Österreich Unterwegs 2015]

Category Variable name Variable label [Unit]

637 [cars/1,000 car ownership rate [Statistik Austria 2014] inhabitants] average trip length 20 [km] [Österreich Unterwegs 2015] Average fuel consumption per car Private car 0.0725 [l/km] [TREMOVE 2009] 1) Average CO2 emission per car 184 [g/km] [TREMOVE 2009] 1) Average trip duration 24 [min] [Österreich Unterwegs 2015]

1) This variables are related to whole Austria, no detailed information is available here.

The key figures for the category ‘private car’ can be seen in Table 3-3 above. The car ownership rate of the implementation area at 637 cars per 1000 inhabitants significantly exceeds the Austrian average of 555 cars [Statistik Austria 2014]. Within the implementation area, the average trip length is 20 km, which is notably longer than the average 11.6 km of the easternmost political districts of Austria, including Vienna [BRAWISIMO 2015]. A 2008 survey also presents a lower number for the province of Lower Austria, with an average trip length of 14.7 km [BMVIT 2011]. These differences can be explained by the particular rural characteristics of the implementation area. The average trip duration of the implementation area is 24 minutes per trip. In comparison, the average trip duration of the easternmost political districts of Austria is longer by 4 minutes [BRAWISIMO 2015]. In Lower Austria the trip duration is longer for men, with an average of 27 minutes, and, at 23 minutes, slightly shorter for women [BMVIT 2011].

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4 The situation before the implementation

Two aspects have been collected before the campaign:  Variables describing the characteristics of participants of the campaign.  Variables describing characteristics of those, who were contacted, but not participating in the campaign.

4.1 Participants of the campaign Variables collected from participants are the core elements of evaluation of the campaign. The following information was collected to enable an impact analysis after the campaign has been carried out. To document a change in the participant’s mobility pattern, their use of different modes of travel have been documented before the campaign takes place. Furthermore the participants have been asked to name their reasons for using or not using the available public transport services in the implementation area. The participants were also asked to list possible improvements of the bus line services.

Table 4-1: Variables for reporting situation before – modal split of participants Category Variable name [Unit]

3.68 [average days per Car and motorcycle drivers week] n=236 persons Motorcycle riders (available only in n.a. [average days per combination with car drivers) week] 0.84 [average days per Car or motorcycle passengers Modal split of week] n=222 persons participants 1.07 [average days per Public transport week] n=229 persons 1.25 [average days per Cycling week] n=225 persons 2.54 [average days per Walking week] n=223 persons

Table 4-1 presents the data obtained by the answers to the questions inquiring after the weekly usage of the specific travel modes, which is also illustrated in percentage shares in figure 4-1 below. Motorised private transport definitely is the most popular travel mode. The average participant uses the car 3.68 days per week as a driver and 0.84 days per week as a passenger, which converts into a 40% and a 9% share of the modal split. The second most popular travel mode is walking with a 26% modal share and an average of 2.54 days per week. On average the bicycle is used 1.25 days per week, which converts to a 13% cycling share. Public transport is only used 1.07 days a week by the participants and amounts to a 9% modal share. In comparison to the modal split of the implementation area, shown in figure 3-1, it is apparent that the participants have a lower percentage in private car use. Equally notable, the ex-ante usage of public transport (12%) exceeds the average

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percentage of the implementation area (7%), which indicates that the people willing to participate in the AMC campaign are more likely using public transport for their travels than the average. The rural influence on the participants’ modal split is apparent when compared with the modal split of Vienna and its surrounding political districts. The public transport use of the latter (30%) more than doubles the percentage of the participants [BRAWISIMO 2015]. Subsequently, the share of motorised private transport only amounts to 43% (30% for car drivers and 11% for car passenger) in these easternmost districts of Austria [ibid.].

Figure 4-1: Modal Split of participants (weighted after number of usage per week)

26% Car drivers Car passengers 40% Public Transport Cycling Walking

13%

12% 9%

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Table 4-2: Variables for reporting situation before – line usage of participants Category Variable name [Unit]

People, who know either line WA50, 79% (209 out of 264 WA51, WL1 and WL2 people) People, who never use line 38% (98 out of 254 WA50, WA51, WL1 and WL2 people) People, use line WA50, WA51, WL1 and 30% (76 out of 254 WL2 less than once a month people) People, use line WA50, WA51, WL1 and 11% (28 out of 254 WL2 less than once a week people) Usage of line of participants People, use line WA50, WA51, WL1 and 20% (52 out of 254 WL2 at least once a week people) Average rating of performance of line 7.74 out of 10 1) (n=158 WA50, WA51, WL1 and WL2 people) Average number of days of those people 2.61 days a week using lines WA50, WA51, WL1 and WL2 (n=52 people) at least once a week People possessing season ticket for the 21% (26 of n=126 people) public transport

