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2 | P a g e

CONTENTS

Page

Summary 3

Acknowledgements 3

1.0 Introduction 4

2.0 Objectives of the Study 5

3.0 Methodology 5

3.1 Field Walkability Survey 5

3.2 Selection of field walkability survey areas 5

3.3 Pedestrian Interview Survey 6

4.0 Data Collection and Analysis 7

5.0 Results and Discussion 9

6.0 Conclusion 18

7.0 References 19

8.0 ANNEXURES

i. Field Walkability Survey Form 21

ii. Field Survey Data Collection Guidelines 22

iii. Field Walkability Survey Area Maps 38

iv. Pedestrian Preference Survey Forms (English & Chinese) 62

v. Results of the Pedestrian Preference Survey -Mean Test

(by Social economic profile) 64

vi. Results of the Pedestrian Preference Survey- ANOVA by

Groups 113

vii. Results of the Pedestrian Preference Survey- Traffic

Mode Count Frequency 141

viii. Results of the Pedestrian Preference Survey- Single mode

of transport (walking) 180

ix. Results of the Pedestrian Preference Survey- Frequency

Analysis by Age Groups 190

x. Results of the Pedestrian Preference Survey- Frequency

Analysis by Household Income 200

SUMMARY

A walkability survey was conducted in Hong Kong as a first step towards helping city planners

understand scope and extent of existing pedestrian conditions and to identify specific pedestrian-

related shortcomings. The methodology for the survey was taken from The Global Walkability

Index (GWI) and Asian Development Bank/ Clean Air for Asian Cities (CAI-Asia) and improved

slightly to suit the local situation in Hong Kong.

It is found that very few elderly (>60 year old) walk from home for their daily travel and not willing

to walk long distance to access a transport. More than fifty percentage of people are satisfied with

the existing pedestrian facilities in the city and those who are not happy feel the need of

improvements in street lighting; clean, weather proof and wider foot paths; reducing road traffic

and speed; removal of obstacles along the walking paths and more crossing points. Elderly prefers

to have more ground level crossings as they do not prefer to walk either subways or elevated

walkways and are not willing to walk long distance to access the crossing points. They further

prefer to have less vehicle traffic on the roads that makes them feel safer and easier to cross the

road.

Among the nine variables that were evaluated in the field observational survey, walkways in

Commercial areas have the best infrastructures and level of service, including provision of facilities

for disables. Apart from commercial areas, all other surveyed areas scored very low in the provision

of facilities for disables. There are plenty rooms for improvements in this aspect in majority areas

of Hong Kong.

ACKNOWLEDGEMENTS

This study is supported by the Hong Kong Polytechnic University under Clean Air and Blue Skies

Project- Phase II, Clean Air Initiatives for Asian Cities (CAI-Asia). We would like to extend our

sincere gratitude to Christine Lee for her immense support from the very beginning of the study to

the end. We also like to appreciate Bert Fabian, Glynda Bathan and all the members from Clean

Air Initiatives for Asian Cities (CAI-Asia). Lastly, a special thanks to the students of Polytechnic

University for conducting the surveys.

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1.0 INTRODUCTION

In the conventional transportation planning practices suggest that personal motor vehicle travel is

far more important than walking, representing about fifty times as many person-miles as non-

motorized travel. From a conventional planning perspective, walking (the activity) is a minor mode

of travel, and walkability deserves only modest public support. However with the rapid urban air

pollution, in modern sustainable mobility management strategies walking is becoming a major

green transportation mode among all the developed and developing countries. The many research

studies, found that Social and physical environmental factors are influence and correlates with

walking behaviors of the people. Walking is the physical activity behavior that is currently the main

focus of environmental and policy initiatives in public health (Owen et al, 2004).

Different agencies and personnel have developed several methodologies to assess walkability in

locations and cities during past decades. But due to lack of relevant data, those indexes did not able

to capture the issues related to pedestrian infrastructures (Eva, et al, 2007). This GWI was

developed by Holly Krambeck, a Master‟s Degree Candidate, of Massachusetts Institute of

Technology and sponsored by the World Bank. The CAI ASIA Center, Philippines initiated this

assessment of GWI among the Asian cities during last few years. So far, this GWI has been

conducted as a pilot studies in the Asian cities of Karachchi, Bangkok, Manila, etc. A pilot study

was carried out prior to the actual surveys, and we made some improvements in the original survey

methodologies in order to suit the local situation and with the objective of future cross country

comparisons. In this end we selected the GWI methodology to assess walkability related issues in

the major cities of Hong Kong. The GWI methodology comprises mainly three components,

namely the Field Walkability Survey, the Pedestrian Interview Survey and the

Government/Stakeholder Survey. However only the Field Walkability Survey and the

Government/Stakeholder Survey results will use to calculate GWI and Pedestrian Interview Survey

is conducted to find out the overall perception of Hong Kong pedestrian facilities, travel behaviors

with socio economic backgrounds and their opinions and expectations about the development of

existing pedestrian facilities.

The „walkability‟ of a community may be conceptualized as the extent to which characteristics of

the built environment and land use may or may not be conducive to residents in the area walking for

either leisure, exercise or recreation, to access services, or to travel to work (Eva et al, 2007). There

are many definitions and ways to consider “walkability”. It can be simply define as the overall

support for pedestrian travel in an area. But, although a significant number of trips are made by

foot in developing cities, pedestrian infrastructure, amenities, and services are often neglected in

municipal planning and budgets (Fang 2005). Because the most developing countries cities do not

make pedestrian planning a priority and there are few incentives for them to do so. Therefore the

major rationale behind the walkability is assessment of the quality of the walking facilities available

in the cities. In this regard the Walkability Index comprises of three components: safety and

security, convenience, and degree of policy support. The expectations from these components are to

determine the relative safety and security of the walking environment, to reflect the relative

convenience and attractiveness of the pedestrian network and to find out the degree to which the

municipal government or policy supports improvements in pedestrian infrastructure and related

services accordingly.

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2.0 OBJECTIVES OF THE STUDY

The main objective of the conducting the walkability index survey in Hong Kong is to identify

specific pedestrian-related shortcomings, and recommendations for next steps to improve pedestrian

conditions and provide city officials with an incentive to address walkability issues. The Global

Walkability Index (GWI) is a comparative study which to rank cities across the world based on the

safety, security, and convenience of their pedestrian environments that helping city planners

understand the scope and extent of local pedestrian conditions relative to other cities. Therefore this

would be a positive step towards improving the quality of the pedestrian environment.

Specifically, the study aims to:

1. Generate awareness of walkability as an important issue in developing cities;

2. Help city planners understand scope and extent of local pedestrian conditions, relative to other

cities.

3. Understand pedestrian opinion on existing pedestrian facilities in the city.

3.0 METHODOLOGY

3.1 Field Walkability Survey

After studying of the Global Walkability Index (GWI) development report of Holly Krambeck, CAI

ASIA/ADB and World Bank guidelines on walkability surveys we conducted 5-6 pilot field surveys

in selected stretches (Whampoa Garden, Nathan Street, etc). The main objective of this survey was

got familiarized and to do field testing of the ratings system provided by CAI ASIA/ADB and

World Bank for different levels of services (LOS) in pedestrian walkways (Annex1) prior to the

actual survey began.

According to the actual field observations and experience obtained through the pilot surveys it was

decided to change the field survey rating descriptions and examples to well suit with the local

condition in Hong Kong. The Hong Kong field walkability survey rating description was developed

considering both of the CAIASIA/ADB and World Bank rating description and no any significant

changes were made and used same field walkability suvey form for the data collection (Annex 1 &

2).

3.2 Selection of field walkability survey areas

According to the GWI guidelines the field observational surveys are to be carried out in the areas

such as commercial, residential, educational, public transport terminals etc. However, in Hong

Kong has mixed land use types and difficult to demarcate as commercial, residential, educational

center. Therefore to have a good representation ten (10) biggest centers of attraction in six types of

land use mixes in urban areas like housing state, educational center, public transport terminals were

6 | P a g e

identified and the most popular commuting pedestrian routes at each of these ten locations were

selected. At least two routes at each location were surveyed.

The centers and the survey routes were then traced out using Google map for reference (Annex 2).

The pilot field survey was conducted in the selected areas prior to the real survey to find out if the

routes selected from the map represent the actual situation. After the pilot survey, some routes

which were not often used by the pedestrian were discarded and selected another most commuting

route for the survey. Similar changes were done for the other areas as well. The students from

Polytechnic University conducted survey in ten areas which were later categorized into six different

area types. The following table 1 shows the name of the top ten centers of attraction and the area

type.

Table 1: Field observational surveys areas

S.N. Name of the Area Area Type

1 Whampoa Garden Residential Area

2 Parc Oasis

6 Hong Kong cultural center Commercial Area

7 Hong Kong Convention and Exhibition Center

8 Kwung Tong Industrial Area

3 Ladies‟s Street Shopping Area

4 Fa Yuen Street

5 Temple Street

9 Hong Kong Central Library Commercial Educational Area

10 Baptist University Residential Educational Area

3.3 Pedestrian Interview Survey

Interviewer administrative questionnaire survey was carried out with random sampling for 1029

students/workers at selected busy streets to identify the pedestrian preference in Hong Kong. A

questionnaire was designed to find out the overall perception of Hong Kong pedestrian facilities

and travel habit. Demographic information was also ascertained for statistical analysis purposes.

A pilot study was carried out in the Polytechnic University premises using CAI ASIA/ADB

questionnaire prior to the actual survey, and necessary changes in the questionnaire were made

accordingly to suite to the local situation. The questionnaire was first written in English and later

translated to Chinese (Annex 3). Interviewers distributed the questionnaires and conducted face to

face interviews for two weeks from 16th to 30th January 2010 at selected location. The following

table 2 shows the work schedule and venue of the pedestrian interview survey.

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Table 2: Pedestrian interview work schedule

4.0 DATA COLLECTION AND ANALYSIS

The pedestrian interview survey involves designing a questionnaire to find out the people‟s

perception of pedestrian facilities. The survey, was targeted the workers and students as potential

interviewees. By reference to the statistical report (Hong Kong Census and Statistics Department

annual reports 2009), there were 3, 497, 000 active workers and 478, 173 students. We decided to

use simple random sampling method for the survey. In pilot study, 48 samples were obtained and

the maximum variance of questions in the questionnaire was 1.2642. After calculation, around 1030

samples were needed for estimating the population mean with a bound on the error of estimation

equals to 0.07. The calculation of sample size can be reference to the following equation.

2

22( 1)

4

Nn

BN

Where n = sample size

= the variance of question in questionnaire

N = the population size

B = bound on the error of estimation

1029 pedestrians (students/workers) at selected busy streets were interviewed. Data were then

entered into statistical software SPSS for analysis. Normality and logical test were applied for

initial testing. The details of the analyzed results are shown in Annex 4.

Day Location Day Location

1 Sun Yuen Long Centre 8 Tai Po Uptown Plaza

2 Sun Yuen Long Centre 9 Sha Tin Town Centre

3 Hung Hom Railway Station 10 Causeway Bay

4 Tsim Sha Tsui 11 Causeway Bay

5 Mong Kok 12 Central

6 Mong Kok 13 Central

7 Mong Kok 14 Central

15 Sha Tin Town Centre

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The field walkability survey is an observational survey which involves the assessment on the

availability and quality of pedestrian infrastructure along selected pedestrian routes. Observers are

required to rank nine different variables from 1 to 5. These variables are briefly explained in the

table 3 below.

Table 3: Levels of Services for Pedestrians

Variables Description

Walking Path Modal Conflict Pedestrians mix with other modes, such as bicycles, motorcycles, or cars.

Availability of Walking Paths( with

Maintenance and Cleanliness)

Clean, pleasant and convenient paths are important for pedestrians.

Availability of crossings Ideally, crossing opportunities should be at least every 300 meters to be

considered acceptable otherwise when there are no opportunities provided for

crossing streets, pedestrians tend to jaywalk, increasing their risk of injury or

harm.

Grade Crossing Safety Exposure to other modes, Exposure time, and the degree to which sufficient

time is allocated for pedestrians to cross at signalized intersections are three

important factors to consider when evaluating how safe it is to cross the street.

Motorist Behavior The degree to which cities can manage motorist behavior will largely impact

the safety of the pedestrian environment.

Amenities Pedestrian amenities, such as benches, street lights, public toilets, and trees

greatly enhance the attractiveness and convenience of the pedestrian

environment, and in turn, the city itself.

Disability Infrastructure Disability Infrastructure typically services all pedestrians, not just those who

are disabled. For wheelchair access, effective walking path width should be, at

a minimum, 1 meter wide.

Obstruction Permanent obstructions (e.g., telephone poles or tress placed in the center of

the walking path), are typically the results of insufficient or ineffective urban

design guidelines. All obstructions, to some degree, impact effective width and

thus should be regulated.

Security from crime This parameter is important in assessing to what degree are the walking paths,

pedestrian bridges, and pedestrian subways perceived to be secure from crime

(pick-pocketing, mugging, unprovoked attack, etc)

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5.0 RESULTS AND DISCUSSION

A. Pedestrian Preference Survey Results

We found that almost 39 percent of daily trips are made entirely on foot, and of the almost 61

percent of the commuters who use different modes of public transport, a large percentage walk

some or large part of their daily commute. (Figure1)

Figure 1: Percentage of people walking and using other transport modes

The willingness of people to walk is largely dependent on travel distance and time. When the travel

distance and time is greater most people are less willing to walk and they tend to take other

convenient modes of transportation. It is evident that more than 60 percent are willing to walk for a

shorter distance and time. (Table 4) Hong Kong has a comparatively larger proportion of population

willing to walk comparing to other cities. In Karachi about 21 percent of the people walk daily

despite inadequate pedestrian facilities (Karachi, 2009) and only about 18.1 percent walk in

Kathmandu (Kathmandu Valley Mapping Program (KVMP), 2001).

