LAND USE IMPACTS ON STATION ACCESS BEHAVIORS OF BANGKOK BUS 1 RAPID TRANSIT PASSENGERS 2 3 4 5 Saksith Chalermpong 6 Department of Civil Engineering, Faculty of Engineering, Chulalongkorn University 7 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand 8 Tel: +662-218-6460 Fax: +662-251-7304; Email: saksith.c@chula.ac.th 9 10 Apiwat Ratanawaraha 11 Department of Urban and Regional Planning, Faculty of Architecture, Chulalongkorn University 12 254 Phayathai Road, Patumwan, Bangkok 10330, Thailand 13 Tel: +662-218-4438 Email: rapiwat@gmail.com 14 15 16 Word count: 4,561 words text + 11 tables/figures x 250 words (each) = 7,311 words 17 18 19 20 21 22 Submission Date: 11/14/14 23

Chalermpong and Ratanawaraha 2 1 ABSTRACT 2 3 This paper provides empirical evidence on the ways in which commuters access the Bus Rapid 4 Transit (BRT) stations in Bangkok. We hypothesize that land use characteristics in areas near BRT 5 stations affect passenger’s travel behavior, particularly, the station-access portion of the trip. We 6 conducted interview surveys of BRT commuters and another survey of land use and transport 7 network characteristics around BRT stations. We find that the three most widely used modes of 8 access are walking, motorcycle taxi, and bus, with average access distances of 373, 1,040, and 9 7,076 meter respectively. In addition, we use the logistic regression technique to model walking 10 access mode choice as a function of land use characteristics of the area around the station where 11 passengers board the BRT, controlling for passengers’ socio-economic and trip characteristics. We 12 find that land use characteristics, including residential, commercial, service, retail, and financial 13 land use intensity in BRT station areas, affect passengers’ tendency to walk to BRT stations. The 14 evidence on the extent of the catchment area and the determinants on travel behaviors has 15 important implications for land use and transportation policies that aim to promote transit-oriented 16 development, particularly those that allow for greater building density around transit stations. 17 18 19 Keywords: Bus Rapid Transit, Transit Station Access, Bangkok, Land Use 20 21

Chalermpong and Ratanawaraha 3 INTRODUCTION 1 2 Bus rapid transit (BRT) is increasingly touted by transportation experts as an effective and feasible 3 alternative to rail transit systems. According to EMBARQ (1), as of October 2014, 186 cities 4 around the world operate 4,757 km of BRT systems, with as many as 31.7 million daily passenger 5 trips. As part of the concepts of Smart Growth and sustainable transportation, the access modes to 6 the BRT are usually assumed to be walking and bicycles. But this assumption may not hold true in 7 cities in developing countries where environmental and infrastructure conditions are not 8 conducive to walking and bicycling, and where alternative feeder modes, such as motorcycle taxis 9 and motor rickshaws, are prevalent. 10 11 Meanwhile, the ongoing expansion of mass transit systems in Bangkok, including a BRT, is 12 accompanied by building densification and changes in land use patterns around transit stations, 13 notably with the development of condominiums and commercial properties. As transit-oriented 14 development is taking shape, commuters’ travel behaviors are also adjusting to the new transport 15 infrastructure. This is applicable not only to those who recently moved to new condominiums but 16 also those who live close to transit stations and shifted commuting modes to rail transit. These 17 factors jointly contribute to the steady rise in rail transit ridership in Bangkok. 18 19 Transit Access Behavior and Catchment Area 20 Although it is evident that more people are using the transit systems in Bangkok, we still know 21 little about their travel behaviors; for instance, how and how far they travel to access the stations, 22 and what factors affect their travel behaviors. Such factors could be at the individual level, such as 23 socio-economic characteristics of the commuters themselves, or at the structural level, such as land 24 use and transporta network characteristics of the areas where they live and around the stations. 25 26 Rail Transit 27 A few studies have provided empirical evidence on how commuters access the transit systems in 28 Bangkok. Netipunya (2) examined the access behaviors of the Bangkok Transit System (BTS) 29 elevated rail, and found that 54 percent of passengers who accessed the station from within 2 km 30 did so by walking. However, this result might not be reliable due to the small sample size (190) and 31 the limited number of stations surveyed. Chalermpong and Wibowo (3) conducted a much larger 32 survey of both BTS and the Mass Rapid Transit (MRT) subway, with the sample size of 1,720, and 33 found that within the 2-km distance, the 37 percent of passengers accessed the stations by 34 walking. They also explored the variation in walking access share at different transit stations and 35 discussed how different land use conditions might be conducive to walking. However, they did not 36 provide evidence of specific effects of different land use types that were linked to walking access 37 behaviors. 38 39 Bus Rapid Transit 40 In addition to rail networks, Bangkok has developed the Bus Rapid Transit (BRT) to supplement 41 the overall transit system. The BRT has tremendous potential as a key instrument to promote 42 transit-oriented development, because it is much less expensive and quicker to develop than rail 43 transit systems. But it currently receives little attention from policy makers and researchers in 44 Thailand, so there is limited evidence related to the Bangkok BRT. In one of the few studies of 45 Bangkok BRT, Purahong (4), who conducted a small survey of passengers at three BRT stations, 46 found that the three most popular modes of access to the stations are walking, motorcycle taxi, and 47

