QUANTIFICATION OF PASSENGERS PREFERENCE FOR IMPROVEMENT OF RAILWAY STATIONS CONSIDERING HUMAN LATENT TRAITS: A CASE STUDY IN METRO MANILA

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1 1408 QUANTIFICATION OF PASSENGERS PREFERENCE FOR IMPROVEMENT OF RAILWAY STATIONS CONSIDERING HUMAN LATENT TRAITS: A CASE STUDY IN METRO MANILA Hidenori OKADA Graduate Student Department of civil Engineering Kagawa University , Hayashi-cho, Takamatsu, Kagawa Japan s02g419@stmail.eng.kagawa-u.ac.jp Ma. Sheilah A. GAABUCAYAN Graduate Student Department of Mechanical and Environmental Informatics Tokyo Institute of Technology Fax No sheilah@plan.cv.titech.ac.jp Kenji DOI Professor Department of civil Engineering Kagawa University Tel: Fax: doi@eng.kagawa-u.ac.jp Akira HOSOMI Researcher ALMEC Corporation Aobadai, Meguro-ku, Tokyo Japan Tel: hosomi@almec.co.jp Abstract: This study is aimed at identifying the cause of low light rail transit (LRT) ridership from the viewpoint of accessibility and intermodality. According to the results of questionnaire survey conducted at several stations of Metro Rail Transit 3 (MRT3) operated in Metro Manila, Philippines, dissatisfaction level and preference level for improvements are quantified by considering human latent traits. In the analysis, users dissatisfaction and preference were decomposed into the element depending on latent traits and independent one. The first one, which includes the improvement of pedestrians accessibility and establishment of transfer terminal between MRT3 and bus, shows a widely perceived demand. The second one, which includes the improvement of amenity and level of service of MRT3 stations, shows a demand specific to some social groups. It is clarified that those who have the second demand belong to a higher income group and thus, supposed to increase according to an increase in average income level. Consequently, this paper suggests the priority areas of improvement in urban rail service that can contribute to the promotion of its ridership. Key Words: light rail transit, intermordality, questionnaire survey, item response model 1. INTRODUCTION In big cities of Asian developing countries that lack the rail transport, synergetic effect between urbanization and motorization is often observed. As a result of the growth in per-capita income, there is an increase in car ownership and expansion of built-up area. Without rail transport, this synergetic effect results not only in chronic traffic jam but also in

2 1409 deterioration of atmospheric environment due to automobile emissions. Metro Manila suffers the most serious traffic problems because of a higher percentage of para-transit and old buses as well as the increase in private cars. Light Rail Transit MRT3 was implemented in December 1999 to solve chronic traffic jam. But unfortunately, the actual utilization of the service was a way below the expected demand. In spite of its advantage as a punctual and efficient mode of transportation as far as capacity for moving people, MRT 3 is at a disadvantage because of higher fare and poor connectivity with other existing transportation modes. MRT3, newly introduced along the major corridor EDSA, is the first case that was implemented by Build-Lease-Transfer (BLT) scheme in the Philippines. The project was financed and built by Metro Rail Transit Corporation (MRTC). Now, MRTC takes a role to lease it to Department of Transportation and Communications on a contract of 25 years. After the end of lease period, the ownership will be transferred to the Government. Average Daily Passenger Volume Break even point (440,000 pax/day) 500, ,000 gap 300, , , / Period Figure 1. Average daily passenger volume of MRT3 Figure 1 shows the recent trend of daily volume of MRT3 ridership. It has attracted less passengers than expected because of high fare and poor connection with other transportation modes. MRT3 was planned to make car owners and bus users to shift to it. However, it has been suffering from low demand and does not even reach the estimated break-even point. Break-even point of MRT3 is 440,000 passengers per a day based on its feasibility study. But when MRT3 opened in December 1999, there were only about 25,000 passengers, which was 4% of break-even level. MRT3 ridership continued to stand only about from 12 to 14% of break-even level. MRT3 project was in the red, it could hardly earn 15% of the rental revenue. When fare reduction was implemented in July 2000, ridership significantly rose to about 150,000 passengers (about 35% of break-even level). Figure 1 shows this effect clearly. After fare reduction, ridership rises slowly and continues to increase. However there is still a considerable gap between break-even and present ridership.