Average Travel

Distance Frequency Percent Average Travel Time Frequency Percent

< 6 km 76 60.3 < = 30 min 79 62.7

6-9 km 8 6.3 31-45 min 30 23.8

9-12 km 9 7.1 46-60 min 10 7.9

12-15 km 6 4.8 61-75 min 2 1.6

> 15 km 27 21.4 76-90 min 2 1.6

- - - > 90 min 3 2.4

Total 126 100.0 Total 126 100.0

Table 4: Willingness of people to walk

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However, the recent study conducted by the Clean Energy Nepal (CEN)/Clean Air Network Nepal

(CANN) to 305 pedestrians in Kathmandu showed that 88.9 percent of commuters‟ daily trips are

made entirely on foot. About 45.8 percent of the pedestrians in Kathmandu feel that the situation of

existing pedestrians‟ facilities in the city is in its worst condition (Cabrido Charina, 2010). Mumbai

has 55% of its population walking regularly. The study of 30 Indian cities shows that on an average,

almost 40% of all trips in urban India still do not involve motorized vehicles. (Pandit A, Bhasin R

& Suri M, 2009).

Also according to the walkability survey completed in Colombo in March 2010 by the University of

Moratuwa, 21% of the pedestrian feel that the pedestrian facilities in Colombo is in fair while 16%

think the facilities are good. Only 16% of the respondents feel that the existing facilities are not

good and only 4% feel that the facilities in the city is in its worst condition. However 44% of the

survey respondents are willing to shift from walking to other mode of transports.

Table 4 illustrates that many people would like to see improvements in walkways, i.e., to remove

obstacles, have wider and leveled footpath; have easy access for disables and reduced vehicle

traffic. In fact, the survey results show that 30 percent have a stronger desire to shift from walking

to other transport modes if no improvement is made to the pedestrian facilities.

Figure 2: Willingness of people to shift from walking to other modes

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Rank

Easy

access

Improved

street

lighting

Wider

footpaths

Level

footpaths

Clean

sidewalks

Reduced

traffic

Reduced

speed

Remove

obstacles

More

crossing pt

Weather

proof

1 64 113 32 51 36 49 76 21 33 90

2 162 243 152 161 142 170 224 140 104 141

3 325 396 305 367 312 336 435 357 324 304

4 297 204 338 312 298 287 200 305 349 270

5 175 64 194 129 232 174 84 198 207 211

Table 5: Pedestrians major preferences of walking facility improvements; Rank 1= Least Wanted; Rank 5= Most wanted

Majority of people who are travelling on MTR and Bus are travelling for more than 15 km but their

average travel time is less than 30 minutes. This somehow reflects that people who travel on a more

expensive mode like MTR/Car/Taxi/Bus have shorter travelling than walking. (Figure 3 and 4)

Figure 3: Travel distance of people with respect to traffic modes

Beyond travel distance, travel time & pedestrian facilities, other factors like household income &

transport cost is also important in determining why people walk. Economically and socially

disadvantaged people tend to rely heavily on walking for transport (Victoria Transport Policy

Institute). In developing cities walking is often considered in terms of providing mobility for the

poorest residents. But a different scenario is observed in the case of Hong Kong. From the survey

result a same number of both low and high income people walk. However, a larger population of

high income group is found to be travelling in a car/taxi than the low income people. (Figure 4)

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Figure 4: People choice of transport mode with respect to their household income

Cross Relationship

Walking and travelling in MTR is a major combination of daily commute for majority of Hong

Kong people. The decision to selection of transport modes are mainly based on the socio economic

factors in the society. The availability of facilities and conditions of walkways, travel distance and

travel time also influence on those decisions making process of the pedestrians.

The analysis of the single mode of transport shows walking is the major mode of transport for poor

and middle income groups in Hong Kong (Figure 5). And majority of the respondents (about 66%)

do not own any kind of vehicle while 15% own a car and this gives a reflection of peoples‟

willingness to walk. Saelens et al. (2003), also argue that the choices to use motorized or non-

motorized transport are based on the proximity (distance) and connectivity (directions of travel)

between trip origin and destination. Walking has to compete with other modes of travel and may be

a particularly disadvantaged choice with respect to travel distance. The relative utility of walking

relative to other modes of travel drops off quickly as distances between destinations increase

(Frank, 2004).

Figure 5: Major transport mode of the income categories Figure 6: Type of vehicle own by the survey respondents

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The travel behaviors change according to the gender, age, socio-economic status and other

environmental factors. It is unclear whether the relationship between the built environment and

physical activity varies by socio-demographic profile. The physical activities of the women and

men also correlate with other environmental factors, neighborhood factors and safety, (Foster et al.

(2004); Bengoechea G., et al. (2005); Suminski et al. (2005)). As per the results from the single

transport mode, walking is a major mode of transport for almost all age groups except for the age

group between 16 to 30 years (Figure 7). More male respondents walk in comparison to females

and no significant preference in walking is found between them. However there is a significant

mean difference occurs in their choice of transport modes, male prefers to travel by bus while

female prefers to travel by two-wheelers. From the chi-square co-relation between gender and

willing to walk to access crossing, male respondents are willing to walk for shorter distance than

females (Table 6 & 7). Also the majority of the people (no different in gender) believe that they are

most exposed to the air pollution while waiting for the transportation and walking. The result is

significant at .05 levels. Tan et al. (2007) also points out that pedestrian comfort may reduce

because of the pollution produced by the vehicles. However, when vehicle traffic volume is little or

the speed is low, pedestrian may feel that the vehicles are not minatory and the road environment

can be comfortable.

Table 6 &7:- Gender willingness to walk to access crossing

Value df Asymp.

Sig. (2-

sided)

Pearson Chi-Square 19.464 6 .003

Likelihood Ratio 20.017 6 .003

Linear-by-Linear

Association

0.020 1 .887

N of Valid Cases 1019

Willing to walk to access crossing

<=50

m

51-100

m

101-

150

m

151-

200 m

201-

250 m

Male 258 161 65 33 14

Female 180 162 58 44 7

Total 438 323 123 77 21

Figure 8: Major mode of transport by age Groups

Figure 7: Major mode of transport by age Groups

14 | P a g e

The majority of the people are willing to walk if the average travel time is less than 45 minutes or

the average travel distance is less than 3km. Also it is interesting to see that the young people of age

category between 16-30 years old are significantly demarcated from other age groups in their

willingness to walk; and they want less traffic on the road to improve walkability. The major

transport mode of the low and middle household income groups in Hong Kong is walking and their

average travel distance is more than 15 km. However there are a considerable percentage of high

income people who also walk in their day to day activities. Ross et. al (2000) found that residents of

socially disadvantaged neighborhoods, both men and women, walked more than those in

advantaged neighborhoods, despite feeling less safe from crime. It is found that there is a stronger

co-relationship between income and the major mode of transport. With the increase of household

income the major mode of transport changes from walking to non walking mode. The major mode

of transport of poor people (<4000HK$) is walking and shift to two wheelers with the increase of

income to HK$4000-HK$15999. The major modes of transport of higher income groups with

HK$28,000-HK$39,999 and >HK$40,000 are minibus and car/taxi.

Based on the mean test analysis (Annex 4), all age groups prefer to have more crossing points.

Elderly people (>60 years) and the age groups between 31-45 years old are not willing to walk for

greater distance for crossings in comparison to other age groups of 46-60 years. Majority of the

respondents, i.e., more than 73% prefer ground crossings. One of the key factors affecting

walkability in Hong Kong is the design of pedestrian crossings and thus crossing time. In general

the road crossings in Hong Kong are located conveniently in comparison to other countries. But due

to some inconvenience in crossing, pedestrians tend to jay-walk. The study results show that the

likelihood of a pedestrian using ground crossing is affected by two factors: high traffic flow and

traffic speed on the road. The footbridges over busy streets are to keep pedestrians from interfering

with motor vehicles rather than to create convenience for pedestrians. The timing of traffic lights

also appears to facilitate the movements of vehicles more than for people (Lai Poh et al, 2009). The

result also illustrates that there is a significant relationship between the level of pedestrian facilities

in the city (good/bad) and willingness to walk to access crossings. According to the socio-economic

data the middle and lower income people are willing to walk greater distance to access the crossings

points.

According to the Post Hoc test results of ANOVA there is a significant effect of 10 major road

improvements on improving walkability in the city at p<0.05 level for three conditions [F(9, 10213)

= 48.94, p = 0.000]. A further analysis of the means of the significant variables with post-hoc tests

is conducted to determine the nature of the effect of different variables on walkability. According to

the results the wider foot paths, clean sidewalks, removal of obstacles and more crossing points are

the most desirables to improve walkability in terms of mean improvement. The weather proof,

reduced traffic, leveled foot paths and easy access for disables are also significantly correlated with

the wider foot paths.

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B. Field Survey Results

The field survey conducted in ten centers of attraction are categorized into six different land use

types covering 24 road stretches and a total length of 11.9 kilometers (Figure 09). The pedestrian

density is calculated using pedestrian count per hour and per meter width of the pedestrian

walkways. The survey result shows that Shopping areas (Fa Yuen Street, Ladies Street and Temple

Street) have the highest pedestrian density (around 1300) in comparison to other areas. Residential

areas (Whampoa Garden and Parc Oasis) on the other hand have comparatively low (around 150)

pedestrian density. (Figure 10)

Figure 09: Length on surveyed road stretch in Kilometers

Figure 08: Major pedestrian improvements need in Hong Kong

16 | P a g e

Figure 10: Pedestrian density in different surveyed areas

Among the six surveyed types of areas, the presence of amenities is high in Commercial and

Residential areas. The areas are less secure from crime due to high pedestrian flow. In terms of

walking path model conflict, it is seen that some conflicts in the Shopping and Industrial areas that

make walking possible but not convenient. The grade crossing safety in Industrial area (Kwun

Tong), Shopping areas (Ladies‟s Street, Fa Yuen Street, Temple Street), Commercial Educational

area (Hong Kong Central Library) and Residential Educational areas (Baptist University) gain low

scores. The grade crossing safety is dependent on three important factors such as exposure to other

modes, exposure time, and whether sufficient time is allocated for pedestrians to cross the road. In

Hong Kong, time allocated for the pedestrians to cross at signalized intersections seems to be less

sufficient for the elderly persons and persons with disabilities.

The results also show that obstructions occur most frequently in the Shopping and Industrial areas.

The obstruction in the walking paths often create cumbersome mainly for the elderly persons and

persons with disabilities. Permanent obstructions (e.g., telephone poles or trees placed in the center

of the walking path), are typically the results of insufficient or ineffective urban design guidelines.

Unwelcome temporary obstructions (e.g., parked cars) are often the results of insufficient or

ineffective public space policy. Welcome temporary obstructions (e.g., vendors, sidewalk cafes)

should be allocated space such that they both enhance the pedestrian environment without

restricting the effective width of walking paths.

The survey results also indicate that disability infrastructure typically services all pedestrians, not

just those persons with disabilities. For example, curb ramps are convenient not just for wheel chair

access, but also for persons with baby pushchairs, shopping carts, or luggage.

17 | P a g e

Old people and persons with disabilities are most vulnerable to crimes (pick-pocketing, mugging,

unprovoked attack, etc). The results from the field survey show that Shopping areas and Industrial

areas are less secure from crime as the area are often crowded. These areas need improvement in

the effective walking width so that they are less crowded and feel more secure and safe.

Figure 11: Scores of six areas by variables

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6.0 CONCLUSION

Based on the pedestrian interview survey results, almost 39 percent of daily trips are made entirely

on foot in Hong Kong. 70 percent of the people are willing to walk with the existing pedestrian

facilities; however 30 percent have a stronger desire to shift from walking to other transport modes

if no improvements made in the pedestrian facilities. They want city to improve street lighting,

clean and wider foot paths, reduce traffic and speed; removal of obstacles from walkways, more

crossing points and weather proof sidewalk. These factors are very important in determining

pedestrians‟ decision to shift from walking to other modes if no improvements are done. MTR is

their first choice of other transport mode if they shift from walking.

About 66 percent of the respondents do not own any kind of vehicle and the major transport mode

for most people are walking, MTR and Bus. Walking is the major transport mode for low and

middle income groups but there are a considerable percentage of high income people who also walk

in their daily commute. Male respondents are found to be walking more in comparison to females

and middle aged people between 16-30 years old are significantly demarcated from other age

groups in their willingness to walk. Many people believe that they are most exposed to the air

pollution while waiting for the transportation and walking.

From the field survey results, Commercial areas gain high scores in terms of the most variables that

were evaluated and Industrial area gain low scores. Residential, Residential Educational,

Commercial and Commercial Educational areas gain high scores in availability of walking paths,

positive motorist behavior, less obstructions and security from crime but these variables gain low

scores in Industrial area. Shopping areas though have the highest pedestrian density; these areas

obtain low scores in grade crossing safety, motorist behavior, obstructions and security from crime.

Also, infrastructures for disables are given less priority in Shopping, Industrial and Residential

Educational areas but are given high attention in Commercial areas.

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7.0 REFERENCES

1. Litmen, T.A, (2009), Economic Value of Walkability, Victoria Transport Policy Institute,

USA

2. Saelens BE, Sallis JF, Frank LD (2003) Environmental correlates of walking and cycling:

Findings from the transportation, urban design, and planning literatures. Annals of

Behavioral Medicine 25(2):80-91

3. Sallis JF, Frank LD, Saelens BE, Kraft MK (2004) Active transportation and physical

activity: opportunities for collaboration on transportation and public health. Transportation

Research Part A, 38:249-268

4. Eva Lesliea, Ester Cerinb, Lorinne duToitc, Neville Owenc and Adrian Baumand (2007),

Objectively Assessing ‘Walkability’ of Local Communities: Using GIS to Identify the

Relevant Environmental Attributes,

5. Billie Giles-Corti, and Robert J. Donovan, (2003), Relative Influences of Individual, Social

Environmental, and Physical Environmental Correlates of Walking, Vol 93, No. 9,

American Journal of Public Health 1583-1589

6. Holly Krambeck, THE GLOBAL WALKABILITY INDEX:TALK THE WALK AND

WALK THE TALK 1, Master‟s Degree Candidate (February 2006) Massachusetts Institute

of Technology Dept. of Civil and Environmental Engineering & Dept. Urban Studies and

Planning, Cambridge, Massachusetts, USA.