Chalermpong and Ratanawaraha 4 public bus. Saneewong (5) conducted a survey of 111 households within 500 meter of BRT 1 stations, and analyzed travel behaviors of residents. She found that only 16.1 percent of the 2 residents used BRT regularly, and among these, most accessed the station by walking, followed by 3 bus. In these studies, neither author attempted to examine factors that affect the travel behaviors of 4 BRT users, or more specifically, whether land use patterns in the station areas affect such travel 5 behaviors. 6

While the evidence on the extent of the catchment area and the determents of the travel 7 behaviors has important implications for land use and transportation policies that aim to promote 8 transit-oriented development, particularly those that allow for greater development density around 9 transit stations, most empirical evidence currently available is from North America, and very little 10 from developing Asia. In this paper, we fill this research gap, by providing empirical evidence on 11 the ways in which commuters access the BRT stations in Bangkok, as well as the factors that affect 12 such behaviors. 13

The results of the paper could be compared to cities of similar conditions, such as Jakarta 14 where informal transport modes provide critical feeder services to the BRT system. It would also 15 be interesting to compare the catchment areas of the BRT system in a mode-rich city such as 16 Bangkok to cities in North America and South Africa where walking and bicyling are considered 17 the key access modes. 18

The following sections provide the background, research design and methodology, and 19 research findings. We conclude the paper with a discussion on the implications for urban 20 development policy, particularly the measures that aim to promote transit-oriented development. 21 22 23 BACKGROUND 24 25 Bangkok Public Transit Systems 26 Bangkok public transit systems consist of five dedicated right-of-way transit lines and 27 approximately 200 public buses and passenger vans services, carrying the total of approximately 28 2.5 million passenger-trips daily. The five transit lines, as illustrated in FIGURE 1, include two 29 elevated rail lines, one subway line, one elevated airport rail service, and one BRT line. TABLE 1 30 provides select key information about each transit system. 31 32 TABLE 1 Transit Ridership in Bangkok 33 34

Transit System (Operator) Number of Stations

Length (km)

Year of Opening

Average Weekday Ridership

Bangkok Transit System (BTSC) 34 30.95 1999 650,000 Mass Rapid Transit Authority (BMCL) 18 21 2004 240,000 Airport Rail Link (SRTET) 8 28.6 2009 47,000 Bangkok Bus Rapid Transit (KT) 12 15 2010 20,000

Source: Bangkok Metropolitan Administration (6). 35 36 Bangkok Bus Rapid Transit 37 The Bangkok BRT system began service in May 2010, serving 12 stations on a 15-km route along 38 a major thoroughfare in Central Bangkok to a suburban neighborhood. The Sathorn terminal 39 station, as shown in FIGURE 2, is an interchange station with the BTS Chong Nonsi station, 40 located near the Silom Central Business District. The other terminal station, Ratchaphruek, is also 41

