Regression analysis related estimation approaches is common in Hedonic pricing
models in real property as well. The functional form of the hedonic regression
equation can either be linear, semi-log, or log-log form (Chin&Chau, 2002; Malpezzi,
2003; Sirman et al., 2005; Xiao, 2017). Most of the studies showed that semi-log
specification has some advantages over the linear form (Follain&Malpezzi, 1980).
Sirmans et al. (2005) confirmed three recognized advantages of log linear model, this
model will reduce heterogeneity, the coefficients are the interpretable as elasticities
and allow the change of prices according to the difference characteristics. The log
linear model is shown in this study because they are the most common. However,
model form appropriate should be explored and, during empirical phase, tests for
heterogeneity and normality will be carried out before accepting the log linear model.
This research is expressed semi-log function as Equation 1, which indicates three
types of independent variables including structural, location and neighborhood
characteristics. Dependent variables and many of independent variables are logs
transformed.
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nt of guidelines, policies, laws or has the
effect of changing the perception of society when considering sidewalks as a public
space. Contribute to built infrastructure on the surface sidewalk for improving the
quality of life, for example, pedestrian walking corridor, connectivity on public
services, limited private vehicles, safety and comfort. Currently, although the
legislation on sidewalk ownership is clearly defined, the actual use and ownership
rights are not strictly controlled by the authorities in HCMC. One of the main reasons
is that the quality of the sidewalk is poor, namely, the sidewalk width is very small,
mostly under 3 meter. Along with traffic jams and vehicle users must run on the
sidewalk. Moreover, the equally important reason is that this thesis proposes
solutions and policies for management levels and subjects in urban infrastructure
management, urban planning management, and necessary in the context of in HCMC
today.
132
Currently, although the legislation on sidewalk ownership is well defined, the actual
use and ownership rights are not strictly controlled by the authorities. One of the main
reasons is poor urban street infrastructure leading to traffic congestion and the driver
on the sidewalk. Moreover, the important reason is that sidewalk management is still
fragmented and local. The use of sidewalks in coexistence with different functions
creates the feeling that owning a sidewalk is no longer a public good. Therefore, the
management of sidewalks is also difficult in this cultural and historical context.
The urban living sidewalks account for the greatest proportion of the whole traffic
system, and a liveliness sidewalks will enrich social and economics activities and
contribute to better social life. The sidewalk is acting as a stage people actively live
in. In conclusion, a liveliness sidewak depends on the primary factors as following
the comfortable physical conditions and adjacent services. When the conditions of a
sidewalks can meet the needs and requests of people, the social life will be enhanced,
and bring in liveliness sidewalk space.
Home-owner decisions
This research results can provide recent information to people planning to buy a
home. Research shows the benefits and usability of sidewalks in front of the house.
The level of willingness to pay for home-buyer can depend on the benefits that the
sidewalk brings.
The empirical results in this study have shown that the wider sidewalk, the higher the
house value. This result only shows the positive relationship between the two
variables. Therefore, in order to reach a deeper conclusion on policy implications,
should sidewalk expansion be considered? With this result, there is not enough basis
to answer, according to the author, the study can analyze more in terms of cost and
benefit in extending sidewalk to be conclusive. This can a suggestion for the next
research direction.
133
In addition, based on research data and research results that can show that when the
sidewalk is extended by 1 meter, the house price will increase by 5 percent. In fact,
if urban planning expand sidewalks, it can only expand in the direction of reducing
the area of the house, because the expansion of sidewalks reduces the width of the
the street is impossible. Thus, when expanding the sidewalk by 1 meter, the length of
the house is reduced by 1 meter, so how much will the lot area be reduced? Based on
the survey data, the author found that the common house width is from 4 to 5 meters,
accounting for 45 percent. If the sidewalk is extended by 1 meter, the house area in
this group decreases about 7 percent.
Are home-buyers willing to accept dwindled home sizes? Home-buyers benefit from
a 1 meter sidewalk extension that increase 5 percent in property value but decline 7
percent in lot size. To answer this question, it depends on the willingness to accept of
home-buyers to consider the benefits and costs of this change.
The liveliness index and property value
Moreover, the research results also show that the higher the Liveliness index the
negative impact on property value. Accordingly, in the more lively sidewalk-
segments, the value of property decrease. However, the urban planners need to
consider maintaining the liveliness in these sidewalks or at least should not remove
it. Because lively sidewalks do not only bring benefit home-owners, particularly
those used as shophouse owners, but can also help some other people earn additional
income on these sidewalk-segments, among them are sidewalk vendors. In particular,
sidewalks in HCMC contribute greatly and can help increase the benefit from the
informal sector. If these sidewalk-segments managed well, the government can gains
a large of revenue from the sidewalk.
The encourage activities on sidewalks
It can be seen that the meaning of activities taking place on sidewalk in HCMC is
very different between day-time and night-time. This is a unique feature in HCMC
134
that is not mixed into any other place in the world. There are the large number of
sidewalk-segment in mixed-use neighborhood showed marked differences. Most of
activities took place in day-time, but these activities seemed to disappear in night-
time, and sidewalk become quiet when houses were closed and there were no people
participating in any activity. However, there are sidewalks that have the opposite
effect, during the day-time, sidewalk only has a few people participate in sidewalk
vending, store spillover activities, but people will spill out and fill these sidewalk
with all activities in night-time as sidewalk vending, store spillover, communal,
pedestrians and transportation means activities.