7. Karachi (2009), A Preliminary survey of Pedestrian Infrastructure in four areas of Karachi /

http://www.cleanairnet.org/caiasia/1412/articles-60499_Arif.pdf)

8. Cabrido Charina, (2010), Walkability in Asian Cities: Assessment of Pedestrian

Infrastructures and Services in Four Areas of Kathmandu City.

9. Pandit A, Bhasin R, Suri M (2009)/

http://timesofindia.indiatimes.com/city/ahmedabad/Ahmedabad-2nd-in-walkability-

index/articleshow/5058499.cms

10. McFadden, D.L., (1978), Quantitative methods for analyzing travel behaviour of

individuals: some recent developments. In: D. Hensher and P. Stopher, eds. Behavioural

travel modelling. London: Croom Helm, pp: 279–318.

11. Frank, L.D., (2004), Economic determinants of urban form: resulting trade-offs between

active and sedentary forms of travel. Am. J. Prev. Med. 27 (3S), pp: 146–153.

12. Ross, R., Freeman, J.A., et al., (2000), Exercise alone is an effective strategy for reducing

obesity and related comorbidities. Exerc. Sport Sci. Rev. 28 (4), pp: 165–170.

13. Foster, C., Hillsdon, M., et al., (2004), Environmental perceptions and walking in English

adults. J. Epidemiol. Community Health 58 (11), pp: 924–928.

14. Bengoechea, G., Spence, E., et al., (2005), Gender differences in perceived environmental

correlates of physical activity. Int. J. Behav. Nutr. Phys. Act. 2, 12.

15. Suminski, R.R., Poston, W.S., et al., (2005), Features of the neighborhood environment and

walking by U.S. adults. Am. J. Prev. Med. 28 (2), pp 149–155.

16. Lai, P.C., Wong, M., Chan, M.H., Wong, W.C., Low, C.T., (2009), An ecological study of

physical environmental risk factors for elderly falls in an urban setting of Hong Kong,

Science of the Total Environment, 407, pp 6157–6165

17. Parker, M.J., Twemlow, T.R., Pryor, G.A., (1996), Environmental hazards and hip

fractures., Age Ageing, 25(4), pp: 322–325.

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18. Southworth, M., (2005), Designing the walkability city. J Urban Planning Development,

131(4), pp: 246–257.

19. Ayres, T.J., Kelkar, R., (2006), Sidewalk potential trip points: a method for characterizing

walkways. Int J Ind Ergon, 36, pp: 1031–1035.

20. TAN, D., WANG, W., LU, J., BIAN, Y., (2007), Research on Methods of Assessing

Pedestrian Level of Service for Sidewalk, Journal of Transportation Systems Engineering

and Information Technology, Volume 7, Issue 5

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ANNEX 1

WALKABILITY IN ASIAN CITIES

FIELD SURVEY

City: Survey Area Name

Direction (L/R) Area Type Peak Hour Yes No

Survey Team Names

Surveyed Road Stretch 1 2 3 4 5 6 7 8 9 10

1. Walking Path Modal Conflict

2. Availability Of Walking Paths (with Maintenance and Cleanliness)

3. Availability Of Crossings

4. Grade Crossing Safety

5. Motorist Behavior

6. Amenities

7. Disability Infrastructure

8. Obstructions

9. Security from Crime

10. Pedestrian count

11. Length of surveyed stretch (Km)

General Description of Area Rough Sketch

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ANNEX 2

Field Survey Data Collection Guidelines (Hong Kong)

1. Walking Path Modal Conflict

Rating Description Example

1. Significant conflict that makes walking impossible

2 Significant conflicts that makes walking possible, but dangerous and inconvenient.

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3 Some conflict – walking is possible, but not convenient

4 Minimal conflict, mostly between pedestrians and non-motorized vehicles

5 No conflict between pedestrians and other modes

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2. Availability of Walking Paths (with maintenance and cleanliness)

Rating Description Example

1 Pedestrian walkways required but not available

2 Pedestrians Walkways available but highly congested , badly maintained and not clean

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3 Pedestrians Walkways available but congested , needs better maintenance and cleanliness

4 Pedestrians Walkways available which are sometimes congested and are clean and well maintained

5 Pedestrian Walkways not required as people can safely walk on roads

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3. Availability of Crossings (Count the number of crossings available per stretch)

Rating Description Example

1. Average distance of controlled crossings/subway/sky walk way is greater than 500m and average speed is high

2. Average distance of controlled crossings/ subway/ sky walk way is between 500-300m and average speed is around 40 Kmph

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3 Average distance of controlled crossings/subway/sky walk way is between 200-300m and average speed is 20-40 Kmph

4 Average distance of controlled crossings/subway/sky walk way is between 100-200m and average speed is 20-40 Kmph

5 There is no need of controlled crossings/subway/sky walk way as pedestrians are safe to cross wherever they like and vehicles and pedestrians coexist

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4. Grade Crossing Safety ( Exposure to Other Modes and Exposure Time, available and required - If the other modes don’t stop to allow you to walk or they keep moving as you run etc...)

Rating Description Example

1 There are significant risk of accidents due to no pedestrians has sufficient time to cross, tend to jay walk extremely long waiting period- more than 60 seconds, crossing time less than 20 seconds

2 Dangerous-Relatively long waiting time and pedestrians faces some risk of being hurt by other modes and barely enough time for most people, insufficient for elderly

3 Difficult to ascertain dangers posed to pedestrians, sufficient time for most pedestrians to cross, not quite enough time for elderly - crossing time between 20-30 seconds

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4 Safe- pedestrian is mostly safe from accident with other modes, reasonable waiting period 10-20 seconds and enough time for elderly to cross- crossing time more than 20 seconds

5 Very Safe- Other modes present no danger to pedestrian

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5. Motorist Behavior

Rating Description Example

1 High traffic disrespect to Pedestrians

2 Traffic disrespect and rarely pedestrians get priority

3 Motorists sometimes yield

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4 Motorists usually obey traffic laws and sometimes yield to pedestrians

5 Motorists obey traffic laws and almost always yield to pedestrians

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6. Amenities (lighting, rain proof, cover/shade, hawker exclusive zones, resting place/benches etc.)

Rating Description Example

1 No Amenities

2 Little amenities at some locations

3 Limited number of provisions for pedestrians

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4 Pedestrians provided some good amenities for major length

5 Pedestrians have excellent amenities such as lighting, cover from sun and rain making walking a pleasant experience

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7. Disability Infrastructure (Footpath should be at least 1m Wide, facilities available for smooth & convenient movement, directions for disability facilities, etc)

Rating Description Example

1 No infrastructure for disabled people is available

2 A limited infrastructure for disabled persons is available for major length and significant inconvenience due to poor construction.

3 Infrastructure for disabled persons is present but no directions and also it is too far from the existing walking paths

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4 Infrastructure for disabled persons is present in good condition, but poorly constructed and mild difficult to use.

5 Infrastructure for disabled persons is present, in good condition, and well placed.

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8. Obstructions

Rating Description Example

1 Pedestrian infrastructure is completely blocked by permanent obstructions

2 Pedestrians are significantly inconvenienced. Effective width <1m.

3 Pedestrian traffic is mildly inconvenienced; effective width is < or = 1 meter.

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4 Obstacle presents minor inconvenience. Effective width is > 1m

5 There are no obstructions

9. Security from Crime

Rating Security when walking – do you feel safe from external elements?

Rating

Description

1 Environment feels very dangerous – pedestrians are highly susceptible to crime

2 Environment feels dangerous – pedestrians are at some risk of crime

3 Difficult to ascertain perceived degree of security for pedestrians

4 Environment feels secure – pedestrians at minimal crime risk

5 Environment feels very secure – pedestrians at virtually no risk of crime

ANNEX 3- Field Walkability Survey Area Maps

1. Whampoa Garden

Section 1: Whampoa Garden Site 3 Blk 8 to Hung Hom MTR station exit B1

0.8 km – 10 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E

8%B7%AF&daddr=22.304135,114.183097&hl=zh-

TW&geocode=FQRVVAEdXlvOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.304661,114.186015&sspn=0.004725,0.

009602&brcurrent=h3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&z=17

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Section 2: Whampoa Garden Site 3 Blk 8 to Whampoa Garden Bus Terminal

0.5 km -7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E

8%B7%AF&daddr=22.304632,114.190564&hl=zh-

TW&geocode=FQRVVAEdXlvOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.304661,114.186015&sspn=0.004725,0.

009602&brcurrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.30

4572,114.190553&spn=0.004725,0.009602&z=17

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Section 3: Whampoa Garden Site 3 Blk 8 to Hung Hom Complex

0.5 km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E

8%B7%AF&daddr=%E5%B7%AE%E9%A4%A8%E9%87%8C&hl=zh-

TW&geocode=FQRVVAEdXlvOBg%3BFQZhVAEdaFvOBg&mra=dme&mrcr=0&mrsp=1&sz=18&dirflg=w&sll=22.306572,114.18787

7&sspn=0.002362,0.004801&brcurrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a

7&ie=UTF8&ll=22.305594,114.189459&spn=0.004725,0.009602&z=17

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Section 4: Whampoa Garden Site 3 Blk 8 to Ferry Pier

0.5km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.304036,114.186895&daddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84

%E9%81%93%E8%B7%AF&hl=zh-

TW&geocode=%3BFfZKVAEdL2bOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.302944,114.189137&sspn=0.004725,0.009602&brcu

rrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.302934,114.189749&spn=0.

004725,0.009602&z=17

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2. Hong Kong Cultural Centre/ Hong Kong Space Museum

Section 1: Hong Kong Cultural Centre/ Hong Kong Space Museum to Tsim Sha Tsui MTR station exit F

0.3 km – 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d

addr=22.295728,114.172186&geocode=FSMwVAEdsxrOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.294963,114.172293&sspn=0.004725,0.009602&brcurrent=3,0x340400edc

87d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&z=17

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Section 2: Hong Kong Cultural Centre/ Hong Kong Space Museum to East Tsim Sha Tsui MTR station exit J

0.4 km – 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d

addr=22.294586,114.173902&geocode=FSMwVAEdsxrOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.294705,114.173012&sspn=0.004725,0.009602&brcurrent=3,0x340400edc

87d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.294626,114.173269&spn=0.004725,0.

009602&z=17

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Section 3: Hong Kong Cultural Centre/ Hong Kong Space Museum to Star Ferry Pier

0.2 km – 2 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d

addr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E8%B7%AF&geocode=FSMwVAEdsxrOBg%3BFe4tV

AEdxRPOBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=16&dirflg=w&sll=22.295569,114.17357&sspn=0.00945,0.019205&brcurrent=3,0x340400edc87

d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.29469,114.170448&spn=0.004725,0.009

602&z=17

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3. Ladies’ Street

Section 1: Ladies’ Street to Mong Kok MTR station exit D3

0.3 km – 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%80%9A%E8%8F%9C%E8%A1%97&daddr=%E4%BA%9E%E7%9A%86%E8%80%8

1%E8%A1%97&hl=zh-

TW&geocode=FeyGVAEd0hzOBg%3BFfqQVAEd3hjOBg&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.318061,114.171767&sspn=0.00472

4,0.009602&brcurrent=3,0x340400c62bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.318398,11

4.171928&spn=0.004724,0.009602&z=17

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Section 2: Ladies’ Street to Yau Ma Tei MTR station exit A2

0.4 km - 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%80%9A%E8%8F%9C%E8%A1%97&daddr=22.315425,114.17053

5+to:%E7%A2%A7%E8%A1%97&hl=zh-

TW&geocode=FeyGVAEd0hzOBg%3BFaGBVAEdpxrOBilfeS8nxwAENDGz5qRNOK3_cw%3BFch7VAEdcBvOBg&mra=dme&mrcr=

0&mrsp=1&sz=17&dirflg=w&sll=22.314389,114.172636&sspn=0.004724,0.009602&brcurrent=3,0x3404009533f68457:0x69f4ecff872

53282,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.31556,114.172196&spn=0.004724,0.009602&z=17&via=1

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4. Fa Yuen Street

Section 1: Fa Yuen Street to Prince Edward MTR station exit B2

0.4 km – 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.32213,114.170533&daddr=%E8%8A%B1%E5%9C%92%E8%A1%97

+to:%E5%A4%AA%E5%AD%90%E9%81%93%E8%A5%BF&geocode=%3BFY6iVAEdXhnOBg%3BFTKjVAEdcBTOBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=0&sz=17&via=1&dirflg=w&sll=22.322249,114.171499&sspn=0.004724,0.009602&brcurrent=3,0x3404

00c62bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.322964,114.171435&spn=0.00

4724,0.009602&z=17

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Section 2: Fa Yuen Street to Mong Kok MTR station exit B1

0.3 km - 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%8A%B1%E5%9C%92%E8%A1%97&daddr=%E5%BF%AB%E5%A

F%8C%E8%A1%97&geocode=FdibVAEdyRrOBg%3BFaqUVAEdTRbOBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.321981,114.171907&sspn=0.004724,0.009602&brcurrent=3,0x340400c62

bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.32084,114.171295&spn=0.004724,0.

