Presentation on theme: "Measuring the Dynamic Behavioural Responses due to the Introduction of a New Extension Tram Line by using Panel Survey: Preliminary Analysis Nursitihazlin."— Presentation transcript:
Measuring the Dynamic Behavioural Responses due to the Introduction of a New Extension Tram Line by using Panel Survey: Preliminary Analysis Nursitihazlin Ahmad Termida Yusak. O. Susilo Joel Franklin Department of Transport Science, KTH Royal Institute of Technology hEART 20141
Introduction Douglas (2003) - A ‘ramp-up’ factor in the patronage growth for 13 new or upgraded rail. Chatterjee (2001) - Longer times and shorter times of responses. Lanzendorf (2003, 2010) - The way the travellers have grown up and their perspectives on their travel modes and habits influences the way we travel and make choices. Simma and Axhausen (2003) – The use of a particular travel mode at a young age positively influences the usage of the same mode for the rest of an individual’s life course, and the usage of other modes negatively. Example of the use of panel data studies: Chatterjee and Ma (2006, 2007), and Yáñez et al. (2010). hEART 20142
Research Questions What are the changes occurred? How many and when the new users start to adopt the new tram? Who are using it earlier than others? Who have adopted the new tram as a part of their regular mode choice? hEART 20143
Case Study: The New Tram Line Service (Tvärbanan) Extension In Stockholm hEART 20144 The Instruments (1)The two-week travel diary (2)Psychological-related surveys (3)Mental map-related questions Survey Design
Respondent Selection and Recruitment Process 100 individuals were targeted. – The main sample: Individuals who are ‘living close’ (approximately 500 metres) from the new tram line’s station. – The control sample: Approximately 20% of the samples are the individuals who are ‘not living close’ (approximately 1 kilometre away) from the new tram line’s station. Overall, 75 individuals (with 14 control samples) participated in all three waves. hEART 20145
6 TABLE 1 The Percentages of Socio-Demographic Characteristics of Respondents in each Wave Characteristics Wave 1Wave 2Wave 3All waves (n = 92)(n = 83)(n = 77)(n = 75) Gender Male28.325.327.325.3 Age (years) Below 220.127.116.11.7 16 - 2510.99.69.19.3 26 - 4545.744.642.941.3 46 - 6526.126.527.328.0 Above 6515.216.918.218.7 Marital status Single22.814.519.518.7 Married41.343.439.040.0 Divorced8.712.013.013.3 Other (e.g. living with partner/friends/relatives/other)18.104.22.1688.0 Employment status Full-time employed37.041.041.641.3 Part-time employed8.710.89.19.3 Self-employed22.214.171.124.7 Looking after the home or family13.012.011.712.0 Permanently retired15.216.918.218.7 Unemployed and seeking for work2.2000 At school4.36.06.56.7 In further or higher education126.96.36.199.3 Permanently sick or disabled188.8.131.52 Unable to work due to short-term illness or injury184.108.40.206 Other (unemployed)220.127.116.11.3 Driving license ownership Owned by respondent72.875.976.676.0 Car ownership Owned at least a car63.066.362.364.0 Gross monthly income (before tax) Low-class income (< 15,000 SEK)12.09.615.616.0 Medium-class income (15,000 - 54,999 SEK)60.962.749.448.0 High-class income (> 55,000 SEK)27.227.735.136.0 Intention in using the new tram service sooner48.9N/A after its opening Did use the new tram service sooner after its openingN/A20.522.122.7 Note: N/A = not applicable. The question on using the new service sooner after its opening defined as individuals who already used the new extension tram line service within one week after its introduction.
Descriptive Analysis What are the changes occurred? (1) Changes in modal split hEART 20147
Descriptive Analysis (cont.) hEART 20148 TABLE 2 Percentage-Point Changes of Mode in General and for the Main and Control Samples WalkCycleMotorcycleCar BusTramSubwayTrainTaxiSkateboardOther driverpassenger General W1 - W2+0.43-1.18+0.07+0.10+0.14+0.99+1.63-0.68-0.19-0.100-0.46 W2 - W3+0.23+0.22-0.30-0.52-0.37-1.33-0.69-1.15-0.790+0.010 W1 - W3+0.66-0.97-0.23-0.42-0.23-0.33+0.94-1.83-0.98-0.10+0.01-0.46 Main Sample W1 - W2+0.22-0.97+0.07+0.53+0.17+0.71+1.87-0.63-0.24-0.070-0.43 W2 - W3-0.04+0.23-0.30-0.86-0.35-1.05-0.72-1.20-0.650+0.010 W1 - W3+0.17-0.73-0.23-0.33-0.17-0.35+1.15-1.83-0.89-0.07+0.01-0.43 Control Sample W1 - W2+0.22-0.220-0.43-0.03+0.29-0.24-0.04+0.06-0.030 W2 - W3+0.27-0.010+0.35-0.03-0.27+0.03+0.04-0.14000 W1 - W3+0.49-0.230-0.09-0.06+0.01-0.220-0.09-0.030