3 1410 The shortage of passengers is likely to be caused not only by still high fare but also other factors. Therefore, we evaluate the quality of overall services of rail transit including intermodal service. The main objective of this study is to identify the cause of small ridership from the viewpoint of accessibility and intermodality. Also, it endeavors to propose relevant policies to encourage demand based on the marketing approach. The Item Response Model (IRM) will be applied in this study. It is a class of non-linear latent variable models that can quantify the degree of passengers dissatisfaction and preference in a cardinal measure by distinguishing individuals latent traits. Using the IRM, latent traits existing behind the dissatisfaction with the current MRT service, which includes not only line-haul service but also terminal service, are identified. The following categories of service are included in the analysis: a) basic level of service of MRT3 as transportation; b) amenity and level of service of MRT3 stations; c) convenience of access by walk; d) commercial establishments in and around the station; and e) transfer between MRT3 and other transportation modes. North Avenue Quezon Avenue Cubao Ayala Taft Avenue Magallanes Figure 2. MRT3 line and target stations in the survey 2. RIDERSHIP AND USERS EVALUATION OF LRT SERVICE 2.1 Questionnaire survey A questionnaire survey was conducted at 6 stations of MRT3 to grasp the current status of ridership, dissatisfaction with overall service, and demands for improvement of LRT service (see Figure 2). In the questionnaire, the respondents were requested to rate their present status on each of the categories. The ratings were expressed on a five-rank scale, namely, whether they are very satisfactory, satisfactory, just right, unsatisfactory, or very unsatisfactory in the dissatisfaction survey, and a three-rank scale, namely, whether they have high demand, demand, or no demand in the demand survey (see Table 1). Also, the respondents were asked

4 1411 to set a priority for improvement measures. In addition, we asked non-users about the for non-utility of the rail service. The survey was conducted in and around of 6 stations; North Avenue, Quezon Avenue, Cubao, Ayala, Magallanes, Taft Avenue. The survey was conducted for three time periods. They are from 7:00 a.m. to 9:00 a.m. (peak hours), from 11:00 a.m. to 1:00 p.m. (lunch time), and from 3:00 p.m. to 6:00 p.m. (off-peak hours) in two days: on November 23rd (Fri.) and 24th (Sat.), We adopted personal interview survey, and collected total number of 1,115 responses. Table 1. Outline of questionnaire survey Item of satisfaction level survey Fare of MRT3 Frequency of trains Travel time Riding comfort Security in station Congestion in station Amenities of station Accessibility of station on foot Commercial activity surrounding the station Transfer between MRT3 and another transportation mode Item of demand level survey Decrease in fare Increase frequency of trains Increase speed of trains Improve comfort of train cars Improve security in station Increase number of ticket booths Increase lavatories in station Improve pedestrian facilities outside the station Install streetlights on adjacent streets Establish kiosk inside the station Establish shopping streets adjoining the stations Establish shopping malls adjoining the stations Establish supermarkets adjoining the stations Establish jeepney terminal adjoining the MRT3 stations Establish bus terminal adjoining the MRT3 stations Establish taxi stands adjoining the MRT3 stations Establish pedestrian walkways adjoining the MRT3 stations 3.2 Summary of the questionnaire result Figure 3 shows the distribution of respondents attributes. The majority of respondents are between the ages of years old. The number of male was a little higher than that of female respondents. Travel to work and to home was the highest purpose for traveling at 60 %.

5 1412 more than 40 yrs old 7% yrs 23% Age yrs 12% yrs 58% 7% Female Male 49% 51% 9% Gender 6% 5% 7% Figure 3. Attributes of respondents 40% Trip purpose 26% Home Office/Work place School Shopping Business Recreation Others Figure 4 summarizes the status of users satisfaction. Dissatisfaction with congestion in stations is highest and followed by expensive fare. Transfer between MRT3 and other transportation modes Commercial activity surrounding the station Accessibility of station on foot Amenities of station Congestion in station Security of station Riding comfort Travel time Frequency of trains Fare of MRT % 20% 40% 60% 80% 100% 1.4 Total % 20% 40% 60% 80% 100% Very unsatisfactory Unsatisfactory Just right Satisfactory Very satisfactory Figure 4. Satisfaction level of MRT3 users Figure 5 shows the status of users demand. Under the influence shown in Figure 3, demand for increasing number of ticket booths is the highest. Also, demands for intermodal service and for pedestrian walkways for easy access to MRT stations are obviously high.