009602&z=17

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Section 3: Fa Yuen Street to Mong Kok East MTR station exit B

0.7 km – 9 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%8A%B1%E5%9C%92%E8%A1%97&daddr=22.321594,114.17252

9&geocode=FdibVAEdyRrOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.321356,114.172969&sspn=0.004724,0.009602&brcurrent=h3,0x340400c6

2bc7810f:0x3ba12a5918081894,,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&z=17

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5. Temple Street

Section 1: Temple Street to Yau Ma Tei MTR station exit C

0.6 km – 7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=Temple+Street&daddr=%E5%BB%9F%E8%A1%97+to:22.31151,1

14.170673&geocode=FfphVAEdYRnOBikbWDPz6gAENDHV8DjVbs83mQ%3BFZhmVAEdlxrOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=2&sz=18&via=1&dirflg=w&sll=22.311768,114.171563&sspn=0.002362,0.004801&brcurrent=3,0

x3404009533f68457:0x69f4ecff87253282,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.309634,114.17195&spn

=0.004725,0.009602&z=17

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Section 2: Temple Street to Jordan MTR station exit A

0.4 km - 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=Temple+Street&daddr=22.305335,114.170365+to:%E5%BD%8C%E6%9

5%A6%E9%81%93&geocode=FfphVAEdYRnOBikbWDPz6gAENDHV8DjVbs83mQ%3BFTdaVAEd_RnOBil9UKUI6wAENDG3ZRio

WIpxzQ%3BFXhaVAEdnh7OBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.306686,114.172465&sspn=0.004725,0.009602&brcurrent=3,0x340400eba

04aacaf:0x48ca3dfe6edcb952,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.3062,114.1724&spn=0.004725,0.0096

02&z=17&via=1

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6. Parc Oasis

Section 1: Parc Oasis Blk 10 to Kowloon Tong MTR station C2

0.4 km -5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.336779,114.175115&daddr=%E5%8F%88%E4%B8%80%E5%B1%85

%E9%81%93&hl=zh-

TW&geocode=%3BFe7IVAEdPivOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.335141,114.177196&sspn=0.004724,0.0

09602&brcurrent=3,0x3404073153dbf8a7:0x1837330af94afb18,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.335

409,114.177496&spn=0.004724,0.009602&z=17

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Section 2: Parc Oasis Blk 10 to Yau Yat Tsuen Bus Terminus

0.5 km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.337314,114.173999&daddr=%E5%8F%88%E4%B8%80%E5%B1%85

%E9%81%93&hl=zh-

TW&geocode=%3BFe7IVAEdPivOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.335548,114.176542&sspn=0.004724,0.0

09602&brcurrent=3,0x340407335121d4d5:0xea6602cb7ee084f0,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.33

5578,114.176649&spn=0.004724,0.009602&z=17

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7. Baptist University

Section 1: Baptist University to Kowloon Tong MTR station exit A2

0.7 km – 7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%81%AF%E5%90%88%E9%81%93&daddr=22.336808,114.177947

&geocode=FSjeVAEdPEjOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.338178,114.18035&sspn=0.004724,0.009602&brcurrent=3,0x3404073153

dbf8a7:0x1837330af94afb18,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&z=17

55 | P a g e

Section 2: Baptist University to Lok Fu MTR station exit B

0.7 km – 8 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%81%AF%E5%90%88%E9%81%93&daddr=22.3379,114.1877&geo

code=FSjeVAEdPEjOBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.338178,114.183354&sspn=0.004724,0.009602&brcurrent=3,0x34040728e

13925c5:0xa6d5e91d75f1c7de,0,0x340406c37eee9427:0xd3b9116677206d6e&ie=UTF8&ll=22.338307,114.18594&spn=0.004724,0

.009602&z=17

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8. Kwun Tong Industrial Centre

Section 1: Kwun Tong Industrial Centre to Kwun Tong MTR station B1

0.4 km – 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.309188,114.225208&daddr=%E9%96%8B%E6%BA%90%E9%81%93

&geocode=%3BFZFzVAEdS_TOBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.309734,114.226044&sspn=0.004725,0.009602&brcurrent=3,0x340401488

3a04d95:0xce2b10a24961854c,0,0x3404014883a04d95:0xf7ab69df5f85d6b3&ie=UTF8&ll=22.310478,114.227117&spn=0.004725,0

.009602&z=17

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Section 2: Kwun Tong Industrial Centre to Kwun Tong Ferry Bus Terminal

0.5 km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%88%88%E6%A5%AD%E8%A1%97&daddr=%E4%B8%8D%

E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E8%B7%AF&geocode=FU9pVAEdR_DOBg%3BFWxlVAEdDeLOBg&hl=

zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.308394,114.224929&sspn=0.004725,0.009602&brcurrent=3,0x34040

14883a04d95:0xce2b10a24961854c,0,0x3404014883a04d95:0xf7ab69df5f85d6b3&ie=UTF8&ll=22.3089,114.225186&spn=0.004

725,0.009602&z=17

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9. Hong Kong Central Library

Section 1: Hong Kong Central Library to Causeway Bay MTR station exit E

0.6 km – 8 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%AB%98%E5%A3%AB%E5%A8%81%E9%81%93&daddr=22.2803

11,114.184996&geocode=FbL4UwEdu2POBg%3B&hl=zh-

TW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.280072,114.188225&sspn=0.004726,0.009602&brcurrent=3,0x34040055b

36dac7f:0x23fa8b1e7120c6a,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22.279765,114.187828&spn=0.004726,0.

009602&z=17

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Section 2: Hong Kong Central Library to Tin Hau MTR station exit A2

0.4 km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.28039,114.189137&daddr=%E8%8B%B1%E7%9A%87%E9%81%93+

to:%E8%8B%B1%E7%9A%87%E9%81%93&geocode=%3BFev_UwEdo23OBg%3BFfoCVAEdrG_OBg&hl=zh-

TW&mra=dme&mrcr=0&mrsp=0&sz=17&via=1&dirflg=w&sll=22.281274,114.191734&sspn=0.004726,0.009602&brcurrent=3,0x3404

01acff3ac4cf:0xa3821671f88c95a,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22.281621,114.191884&spn=0.0047

26,0.009602&z=17

60 | P a g e

10. Hong Kong Convention and Exhibition Centre

Section 1: Hong Kong Convention and Exhibition Centre to Wan Chai Ferry Pier

0.5 km – 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E5%8D%9A%E8%A6%BD%E9%81%93&daddr=22.281879,114.17572

6&hl=zh-

TW&geocode=FYEFVAEd2CPOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.282395,114.175125&sspn=0.004726,

0.009602&brcurrent=3,0x3404004bfd731ce7:0x82db136932b588ce,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22

.282505,114.175243&spn=0.004726,0.009602&z=17

61 | P a g e

Section 2: Hong Kong Convention and Exhibition Centre to Wan Chai MTR station exit A1

0.9km – 12 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E5%8D%9A%E8%A6%BD%E9%81%93&daddr=%E9%A7%B1%E5%8

5%8B%E9%81%93&hl=zh-

TW&geocode=FYEFVAEd2CPOBg%3BFUTwUwEdOiXOBg&mra=mi&mrsp=1&sz=17&dirflg=w&sll=22.278543,114.17564&sspn=0.

004726,0.009602&brcurrent=3,0x3404004bfd731ce7:0x82db136932b588ce,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF

8&ll=22.27895,114.176949&spn=0.004726,0.009602&z=17

62 | P a g e

WALKABILITY IN ASIAN CITIES

PEDESTRIAN PREFERENCE SURVEY

1. Travel Behavior How much time they spend in each mode, how much is the average travel time in one direction for a major trip say to office or school? Analysis of this would help in understanding the trip preference. It is also

important to understand if they are captive or choice riders and for this reason we need to ask for

availability of vehicle ownership.

1.1 Mode of transportation commonly used per day and average travel time spent on each mode (please

tick) – estimates for one way can be considered

Mode 0

min

1- 15

min

16-30

min

31-45

min

46-60

min

61-75

min

76-90

min

> 90

min

Walk

Cycle

MTR

Two Wheeler

Car/Taxi

Mini Bus

Bus

Others

1.2 Average Travel Time (One Way) from residence to main destination (please tick)

<=15 min 16-30 min 31-45 min 46-60 min 61-75 min 76-90 min > 90 min

1.3 Average Travel Distance (one Way) from residence to main destination (please tick)

<= 3 km 3 – 6 km 6 – 9 km 9 – 12 km 12 – 15 km > 15 km

If don’t know, please state out the district:

Starting point: _____________________ Terminal point: _______________________

1.4 What type of vehicle(s) does your family own? (please tick)

Bicycle Car Two Wheeler No Vehicle Others

2. Pedestrian Preference

Pedestrian preference survey is mainly to understand pedestrian needs and desire. It is also intended to

understand their concerns on air pollution and other issues such as subways and skywalks. Also we need to

determine if they would migrate to other modes if improvements are not made

2.1 How do you rate the Pedestrian facilities in the city?

□ Worst □ Bad □ Fair □ Good □ Best

2.2 If you have to cross the road what do you prefer? (please tick)

□ Ground Crossing (at-grade) □ Skywalks (overhead crossings) □ Subways (underground)

2.3 Please tick in the appropriate boxes. ( 1 = The least wanted ; 5 = The most wanted)

1 2 3 4 5

Easy access for people with special abilities □ □ □ □ □

Improved street lighting □ □ □ □ □

Wider footpaths □ □ □ □ □

A more Level footpaths □ □ □ □ □

Clean sidewalks □ □ □ □ □

Reduced the traffic on road □ □ □ □ □

Reduced traffic speed on road □ □ □ □ □

Remove obstacles/parking from footpath □ □ □ □ □

More crossing points □ □ □ □ □

Weather proof to cover the walkway □ □ □ □ □

2.4 How far are you willing to walk to access crossings, skywalks/subways (please tick)

< =50 m 51 – 100 m 101 – 150 m 151 – 200 m 201 – 250 m 251 – 300 m > 300 m

2.5 When do you think are you most exposed to air pollution?

Walking Cycle Bus MTR Light bus Car/taxi Two Wheeler Waiting for transportation

2.6 Do you plan to shift from walking to other mode in future if no improvement is done?

□ Yes □ No

If yes, what is your choice?

Cycle Bus MTR Light bus Car/taxi Two Wheeler

3. Socio-Economic Profile(please tick)

3.1 Sex

3.2 Age

≦15 Years old 16 – 30 Years old 31 – 45 Years old 46 – 60 Years old > 60 Years old

3.3 Household Income

< $4000

(USD 510)

$4000 - $15999

(USD 510 -2050)

$16000 - $27999

(USD 2050 - 3600)

$28000 - $39999

(USD 3600–5100)

> $40000

(USD 5100)

Male Female

ANNEX 4

亞洲地區步行指數

行人步行習慣調查

1. 乘坐交通工具的習慣

以下的問題旨在了解市民平均單程有多少時間用於以下各種交通工具，這研究有助了解和明白市民乘坐交通工具的習慣

1.1 以每天計算，平均會花多少時間在以下的交通工具上:（以單程計算: 上班 /上學）(請加上 )

0 分鐘 1- 15 分鐘 16-30 分鐘 31-45 分鐘 46-60 分鐘 61-75 分鐘 76-90 分鐘 > 90 分鐘

步行

踏單車

電單車

港鐵

私家車/的士

中型汽車 (小巴)

巴士

其他

1.2 以單程計算，由居住地方至主要目的地乘坐交通工具的平均時間為: (請加上 )

<=15 分鐘 16-30 分鐘 31-45 分鐘 46-60 分鐘 61-75 分鐘 76-90 分鐘 > 90 分鐘

1.3 以單程計算，由居住地方至主要目的地的距離為：(請加上 )

<= 3 公里 3 – 6 公里 6 – 9 公里 9 – 12 公里 12 – 15 公里 > 15 公里

如不清楚，可寫下地區： 出發地：_______________ 終點：_____________

1.4 請問你家中所擁有的交通公具為：(請加上 )

2. 步行取向研究

步行取向研究是主要用作了解行人的需要和要求，同時有助了解受訪者對空氣污染及其他設施（如天橋或隧道）之意見..

2.1 你認為香港的行人步行設施是下列哪一項 ? (請加上 )

□非常差 □差 □中等 □好 □非常好

2.2 如果你需要橫過馬路，你會選擇以下哪項？(請加上 )

在馬路上橫過

行人天橋

行人隧道

2.3 你願意步行多遠使用橫過馬路的設施？(請加上 )

< 50 米 51 – 100 米 101 – 150 米 151 – 200 米 201 – 250 米 251 – 300 米 > 300 米

2.4 請於適當位置加上 (1=最不需要改善 ; 5 = 最需要改善)

1 2 3 4 5

增加傷殘人仕設施 □ □ □ □ □

增加街燈 □ □ □ □ □

擴寬行人路 □ □ □ □ □

使行人路更平坦 □ □ □ □ □

改善行人路的衛生情況 □ □ □ □ □

減少車輛的行駛 □ □ □ □ □

減慢車輛的行車速度 □ □ □ □ □

清除行人路上的障礙物 □ □ □ □ □

增加橫過馬路的地點 □ □ □ □ □

增加有蓋的行人路 □ □ □ □ □

2.5 你何時會覺得自己最暴露於受污染的空氣之中? (請加上 )

步行 踏單車 巴士上 港鐵上 小巴上 私家車上/的士上 電單車上 路旁候車時

2.6 如果在未來的日子，行人路的設施没有改善，你會否由步行轉變為其他方法前往目的地？(請加上 )

□會 □不會

如果會，你會轉為以下哪項？(請加上 )

單車 巴士 港鐵  小巴 私家車/的士 電單車

3. 個人資料

3.1 性別 : (請加上 )

男 女

3.2 年齡: (請加上 )

15 歲或以下 16 – 30 歲 31 – 45 歲 46 – 60 歲 大於 60 歲

3.3 家庭入息: (請加上 )

少於 $4000

(USD 510)

$4000 - $15999

(USD 510 -2050)

$16000 - $27999

(USD 2050 - 3600)

$ 28000 - $39999

(USD 3600–5100)

多於 $40000

(USD 5100)

 

單車  私家車  電單車  没有  其他 

ANNEX 5

Results of the Pedestrian Preference Survey Mean Test (by Social economic profile)

By Gender

ANOVA

Sum of Squares df Mean Square F Sig.