1) Where 1 equals poor and 10 equals best performance

The bus lines are known to a majority of 209 out of 264 participants (79%) but 38% never use the lines and 30% use the lines less than once a month. 11% of the participants use the lines less than once a week and merely 20% use the bus lines at least once a week. On average, the participants who use the bus lines at all use them 2.61 days a week. 21% of the participants possess a season ticket for the public transport, which matches exactly the average number for Lower Austria in 2009 [Statistiks Austria 2013] The performance rating of 7.74 points shows high satisfaction with the bus lines in general.

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Reasons for using/not using the public transport line and possible improvements have been collected by open answers, and classified in order to be able to compare the results between the different implementation areas. The list of answer categories from the first draft (see Deliverable D6.1) has been extended based on the open answers given by the participants. The additional categories are marked green/italic style.

Table 4-3: Classification of open answers - reasons for not using line WA50, WA51, WL1 and WL2 Reasons n=91 responds from 56 [%] - of people have named people this reason Time table – frequency of links 26 46% Time table – operation time 14 25% Location of pt stop 11 20% Need to carry heavy goods 10 18% Travel time 9 16% Travel comfort 9 16% Need to change lines to often 4 7% Cost, Ticket tariff 3 5% Lack of information about the service 1) 3 5% Time table – links to other lines 2 4% Time table – not understandable 1 (visibility, readable) 2% 1) The additional category was created to represent the 3 participants that stated they had not yet at all informed themselves about the public transport services.

Figure 4-2: Reasons for not using line WA50, WA51, WL1 and WL2

[number of entries from 56 people] 0 10 20 30

Time table – frequency of links Time table – operation time Location of pt stop Need to carry heavy goods Travel time Travel comfort Need to change lines to often Cost, Ticket tariff Lack of information about the… Time table – links to other lines Time table – not understandable

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Table 4-4: Classification of open answers - reasons for using line WA50, WA51, WL1 and WL2 Reasons n=156 entries from [%]- of people have named 70 people this reason Time table – frequency of links 30 43% No car available 25 36% Location of pt stop 19 27% No stress, safe trip 19 27% Travel comfort 18 26% Cost, Ticket tariff 13 19% Search for parking space 1) 8 11% Time table – operation time 5 7% Direct link 5 7% Consuming alcohol 5 7% Using travel time for other activities 4 6% Travel time 3 4% Environmental protection 2 3% 1) Eight participants explained that they used public transport because of a lack of available parking space or because of a parking fee at their travel destination.

Figure 4-3: Reasons for using line WA50, WA51, WL1 and WL2

[number of entries from 70 persons] 0 10 20 30 40 Time table – frequency of links No car available Location of pt stop No stress, safe trip Travel comfort Cost, Ticket tariff Search for parking space Time table – operation time Direct link Consuming alcohol Using travel time for other activities Travel time Environmental protection

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Reasons not using the bus is clearly based on the subjective perception of the public transport supply and the individual expectation towards an acceptable public transport service density of the participants (almost every second person). The most frequently raised argument of not using the bus line which is not related to supply indicators of the public transport service is the need to carry heavy goods with a share of 18% of persons. On the other side 43% of persons using the bus argued the proper service frequency is the main driver to use the bus. On second place with 36% the argument of using the bus is having no alternatives (no access to a car).

Table 4-5: Classification of open answers - improvement suggestions for the PT service Improvement suggestions n=58 entries from 53 [%]- of people have named people this reason Time table – frequency of links 14 26% Time table – operation time 14 26% Travel comfort 11 21% Cost, Ticket tariff 6 11% Location of pt stop 5 9% Direct link 5 9% Time table - readability (font size) 1) 3 6% 1) Out of the eleven participants that suggested improving the travel comfort, three suggested the construction of weather protection at the bus stop.

Figure 4-4: Improvement suggestions [number of entries from 53 people]

0 2 4 6 8 10 12 14 16

Time table – frequency of links

Time table – operation time

Travel comfort

Cost, Ticket tariff

Location of pt stop

Direct link

Time table - readability (font size)

In line with the main criticism the density of the public transport supply (in terms of frequency and operation time) is the main issue for improvements of the bus lines, followed by travel comfort. Other points were raised less frequently (see figure 4-4).

