Valuing rider quality attributes in the Swedish special transport services

Transcription

1 Valuing rider quality attributes in the Swedish special transport services Stig Knutsson Infrastructure and Planning Royal Institute of Technology, Stockholm Version

2 Valuing rider quality attributes in the Swedish special transport services Abstract Methodology for calculating rider quality in Special Transport Services using utility modelling has been infrequently discussed in the literature. In this paper the model used is based on a basic logit formulation and estimated with the ALOGIT programme. A rider quality index of Swedish Special Transport Services (färdtjänst) is provided as a platform for the calculations based on data from the Stockholm County The paper compares the Swedish values of five key Quality attributes. In addition and as a consequence of the findings a customer profile is presented of low and high willingness to pay for the Special Transport Services in the Stockholm County. Finally a CBA approach is introduced and examined against the empirical results in a consequence scheme. This is done in the light of some actual rationalisation strategies in Swedish Special Transport Services. Introduction In a Swedish context there is no published attempt known modelling Special Transport Services (STS) travel demand in terms of rider quality attributes. The mode färdtjänst is the main STS traffic mode in Sweden. In Sweden we have had a rapid volume growth and evaluation of the Special Transport services, from the early 70`s and the following 15 years. From the late 80 s and forward we can observe an increasing need for governmental cost reduction. The present situation is a result of the strongly expressed demand for Swedish transportation policy effectiveness, that is, in terms of governmental spending. In Sweden and abroad it is common to measure productivity from the producer perspective. It is rare to present productivity also using rider quality attributes. We have a lack of research in the particular segment, also in Sweden. Sutton 1 used the Multinominal Logit Model in his work on estimating travel demand in STS. He chooses fare, transportation time and travel frequency as parameters in his analysis. Social evaluation methods like cross-sector benefits and marginal social benefit are both infrequent and underdeveloped in the international literature. 2 Even if most researchers only deal with the productive apparatus from the production aspect some attention has also been given to the rider Quality aspects. McKnight et al provides a rider Quality Index in1986. McKee offers an outline of a rider Quality model intended to focus on rail vehicles accessible to disabled passengers in1993. In the present paper, we report on a study using rider quality attributes to estimate travel demand. To be able to construct the survey questionnaire the standard Stated Preference techniques were used. 3 For the statistic analysis we employed a basic Logit model. 4 1 Sutton Sutton and McLaughlin 1991, Lund and Oxley 1992, Gillingwater et al Jones 1989, Pearmain 1991, Widlert Algers

3 Methods A rider quality index of Swedish Special Transport Services (färdtjänst) is provided as a platform for the planned Stated Preference experiments. The index is both based on the result of an international literature survey of existing quality indexes, produced from a customer perspective, and adapted to the Swedish context and needs. The index has its rots in quality aspects from a broad spectrum of different time and society transportation contexts: 1. a general model of passenger traffic by Woodson a set of strategic goals from Greater Stockholm Public Transport, Sweden a Special Transportation rider quality index from the US by McKnight et al a rider index approach especially focusing people bound to the wheel chair from the US by McKee an evaluation of the Swedish Special Transport Service (färdtjänst) by the National Board of Health and Welfare The index is meant to map the most important parts of rider quality in a Swedish context based on customer utility and well-being in terms of the right to make choices, to act independently, and to keep dignity and self-esteem. However, the purpose of the present paper is not to explore the index itself in detail, consequently it is placed as Appendix 1. The study was designed as a carefully constructed customer postal questionnaire in the Greater Stockholm area, in which socio-economic information was collected about the respondent and her household, information related to Special Transport Services (färdtjänst) trips and responses to Stated Preference experiments. The questionnaire included a set of four choice Stated Preference situations. It was distributed to 2241 färdtjänst holders in the Stockholm County in late The reply frequency was 65%. Based on our rider quality index in Appendix 1 the following six key attributes were motivated to depict the rider quality in Special Transport Service (färdtjänst) in the postal questionnaire: Based on this exposition the following six key attributes were motivated to depict the rider quality of the färdtjänsten as crucial for rider quality in the Swedish context: Waiting time in the telephone switchboard Pick up time Prebooking time In-vehicle time Driver behaviour Fare Basically three motives are placed in the forefront for choosing the above attributes. First, the quality standard of Special Transport Services (färdtjänst) must be compared with the standard of the present public transport in Swedish big city context, this as a result of the common interpretation of the Swedish legislation. Second, the chosen attributes correspond in a favourable way with the established value of time modelling approach for passenger traffic 5 Woodson, W E et al 1992, p SL 1996, bilaga s 56f 7 McKnight 1986, pp McKee, C 1993, p Socialstyrelsen 1997, s 59 3