Q1.1 Mode of transportation

(walking)

Between Groups 6.346 1 6.346 3.498 .062

Within Groups 1861.105 1026 1.814

Total 1867.451 1027

Q1.1 Mode of transportation

(Cycle)

Between Groups .005 1 .005 .024 .876

Within Groups 217.757 1026 .212

Total 217.763 1027

Q1.1 Mode of transportation

(MTR)

Between Groups 7.599 1 7.599 2.241 .135

Within Groups 3478.653 1026 3.390

Total 3486.252 1027

Q1.1 Mode of transportation (Two

Wheeler)

Between Groups 6.399 1 6.399 7.946 .005

Within Groups 826.289 1026 .805

Total 832.688 1027

Q1.1 Mode of transportation

(Car/Taxi)

Between Groups .811 1 .811 1.781 .182

Within Groups 466.667 1025 .455

Total 467.478 1026

65 | P a g e

Q1.1 Mode of transportation (Mini

Bus)

Between Groups 1.222 1 1.222 1.887 .170

Within Groups 664.276 1026 .647

Total 665.498 1027

Q1.1 Mode of transportation (Bus) Between Groups 27.954 1 27.954 10.650 .001

Within Groups 2690.497 1025 2.625

Total 2718.452 1026

Q1.1 Mode of transportation

(Others)

Between Groups .389 1 .389 1.568 .211

Within Groups 254.178 1025 .248

Total 254.567 1026

Q2.3 Easy Access Between Groups 1.226 1 1.226 .969 .325

Within Groups 1293.736 1023 1.265

Total 1294.962 1024

Q2.3 Improved street lighting Between Groups 3.387 1 3.387 3.037 .082

Within Groups 1138.533 1021 1.115

Total 1141.920 1022

Q2.3 Wider footpaths Between Groups .893 1 .893 .798 .372

Within Groups 1143.106 1022 1.118

Total 1143.999 1023

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Q2.3 Level footpaths Between Groups .041 1 .041 .037 .847

Within Groups 1105.228 1021 1.082

Total 1105.269 1022

Q2.3 Clean sidewalks Between Groups .011 1 .011 .009 .923

Within Groups 1222.290 1021 1.197

Total 1222.301 1022

Q2.3 Reduced traffic Between Groups .158 1 .158 .131 .717

Within Groups 1223.900 1018 1.202

Total 1224.058 1019

Q2.3 Reduced speed Between Groups .453 1 .453 .432 .511

Within Groups 1069.512 1020 1.049

Total 1069.965 1021

Q2.3 Remove obstacles Between Groups .139 1 .139 .134 .714

Within Groups 1059.782 1022 1.037

Total 1059.921 1023

Q2.3 More crossing point Between Groups 3.286 1 3.286 3.125 .077

Within Groups 1070.463 1018 1.052

Total 1073.749 1019

Q2.3 Weather proof Between Groups .008 1 .008 .006 .940

Within Groups 1484.188 1017 1.459

67 | P a g e

Means Plots

Total 1484.196 1018

Average of Q2.3 Between Groups .006 1 .006 .016 .898

Within Groups 160.851 465 .346

Total 160.857 466

Q2.4 Willing to walk to access

crossing

Between Groups .038 1 .038 .020 .888

Within Groups 1931.363 1017 1.899

Total 1931.401 1018

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69 | P a g e

By Age group

ANOVA

Sum of Squares df Mean Square F Sig.

Q1.1 Mode of transportation

(walking)

Between Groups .269 4 .067 .037 .997

Within Groups 1867.182 1023 1.825

Total 1867.451 1027

Q1.1 Mode of transportation

(Cycle)

Between Groups .994 4 .249 1.173 .321

Within Groups 216.769 1023 .212

Total 217.763 1027

Q1.1 Mode of transportation

(MTR)

Between Groups 37.233 4 9.308 2.761 .027

Within Groups 3449.019 1023 3.371

Total 3486.252 1027

Q1.1 Mode of transportation (Two

Wheeler)

Between Groups 6.965 4 1.741 2.157 .072

Within Groups 825.723 1023 .807

Total 832.688 1027

Q1.1 Mode of transportation

(Car/Taxi)

Between Groups 4.315 4 1.079 2.380 .050

Within Groups 463.163 1022 .453

Total 467.478 1026

Q1.1 Mode of transportation (Mini

Bus)

Between Groups 4.026 4 1.007 1.557 .184

Within Groups 661.472 1023 .647

Total 665.498 1027

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Q1.1 Mode of transportation (Bus) Between Groups 4.914 4 1.228 .463 .763

Within Groups 2713.538 1022 2.655

Total 2718.452 1026

Q1.1 Mode of transportation

(Others)

Between Groups 1.096 4 .274 1.105 .353

Within Groups 253.470 1022 .248

Total 254.567 1026

Q2.3 Easy Access Between Groups 5.042 4 1.261 .997 .408

Within Groups 1289.919 1020 1.265

Total 1294.962 1024

Q2.3 Improved street lighting Between Groups 3.601 4 .900 .805 .522

Within Groups 1138.319 1018 1.118

Total 1141.920 1022

Q2.3 Wider footpaths Between Groups 5.117 4 1.279 1.145 .334

Within Groups 1138.882 1019 1.118

Total 1143.999 1023

Q2.3 Level footpaths Between Groups 5.381 4 1.345 1.245 .290

Within Groups 1099.888 1018 1.080

Total 1105.269 1022

Q2.3 Clean sidewalks Between Groups 1.533 4 .383 .320 .865

Within Groups 1220.769 1018 1.199

Total 1222.301 1022

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Q2.3 Reduced traffic Between Groups 13.765 4 3.441 2.886 .022

Within Groups 1210.293 1015 1.192

Total 1224.058 1019

Q2.3 Reduced speed Between Groups 7.560 4 1.890 1.809 .125

Within Groups 1062.405 1017 1.045

Total 1069.965 1021

Q2.3 Remove obstacles Between Groups 7.465 4 1.866 1.807 .125

Within Groups 1052.456 1019 1.033

Total 1059.921 1023

Q2.3 More crossing point Between Groups 11.343 4 2.836 2.709 .029

Within Groups 1062.406 1015 1.047

Total 1073.749 1019

Q2.3 Weather proof Between Groups 3.486 4 .871 .597 .665

Within Groups 1480.710 1014 1.460

Total 1484.196 1018

Average of Q2.3 Between Groups 1.131 4 .283 .818 .514

Within Groups 159.726 462 .346

Total 160.857 466

Q2.4 Willing to walk to access

crossing

Between Groups 18.647 4 4.662 2.471 .043

Within Groups 1912.755 1014 1.886

Total 1931.401 1018

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By Household income

ANOVA

Sum of Squares df Mean Square F Sig.

Q1.1 Mode of transportation

(walking)

Between Groups 22.077 4 5.519 3.041 .017

Within Groups 1840.057 1014 1.815

Total 1862.133 1018

Q1.1 Mode of transportation

(Cycle)

Between Groups 1.156 4 .289 1.359 .246

Within Groups 215.697 1014 .213

Total 216.854 1018

Q1.1 Mode of transportation

(MTR)

Between Groups 9.828 4 2.457 .725 .575

Within Groups 3437.654 1014 3.390

Total 3447.482 1018

Q1.1 Mode of transportation (Two

Wheeler)

Between Groups 16.160 4 4.040 5.020 .001

Within Groups 815.995 1014 .805

Total 832.155 1018

Q1.1 Mode of transportation

(Car/Taxi)

Between Groups 20.322 4 5.080 11.519 .000

Within Groups 446.798 1013 .441

Total 467.120 1017

Q1.1 Mode of transportation (Mini

Bus)

Between Groups 6.427 4 1.607 2.479 .043

Within Groups 657.191 1014 .648

Total 663.617 1018

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Q1.1 Mode of transportation (Bus) Between Groups 11.764 4 2.941 1.105 .353

Within Groups 2695.517 1013 2.661

Total 2707.281 1017

Q1.1 Mode of transportation

(Others)

Between Groups .494 4 .124 .493 .741

Within Groups 253.962 1013 .251

Total 254.457 1017

Q2.3 Easy Access Between Groups 31.793 4 7.948 6.407 .000

Within Groups 1254.255 1011 1.241

Total 1286.047 1015

Q2.3 Improved street lighting Between Groups 9.160 4 2.290 2.063 .084

Within Groups 1120.059 1009 1.110

Total 1129.219 1013

Q2.3 Wider footpaths Between Groups 2.278 4 .569 .508 .730

Within Groups 1131.417 1010 1.120

Total 1133.695 1014

Q2.3 Level footpaths Between Groups .578 4 .144 .133 .970

Within Groups 1095.881 1009 1.086

Total 1096.459 1013

Q2.3 Clean sidewalks Between Groups 3.554 4 .888 .743 .563

Within Groups 1207.059 1009 1.196

Total 1210.612 1013

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Q2.3 Reduced traffic Between Groups 4.956 4 1.239 1.031 .390

Within Groups 1208.854 1006 1.202

Total 1213.810 1010

Q2.3 Reduced speed Between Groups 4.008 4 1.002 .961 .428

Within Groups 1050.913 1008 1.043

Total 1054.920 1012

Q2.3 Remove obstacles Between Groups 6.703 4 1.676 1.623 .166

Within Groups 1043.035 1010 1.033

Total 1049.738 1014

Q2.3 More crossing point Between Groups 17.487 4 4.372 4.208 .002

Within Groups 1045.168 1006 1.039

Total 1062.655 1010

Q2.3 Weather proof Between Groups 12.126 4 3.031 2.080 .081

Within Groups 1464.690 1005 1.457

Total 1476.816 1009

Average of Q2.3 Between Groups .717 4 .179 .517 .723

Within Groups 160.139 462 .347

Total 160.857 466

Q2.4 Willing to walk to access

crossing

Between Groups 5.297 4 1.324 .693 .597

Within Groups 1920.882 1005 1.911

Total 1926.179 1009

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Q3.1 Gender * Q1.2 Average Travel Time

Crosstab

Count

Q1.2 Average Travel Time

<=15 min 16-30 min 31-45 min 46-60 min 61-75 min 76-90 min

Q3.1 Gender Male 32 107 150 135 54 28

Female 37 108 120 101 49 18

Total 69 215 270 236 103 46

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Crosstab

Count

Q1.2 Average Travel

Time

> 90 min Total

Q3.1 Gender Male 57 563

Female 32 465

Total 89 1028

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.775a 6 .187

Likelihood Ratio 8.818 6 .184

Linear-by-Linear Association 6.381 1 .012

N of Valid Cases 1028

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 20.81.

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Q3.1 Gender * Q1.3 Average Travel Distance

Crosstab

Count

Q1.3 Average Travel Distance

<=3 km 3-6 km 6-9 km 9-12 km 12-15 km

Q3.1 Gender Male 78 65 71 75 62

Female 72 44 47 53 42

Total 150 109 118 128 104

Crosstab

Count

Q1.3 Average Travel

Distance

> 15 km Total

Q3.1 Gender Male 210 561

Female 205 463

Total 415 1024

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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 7.545a 5 .183

Likelihood Ratio 7.564 5 .182

Linear-by-Linear Association 1.285 1 .257

N of Valid Cases 1024

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 47.02.

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Q3.1 Gender * Q2.2 Prefer way to cross the road

Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing Skywalks Subways Total

Q3.1 Gender Male 410 93 58 561

Female 345 86 34 465

Total 755 179 92 1026

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 3.176a 2 .204

Likelihood Ratio 3.215 2 .200

Linear-by-Linear Association 1.065 1 .302

N of Valid Cases 1026

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 41.70.

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Q3.1 Gender * Q2.4 Willing to walk to access crossing

Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m 51-100 m 101-150 m 151-200 m 201-250 m

Q3.1 Gender Male 258 161 65 33 14

Female 180 162 58 44 7

Total 438 323 123 77 21

Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m >300 m Total

Q3.1 Gender Male 2 25 558

Female 3 7 461

Total 5 32 1019

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 19.464a 6 .003

Likelihood Ratio 20.017 6 .003

Linear-by-Linear Association .020 1 .887

N of Valid Cases 1019

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Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m 51-100 m 101-150 m 151-200 m 201-250 m

Q3.1 Gender Male 258 161 65 33 14

Female 180 162 58 44 7

a. 2 cells (14.3%) have expected count less than 5. The minimum expected count is 2.26.

Q3.1 Gender * Q2.5 When do you think you are most exposed to air pollution

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking Cycle Bus MTR Light Bus Car/Taxi

Q3.1 Gender Male 169 8 30 5 3 5

Female 112 4 8 8 3 2

Total 281 12 38 13 6 7

Crosstab

Count

Q2.5 When do you think you are most

exposed to air pollution

Two Wheeler

Waiting for

transportation Total

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Q3.1 Gender Male 8 326 554

Female 5 320 462

Total 13 646 1016

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 20.193a 7 .005

Likelihood Ratio 21.007 7 .004

Linear-by-Linear Association 10.144 1 .001

N of Valid Cases 1016

a. 4 cells (25.0%) have expected count less than 5. The minimum expected count is 2.73.

Q3.1 Gender * Q2.6 Do you plan to change mode

Crosstab

Count

Q2.6 Do you plan to change mode

Yes No Total

Q3.1 Gender Male 155 406 561

Female 151 312 463

Total 306 718 1024

93 | P a g e

Chi-Square Tests

Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided)

Pearson Chi-Square 3.007a 1 .083

Continuity Correctionb 2.774 1 .096

Likelihood Ratio 3.001 1 .083

Fisher's Exact Test

.087 .048

Linear-by-Linear Association 3.004 1 .083

N of Valid Cases 1024

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 138.36.

b. Computed only for a 2x2 table

Q3.2 Age * Q1.2 Average Travel Time

Crosstab

Count

Q1.2 Average Travel Time

<=15 min 16-30 min 31-45 min 46-60 min 61-75 min

Q3.2 Age <=15 Years old 4 13 6 4 1

16-30 Years old 35 107 163 139 60

31-45 Years old 15 45 45 41 21

46-60 Years old 14 41 43 42 18

> 60 Years old 1 9 13 10 3

Total 69 215 270 236 103

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Crosstab

Count

Q1.2 Average Travel Time

76-90 min > 90 min Total

Q3.2 Age <=15 Years old 2 1 31

16-30 Years old 28 49 581

31-45 Years old 9 20 196

46-60 Years old 5 15 178

> 60 Years old 2 4 42

Total 46 89 1028

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 22.916a 24 .525

Likelihood Ratio 22.794 24 .532

Linear-by-Linear Association .002 1 .966

N of Valid Cases 1028

a. 8 cells (22.9%) have expected count less than 5. The minimum expected count is 1.39.