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4.2 Persons who did not participating in the campaign It is always difficult to get information from persons who are not willing to participate in a survey or campaign. Therefore, the information requested is reduced to two key variables to be able to identify the particularities of users and non-users of the public transport line among this group of people. Depending on the approach of contacting people and their personal patience, it is obvious, that information cannot be collected from everyone. However, it is important to ask a minimum number of people in order to identify the characteristics of these persons. The more detailed questions, inquiring after the person’s reasons for not participating or their motivation to use or not to use public transport services, were not asked.

Table 4-6: Variables for reporting situation before / non participants Category Variable name Unit

76% (303 out of People who know line WA50, WA51, WL1 and WL2 398 people) 42% (19 out of 45 People who use line WA50, WA51, WL1 and WL2 people)

It is apparent that the majority – 303 out of the 398 people, whose answer was obtained, know the bus lines of their municipalities, although they are not willing to participate in the campaign. This rate is similar to the knowledge level of the participants of the campaign (79%). Furthermore 42% have already used the bus at least once in their life time, which is a share clearly below the rate of the participants of the campaign (62%). However, only 45 people were willing to answer this question, which means the result of this variable is somehow limited.

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5 Summary and conclusion

The Ex ante Evaluation presents the data collected before the implementation of the AMC-campaign. This includes figures describing the implementation area, the participants’ mobility behaviour and their perception of the public transport services within their municipalities.

The variation in modal split is considerable when comparing the results of the participants and the general data of the implementation area. The mode distribution of the relevant municipalities shows a car usage of 74%, whereas the participants of the campaign exhibit a lower percentage of only 49%. Equally notable is that the participants’ usage of public transport (12%) exceeds the general percentage of the implementation area (7%). The ratio of participants that generally use the public transport services of their municipalities is 61% and the different bus lines are known to 79% of the people. The average performance rating of the lines is 7.74 out of 10. The frequency of links of the bus service is most often given in answer to the question: what are the reasons of not using the public transport services and is also one of the top suggestions for improvement, alongside with the bus service operation time. However the frequency of links is also one of the top reasons given for using the bus lines of the implementation area. The share of captive bus riders is ca. 36%.

Based on these findings the impact of the AMC-campaign will be assessed at a later stage of the SmartMove project. Furthermore the profile of the implementation area can be used as a frame of reference to allow comparability across the different implementation areas of the SmartMove project and analyse possible relations between these framework conditions and the campaign itself.

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6 References

BMVIT (2011). Österreich - Verkehr in Zahlen. Ausgabe 2011. Bundesministerium für Verkehr, Innovation und Technologie Abteilung II/Infra 5. Vienna BRAWISIMO (2015). BRAWISIMO – Region Bratislava Wien: Studie zum Mobilitätsverhalten. Bundesministerium für Verkehr, Innovation und Technologie. Vienna NÖ Landesakademie (2008). Mobilität in NÖ. Ergebnisse der Landesweiten Mobilitätsbefragung. Amt der NÖ Landesregierung Abteilung Gesamtverkehrsangelegenheiten. Heft 26. St. Pölten NOE Statistik (2014). Zahlen und Fakten in Niederösterreich. Statistisches über Bezirke und Gemeinden. Amt der Niederösterreichischen Landesregierung, http://www01.noel.gv.at/scripts/cms/ru/ru2/suchen_ssi.asp (08.11.2015) Österreich Unterwegs (2015): Travel survey. Österreichische Mobilitätserhebung 2013/14. Bundesminiterium für Verkehr, Innovation und Technologie. Vienna Statistik Austria (2011). Konsumentenerhebung 2009/07, http://www.statistik.at/web_de/statistiken/soziales/ausstattung_privater_haushalte/059000.html (11.12.2013] Statistik Austria (2014). Kraftfahrzeuge – Neuzulassungen, http://www.statistik.at/web_de/statistiken/energie_umwelt_innovation_mobilitaet/verkehr/strasse/k raftfahrzeuge_-_neuzulassungen/index.html (20.11.2015) Statistik Austria (2015). „Ein Blick auf die Gemeinde“, http://www.statistik.at/blickgem/index.jsp (08.11.2015) TREMOVE (2009). Official site of the TREMOVE model, http://www.tremove.org PublicTransport Statistics Report – Issue 1, Brussels, Belgium (includes detailed database) (09.11.2015)

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