Chalermpong and Ratanawaraha 5 an interchange station with the BTS extension’s Talat Phlu station, which began service in 1 February 2013. 2 3 Operator The BRT is operated by BMA’s holding enterprise Krungthep Thanakom, which 4 contracts out the operation to BTSC. 5 6 Fare The initial fare was 10-Baht flat ($0.33), and the initial daily ridership was around 10,000. In 7 April 2013, the fare was lowered to 5-Baht flat ($0.17), in an attempt to boost ridership, which 8 stood at approximately 16,000 at that time. The fare collection is integrated with the BTS smart 9 card system, but not the MRT subway or other public buses. 10 11 Ridership Currently, the average weekday ridership is about 20,000. FIGURE 3 shows the 12 average daily ridership of the BRT by stations in July 2013. (7) The ridership is greatest at Sathorn, 13 the terminal and interchange station with the BTS system, with an average weekday passenger of 14 6,800. The general trend is that the ridership declines with the distance away from Sathorn and 15 bottoms out at Rama IX Bridge Station, with an average weekday passenger of 500. The ridership 16 rises again as we move toward Ratchapruek, the other terminal station with an interchange with the 17 BTS, with an average weekday passenger of about 2,300. The BRT is more intensively utilized on 18 weekdays than on weekends, with the ridership on weekdays more than doubled those on 19 weekends at most stations. 20 21 22

Chalermpong and Ratanawaraha 6

1 2 FIGURE 1 Bangkok public transit systems. (Source: Globe-trotter - Own work. Licensed 3 under Creative Commons Attribution-Share Alike 3.0 via Wikimedia Commons - 4 http://commons.wikimedia.org/wiki/File:Bangkok-transit-map.svg#mediaviewer/File:Bang5 kok-transit-map.svg) 6 7

Chalermpong and Ratanawaraha 7

1 FIGURE 2 Bangkok BRT Sathorn Terminal Station 2 (Source: "Sathorn Station (Bangkok BRT)" by Sry85. Licensed under Creative Commons 3 Attribution-Share Alike 3.0 via Wikimedia Commons - 4 http://commons.wikimedia.org/wiki/File:Sathorn_Station_(Bangkok_BRT).jpg#mediaview5 er/File:Sathorn_Station_(Bangkok_BRT).jpg)) 6 7 8 9

Chalermpong and Ratanawaraha 8

1 FIGURE 3 Bangkok BRT ridership. (Source: Krungthep Thanakom (7)) 2 3 4 Land Use Characteristics of the Study Area The BRT corridor passes through mixed use 5 neighborhoods with the terminal station located in the city’s main financial district. The next four 6 stations are located along Narathiwas Road, which cuts through primarily residential 7 neighborhoods. The BRT route then turns onto Rama III Road, 6-lane major arterial that runs 8 parallel to the Chao Phraya River. Six stations are located along this stretch, approximately half of 9 the entire length of the route. Land use in this section is more commercial, with some residential 10 development near the river front and in the middle section of the route. 11

The Yannawa district, where much of the middle section of the BRT route is located, was 12 originally farmlands, but experienced growth in industrial development in the 1970s and 80s, 13 owing to its easy access to river transportation. In 1990s, the area was envisioned to be the new 14 CBD of Bangkok. The BMA invested heavily on road construction in the area, including Rama III 15 Road, three flyover bridges, an expressway, and three bridges over the Chao Phraya River. Thanks 16 to these investments and development incentives provided by the city government, commercial 17 properties began to develop rapidly in the area in the late 1990s. However, because of the financial 18 crisis in 1997, many of the projects were delayed or canceled. 19

Despite failing to become the new CBD, Yannawa and Rama III still attract new 20 development, primarily residential, thanks to the proximity to the river and open space, which 21 appeal to residents in search of green areas close to the city. However, before the BRT, there was a 22 major lack of public transit service. Dependency on private vehicle is thus a norm. But in early 23 2000s, traffic congestion on Narathiwas and Rama III Roads were relatively moderate, compared 24 with other main roads in Bangkok, thanks to aggressive investments in roads in the 1990s. It 25 seemed to be the only politically feasible corridor where an exclusive bus lane can be introduced. 26 The BRT project was thus conceived with little consideration about land use in the area where it 27 would serve. 28 29 30

0

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Chalermpong and Ratanawaraha 9 RESEARCH QUESTION AND HYPOTHESIS 1 2 Past research shows that urban environment, including not only land use types, but also 3 transportation network characterisitics and pedestrian amenities, play an important role in 4 passenger’s decision to use non-motorized modes, as opposed to motorized modes. 5 Transit-Oriented Development (TOD) policies, therefore, involve shaping land use and 6 transportation characteristics in transit station areas, so that they are conducive to walking, cycling 7 and transit use. However, in the case of Bangkok, road and transportation networks cannot be 8 changed easily, because of difficulties in land acquisition due to public opposition. In this study, 9 we choose to focus on the impact of land use on travel behaviors. Specifcally, we ask whether and 10 how land use characteristics in BRT station areas affect passenger’s travel behavior, particularly, 11 the station-access portion of the trip. 12