95 | P a g e

Q3.2 Age * Q1.3 Average Travel Distance

Crosstab

Count

Q1.3 Average Travel Distance

<=3 km 3-6 km 6-9 km 9-12 km 12-15 km

Q3.2 Age <=15 Years old 13 3 4 2 4

16-30 Years old 72 61 58 68 58

31-45 Years old 27 27 31 24 23

46-60 Years old 31 13 20 31 15

> 60 Years old 7 5 5 3 4

Total 150 109 118 128 104

Crosstab

Count

Q1.3 Average Travel

Distance

> 15 km Total

Q3.2 Age <=15 Years old 5 31

16-30 Years old 263 580

31-45 Years old 62 194

46-60 Years old 67 177

> 60 Years old 18 42

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Crosstab

Count

Q1.3 Average Travel

Distance

> 15 km Total

Q3.2 Age <=15 Years old 5 31

16-30 Years old 263 580

31-45 Years old 62 194

46-60 Years old 67 177

> 60 Years old 18 42

Total 415 1024

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 46.128a 20 .001

Likelihood Ratio 42.069 20 .003

Linear-by-Linear Association .624 1 .429

N of Valid Cases 1024

a. 8 cells (26.7%) have expected count less than 5. The minimum expected count is 3.15.

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Q3.2 Age * Q2.2 Prefer way to cross the road

Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing Skywalks Subways Total

Q3.2 Age <=15 Years old 22 7 2 31

16-30 Years old 421 109 49 579

31-45 Years old 141 33 22 196

46-60 Years old 136 28 14 178

> 60 Years old 35 2 5 42

Total 755 179 92 1026

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.353a 8 .400

Likelihood Ratio 9.788 8 .280

Linear-by-Linear Association .599 1 .439

N of Valid Cases 1026

a. 2 cells (13.3%) have expected count less than 5. The minimum expected count is 2.78.

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Q3.2 Age * Q2.4 Willing to walk to access crossing

Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m 51-100 m 101-150 m 151-200 m 201-250 m

Q3.2 Age <=15 Years old 13 9 4 2 0

16-30 Years old 254 178 71 47 10

31-45 Years old 94 59 22 8 4

46-60 Years old 58 63 22 18 6

> 60 Years old 19 14 4 2 1

Total 438 323 123 77 21

Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m >300 m Total

Q3.2 Age <=15 Years old 0 2 30

16-30 Years old 1 17 578

31-45 Years old 2 5 194

46-60 Years old 1 8 176

> 60 Years old 1 0 41

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Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m >300 m Total

Q3.2 Age <=15 Years old 0 2 30

16-30 Years old 1 17 578

31-45 Years old 2 5 194

46-60 Years old 1 8 176

> 60 Years old 1 0 41

Total 5 32 1019

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 24.744a 24 .420

Likelihood Ratio 25.467 24 .381

Linear-by-Linear Association 1.169 1 .280

N of Valid Cases 1019

a. 15 cells (42.9%) have expected count less than 5. The minimum expected count is .15.

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Q3.2 Age * Q2.5 When do you think you are most exposed to air pollution

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking Cycle Bus MTR Light Bus Car/Taxi

Q3.2 Age <=15 Years old 2 1 4 1 0 0

16-30 Years old 167 9 22 9 2 2

31-45 Years old 56 0 6 3 1 3

46-60 Years old 49 2 5 0 3 2

> 60 Years old 7 0 1 0 0 0

Total 281 12 38 13 6 7

Crosstab

Count

Q2.5 When do you think you are most

exposed to air pollution

Two Wheeler

Waiting for

transportation Total

Q3.2 Age <=15 Years old 2 20 30

16-30 Years old 7 353 571

31-45 Years old 4 122 195

46-60 Years old 0 117 178

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> 60 Years old 0 34 42

Total 13 646 1016

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 46.111a 28 .017

Likelihood Ratio 48.934 28 .008

Linear-by-Linear Association 1.940 1 .164

N of Valid Cases 1016

a. 24 cells (60.0%) have expected count less than 5. The minimum expected count is .18.

Q3.2 Age * Q2.6 Do you plan to change mode

Crosstab

Count

Q2.6 Do you plan to change mode

Yes No Total

Q3.2 Age <=15 Years old 9 22 31

16-30 Years old 170 410 580

31-45 Years old 56 139 195

46-60 Years old 56 122 178

> 60 Years old 15 25 40

Total 306 718 1024

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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 1.547a 4 .818

Likelihood Ratio 1.500 4 .827

Linear-by-Linear Association .863 1 .353

N of Valid Cases 1024

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 9.26.

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Q3.3 Household Income * Q1.2 Average Travel Time

Crosstab

Count

Q1.2 Average Travel Time

<=15 min 16-30 min 31-45 min 46-60 min

Q3.3 Household Income <$4000 7 23 19 18

$4000-$15999 19 77 93 81

$16000-$27999 27 66 93 74

$28000-$39999 9 28 37 37

>40000 6 20 25 24

Total 68 214 267 234

Crosstab

Count

Q1.2 Average Travel Time

61-75 min 76-90 min > 90 min Total

Q3.3 Household Income <$4000 8 7 10 92

$4000-$15999 29 17 30 346

$16000-$27999 33 12 25 330

$28000-$39999 18 6 13 148

>40000 14 4 10 103

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Crosstab

Count

Q1.2 Average Travel Time

61-75 min 76-90 min > 90 min Total

Q3.3 Household Income <$4000 8 7 10 92

$4000-$15999 29 17 30 346

$16000-$27999 33 12 25 330

$28000-$39999 18 6 13 148

>40000 14 4 10 103

Total 102 46 88 1019

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 13.355a 24 .960

Likelihood Ratio 12.958 24 .967

Linear-by-Linear Association .278 1 .598

N of Valid Cases 1019

a. 2 cells (5.7%) have expected count less than 5. The minimum expected count is 4.15.

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Q3.3 Household Income * Q1.3 Average Travel Distance

Crosstab

Count

Q1.3 Average Travel Distance

<=3 km 3-6 km 6-9 km 9-12 km 12-15 km

Q3.3 Household Income <$4000 15 14 8 17 10

$4000-$15999 51 48 43 40 28

$16000-$27999 53 30 36 32 37

$28000-$39999 18 7 17 18 13

>40000 12 10 13 17 16

Total 149 109 117 124 104

Crosstab

Count

Q1.3 Average Travel

Distance

> 15 km Total

Q3.3 Household Income <$4000 28 92

$4000-$15999 133 343

$16000-$27999 142 330

$28000-$39999 74 147

>40000 35 103

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Crosstab

Count

Q1.3 Average Travel

Distance

> 15 km Total

Q3.3 Household Income <$4000 28 92

$4000-$15999 133 343

$16000-$27999 142 330

$28000-$39999 74 147

>40000 35 103

Total 412 1015

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 32.765a 20 .036

Likelihood Ratio 33.069 20 .033

Linear-by-Linear Association 5.995 1 .014

N of Valid Cases 1015

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 9.43.

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Q3.3 Household Income * Q2.2 Prefer way to cross the road

Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing Skywalks Subways Total

Q3.3 Household Income <$4000 61 23 8 92

$4000-$15999 256 57 32 345

$16000-$27999 242 60 27 329

$28000-$39999 114 20 14 148

>40000 75 18 10 103

Total 748 178 91 1017

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 5.879a 8 .661

Likelihood Ratio 5.669 8 .684

Linear-by-Linear Association .336 1 .562

N of Valid Cases 1017

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.23.

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Q3.3 Household Income * Q2.4 Willing to walk to access crossing

Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m 51-100 m 101-150 m 151-200 m

Q3.3 Household Income <$4000 38 27 11 11

$4000-$15999 144 106 52 25

$16000-$27999 146 103 34 22

$28000-$39999 63 51 17 11

>40000 44 32 7 8

Total 435 319 121 77

Crosstab

Count

Q2.4 Willing to walk to access crossing

201-250 m 251-300 m >300 m Total

Q3.3 Household Income <$4000 1 0 4 92

$4000-$15999 8 0 6 341

$16000-$27999 8 0 15 328

$28000-$39999 3 1 2 148

>40000 1 4 5 101

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Crosstab

Count

Q2.4 Willing to walk to access crossing

201-250 m 251-300 m >300 m Total

Q3.3 Household Income <$4000 1 0 4 92

$4000-$15999 8 0 6 341

$16000-$27999 8 0 15 328

$28000-$39999 3 1 2 148

>40000 1 4 5 101

Total 21 5 32 1010

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 46.316a 24 .004

Likelihood Ratio 35.676 24 .059

Linear-by-Linear Association .055 1 .814

N of Valid Cases 1010

a. 11 cells (31.4%) have expected count less than 5. The minimum expected count is .46.

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Q3.3 Household Income * Q2.5 When do you think you are most exposed to air pollution

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking Cycle Bus MTR Light Bus

Q3.3 Household Income <$4000 27 1 1 0 0

$4000-$15999 91 4 19 7 2

$16000-$27999 92 4 9 4 2

$28000-$39999 39 0 6 0 1

>40000 29 2 3 2 1

Total 278 11 38 13 6

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Car/Taxi Two Wheeler

Waiting for

transportation Total

Q3.3 Household Income <$4000 1 1 60 91

$4000-$15999 2 5 212 342

$16000-$27999 1 4 207 323

$28000-$39999 1 1 100 148

>40000 2 2 62 103

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Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Car/Taxi Two Wheeler

Waiting for

transportation Total

Q3.3 Household Income <$4000 1 1 60 91

$4000-$15999 2 5 212 342

$16000-$27999 1 4 207 323

$28000-$39999 1 1 100 148

>40000 2 2 62 103

Total 7 13 641 1007

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 19.180a 28 .893

Likelihood Ratio 23.814 28 .691

Linear-by-Linear Association .016 1 .900

N of Valid Cases 1007

a. 27 cells (67.5%) have expected count less than 5. The minimum expected count is .54.

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Q3.3 Household Income * Q2.6 Do you plan to change mode

Crosstab

Count

Q2.6 Do you plan to change mode

Yes No Total

Q3.3 Household Income <$4000 25 66 91

$4000-$15999 94 250 344

$16000-$27999 101 228 329

$28000-$39999 43 105 148

>40000 39 64 103

Total 302 713 1015

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 4.614a 4 .329

Likelihood Ratio 4.490 4 .344

Linear-by-Linear Association 3.063 1 .080

N of Valid Cases 1015

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 27.08.

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ANNEX 6

Results of the Pedestrian Preference Survey ANOVA BY GROUPS

Correlation test (Q2.1 vs Q2.4)

Correlations

Q2.1 Rate the Pedestrian

facilities

Q2.4 Willing to walk to

access crossing

Q2.1 Rate the Pedestrian facilities Pearson Correlation 1 .055

Sig. (2-tailed)

.081

N 1026 1016

Q2.4 Willing to walk to access crossing Pearson Correlation .055 1

Sig. (2-tailed) .081

N 1016 1019

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ANOVA within Q2.3

Descriptives

Q2.3

N Mean Std. Deviation Std. Error

Easy access 1025 3.3493 1.12455 .03513

Improved street lighting 1023 2.8671 1.05704 .03305

Wider footpaths 1024 3.4990 1.05749 .03305

Level footpaths 1023 3.3011 1.03994 .03251

Clean sidewalks 1023 3.5376 1.09361 .03419

Reduced traffic 1020 3.3637 1.09601 .03432

Reduced speed 1022 2.9941 1.02370 .03202

Remove obstacles 1024 3.5088 1.01789 .03181

More crossing point 1020 3.5843 1.02651 .03214

Weather proof 1019 3.3651 1.20746 .03783

Total 10223 3.3370 1.09829 .01086

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Descriptives

Q2.3

95% Confidence Interval for Mean

Lower Bound Upper Bound Minimum Maximum

Easy access 3.2803 3.4182 1.00 5.00

Improved street lighting 2.8022 2.9319 1.00 5.00

Wider footpaths 3.4342 3.5639 1.00 5.00

Level footpaths 3.2373 3.3649 1.00 5.00

Clean sidewalks 3.4705 3.6047 1.00 5.00

Reduced traffic 3.2964 3.4311 1.00 5.00

Reduced speed 2.9313 3.0570 1.00 5.00

Remove obstacles 3.4464 3.5712 1.00 5.00

More crossing point 3.5212 3.6474 1.00 5.00

Weather proof 3.2908 3.4393 1.00 5.00

Total 3.3157 3.3583 1.00 5.00

116 | P a g e

ANOVA

Q2.3

Sum of Squares df Mean Square F Sig.

Between Groups 509.746 9 56.638 48.937 .000

Within Groups 11820.340 10213 1.157

Total 12330.086 10222

Post Hoc Tests

Multiple Comparisons

Q2.3, LSD

(I) Variables (J) Variables

95% Confidence Interval

Mean Difference

(I-J) Std. Error Sig. Lower Bound Upper Bound

Easy access Improved street lighting .48221* .04754 .000 .3890 .5754

Wider footpaths -.14976* .04753 .002 -.2429 -.0566

Level footpaths .04819 .04754 .311 -.0450 .1414

Clean sidewalks -.18837* .04754 .000 -.2816 -.0952

Reduced traffic -.01446 .04758 .761 -.1077 .0788

Reduced speed .35514* .04756 .000 .2619 .4484

Remove obstacles -.15952* .04753 .001 -.2527 -.0663

117 | P a g e

More crossing point -.23505* .04758 .000 -.3283 -.1418

Weather proof -.01580 .04759 .740 -.1091 .0775

Improved street lighting Easy access -.48221* .04754 .000 -.5754 -.3890

Wider footpaths -.63197* .04756 .000 -.7252 -.5387

Level footpaths -.43402* .04757 .000 -.5273 -.3408

Clean sidewalks -.67058* .04757 .000 -.7638 -.5773

Reduced traffic -.49667* .04760 .000 -.5900 -.4034

Reduced speed -.12707* .04758 .008 -.2203 -.0338

Remove obstacles -.64173* .04756 .000 -.7350 -.5485

More crossing point -.71726* .04760 .000 -.8106 -.6239

Weather proof -.49801* .04761 .000 -.5913 -.4047

Wider footpaths Easy access .14976* .04753 .002 .0566 .2429

Improved street lighting .63197* .04756 .000 .5387 .7252

Level footpaths .19795* .04756 .000 .1047 .2912

Clean sidewalks -.03861 .04756 .417 -.1318 .0546

Reduced traffic .13530* .04759 .004 .0420 .2286

Reduced speed .50489* .04757 .000 .4117 .5981

Remove obstacles -.00977 .04754 .837 -.1030 .0834

More crossing point -.08529 .04759 .073 -.1786 .0080

Weather proof .13396* .04760 .005 .0406 .2273

Level footpaths Easy access -.04819 .04754 .311 -.1414 .0450

118 | P a g e

Improved street lighting .43402* .04757 .000 .3408 .5273

Wider footpaths -.19795* .04756 .000 -.2912 -.1047

Clean sidewalks -.23656* .04757 .000 -.3298 -.1433

Reduced traffic -.06265 .04760 .188 -.1560 .0307

Reduced speed .30695* .04758 .000 .2137 .4002

Remove obstacles -.20771* .04756 .000 -.3009 -.1145

More crossing point -.28324* .04760 .000 -.3765 -.1899

Weather proof -.06399 .04761 .179 -.1573 .0293

Clean sidewalks Easy access .18837* .04754 .000 .0952 .2816

Improved street lighting .67058* .04757 .000 .5773 .7638

Wider footpaths .03861 .04756 .417 -.0546 .1318

Level footpaths .23656* .04757 .000 .1433 .3298

Reduced traffic .17391* .04760 .000 .0806 .2672

Reduced speed .54351* .04758 .000 .4502 .6368

Remove obstacles .02885 .04756 .544 -.0644 .1221

More crossing point -.04668 .04760 .327 -.1400 .0466

Weather proof .17257* .04761 .000 .0792 .2659

Reduced traffic Easy access .01446 .04758 .761 -.0788 .1077

Improved street lighting .49667* .04760 .000 .4034 .5900

Wider footpaths -.13530* .04759 .004 -.2286 -.0420

Level footpaths .06265 .04760 .188 -.0307 .1560

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Clean sidewalks -.17391* .04760 .000 -.2672 -.0806