6 1413 Establish pedestrian walkways adjoining the MRT3 stations Establish taxi stands adjoining MRT3 stations Establish bus terminals adjoining the MRT3 stations Establish jeepney terminals adjoining the MRT3 stations Establish shopping streets adjoining the stations Establish shopping malls adjoining the stations Establish supermarkets adjoining the stations Establish kiosks in inside the station Install streetlights on adjacent streets Improve pedestrian facilities outside the station Establish lavatories in station Increase number of ticket booths Improve security in station Improve comfort of train cars Increase speed of trains Increase frequency of trains Decrease in fare % 20% 40% 60% 80% 100% High demand Moderate demand No demand Figure 5. Present status of demand level The demand survey also includes questions on priority of improvement. Figure 6 shows the magnitude of priority for each improvement as a weighted score. This figure indicates well that people do not only find improvement in fare but also in overall services as important for increased level of satisfaction. Transfer between MRT3 and other transportation modes Commercial improvement adjoining the stations Convenience of access of stations Level of service of MRT3 stations Level of basic service of MRT3 as transportation Weighted score 1st 2nd 3rd 4th 5th Figure 6. Weighted score of respective improvements

7 1414 Figure 7 shows components of access mode and egress mode. About access mode to the MRT3 station, 70 percent are by jeepney and bus. Access by walking is less than 20 percent. Conversely, egress on foot stands high at 50 percent, followed by jeepneys at 30 percent. Access mode % 20% 40% 60% 80% 100% Egress mode % 20% 40% 60% 80% 100% Walk Tricycle Jeepney Bus Taxi/FX Others Figure 7.Components of access and egress modes Figure 8 shows the distribution of MRT users tolerable walking time to and from the station. This figure shows that the respondents do not want to walk over 10 minutes. Thus, they opt not to use the MRT3 if they have to walk to and from the station for more than 20 minutes. 12% 5% 5% 2% 5% 36% 35% less than 6 min min min min min min. more than 60 min. Figure 8. Tolerable walking time of MRT3 users Figure 9 shows the composition of the means of terminal transportation by access time zone. As access time becomes longer, the fall in the percent of walking as a means of access to the station becomes more remarkable. The number of MRT users who come from places that take more than 10 minutes of traveling is quite limited. The rate of tricycle as a transportation mode also shows the same tendency. On the other hand, the rate of jeepney users increases until 20 minutes, and decreases after that time. As a whole, access by any mode is seen to decrease after peak time of minutes.

8 Frequency (pax.) Time (min.) Walk Tricycle Jeepney Bus Taxi/FX Others Figure 9. Composition of the modes of terminal transportation by access time zone In addition, we will try to identify the reason why some people do not use the MRT. As indicated in the Figure 10, the reason for not utilizing the MRT3 is that there is no connection or line going to the desired destination. Moreover, inconvenient transfer between MRT3 and other transportation modes is given as a reason for non-utility rates higher (22%) than expensive fare (16%). This indicates that to attract more riders, it is more important to improve the transfer between MRT and other transportation modes than to reduce fare. 22% 7% 5% 2% 1% 6% 16% 41% No line going to your desired destination Expensive fare Schedule of first train too late Schedule of last train too early Travel time is longer using MRT3 Dangerous Inconvenient transfer between MRT3 and other transportation modes Others Figure 10. Reasons of no use