To test the hypothesis, we use two sources of empirical data. First, we conducted an 13 interview survey of BRT passengers in order to obtain information about their socio-economic and 14 trip characteristics. The second source is from a survey of land use and transport network 15 characteristics within the radius of 500 m of BRT stations. The BRT access mode choice is then 16 modeled as a function of land use and transport network characteristics of the area around the 17 station where passengers boarded the BRT, controlling for their socio-economic and trip 18 characteristics. 19 20 21 DATA COLLECTION 22 23 Passenger Survey Data 24 We conducted interview surveys of passengers at all 12 BRT stations during the morning peak 25 hours on weekdays between November 14 to 29, 2013 and June 15 to 19, 2014. The first survey 26 was conducted during the period of political unrests in Bangkok, where many main streets were 27 closed, leading to unusually high ridership on rail transit systems. The second survey was 28 conducted after the military coup in May 2014, when the political situation became more quiet, 29 and normal commuting behaviors resumed. Throughout the survey periods, the BRT ridership 30 stayed relatively stable, indicating that the BRT was not a viable alternative for commuters along 31 the BRT corridor even with the street closing. Also, because only certain main streets in the city 32 center were closed while side streets were not, the feeder modes were still able to transport 33 commuters to the rail and BRT systems in most areas. This means the closing of main streets did 34 not have a significant impact on the mode of access to the BRT and on the validity of the data we 35 collected. 36

In both parts of the survey, passengers were randomly selected and interviewed on the 37 station platform about the details of their access trip to the station and their socio-economic 38 characteristics. The total sample size is 829, which consists of 440 and 389 individual BRT 39 passengers, from the first and second surveys, respectively. Descriptive statistics of the survey data 40 are provided in TABLE 2 and FIGURE 4. 41 42 43 44 45 46 47

Chalermpong and Ratanawaraha 10 TABLE 2 Descriptive Statistics of BRT Passenger Survey Data 1 2 Variables Mean S.D. Minimum Maximum Socio-economic Age (year) 30.46 10.55 12 75 Household size (person) 3.29 1.90 1 10 Income (Baht/month) 24649.85 22985.91 1500 250000 Household income (Baht/month) 76406.02 91430.23 6000 1000000 Transportation-related Household motorcycle ownership 0.19 0.43 0 3 Household car ownership 0.48 0.69 0 6 Trip frequency 9.74 1.93 4 14 Access distance (meter) 3759.81 6701.58 5 35000 Access time (minute) 17.37 20.00 1 120 Access cost (Baht), paid passengers only 18.01 15.21 5 120 Egress distance (meter) 255.86 317.26 10 4000 Total trip time (minute) 44.70 24.18 5 120

3

Chalermpong and Ratanawaraha 11

1

2

3 4 FIGURE 4 Characteristics of surveyed BRT passengers 5 6 7 Land Use Data 8 We acquired land use data for the 12 BRT station areas, from the survey by Yongyat (8). The land 9 use data consist of the number of units of real-estate properties of different types that are located 10 within 500-meter radius of BRT stations. Details about survey methodology can be found in 11 Yongyat (9). The summary of land use data is provided in TABLE 3. As discussed in the previous 12 section, the BRT corridor consists mainly of residential areas, and this is reflected in the large 13 average number of housing units in station areas. Also, there is high concentration of office and 14 service-related properties at some stations, notably Sathorn, which is near the Silom CBD. As with 15

23%

75%

2%

Marital Status

Married

Single

Widowed/divorced

73%

4% 1% 4%

18%

Occupation

Employee

Government employee

Others

Business owner

Student

82%

15%

3%

Trip purpose

Work

Education

Others

66%

34%

Gender

Female

Male

2%

12%

15%

55%

16%

Education

Below highschool

Highschool

Bachelor student

Bachelor's degree

Higher thanbachelor's

18%

26%

15%

30%

11%

Type of residence

Condominium

Dormitory

Shophouse

Single familydetached

Townhouse

Chalermpong and Ratanawaraha 12 typical urban development in Thailand, the mixed land use is common in most station areas, where 1 residential, commercial, and service uses coexist. In some station areas, even industrial properties 2 are present, which was a legacy of development around of Chaopraya River ports. 3 4 5 TABLE 3 Summary of Land Use Data within 500 meter of BRT Station Areas 6 7 Land Use Type Average S.D. Minimum Maximum Number of Properties

