Designing Employee Shuttle Service for Employees of CBD Rodney Asinas Urban and Transport Planner, Senior Associate Ayala Land, Inc.

Previously presented at the 12th International Conference of the Eastern Asia Society for Transportation Studies (EASTS) in September 2017 at the Sheraton Hotel, Ho Chi Minh, Vietnam Table of Contents

• Introduction • Problem & Objectives • Hypothesis • Scope and Limitations • Methodology • Sample Size • Survey Results • Potential Routes • Summary & Recommendations INTRODUCTION

Estimated Number of Trips per Day

Modal Split in Makati CBD 0% 20% 40% 60% 80% 100%

Vehicles 67,369 7,735 Private Public

Year Pax 80,843 329,619

• Around 12.8 million person trips are made per day in Metro (JICA Dream Plan,2014) • Around 78% of road occupancy is taken up by private vehicles, while only transporting 31% of total person trips • In Makati CBD, road occupancy of private vehicles at Makati CBD goes up to 90% (ALI internal traffic study, 2008) PROBLEM:

 Due to worsening traffic conditions in , commuter and driving experience continue to deteriorate affecting employee productivity OBJECTIVE:  Identify a feasible alternative transportation modes that would be acceptable to the company, employee, and transport provider

o Understand demand side by • Origins and Destinations • Mode Preference analyzing current travel patterns • Trip Chain • Estimated Travel Demand • Willingness to Pay o Determine routes to be served and identify appropriate alternate • Based on demand, identify routes which will be served mode of transportation which will • Identify parameters which satisfy employee best serve both the company and preferences employees HYPOTHESIS:

 Numerous factors affect employees’ decision in choosing his/her way of travel : • Socio-economic • Travel preferences o Rank in the company o Convenience and o Gender Comfort o Travel Cost o Promptness o Seating • Geography-related o Cost o Location of residence o Frequency of trips o Travel time o Number of transfers SCOPE AND LIMITATION:

Study limited to Makati CBD employees. Specifically, employees of Ayala Group of Companies SAMPLE SIZE:

Ayala Group of Companies’ workforce totals to 48,996 employees. (Based on Ayala Corporation Integrated Report 2016)

These are distributed across Luzon, Visayas, and Mindanao. Assuming that around 5,000 works at Makati, sample size can be determined using the formula below:

Necessary Sample Size = (Z-score)2 * StdDev*(1-StdDev) / (margin of error)2 Assuming 99% confidence level, a .5 standard deviation and 5% confidence interval

Necessary Sample Size = (2.576)2 * .5*(.5) / (.05)2 = 663

At the minimum the study should have at least 663 samples. METHODOLOGY:

 Conducted online survey to Ayala Group of Companies: • Ayala Corp. • Ayala Land and subsidiaries • Makati Development Corp. • BPI & BFB • APEC Schools

 Survey included questions pertaining to: • Type and number of modes used per trip, travel cost • Location of residence • Gender • Rank in the company • Travel preferences • Are you willing to shift to this transport service? • How much are you willingness to pay for this new service? SURVEY RESULTS: SAMPLE SIZE & DISTRIBUTION

 2,119 samples DistributionGENDER of Samples by Gender Female Male

1% 2% 8% 7% 36% 21% 64%

58% 3%

Distribution RANKof Samples by Rank

Rank and File Middle Management Senior Management

Ayala Corp Ayala Land and Subsidiaries 2% Makati Development Corp. BPI & BFB Ayala Foundation APEC Schools 41% 57% HR Mall, Integreon SURVEY RESULTS: MODAL SPLIT

• 70-72% of the samples take public transport, 22-23% use private vehicles, 4- 5% use Taxi or TNVS SURVEY RESULTS: TRIP CHAIN

Chain Count UV Express 237 Number of Modes used per Trip Tricycles-UV Express 122 60%

Bus 103 50% PUJ 65 40% PUJ-UV Express 64 PUJ-Bus 58 30% Bus-PUJ 38 20% Tricycles-PUJ-UV Express 34 Percent Samples Percent of 10% Tricycles-PUJ 33 UV Express-Bus 33 0% 1 2 3 4 PUJ-PUJ 32 Number of Modes UV Express-PUJ 28 Tricycles-Bus-PUJ 20 Tricycles-Bus 19 • ~49% take two to four modes of transport to get MRT 3 18 to work / go home UV Express-Tricycles 18 UV Express-UV Express 17 PUJ-Bus-PUJ 17 • Tricycles and PUJs serve as feeder modes UV Express-MRT 3 16 Tricycles-PUJ-Bus 15 • Modes used for longer travel – UV Express or PUJ-LRT 1-Bus 14 Buses Bus-MRT 3 13 Bus-Bus 13 LRT 1-Bus 12 Tricycles 11 Average Travel Time Average Number of Transfers

• Shortest average travel time is ~40 minutes (Makati). Travel time gets longer as you get farther. Southern cities/municipalities have slightly shorter travel time than its northern counterparts due to expressways. • Number of transfers also slightly higher to cities/municipalities north of Metro Manila Average Private Transport Expense Average Public Transport Expense

• Public transport spend around <10 – 150 pesos per trip. • Private car users significantly spend more than public transport users due to fuel, parking fees • Car users residing in cities / municipalities south of Metro Manila also spend for toll fees Distribution of Employees According to Number of Employees Interested in Residence Location New Transport Service

• Concentration of Employees mostly in Metro Manila, particularly in and Manila • High potential demand in Metro Manila • As a municipality/city goes farther from MCBD, number of employees residing in it goes lower Percentage of Interested Employees to Distribution of Employees According to Total Employees Residing in Residence Location Municipality/City