4 from the Swedish National Road Administration and the National Rail Administration in Third, to catch the attention on the very key attributes which, in a successful way, depict the day prism 11 of the customer. For the statistic analysis a basic Logit model 12 was employed. The utility function was formulated as follows: u1 = p10 + p11*fb + p12*vv + p13*ht + p14*rt + p15*p + p16*fbet (1) u2 = 0 u1 = utility function p11 p16 = coefficients to be measured p10 = Constant Term Attribute Level I Level II Measurement FB = Prebooking time minutes VV = Waiting time in the telephone 0 20 minutes switchboard HT = Pick up time 0 20 minutes RT = In-vehicle time minutes P = Fare minutes FBET Driver behaviour 0 No statement = 1 Statement "The driver is nice and helpful A method to fix the price of the quality attributes is introduced in two steps. We use the utility function in equation 1 above as a point of departure. 60 minutes in-vehicle time give us a tribute to u1 equal to p14 * 60. If the exact fare which contribute to the utility function as 60 minutes in-vehicle time is represent by K we get: p15 * K = p14 * 60 (2) K = p14 * 60/p15 K is the cost that the traveller value equal with one hour of in-vehicle time. As a consequence, we get a measurement of in-vehicle time, the value of in-vehicle time. The value can be used 10 Vägverket/Banverket 1995, s Hägerstrand, T Algers, S

5 as an input value in CBA estimations in the field. The attribute Driver behaviour (FBET) does not have a connection with the value of time in the same way as in-vehicle time. Instead, the transformation equation for this attribute is formulated as follows: FBET = p16/p15 (3) To run the estimations the ALOGIT programme 13 was chosen. Results The values presented below constitute the main findings. In the table all the estimates are expressed in Swedish kronor. Table 1 Main results. Estimated rider quality variables. Swedish kronor. Variable Maximu Minimu Median Mean s m m Pick up time Waiting time in the telephone switchboard In-vehicle time Prebooking time Driver behaviour In addition a CBA approach is introduced and examined against the empirical results in a consequence scheme. This is done in the light of some actual rationalisation strategies in Swedish Special Transport Services. 13 Hauge Consulting Group

6 Symbol e Strategy Willingness to pay Pick up time Waiting time in the telephone switchboa rd Prebooking time Invehicle time A Transfer to bus advantage advantage advantage drawba ck A Service line advantage advantage advantage drawba ck A Winding line drawback advantage advantage drawba ck A Scheduled traffic drawback advantage advantage drawba ck C1 Adjust departure drawback 0 0 drawba time ck C1 Allow divergence from wanted drawback 0 0 drawba depart time ck Driver behaviour drawback advantage drawback drawback drawback drawback Figure 1 Vital rationalisation strategies for travel demand grouped after effect on rider quality and willingness to pay Discussion This paper presented a methodology for calculating rider quality in Special Transport Services using utility modelling. Furthermore, the model used is based on a basic Logit formulation and estimated with the ALOGIT programme. This methodology has been infrequently discussed in the international STS Transportation literature. Sutton used a disaggregated choice model in 1990.This is the only material found using this approach. Estimated rider quality variables are shown in the table Main results in the Result section. Based on customer preferences, the variable path is divided into two separate groups. The main problem in the first subgroup, (Waiting time for telephone switchboard and Pick up time) with high mean values, is lack of planning opportunities in daily life. The questions on the Transportation timetable are as important for this group of customers as for non-disabled people. Employment strongly influences your possibility to plan your own time spent, during the day. The variation width in the values for these two variables highlights the dependence between a time-fixed daily schedule or lack thereof and travel demand. Prebooking time is always stipulated in the local guidelines and information handouts and is therefore better known by the travellers in general. The table below shows the employment example in detail: 6

7 Table 2. Calculation results of employment/ student respective others. Swedish kronor Variable Employment Others / student Estimate Estimate Constant 0,421 0,258 t-value 3,6 5,2 Prebooking time -0,016-0,007-4,0-4,3 Waiting time in the telephone -0,078-0,056 switchboard -9,6-17,6 Pick up time -0,095-0,063-11,4-19,4 In-vehicle time -0,009-0,008-1,3-2,4 Fare -0,024-0,034-5,5-18,3 Driver behaviour -0,017-0,021-0,1-0,4 Obs-number ρ 2, con 0,429 0,312 Likelihood -255, ,070 ID 3 4 * not significant Table 3 Monetary valuation of employment/ student respective others. Swedish kronor. Variable Employment Others / student Prebooking time Waiting time in the telephone switchboard Pick up time In-vehicle time * 13 Driver behaviour * * ID 3 4 * not significant 7