Descriptive Analysis (cont.) (2)Changes in travel characteristics hEART 20149 TABLE 3 Travel characteristics WAVE 1WAVE 2WAVE 3NTS 2011 ControlMainControlMainControlMainDATA (n = 14)(n = 61)(n = 14)(n = 61)(n = 14)(n = 61) Number of trips Trips/person24.427.022.628.824.524.4 Trips/person/day1.741.931.612.061.751.741.86 Travel distance (kilometres traveled) Traveled distance/person230.5264.1221.3230.6261.5247.9 Traveled distance/person/day16.518.915.816.518.717.744.4 Travel time (minutes) Travel time/ person529.7726.8540.9711.7616.6706.2 Travel time/person/day37.851.938.650.844.050.4 Travel time/person/day/trip21.726.924.024.725.229.028.7 Trip purposes (% of trips) Pick-up or drop-off somebody18.104.22.168.22.214.171.124 Private business126.96.36.199.188.8.131.52 Professional business00.20.30.10.90.66.0 School/education184.108.40.206.220.127.116.11 Work23.217.019.316.420.417.815.8 Shopping daily needs18.104.22.168.22.214.171.124 Shopping long-term needs2.93.03.24.02.3 7.1 Leisure7.618.47.316.812.216.030.1 Other (e.g. doing research)0.60.701.30.93.012.6 Go back home46.039.645.942.742.940.60 Number of transfer(s) made in a single trip (% of trips) No transfer85.084.184.285.289.586.468.3 1 transfer10.312.011.712.56.411.916.4 2 transfers126.96.36.199.03.81.712.0 3 transfers0.6000.3 03.3 Percentage of trips with different modes As a public transport user46.043.252.846.044.342.018.0 As a private vehicle user34.320.826.624.033.220.731.7 Walking and cycling19.135.919.929.922.437.345.9 Use both PT and private vehicle0.60.10.60.1002.2 Other user (e.g. flight, maritime)0000002.2
Descriptive Analysis (cont.) How many and when the new users start to adopt the new tram? Time taken for the respondents to use the new tram service after its introduction: hEART 201410
Multivariate Analysis Who use the new tram earlier than others? hEART 201411 Marginally (at α = 10%), the elderly (age above 65), with middle-income (15,000 – 54,999 SEK) and who have no dependent children within their household are likely to use the new tram earlier than others.
Multivariate Analysis (Cont.) Who have adopted the new tram service as a part of their regular mode choice? Marginally (at α = 5%), high income travellers (more than 55,000 SEK), hold a driving license and public transport season ticket, have no dependent children within their household and the travellers who used the tram mode in the previous day are likely to adopt the new tram service as a part of their regular mode choice. hEART 201412
Conclusions Changes in modal split = The tram shares increased by +0.94 pp, whilst subway shares decreased by -1.83 pp. Changes in travel characteristics = The main sample made more trips in wave 2 survey compared to other waves, and public transport users for both sample groups are at their lowest in wave 3 but with the highest value of walking and cycling user type. The ‘quick-response’ users = The elderly, middle-income travellers, and have no dependent children within their household. The new tram line service user = High-income travellers, hold a driving license and public transport season ticket, have no dependent children within their household and the ones who used the tram mode in the previous day. The panel data of this study has a large potential to study the dynamics and learning processes of individuals in using a new transport service. hEART 201413
Further Directions of the Study The travellers’ objective and subjective factors over time (in all waves) may be examined. The use of a TPB model towards the time-scale responses is also in our interest for future studies. A more systematic analysis on the changes in individuals’ mental map over time would also be some original and useful topics to be studied in the future. hEART 201414
References 1.Douglas, N. Patronage Ramp-Up Factors for New Rail Services. Douglas Economics Ltd. Report, February 2003. www.douglaseconomics.co.nz/reports.htm. Accessed May 28, 2013.www.douglaseconomics.co.nz/reports.htm 2.Chatterjee, K. (2001). Asymmetric Churn – Academic Jargon or a Serious Issue for Transport Planning? Transport Planning Society, April 2001. www.tps.org.uk/files/Main/Library/2001/0001chatterjee.pdf. Accessed May 28, 2013.www.tps.org.uk/files/Main/Library/2001/0001chatterjee.pdf 3.Lanzendorf, M. Mobility Biographies: A New Perspective for Understanding Travel Behavior. Presented at 10th International Conference on Travel Behavior Research, Lucerne, August 2003. 4.Lanzendorf, M. Key Events and Their Effect on Mobility Biographies: The Case of Childbirth. International Journal of Sustainable Transportation. Vol. 4, No. 5, 2010, pp. 272-292. 5.Simma, A. and Axhausen, K.W. Commitments and Modal Usage: Analysis of German and Dutch Panels. In Transportation Research Record: Journal of the Transportation Research Board. No. 1854, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 22-31. 6.Chatterjee, K. and Ma, K. Behavioural Responses to A New Transport Option: A Dynamic Analysis Using A Six-Month Panel Survey. Presented at 11 th International Conference on Travel Behavior Research, Kyoto, August 2006. 7.Chatterjee, K. and Ma, K. Modelling the Timing of User Responses to a New Urban Public Transport Service: Application of Duration Modelling. In Transportation Research Record: Journal of the Transportation Research Board, No. 2010, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 62-72. 8.Yáñez, M. F., Mansilla, P. and Ortúzar, J. de D. The Santiago Panel: Measuring the Effects of Implementing Transantiago. Transportation, Vol. 37, 2010, pp. 125-149. hEART 201416