• While there’s higher interest in the transport service due to sheer number, employees living in farther places has higher interest in transport service • Cities and municipalities outside Metro Manila have around 75-100% acceptance rate Logistic Regression Results for Public Transport Users Model 1 Model 2 Model 3 Variable Coefficient P>|z| Coefficient P>|z| Coefficient P>|z| • For public transport _cons 0.4561361 0.00 0.5100128 0.000 0.159161 0.538 users, travel time, Travel Time 0.0081518 0 0.0092967 0 0.0090755 0 travel expense, have Travel Expense 0.005948 0.012 0.0082489 0.001 0.0025522 0.001 Number of n/a -0.2633696 0.001 -0.2688841 0.001 positive correlation to Transfers them saying ‘yes’ to Gender n/a n/a 0.1734311 -1.27 Rank & File n/a n/a 0.566635 0.019 the new transport Manager n/a n/a 0.4555677 0.063 service • Number of transfers has a LR chi2 65.655 75.79 82.62 negative correlation Prob > chi2 0 0 0 Pseudo R2 0.0398 0.0460 0.0502

Logistic Regression Results for Private Vehicle Users Model 1 Model 2 Model 3 Variable • For private car users, Coefficient P>|z| Coefficient P>|z| Coefficient P>|z| _cons 0.6313662 0.028 0.5664508 0.080 -0.4127995 0.385 travel time and travel Travel Time 0.0085354 0.023 0.0086632 0.021 0.0081984 0.031 expense also has Travel Expense 0.0006788 0.340 0.006863 .336 0.0007618 0.302 positive correlation Gender n/a 0.0990884 0.665 .0876125 0.705 Rank & File n/a n/a 1.136808 .004 Manager n/a n/a 1.013808 0.015

LR chi2 7.66 7.85 15.45 Prob > chi2 0.0217 0.0493 0.0086 Pseudo R2 0.0156 0.0160 0.0315 Travel Preferences:

Factors important going to work Factors important going home 40% 40% 35% 35% 29% 30% 27% 30% 25% 25% 22% 20% 19% 20% 18% 20% 17% 16% 17% 14% 15% 15% 10% 10%

5% 2% 5% 1% 0% 0%

• Convenience and Comfort ranked first for both trips • For trips going to work, promptness ranked second (possibly to avoid tardiness) • For trips going home, assured seating is second priority • Reasonable cost ranked third for both trips Employees’ Willingness to Pay for a Better Service Willingness to Willingness to Pay – Average of Total Average Travel Time City/Municipality Pay – Public Private (Php) Fare (Php) (minutes) (Php) Quezon City 13 14 58 82-112 Makati City 13 7.5 22.5 38.5-65 Manila City 20 13 51 56-85 Parañaque City 18.4 15 64 54-84 City 15 10.7 51 64-94 City 11 10.7 43 51-81 Las Piñas City 13.3 10.3 73 67-97 City 8 11 43 42-72 Bacoor, Cavite 8 15.6 77 86-116 City 16 11.6 27 42-70 City 23.6 14.1 73 96-125 Caloocan City 8 14.7 71 93-123 Muntinlupa City 15.7 16.3 60 59-89 , Rizal 6.67 10 59 95-125 San Pedro, Laguna 6.67 6.67 88 84-114 City 20 4 70 100-130 Imus, Cavite 8 8 79 95-124 Valenzuela City 26.7 5 72 106-136 Malabon City 0 12 80 89-119 Dasmariñas, Cavite 6.67 10 100 112-142

• Private vehicle users tend to have higher willingness to pay for the provision of better transport service • Overall, employees are willing to pay ~20% more on top of their existing travel expense ALTERNATIVE TRANSPORT – POTENTIAL ROUTES

Trinoma

Cubao

Tikling/Ortigas Ext.

MCBD

ATC

Imus

Pacita • Considering other factors such as travel time, number of transfers, it is recommended that Trinoma – Makati CBD be the pilot route • Site also gives chance to employees living to the north of QC SUMMARY

IDENTIFY FEASIBLE ALTERNATIVE TRANSPORT MODE (Acceptable to the Company, Employee, Transport Provider)

1.1 Understand Travel Pattern Origins and Destinations 75% live in Metro Manila, 25% reside in Rizal, Cavite, Bulacan

Trip Chain 51% use one mode, 49% 2-4 modes

Mode Preference Bus and UV Express used for longer travel PUJs & Tricycles used as feeder modes Estimated Travel Demand 1,683 employees indicated interest (274 private car users) Proportion-wise, employees living in farther areas are generally more accepting (75-100% interest) Willingness to Pay Employees look for more convenient and comfortable mode of transport. Promptness and reasonable price are also desired

Employees are willing to pay 20% more on top of their existing travel expense 1.2 Determine Route and Identify Alternate Mode of Transport

• Trinoma – Makati to be the pilot route

• Must be convenient and comfortable, has assured seating, with reasonable transport cost.

• Two options were identified – Shuttle Service or Partnering with Transport Network Companies NEXT STEPS AND RECOMMENDATIONS

• Examine aspects on the financial side – which of the options are more financially viable for the employee, employer, and transport provider

• Study can be used as guideline for designing transport service and can be replicated for other CBDs / mixed use developments. However, it can still benefit from further analyses • Further examination of travel preference to pinpoint needs and wants of employees (per area) • Deeper statistical analysis to get better interpretation • Logistic Regression with interaction of variables • Contingent Valuation

• Should the pilot route become a success, proceed with the implementation of transport service for other areas THANK YOU!