Single-family detached 81.08 59.70 13 211 Multi-family housing 41.25 27.98 6 93 Office buildings 13.42 10.96 3 42 Service (gas station, etc.) 6.50 4.08 0 16 Restaurants 2.17 2.98 0 9 Financial (bank, etc.) 1.42 1.62 0 6 Industrial (factory, warehouse, etc.) 1.17 0.83 0 3 Retail shops 0.92 1.24 0 4 Shopping malls 0.42 0.67 0 2

8 Note: These are the number of building units that belong to each land use type. For example, a condominium with 9 several dwelling units is counted as one in the multi-family housing category. An office building with several business 10 units is also counted as one in the office building category. A stand-alone restaurant or shop is counted as one in its 11 respective category. A building with multiple uses, which is quite rare in the BRT corridor, is counted in the category 12 of its most dominant use. 13 14 15 RESEARCH FINDINGS 16 17 Access Mode Share and Distance 18 TABLE 4 shows the access mode share in the sample of BRT passengers. The majority (94%) of 19 the passengers accessed the BRT by one access mode, whereas less than 7% did so by using more 20 than one access mode. The four access modes with the largest share include walking (42%), 21 motorcycle taxi (20%), bus (9%), and car drop-off (9%). The combined share of all other modes is 22 less than 20%. TABLE 4 shows the statistics of access distance by modes. As expected, the 23 average walk access distance, at 373m, is significantly shorter than all other modes. This is 24 followed by bicycle and motorcycle taxi, which have average access distances of 843 m and 1,040 25 m respectively. The average access distances by motorized modes range from 2.5 km for 26 motorcycle drop-off to almost 20 km for public vans. 27

TABLE 5 shows that there is a wide range of walk access by station. This could be 28 because different stations are surrounded by different patterns of land use, and experience different 29 levels of redevelopment. As a result, the patterns of access modes are different. The share of walk 30 access is evidently low for terminal stations, particularly the outer end of the line where public 31 buses account for more than half of the mode share. However, in general, the feeder bus mode 32 share is small. This is primarily because there are very few bus routes that serve as a feeder mode 33 to the BRT, most of which serve only the terminal stations. 34 35 36 37

Chalermpong and Ratanawaraha 13 TABLE 4 Access Mode Share and Average Access Distance 1 2

Access mode Percent Average Access Distance (m)

S.D. of Access Distance (m)

One access mode 93.61 3,177.10 6,084.06 Non-motorized modes

Walking 42.05 373.35 283.70 Bicycle 0.84 842.86 723.09

Public modes Motorcycle taxi 19.88 1,039.63 894.61 Bus 9.16 7,076.32 5,423.13 Songtaew 3.01 2,682.00 3,718.73 Rail transit 1.33 6,409.09 3,679.80 Van 0.96 19,968.75 11,877.68 Taxi 0.48 8,250.00 7,804.91

Private motorized modes Car drop off 9.16 10,623.67 9,217.58 Motorcycle drop off 3.25 2,538.46 3,567.64 Self-driven car 2.77 15,369.57 10,714.49 Self-driven motorcycle 0.72 11,333.33 8,041.56

Two or more access mode transfers 6.39 12,433.29 9,143.46 3 4 TABLE 5 Access Mode Share by Station 5 6

Station

Sample

size

Non-motorized Public Private

Walk Bi- cycle

Motor- cycle Taxi Bus

Song- taew

Rail Transit Van Taxi

Car drop off

Motor- cycle drop off

Private car

Motor- cycle

Arkhan Songkhro 52 73.08 1.92 1.92 0 0 0 0 1.92 7.69 3.85 9.62 0 Rama III Bridge 80 70 0 8.75 10 0 0 0 0 7.5 3.75 0 0 Charoen Rath 50 68 2 8 4 0 0 0 0 6 4 6 2 Technic Krungthep 73 58.9 1.37 16.44 6.85 0 0 0 1.37 4.11 1.37 8.22 1.37