9 QUANTIFICATION OF ON USERS DISSATISFACTION AND PREFERENCE USING THE ITEM RESPONSE MODEL 3.1 Methodology Recently, Item Response Model has been applied to the characterization of users dissatisfaction and demand. Doi and Aoki(1999) applied this method to the evaluation of station services in Tokyo Metropolitan area. Similarly with the preceding study, we analyze the users response in the case that users level of demand for railway services is provided by multiple-choice type questions. In our survey, users are asked to rank their satisfaction level and demand for improvement of specific railway services with mark-sheet style. Here, it can be assumed that not only individuals present situation but also their latent traits affect the level of users satisfaction and demand for railway services. Therefore, we introduce parameter ζ which expresses psychological latent variable of users and define the following equation as the probability of alternative k (e.g. satisfactory ) to be judged more appropriate than the other alternative l (e.g. unsatisfactory ). Pr( k > k l l) = Pr ob( ξ ξ 0) (1) where psychological latent trait ξ k and ξ l are regarded as random variables that follow normal distribution. If the expectation E( ζ k ) is expressed as E ( ζ k ) = b k + α kθ by using individual s latent trait θ, which is independent from the alternatives, equation (1) is able to be represented as follows. bk bl + ( ak al ) θ Pr( k > l) = Φ (2) 2σ where Φ denotes the cumulative function of normal distribution with variance σ. Furthermore, to make operation easy, we draw the following equation with an approximation of Φ by using the logistic function. 1 Pr( k > l) = (3) D 1+ exp ( bk bl + ( ak al ) θ 2σ where D is the approximation constant.

10 1417 The above model can be easily extended to a multi-nominal response model on the assumption of independence from irrelevant alternatives (IIA) as follows; P k ( β k + α kθ ) ( β α θ ) exp ( φ ) = K exp (4) = + l 1 k k Where P k is the probability that a respondent chooses a specific alternative k among choice set K. Parameter θ denotes the latent trait of the respondent and α k, β k are item parameters. When applying this model, respondents are asked to choose the most appropriate item that reflects his/her satisfaction level and demand level. In the above model, parameters θ, α, and β are estimated according to the following procedure. STEP 0: Setting the log-likelihood function. max N J K θ, a, b n= 1 j= 1 k = 1 δ njk ln Pr jk ( θ ) n N J K K = δ njk ( b jk + a jkθ n ) ln exp( b jl + a jlθ n ) = = = = (5) n 1 j 1 k 1 l 1 1: Initialize the value of latent trait parameter θ. 2: Estimate item parameters, α and β, under the given values of θ. 3: Estimate latent trait parameter θ, under estimated value of α and β in Step 2 4: Iterate Step 2 and 3 until satisfying the given convergence condition. This procedure is called the EM algorithm. Equation (5) is applied to both satisfaction response and demand response as follows: Satisfaction response model: Demand response model: P jk R jk ( β jk + α jkφ) ( β α φ) exp ( φ ) = K exp (6) = jl + 1 jl l ( b jk + a jkθ ) ( b a θ ) exp ( θ ) = K exp (7) = jl + 1 jl l where both models have same functional form although their latent trait parameters and item parameters are differentiated.

11 1418 Table 2. Estimated values of latent parameter Attributes Latent dissatisfaction level Latent demand level Average Standerd deviation Average Standerd deviation Gender Male Female Age yrs yrs yrs more than 40 yrs old Income Less than P5, P5,001 - P10, P10,001 - P15, P15,001 - P20, P20,001 - P25, P25,001 - P30, More than P30, φ θ 3.2 Estimation results Estimated values of latent trait parameters φ and θ are shown in Table 2. Attribute categories with positive average value of parameters are the brackets that have higher dissatisfaction and higher demand for improvement. As for the effect of gender and age, females value of φ is relatively higher than males and value for older age bracket is less than younger age bracket. Income effect is not clearly expressed in Table 2. Response probability P Congestion in station Just Right Dissatisfaction Satisfaction Response probability P Satisfaction Transfer Dissatisfaction Just Right Latent dissatisfaction level φ Latent dissatisfaction level φ Figure 11. Estimated response curves (examples)