8 There are differences between the values of the attributes both in side each categorises itself, and between the two categorises. There are frequently timetable restrictions involved in the employment situation. Therefore, on the one hand the parameters Pick up time and Waiting time in the telephone switchboard are essential to obtain punctuality. In-vehicle time itself is less important compared with previous attributes. Therefore, the willingness to pay for exactness in Special Transport supply is high in comparison with the attribute In-vehicle time itself. On the other hand, if a person is out of work or a senior citizen he can spend his time more freely. He is not strongly depending on exactness in transport delivery on time. As a result the values are decreasing. A limitation of the study is a weakness in the estimation results for the variable Driver behaviour. Only two estimates of the total number of equations executed are statistically proven. As a consequence the findings in this part need to be more thoroughly examined in other utility model specifications. With this shortcoming in mind, a customer profile can be presented of low and high willingness to pay for the Special Transport Services in the Stockholm County: High willingness to pay Woman Household income Sek Low confidence in Special Transport Services Highest travel consumption Low willingness to pay Man Not bound to the wheel chair Not employed or student Household income < Sek High/neutral confidence in Special Transport Services Purpose of travel: chiropody Lowest travel consumption Figure 2: Customer profile of low and high willingness to pay for the Special Transport Services in the Stockholm County From of the figure above, two quite different personal life conditions are highlighted depending on if the respondent needs to control the Transportation timetable or not because of the number of daily time-fixed meetings. Conclusions The mode färdtjänst is the main Special Transport Services (STS) traffic mode in Sweden. In a Swedish context there is no published attempt known modelling STS travel demand in terms of rider quality attributes. In this project STS rider quality values can be compared with up-to-date rider quality values for ordinary riders in passenger traffic in Sweden for the first time. In addition this give us an opportunity to test the findings in a sketch to a CBAapproach. 8

9 References Gillingwater, D: Resourcing non-conventional and accessible public transport in the U.K., Department of Transport Technology, University of Transport, Loughborough, TT 8803, 1988 Gillingwater, D et al: Community Transport: Policy, Planning, Practice. Transportation Studies Volume 15, 1995 Jones, P: An Overview of Stated Preference Techniques. P.T.R.C course lecture notes, Oxford university transport studies unit, Oxford 1989 Larsson, H: Det offentliga åtagandet i samhällsbetalda resor, Statskontoret, Rapport 199/96-5, Stockholm 1996 Lund, T and Oxley, P: Cross-Sector Benefits of Accessible Public Transport, XX th Summer Annual Meeting, University of Manchester, Institute of Sience & Technology, England 1992 McKee, C: Rail vehicles accessible to disabled passangers. Proceedings of Seminar J held at the PTRC European Transport, Highways and Planning 21 st Summer Annual Meeting 1993, UMIST, Vol. P371 McKnight, C E et al: Using Quality to Predict Demand for Special Transportation, Behavioural Research for Transport Policy, pp , VNU Science Press, Utrecht 1986 Paaswell, R E: Estimation of Demand for Transit Service Among the Transportation Disadvantaged, Transportation Research Record 660, pp Hoel och Davis 1984 Pagano A M: Production function based Quality and Efficiency Measures for Special Transportation Services, Mobility and Transport for Elderly and Disabled Persons, Proceedings of the 6 th International Conference, Vol 1, Lyon 1992 Pearmain, D et al: Stated preference techniques: a guide to practice, Steer Davies Gleave. Hague consulting group uo 1991, 2 uppl Sundvall, B et al: Demand-Responsive Public Transport. Twelve Case Studies in Europa, TFK Report 1993:5E, Stockholm 1993 Sutton, J C: Transport Coordination and Social Policy, Avebury Press, Aldershot 1988 Sutton, J: Travel choice and mobility handicapped: some preliminary investigations utilising a disaggregated choice model, Transportation Planning and Technology, Vol 14, p , 1990 Sutton, J C: Economic evalution of the performance of special needs transport services, Proceeding, XX th Summer Annual Meeting, PTRC, University of Manchester 1992 Thatcher, R H et al: ADA Paratransit Handbook: Implementing the Complementary Paratransit Service Requirments of the Americans with Disabilities Act of 1990, UMTA, Washington

10 Widlert, S: Stated preferences: ett sätt att skatta värderingar och beteende, KTH, Inst för Trafikplanering, Transek, Stockholm

11 Appendix 1 The Swedish rider quality index (IRK) N o Group of attributes Attributes 1 Information Information access 2 Understandable information 3 Faultless and complete information 4 Unambiguous information 5 Dignity Being taken seriously as a traveller 6 Confidence with respect to what to do and where to go 7 Personal privacy 8 Reliability of service 9 Safety day and night time 10 Medical emergency capability 11 Suitable and motivated driver 12 Courtesy & friendliness 13 Familiarity with personal needs 14 Comfort Service on weekdays 15 Service on weekend 16 Punctuality, departure 17 Punctuality, arrival 18 Freedom from crowding 19 Booking 20 Follow-up to complaints 21 Few restrictions 22 Prebooking of return 23 Smoothness of ride 24 Vehicle inside design 25 Number of steps 26 Space and seating 27 Lift (or ramp) 28 Distance to vehicle 29 Driver assistance 30 Ease of complaining 31 Possibility to choose departure time 32 Travel time Reasonable in-vehicle time 33 Waiting time away from home 34 Waiting time in the telephone 11

12 switchboard 35 Total trip time 36 Delays on vehicle 37 Prebooking time 38 Punctuality, pick up time 39 Fare Worth its price compared to public transport 40 Fare 12