Wat Pariwas 58 53.45 1.72 32.76 0 3.45 0 0 0 3.45 1.72 1.72 1.72 Rama IX Bridge 49 51.02 0 28.57 2.04 0 0 0 0 8.16 8.16 2.04 0 Wat Dorkmai 61 39.34 1.64 44.26 1.64 4.92 0 0 0 3.28 4.92 0 0

Wat Darn 60 38.33 0 30 1.67 6.67 0 0 0 18.33 1.67 1.67 1.67

Thanon Chan 81 34.57 0 34.57 7.41 7.41 0 0 0 11.11 3.7 1.23 0

Sathorn 48 31.25 0 10.42 4.17 2.08 20.83 12.5 0 16.67 2.08 0 0 Nara-Rama III 76 28.95 2.63 26.32 3.95 1.32 0 2.63 1.32 25 0 6.58 1.32

Ratchpruek 78 8.97 0 11.54 56.41 7.69 1.28 0 0 6.41 6.41 0 1.28

7 8 9 10

Chalermpong and Ratanawaraha 14 Distribution of Access Distance 1 FIGURE 5 shows the cumulative distribution of access distance of the four most wisedly used 2 modes. Since access distances by walking and motorcycle taxi are of different order of magnitude 3 from those by bus and car drop-off, two cumulative plots were made for the sake of clarity. As 4 shown in FIGURE 5(a), the 85th percentile of walking access distances is 600 m, comparatively 5 short in relation to the result from a recent BRT study in China (9), in which the distance was found 6 to be about 900 m. This could be because of the popularity of motorcycle taxis as an access mode 7 in Thailand. FIGURE 3(b) shows that the 85th of access distance by motorcycle taxi is 1,700 m, 8 which is shorter than the 85th percentile of walking access distance to certain types of BRT station 9 that was found in the China’s study. 10 11 12

13

14 15 FIGURE 5 Cumulative distribution of access distance by modes 16

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Chalermpong and Ratanawaraha 15

The distributions of access distances by bus and car drop-off are quite different from those 1 by walking and motorcycle taxis, as shown in FIGURE 5(b). The 85th percentiles of access 2 distances are approximately 15 km and 20 km for bus and car drop-off, respectively. These 3 findings show that a substantial share of BRT passengers, almost 20% of the current users, are 4 willing to travel great distance to use the BRT. This is probably due to the fact that rapid transit 5 service coverage is still lacking in many areas of Bangkok, particularly in the south and western 6 part of the city. 7 8 Logistic Regression Analysis 9 We hypothesize that the choice of walking access to transit stations depends on land use 10 characteristics the station areas. To test this hypothesis, we estimate the logistic regression of the 11 probability that a passenger walks to access a transit station as a function of passengers’ 12 characteristics and land use charateristics of the station areas. The specification of logistic 13 regression is shown in equation (1). 14 15

LγXβ +=

− W

W

PP

1ln (1) 16

17 where WP is the probability that a passenger walks to access the BRT Station, X is a vector of 18 passenger characteristics, including socio-economic, housing, and transportation-related 19 characteristics, L is a vector of land use characteristics of station areas, β and γ are vectors of 20 logistic regression coefficients. 21

Since the maximum walking access distance in our sample is 2 km, we selected only cases 22 in the sample where BRT passengers traveled, by walking or other modes, from within 2 23 kilometers of BRT stations. This is to ensure that walking is possible for all individuals in the 24 sample that is used for model estimation. TABLE 6 shows the results of two specifications of 25 logistic regressions. In the first specification, we include only socio-economic, housing, and 26 transportation-related characteristics of BRT passengers. Although we tested a number of 27 variables, in this specification, the coefficient estimates for only some of them are statistically 28 significant, and these are reported in TABLE 6. The pseudo R2 for this specification is 0.3621, 29 implying similar level of goodness of fit compared with other similar studies. (2, 3) 30