Reduced speed .36960* .04761 .000 .2763 .4629

Remove obstacles -.14506* .04759 .002 -.2384 -.0518

More crossing point -.22059* .04764 .000 -.3140 -.1272

Weather proof -.00134 .04765 .978 -.0947 .0921

Reduced speed Easy access -.35514* .04756 .000 -.4484 -.2619

Improved street lighting .12707* .04758 .008 .0338 .2203

Wider footpaths -.50489* .04757 .000 -.5981 -.4117

Level footpaths -.30695* .04758 .000 -.4002 -.2137

Clean sidewalks -.54351* .04758 .000 -.6368 -.4502

Reduced traffic -.36960* .04761 .000 -.4629 -.2763

Remove obstacles -.51466* .04757 .000 -.6079 -.4214

More crossing point -.59018* .04761 .000 -.6835 -.4969

Weather proof -.37093* .04763 .000 -.4643 -.2776

Remove obstacles Easy access .15952* .04753 .001 .0663 .2527

Improved street lighting .64173* .04756 .000 .5485 .7350

Wider footpaths .00977 .04754 .837 -.0834 .1030

Level footpaths .20771* .04756 .000 .1145 .3009

Clean sidewalks -.02885 .04756 .544 -.1221 .0644

Reduced traffic .14506* .04759 .002 .0518 .2384

Reduced speed .51466* .04757 .000 .4214 .6079

120 | P a g e

More crossing point -.07552 .04759 .113 -.1688 .0178

Weather proof .14373* .04760 .003 .0504 .2370

More crossing point Easy access .23505* .04758 .000 .1418 .3283

Improved street lighting .71726* .04760 .000 .6239 .8106

Wider footpaths .08529 .04759 .073 -.0080 .1786

Level footpaths .28324* .04760 .000 .1899 .3765

Clean sidewalks .04668 .04760 .327 -.0466 .1400

Reduced traffic .22059* .04764 .000 .1272 .3140

Reduced speed .59018* .04761 .000 .4969 .6835

Remove obstacles .07552 .04759 .113 -.0178 .1688

Weather proof .21925* .04765 .000 .1258 .3127

Weather proof Easy access .01580 .04759 .740 -.0775 .1091

Improved street lighting .49801* .04761 .000 .4047 .5913

Wider footpaths -.13396* .04760 .005 -.2273 -.0406

Level footpaths .06399 .04761 .179 -.0293 .1573

Clean sidewalks -.17257* .04761 .000 -.2659 -.0792

Reduced traffic .00134 .04765 .978 -.0921 .0947

Reduced speed .37093* .04763 .000 .2776 .4643

Remove obstacles -.14373* .04760 .003 -.2370 -.0504

More crossing point -.21925* .04765 .000 -.3127 -.1258

*. The mean difference is significant at the 0.05 level.

121 | P a g e

Means Plots

122 | P a g e

T-Test (between walk and non-walk)

ANOVA

Sum of Squares df Sig

Q2.1 Rate the Pedestrian facilities Between Groups .142 1 0.600

Within Groups 528.065 1024

Total 528.207 1025

Q2.2 Prefer way to cross the road Between Groups .021 1 0.821

Within Groups 418.674 1025

Total 418.695 1026

Q2.3 Easy Access Between Groups 3.302 1 0.106

Within Groups 1291.660 1023

Total 1294.962 1024

Q2.3 Improved street lighting Between Groups 2.113 1 .0169

Within Groups 1139.807 1021

Total 1141.920 1022

Q2.3 Wider footpaths Between Groups 1.968 1 0.185

Within Groups 1142.031 1022

Total 1143.999 1023

Q2.3 Level footpaths Between Groups 1.512 1 0.237

Within Groups 1103.757 1021

123 | P a g e

Total 1105.269 1022

Q2.3 Clean sidewalks Between Groups .069 1 0.810

Within Groups 1222.232 1021

Total 1222.301 1022

Q2.3 Reduced traffic Between Groups .663 1 0.458

Within Groups 1223.394 1018

Total 1224.058 1019

Q2.3 Reduced speed Between Groups .117 1 0.739

Within Groups 1069.848 1020

Total 1069.965 1021

Q2.3 Remove obstacles Between Groups .263 1 0.615

Within Groups 1059.658 1022

Total 1059.921 1023

Q2.3 More crossing point Between Groups .905 1 0.354

Within Groups 1072.844 1018

Total 1073.749 1019

Q2.3 Weather proof Between Groups .309 1 0.646

Within Groups 1483.887 1017

Total 1484.196 1018

124 | P a g e

Crosstab between Q 2.2 and Q 2.4

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 20.787a 12 .054

Likelihood Ratio 18.587 12 .099

Linear-by-Linear Association 2.984 1 .084

N of Valid Cases 1017

a. 6 cells (28.6%) have expected count less than 5. The minimum expected count is .45.

125 | P a g e

ANOVA (Q 2.6 and Q 2.3)

ANOVA

Sum of Squares df Sig

Q2.1 Rate the Pedestrian facilities Between Groups 1.673 1 0.072

Within Groups 524.488 1020

Total 526.160 1021

Q2.3 Easy Access Between Groups .163 1 0.719

Within Groups 1284.791 1019

Total 1284.954 1020

Q2.3 Improved street lighting Between Groups 14.763 1 0.000

Within Groups 1118.352 1017

Total 1133.115 1018

Q2.3 Wider footpaths Between Groups 5.643 1 0.025

Within Groups 1135.356 1018

Total 1140.999 1019

Q2.3 Level footpaths Between Groups 3.258 1 0.083

Within Groups 1100.852 1017

Total 1104.110 1018

Q2.3 Clean sidewalks Between Groups 16.154 1 0.000

Within Groups 1201.141 1017

Total 1217.295 1018

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Q2.3 Reduced traffic Between Groups 4.476 1 0.054

Within Groups 1215.319 1014

Total 1219.795 1015

Q2.3 Reduced speed Between Groups 5.493 1 0.022

Within Groups 1058.491 1016

Total 1063.984 1017

Q2.3 Remove obstacles Between Groups 8.958 1 0.003

Within Groups 1047.923 1018

Total 1056.881 1019

Q2.3 More crossing point Between Groups 10.291 1 0.002

Within Groups 1060.598 1014

Total 1070.889 1015

Q2.3 Weather proof Between Groups 12.906 1 0.003

Within Groups 1470.217 1013

Total 1483.123 1014

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Chi Square test (Walking/non-walking mode vs Q2.4, Q2.5, Q2.6)

Q1.1 Walk/Traffic Mode * Q2.4 Willing to walk to access crossing

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 6.756a 6 .344

Likelihood Ratio 6.774 6 .342

Linear-by-Linear Association 1.156 1 .282

N of Valid Cases 1019

a. 2 cells (14.3%) have expected count less than 5. The minimum expected count is 1.95.

Q1.1 Walk/Traffic Mode * Q2.5 When do you think you are most exposed to air pollution

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 3.865a 7 .795

Likelihood Ratio 3.839 7 .798

Linear-by-Linear Association .012 1 .912

N of Valid Cases 1016

a. 5 cells (31.3%) have expected count less than 5. The minimum expected count is 2.34.

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Q1.1 Walk/Traffic Mode * Q2.6 Do you plan to change mode

Chi-Square Tests

Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided)

Pearson Chi-Square .001a 1 .980

Continuity Correctionb .000 1 1.000

Likelihood Ratio .001 1 .980

Fisher's Exact Test

1.000 .517

Linear-by-Linear Association .001 1 .980

N of Valid Cases 1025

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 118.82.

b. Computed only for a 2x2 table

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Chi-Square test for Q2.2 vs Q2.3

Q2.2 Prefer way to cross the road * Q2.3 Easy Access

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 12.727a 8 .122

Likelihood Ratio 14.219 8 .076

Linear-by-Linear Association 1.060 1 .303

N of Valid Cases 1023

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.76.

Q2.2 Prefer way to cross the road * Q2.3 Improved street lighting

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 1.621a 8 .991

Likelihood Ratio 1.580 8 .991

Linear-by-Linear Association .104 1 .748

N of Valid Cases 1021

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.86.

Q2.2 Prefer way to cross the road * Q2.3 Wider footpaths

Chi-Square Tests

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Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 5.710a 8 .680

Likelihood Ratio 5.858 8 .663

Linear-by-Linear Association .162 1 .687

N of Valid Cases 1022

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 2.88.

Q2.2 Prefer way to cross the road * Q2.3 Level footpaths

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 7.976a 8 .436

Likelihood Ratio 7.958 8 .438

Linear-by-Linear Association 2.241 1 .134

N of Valid Cases 1021

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 4.55.

Q2.2 Prefer way to cross the road * Q2.3 Clean sidewalks

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.626a 8 .375

Likelihood Ratio 8.948 8 .347

Linear-by-Linear Association .084 1 .772

N of Valid Cases 1021

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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.626a 8 .375

Likelihood Ratio 8.948 8 .347

Linear-by-Linear Association .084 1 .772

N of Valid Cases 1021

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 3.24.

Q2.2 Prefer way to cross the road * Q2.3 Reduced traffic

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 18.456a 8 .018

Likelihood Ratio 19.678 8 .012

Linear-by-Linear Association 2.774 1 .096

N of Valid Cases 1018

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 4.43.

Q2.2 Prefer way to cross the road * Q2.3 Reduced speed

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 21.571a 8 .006

Likelihood Ratio 20.447 8 .009

Linear-by-Linear Association 11.822 1 .001

N of Valid Cases 1020

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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 21.571a 8 .006

Likelihood Ratio 20.447 8 .009

Linear-by-Linear Association 11.822 1 .001

N of Valid Cases 1020

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6.85.

Q2.2 Prefer way to cross the road * Q2.3 Remove obstacles

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 11.276a 8 .187

Likelihood Ratio 11.451 8 .177

Linear-by-Linear Association .838 1 .360

N of Valid Cases 1022

a. 2 cells (13.3%) have expected count less than 5. The minimum expected count is 1.89.

Q2.2 Prefer way to cross the road * Q2.3 More crossing point

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.365a 8 .399

Likelihood Ratio 8.480 8 .388

Linear-by-Linear Association 1.084 1 .298

N of Valid Cases 1018

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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 8.365a 8 .399

Likelihood Ratio 8.480 8 .388

Linear-by-Linear Association 1.084 1 .298

N of Valid Cases 1018

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 2.98.

Q2.2 Prefer way to cross the road * Q2.3 Weather proof

Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 7.284a 8 .506

Likelihood Ratio 8.247 8 .410

Linear-by-Linear Association 1.236 1 .266

N of Valid Cases 1017

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.05.