12 1419 Figure 11 show the relationship between estimated value of latent trait and response probabilities as response curves. Regarding the response curves of congestion, the response probability of dissatisfaction clearly increases as the value of latent dissatisfaction φ increases. In the case of the transfer, the increase in the probability of dissatisfaction according to the increase in φ is relatively not sharp. Dissatisfaction with the transfer seems less sensitive to latent trait φ than that with congestion in station. The difference in this sensitivity is expressed by parameter α in equation (5). By using the estimated parameters, it is possible to characterize users demand. Horizontal axis of Figure 12 shows the difference of parameter b between high demand and no demand. Another axis shows the difference of parameter a. Magnitude of δ b indicates demand level independent of users latent trait θ, thus higher value of δ b lead to higher demand of users in common. Magnitude of δ a shows demand level dependent on latent trait θ. User-specific or situation-specific demand is assumed to have higher value of δ a. 1.5 Establish lavatories in station Effect of latent trait Group C Establish jeepney Improve comfort of train cars Decrease in Increase frequency of trains Group B Establish supermarkets adjoing the stations Improve security of stations Establish shopping malls adjoing the stations Group A Establish bus terminals Install streetlights on adjacent Increace mumber of ticket booths Level of demand independent of latent trait δ b Improve pedestrian facilities outside the stations Figure 12. Characterization of demand factors In Figure 12, demand factors are categorized into three groups. Group A corresponds to the widely perceived factors or that which is perceived by the majority. Group B is user-specific demand, and Group C is intermediate one between them. Improvement of pedestrian facilities outside the stations, installation streetlights on adjacent streets and increase in number of ticket booths are the typical factors of Group A. Improvement in comfort of train cars, and establishment of lavatories in stations are included in Group C. Those who have a strong

13 1420 demand for these factors are people who belong to the higher income class. In setting the priority areas of improvement, magnitude of θδ a + δb, which is a total demand combining two effects δ a and δ b in Figure 12, can be used as an adequate indicator. If there is a little variance in latent demand among users, then we should give higher priority to the measures in Group A than those in Groups B and C. However, it is cope with user-specific demand in Group C when and where the number of users with higher level of latent demand is not negligible. Users from some stations such as Ayala and Cubao have relatively higher level of latent demand. 4. CONCLUSIONS Based on the results of the survey on MRT3 in Metro Manila, the most dominant factor of passengers dissatisfaction is congestion within stations, followed by: relatively higher fare compared with other public transport modes, and inconvenient access to stations. Non-users of MRT3 complained about the inconvenience of transfer between LRT and other transportation modes as the first reason, excluding the lack of service in desired area. Through the application of the IRM we are able to evaluate the magnitude of dissatisfaction and resulting demand in a objective scale with the passengers demand for improvement grouped into two categories; those which are irrelevant from passengers latent traits, and those depending on such traits. The first one, which includes the improvement of pedestrians accessibility and establishment of transfer terminal between MRT and bus as well as the reduction of fare, shows a widely perceived demand. The second one, which includes the improvement of amenity and level of service of MRT stations, shows a demand specific to some social groups. It is clarified that those who have the second demand belong to a higher income group and thus, supposed to increase according to an increase of average income level. It is also necessary to set a clear benchmark of improvement. In our study, it was shown that when it takes over 20 minutes for access, people will not use the MRT. In addition, in the study area, the user s tolerable time for walking is at most 10 minutes. To ensure easy access within a benchmark of 10 minutes, establishment of walkways and other pedestrian facilities will be likely to be most effective. This policy is recommended as an extension of sidewalk and road clearing policy promoted by the Metro Manila Development Authority.

14 1421 a) Books and Books chapters REFERENCES Baker, F.B.(1992) Item Response Theory, Marcel Dekker. b) Journal papers Kenji DOI and Takashi AOKI (1999) Quantification of user s preference for improvement of railway stations considering human latent traits, Journal of the Japan Society of Civil Engineers, No.625, IV-44,15-27 Ryuji Nakamura, Shigeru Kashima (1991) LRT-mode choice characteristics in Metro Manila, Proceedings of Infrastructure Planning, Vol.14 (1), Ryuji Nakamura, Shigeru Kashima (1989) A study on LRT choice characteristics in Metro Manila, Proceedings of Infrastructure Planning, Vol.12, Bock,R.D(1972) Estimating item parameters and latent ability when response are scored in two or more categories, Psychnometorika, Vol.37, No.1. Abrahamowicz, M and Ramsay, J.O.(1992) Multi ategorical spline model for item response theory, Psychnometorika, Vol.57.