The marginal effects of explanatory variables, evaluated at the sample mean, are also 31 reported in TABLE 6. For example, according to the no-land use logistic model, a 1000-Baht 32 increase in monthly income would reduce the probability of walking access by 0.34 percent and a 33 100-meter increase in access distance would reduce the probability of walking access by 10.22 34 percent. The probability of a male passenger would walk is 24.19 percent greater than a female 35 passenger, possibly due to the security concerns among female passengers. The probability that 36 passengers who live with relatives would walk is 21.17 lower than that of passengers who own or 37 rent a residence for themselves, probably due to the fact that the latter group of passengers might 38 choose a residence location that is more convenient to walk to the BRT station. Passengers in 39 households that own at least one car have 8.88% higher probability of walking than those without 40 a car. On the other hand, those in households that own at least one motorcycle have 10.97% lower 41 than those without a motorcycle. One possible explanation for these inconsistent results is that 42 members of households with motorcycles can easily get a ride to the station, while those with cars 43 cannot, due to the difficulties in maneuvering the car in small alleys. 44 45

Chalermpong and Ratanawaraha 16 TABLE 6 Logistic Regression Results and Marginal Effects 1 2

Variable No land use With land use

Coefficient p-value Marginal Effect Coefficient p-value Marginal

Effect Socio-economic Age 0.0197 0.1730 0.0049 0.0270 0.0750 0.0066 Male dummy 0.9774 0.0000 0.2419 1.1034 0.0000 0.2704 Monthly income ('000 B) -0.0139 0.0150 -0.0034 -0.0133 0.0380 -0.0033 Housing Living with relative dummy -0.8555 0.0120 -0.2117 -0.6922 0.0610 -0.1697 Transportation-related Access distance ('00 m) -0.4132 0.0000 -0.1022 -0.4418 0.0000 -0.1083 Household car ownership 0.3589 0.0960 0.0888 0.3883 0.0880 0.0952 Household motorcycle ownership -0.4433 0.1050 -0.1097 -0.4961 0.1000 -0.1216 Land use Number of single family houses 0.0107 0.0650 0.0026 Number of multi-family houses -0.0311 0.0300 -0.0076 Number of office buildings 0.1716 0.0000 0.0421 Number of service stores -0.7314 0.0000 -0.1793 Number of retail shops 1.1332 0.0320 0.2778 Number of commercial buildings -1.5166 0.0130 -0.3717 Number of shopping malls 1.5308 0.0140 0.3752 Number of restaurants 0.2048 0.0440 0.0502 Number of industrial buidlings 1.4782 0.0010 0.3623 Constant 2.2694 0.0000 1.7308 0.0270 Number of observations 500 494 Pseudo R2 0.3621 0.4219 LL(beta) -217.1750 -194.007 LL(0) -340.4647 -335.577

3 4

The second specification of our logistic regression includes land use characteristics of 5 station areas, in addition to passengers’ characteristics. With the inclusion of land use variables, the 6 pseudo R2 for this specification improves to 0.4219. All land use variables are statistically 7 significant at the 0.05 level, implying a critical link between land use and walking access behavior. 8 We also perform the Likelihood Ratio Test (LRT) to test the validity of the no-land use 9 specification; i.e., one with coefficients for nine land use variables restricted to zero, versus the 10 with-land use, or unrestricted, specification. The test statistic for the null hypothesis that the 11 restrictions are true is distributed Chi-squared with 9 degrees of freedom and can be computed as 12 follows: 13 14

67.2134.46))007.194(175.217(2)(2 29,01.0 =>=−−−−=−− χUR LLLL 15

16 Since the computed test statistic exceeds the critical value, we can reject the no-land use 17

Chalermpong and Ratanawaraha 17 specification at the 0.01 level of significance. 1

As with the results from the no-land use specification, the marginal effects of various 2 explanatory variables can be calculated based on the sample mean. The marginal effects of 3 passengers’ characteristics in the with-land use specification do not differ markedly from those in 4 the no-land use specification, as shown in TABLE 6. 5

As for the effects of land use, the marginal effects of different land use types differ 6 substantially, due to the varying number of existing properties with different land-use types. 7 Because of the relatively large number of properties in housing and office categories, the marginals 8 of these variables are somewhat small. The results imply that a marginal increase in the number of 9 single family houses in the station area would increase the probability of walking access by 0.26 10 percent, but the corresponding increase in the number of multi-family houses would reduce the 11 probability by 0.76 percent. A unit increase in the number of office building is associated with a 12 4.21 percent increase in the probability of walking access. 13