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ANNEX 7

Results of the Pedestrian Preference Survey TRAFFIC MODE COUNT FREQUENCY

Number of mode

Frequency Table

Q1.1 Number of mode

Frequency Percent Valid Percent Cumulative Percent

Valid 1.00 126 12.2 12.2 12.2

2.00 465 45.2 45.2 57.4

3.00 247 24.0 24.0 81.4

4.00 120 11.7 11.7 93.1

5.00 49 4.8 4.8 97.9

6.00 14 1.4 1.4 99.2

7.00 4 .4 .4 99.6

8.00 4 .4 .4 100.0

Total 1029 100.0 100.0

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Major Transport Mode

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 401 39.0 39.0 39.0

Cycle 4 .4 .4 39.4

MTR 344 33.4 33.4 72.8

Two Wheeler 53 5.2 5.2 77.9

Car/Taxi 20 1.9 1.9 79.9

Mini Bus 21 2.0 2.0 81.9

Bus 174 16.9 16.9 98.8

Others 12 1.2 1.2 100.0

Total 1029 100.0 100.0

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Transport Mode (Walk/Vehicle)

Q1.1 Walk/Traffic Mode

Frequency Percent Valid Percent Cumulative Percent

Valid Walk 401 39.0 39.0 39.0

Vehicle 628 61.0 61.0 100.0

Total 1029 100.0 100.0

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Selected cases for worst and bad in question 2.1

Frequency Table

Q2.3 Easy Access

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 10 3.7 3.7 3.7

Less wanted 52 19.0 19.2 22.9

Fair 82 30.0 30.3 53.1

Wanted 78 28.6 28.8 81.9

The most wanted 49 17.9 18.1 100.0

Total 271 99.3 100.0

Missing System 2 .7

Total 273 100.0

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Q2.3 Improved street lighting

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 30 11.0 11.0 11.0

Less wanted 65 23.8 23.9 34.9

Fair 100 36.6 36.8 71.7

Wanted 59 21.6 21.7 93.4

The most wanted 18 6.6 6.6 100.0

Total 272 99.6 100.0

Missing System 1 .4

Total 273 100.0

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Q2.3 Wider footpaths

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 12 4.4 4.4 4.4

Less wanted 52 19.0 19.2 23.6

Fair 79 28.9 29.2 52.8

Wanted 86 31.5 31.7 84.5

The most wanted 42 15.4 15.5 100.0

Total 271 99.3 100.0

Missing System 2 .7

Total 273 100.0

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Q2.3 Level footpaths

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 20 7.3 7.4 7.4

Less wanted 68 24.9 25.0 32.4

Fair 91 33.3 33.5 65.8

Wanted 68 24.9 25.0 90.8

The most wanted 25 9.2 9.2 100.0

Total 272 99.6 100.0

Missing System 1 .4

Total 273 100.0

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Q2.3 Clean sidewalks

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 10 3.7 3.7 3.7

Less wanted 42 15.4 15.5 19.2

Fair 94 34.4 34.7 53.9

Wanted 70 25.6 25.8 79.7

The most wanted 55 20.1 20.3 100.0

Total 271 99.3 100.0

Missing System 2 .7

Total 273 100.0

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Q2.3 Reduced traffic

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 13 4.8 4.8 4.8

Less wanted 61 22.3 22.6 27.4

Fair 80 29.3 29.6 57.0

Wanted 70 25.6 25.9 83.0

The most wanted 46 16.8 17.0 100.0

Total 270 98.9 100.0

Missing System 3 1.1

Total 273 100.0

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Q2.3 Reduced speed

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 27 9.9 10.0 10.0

Less wanted 74 27.1 27.4 37.4

Fair 109 39.9 40.4 77.8

Wanted 43 15.8 15.9 93.7

The most wanted 17 6.2 6.3 100.0

Total 270 98.9 100.0

Missing System 3 1.1

Total 273 100.0

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Q2.3 Remove obstacles

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 7 2.6 2.6 2.6

Less wanted 53 19.4 19.6 22.2

Fair 100 36.6 37.0 59.3

Wanted 66 24.2 24.4 83.7

The most wanted 44 16.1 16.3 100.0

Total 270 98.9 100.0

Missing System 3 1.1

Total 273 100.0

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Q2.3 More crossing point

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 9 3.3 3.3 3.3

Less wanted 31 11.4 11.4 14.8

Fair 97 35.5 35.8 50.6

Wanted 80 29.3 29.5 80.1

The most wanted 54 19.8 19.9 100.0

Total 271 99.3 100.0

Missing System 2 .7

Total 273 100.0

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Q2.3 Weather proof

Frequency Percent Valid Percent Cumulative Percent

Valid The least wanted 31 11.4 11.5 11.5

Less wanted 35 12.8 13.0 24.4

Fair 84 30.8 31.1 55.6

Wanted 69 25.3 25.6 81.1

The most wanted 51 18.7 18.9 100.0

Total 270 98.9 100.0

Missing System 3 1.1

Total 273 100.0

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Average Travel time and travel distance for each mode

Major mode = walking

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 min 66 16.5 16.5 16.5

16-30 min 125 31.2 31.2 47.6

31-45 min 101 25.2 25.2 72.8

46-60 min 54 13.5 13.5 86.3

61-75 min 18 4.5 4.5 90.8

76-90 min 7 1.7 1.7 92.5

> 90 min 30 7.5 7.5 100.0

Total 401 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 126 31.4 31.5 31.5

3-6 km 65 16.2 16.3 47.8

6-9 km 48 12.0 12.0 59.8

9-12 km 42 10.5 10.5 70.3

12-15 km 30 7.5 7.5 77.8

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> 15 km 89 22.2 22.3 100.0

Total 400 99.8 100.0

Missing System 1 .2

Total 401 100.0

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Major mode = Cycle

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid 16-30 min 2 50.0 50.0 50.0

31-45 min 1 25.0 25.0 75.0

> 90 min 1 25.0 25.0 100.0

Total 4 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid 3-6 km 2 50.0 50.0 50.0

> 15 km 2 50.0 50.0 100.0

Total 4 100.0 100.0

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Major mode = MTR

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 min 1 .3 .3 .3

16-30 min 43 12.5 12.5 12.8

31-45 min 84 24.4 24.4 37.2

46-60 min 106 30.8 30.8 68.0

61-75 min 51 14.8 14.8 82.8

76-90 min 23 6.7 6.7 89.5

> 90 min 36 10.5 10.5 100.0

Total 344 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 7 2.0 2.0 2.0

3-6 km 23 6.7 6.7 8.7

6-9 km 25 7.3 7.3 16.0

9-12 km 52 15.1 15.2 31.2

12-15 km 44 12.8 12.8 44.0

> 15 km 192 55.8 56.0 100.0

Total 343 99.7 100.0

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Missing System 1 .3

Total 344 100.0

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Major mode = two wheeler

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid 16-30 min 11 20.8 20.8 20.8

31-45 min 15 28.3 28.3 49.1

46-60 min 14 26.4 26.4 75.5

61-75 min 6 11.3 11.3 86.8

76-90 min 3 5.7 5.7 92.5

> 90 min 4 7.5 7.5 100.0

Total 53 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 5 9.4 9.4 9.4

3-6 km 3 5.7 5.7 15.1

6-9 km 10 18.9 18.9 34.0

9-12 km 6 11.3 11.3 45.3

12-15 km 5 9.4 9.4 54.7

> 15 km 24 45.3 45.3 100.0

Total 53 100.0 100.0

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Major mode = Car/taxi

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid 16-30 min 6 30.0 30.0 30.0

31-45 min 6 30.0 30.0 60.0

46-60 min 4 20.0 20.0 80.0

61-75 min 1 5.0 5.0 85.0

> 90 min 3 15.0 15.0 100.0

Total 20 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 1 5.0 5.0 5.0

3-6 km 3 15.0 15.0 20.0

6-9 km 4 20.0 20.0 40.0

9-12 km 2 10.0 10.0 50.0

12-15 km 1 5.0 5.0 55.0

> 15 km 9 45.0 45.0 100.0

Total 20 100.0 100.0

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Major mode = Mini Bus

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 min 1 4.8 4.8 4.8

16-30 min 6 28.6 28.6 33.3

31-45 min 10 47.6 47.6 81.0

46-60 min 2 9.5 9.5 90.5

61-75 min 1 4.8 4.8 95.2

> 90 min 1 4.8 4.8 100.0

Total 21 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 1 4.8 4.8 4.8

3-6 km 3 14.3 14.3 19.0

6-9 km 2 9.5 9.5 28.6

9-12 km 2 9.5 9.5 38.1

12-15 km 2 9.5 9.5 47.6

> 15 km 11 52.4 52.4 100.0

Total 21 100.0 100.0

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Major mode = Bus

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 min 2 1.1 1.1 1.1

16-30 min 19 10.9 10.9 12.1

31-45 min 48 27.6 27.6 39.7

46-60 min 54 31.0 31.0 70.7

61-75 min 25 14.4 14.4 85.1

76-90 min 12 6.9 6.9 92.0

> 90 min 14 8.0 8.0 100.0

Total 174 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 9 5.2 5.2 5.2

3-6 km 11 6.3 6.4 11.6

6-9 km 26 14.9 15.1 26.7

9-12 km 23 13.2 13.4 40.1

12-15 km 20 11.5 11.6 51.7

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> 15 km 83 47.7 48.3 100.0

Total 172 98.9 100.0

Missing System 2 1.1

Total 174 100.0

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Major mode = others

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid 16-30 min 3 25.0 25.0 25.0

31-45 min 5 41.7 41.7 66.7

46-60 min 2 16.7 16.7 83.3

61-75 min 1 8.3 8.3 91.7

76-90 min 1 8.3 8.3 100.0

Total 12 100.0 100.0

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 1 8.3 8.3 8.3

6-9 km 3 25.0 25.0 33.3

9-12 km 1 8.3 8.3 41.7

12-15 km 2 16.7 16.7 58.3

> 15 km 5 41.7 41.7 100.0

Total 12 100.0 100.0

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ANNEX 8

Results of the Pedestrian Preference Survey

Single mode of transport

Frequency Table of Single walking mode

Gender

Q3.1 Gender

Frequency Percent Valid Percent Cumulative Percent

Valid Male 68 54.0 54.4 54.4

Female 57 45.2 45.6 100.0

Total 125 99.2 100.0

Missing System 1 .8

Total 126 100.0

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AGE

Q3.2 Age

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 Years old 7 5.6 5.6 5.6

16-30 Years old 73 57.9 58.4 64.0

31-45 Years old 26 20.6 20.8 84.8

46-60 Years old 17 13.5 13.6 98.4

> 60 Years old 2 1.6 1.6 100.0

Total 125 99.2 100.0

Missing System 1 .8

Total 126 100.0

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Household Income

Frequency Table

Q3.3 Household Income

Frequency Percent Valid Percent Cumulative Percent

Valid <$4000 11 8.7 8.9 8.9

$4000-$15999 48 38.1 38.7 47.6

$16000-$27999 39 31.0 31.5 79.0

$28000-$39999 11 8.7 8.9 87.9

>40000 15 11.9 12.1 100.0

Total 124 98.4 100.0

Missing System 2 1.6

Total 126 100.0

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Average Travel Time

Frequency Table

Q1.2 Average Travel Time

Frequency Percent Valid Percent Cumulative Percent

Valid <=15 min 42 33.3 33.3 33.3

16-30 min 37 29.4 29.4 62.7

31-45 min 30 23.8 23.8 86.5

46-60 min 10 7.9 7.9 94.4

61-75 min 2 1.6 1.6 96.0

76-90 min 2 1.6 1.6 97.6

> 90 min 3 2.4 2.4 100.0

Total 126 100.0 100.0

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Average Travel Distance

Frequency Table

Q1.3 Average Travel Distance

Frequency Percent Valid Percent Cumulative Percent

Valid <=3 km 66 52.4 52.4 52.4

3-6 km 10 7.9 7.9 60.3

6-9 km 8 6.3 6.3 66.7

9-12 km 9 7.1 7.1 73.8

12-15 km 6 4.8 4.8 78.6

> 15 km 27 21.4 21.4 100.0

Total 126 100.0 100.0

Bar Chart

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ANNEX 9

Results of the Pedestrian Preference Survey

Frequency Analysis by Age Groups

Frequencies (For age <15)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 20 64.5 64.5 64.5

MTR 6 19.4 19.4 83.9

Mini Bus 1 3.2 3.2 87.1

Bus 2 6.5 6.5 93.5

Others 2 6.5 6.5 100.0

Total 31 100.0 100.0

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Frequencies (For 16 < age <30)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 208 35.8 35.8 35.8

Cycle 3 .5 .5 36.3

MTR 217 37.3 37.3 73.7

Two Wheeler 40 6.9 6.9 80.6

Car/Taxi 7 1.2 1.2 81.8

Mini Bus 4 .7 .7 82.4

Bus 99 17.0 17.0 99.5

Others 3 .5 .5 100.0

Total 581 100.0 100.0

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Frequencies (For 31 < age < 45)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 76 38.8 38.8 38.8

MTR 63 32.1 32.1 70.9

Two Wheeler 5 2.6 2.6 73.5

Car/Taxi 6 3.1 3.1 76.5

Mini Bus 7 3.6 3.6 80.1

Bus 35 17.9 17.9 98.0

Others 4 2.0 2.0 100.0

Total 196 100.0 100.0

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Frequencies (For 46 < age < 60)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 75 42.1 42.1 42.1

Cycle 1 .6 .6 42.7

MTR 48 27.0 27.0 69.7

Two Wheeler 6 3.4 3.4 73.0

Car/Taxi 7 3.9 3.9 77.0

Mini Bus 6 3.4 3.4 80.3

Bus 32 18.0 18.0 98.3

Others 3 1.7 1.7 100.0

Total 178 100.0 100.0

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Frequencies (For age > 60)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 21 50.0 50.0 50.0

MTR 10 23.8 23.8 73.8

Two Wheeler 2 4.8 4.8 78.6

Mini Bus 3 7.1 7.1 85.7

Bus 6 14.3 14.3 100.0

Total 42 100.0 100.0

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ANNEX 10

Results of the Pedestrian Preference Survey

Frequency Analysis by Household Income

Frequencies (Household income < $4000)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 44 47.8 47.8 47.8

Cycle 1 1.1 1.1 48.9

MTR 28 30.4 30.4 79.3

Two Wheeler 4 4.3 4.3 83.7

Car/Taxi 3 3.3 3.3 87.0

Bus 12 13.0 13.0 100.0

Total 92 100.0 100.0

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Frequencies ($4000 < Household income < $15999)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 119 34.4 34.4 34.4

Cycle 2 .6 .6 35.0

MTR 129 37.3 37.3 72.3

Two Wheeler 31 9.0 9.0 81.2

Mini Bus 5 1.4 1.4 82.7

Bus 56 16.2 16.2 98.8

Others 4 1.2 1.2 100.0

Total 346 100.0 100.0

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Frequencies ($16000 < Household income < $27999)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 140 42.4 42.4 42.4

MTR 100 30.3 30.3 72.7

Two Wheeler 11 3.3 3.3 76.1

Car/Taxi 6 1.8 1.8 77.9

Mini Bus 10 3.0 3.0 80.9

Bus 60 18.2 18.2 99.1

Others 3 .9 .9 100.0

Total 330 100.0 100.0

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Frequencies ($28000 < Household income < $39999)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 58 39.2 39.2 39.2

MTR 51 34.5 34.5 73.6

Two Wheeler 6 4.1 4.1 77.7

Car/Taxi 1 .7 .7 78.4

Mini Bus 4 2.7 2.7 81.1

Bus 27 18.2 18.2 99.3

Others 1 .7 .7 100.0

Total 148 100.0 100.0

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Frequencies (Household income > $40000)

Q1.1 Transport Mode

Frequency Percent Valid Percent Cumulative Percent

Valid walk 36 35.0 35.0 35.0

Cycle 1 1.0 1.0 35.9

MTR 30 29.1 29.1 65.0

Two Wheeler 1 1.0 1.0 66.0

Car/Taxi 10 9.7 9.7 75.7

Mini Bus 2 1.9 1.9 77.7

Bus 19 18.4 18.4 96.1

Others 4 3.9 3.9 100.0

Total 103 100.0 100.0

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