As for property types with fewer existing units in station areas, the marginal effects are 14 somewhat larger than those discussed above. For example, a marginal increase in the number of 15 retail shops and shopping malls increases the probability of walking access by 27.78 and 37.52 16 percent, respectively, whereas the corresponding increase in the number of service stores and 17 financial services reduce the probability by 17.93 and 37.17 percent, respectively. One unexpected 18 finding is that industrial land use is associated with higher probability of walking access. A unit 19 increase in the number of industrial properties increases the probability of walking access by 36.23 20 percent, while the corresponding increase in the number of restaurants increases the probability by 21 only 5.02 percent. 22 23 24 CONCLUSIONS AND POLICY IMPLICATIONS 25 26 In this paper, we investigate the relationship between station access behaviors of Bangkok BRT 27 passengers and land use characteristics of BRT station areas. We analyzed the access behavior data 28 and found that the three most widely-used modes of access to BRT stations in Bangkok are 29 walking, motorcycle taxi, and bus respectively. The average distance traveled per mode also 30 increases in that order. Using the land use data from a field survey, we estimated the logistic 31 regression model of the walking access probability as a function of land use characteristics, 32 controlling for passenger’s socio-economic characteristics. The modeling results reveal a critical 33 link between land use and walking access to BRT stations. Based on the evidence regarding access 34 mode share and average access distance, we conclude that the catchment area for a transit station 35 depends on the types and availability of feeder modes in that area. We also conclude that land use 36 intensity in BRT station areas affects the probability of walking access to BRT stations. 37 38 Policy Implications 39 40 The research findings have a few important implications for urban development policies in 41 Bangkok, and possibly elsewhere. The extent of the catchment area of the BRT system, as well as 42 the structural effects of land use characteristics on travel behaviors, provides a quantitative basis 43 for designing an incentive measure for a TOD policy. The 2013 Bangkok Comprehensive Plan 44 allows additional density for redential and commercial development projects that are located 45 within a radius of 500 m from rail transit stations. Our findings may be used to determine a more 46

Chalermpong and Ratanawaraha 18 appropriate radius for allowing additional density of new buildings around BRT stations in the 1 future. 2

Our findings also suggest that different transit stations have different levels of TOD 3 potential and conditions. This means different types of stations require different policy measures to 4 promote urban development. Moreover, the evidence on access mode shares can also be used to 5 design appropriate facilities around transit stations, as well as network planning for feeder service 6 systems. The evidence on the access distance of access modes also indicates that the TOD policy 7 for Bangkok has to be different from other cities in which the importance of walking and bicycles 8 as the feeder system is stressed. Motorcycle taxis play a prominent role in providing access for 9 BRT and other transit users in this city. This suggests that the TOD policy has to include such an 10 informal, but important, mode of transport in the future transport plan. Such a plan should also 11 include rationalization of bus routes so that they provide better feeder access to the BRT system. 12

In terms of future research, other types of models could be adopted to analyze the data and 13 obtain results that could be compared to those from the single-choice model adopted in this paper. 14

15 16

ACKNOWLEDGMENTS 17 18 The authors thank the Rockefeller Foundation for financial support and Ponlachat Yongyat for 19 helping with the surveys. 20 21

22 REFERENCES 23 24 1. EMBARQ. Global BRT Data. BRTdata.org Accessed November 3, 2014. 25 2. Netipunya, P. Transit Station Accessibility: A Case Study of Commutures in 26

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3. Chalermpong, S. and S. S. Wibowo. Transit Station Access Trips and Factors 29 Affecting Propensity to Walk to Transit Stations in Bangkok, Thailand. Journal of 30 the Eastern Asia Society for Transportation Studies, No. 7, 2007, pp. 1806–1819. 31

4. Purahong, K. Access Improvement for Bus Rapid Transit (BRT) Stations Using 32 Non-motorized Transportation in Yan Nawa District, Bangkok. (In Thai) 33 Unpublished Master’s Thesis. Division of Urban and Environmental Planning, 34 Faculty of Architecture, Kasetsart University, 2011. 35

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6. Statistics Book 2013. Bangkok Metropolitan Admistration. Strategy and Evaluation 39 Department office.bangkok.go.th/pipd/07Stat(Th)/Stat_57_6M/Stat_Detail.htm 40 Accessed July 15, 2014. 41

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