In society, when the government does not meet the needs of the people, the private
sector regulates itself. It also means that if there is no public space to take place,
people can create them. In the context of an integrated planning and urban
infrastructure planning that has not focused enough on household economic activities
and the informal economic sector, the study provides a basis for policy
recommendations in urban management. Research provides new knowledge,
potentially applicable to similar economies and similar cultures. The study is based
on previous studies on the role of sidewalks and public spaces in Vietnam. The study
allows us to open up new research directions in Vietnam in the issue of urban
infrastructure affecting economic activities. Especially, the planning of sidewalk
usage and the research housing price that adjacent sidewalks.
5.3 Limitations
Nevertheless, this thesis has some limitations. In terms of its data characteristics, the
main sources of data used for this thesis were obtained from walk-by observation,
direct observation, and survey with 283 observations. This is only a temporary
acceptable level and research should be conducted at a larger sample size. In addition,
during the data collection process, the study did not conduct interviews with a number
of people directly involved in activities at the sidewalk-segments. Besides, this study
135
has not considered the aspects of sidewalk ownership, the purpose of using sidewalks
to contribute to the official or informal economic activities in HCMC.
In this study, the author has calculated the liveliness index of the sidewalk-segments
based on the mixed-method. The limitation of this study is that the author has not
classified in detail as the characteristics of the people participating in the activities
such as age, gender, level of education, job, level of income. The level of education
or income is very important because it affects the level of perception and decision of
each person’s actions when using public spaces. Besides, the investment in
equipment and tools during the recording process is also very limited. Researcher and
participants may face many dangers when the survey during at night, so partly
collected data is somewhat incomplete.
LIST OF AUTHOR’S PUBLISHED PAPERS
1. Thu Nguyen (2019). The value of sidewalk in real property in commercial-
residential neighborhood. In International conference on business and finance
2019, ISBN: 978-604-922-764-6.
2. Nguyễn Thị Hồng Thu (2020). Giá trị kinh tế của vỉa hè tại Thành phố Hồ Chí
Minh. Tạp chí khoa học Đại học Mở Thành phố Hồ Chí Minh, 15(2), 73-83.
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APPENDIX
Appendix A: Choosing observational scale and good view
Fine scale: Gehl (1987) asserts that when we talk about social range in vision, 100
meters is a boundary, the point at which we can see people in motion and their body
language in roughly, and 25 meters is another significant threshold, only under which
we can precisely read facial expression and principal emotions.
A good view
It is quite interesting to look at our city, glance at surroundings and people, whether
when we are walking, standing or sitting. A good view is essential in streets. It should
be noticed that our downward and upward sights are different. We look down to
figure out where we step on, about 70-80 degrees below the horizon, while look up,
the angle of vision is limited to 50-55 degrees above the horizon (Figure 6-31). In
addition, our head is usually inclined about 10 degrees downward during normal
walking so that we can better assess the situation around. By contrast, raising our
head upwards is much more difficult (Tilley, 2002).
Appendix B: Category and percentage of activities in HCMC.
Observed activity Analytical category Percentage
Sidewalk vendor attending to buyers
- Breakfast or dinner food
- Drink shop
- Motorbike taxi drivers
- shoes or clothing marker repairing a shoes or
clothing
Sidewalk vending
21%
Children washing plates in front of house Domestic use
9%
Women cooking outside a house or a local food store
People bathing in front of house
Family eat lunch or dinner in front of house
Family members sleep in front of house
Women standing and chatting outside a store Communal
6%
People chatting and drinking
Young men chatting, drinking, smoking
Children playing outside or playing football
People seating and watching sidewalk activities
under the shade
Lady tapping on her phone
Boy seating under the tree resting
Man observing the sidewalk outside a cafe shop
People excercise in front of house
People participate in event on sidewalk
Mechanic fixing a cars or motorbike Store spillover
51%
Cars or motorbike washers, washing
Store operator selling at a house
Women attending to customers at a shop
Shop operator siting outside the store
Shop operator watching sidewalk activities
Shop keeper talking on the phone
A lady buying from the shop keeper
Men drinking cafe at a cafe shop
Shop owner display of goods
Customer cars or motorbikes parking space
Men at work on street construction Sidewalk occupancy
of pedestrians and
transportation means
activities
13%
Motorbike drivers negotiating with customers
Man offloading from a vehicle
Motorbike drivers waiting for their customer
Standing and resting by a motorbike
Pedestrians and walkers
Motorbike drivers ride on sidewalk when traffic jam
Appendix C: Some pictures describe activities on sidewalks
Parking lots front shops/stores Walking on the streets
Food shops on the sidewalk
Vendors
Physical characteristics Household activities
Appendix D: Frequency and Percent of dummy variables
Corner variable
Corner | Freq. Percent Cum.
------------+-----------------------------------
0 | 257 90.81 90.81
1 | 26 9.19 100.00
------------+-----------------------------------
Total | 283 100.00
Rental variable
Rental | Freq. Percent Cum.
------------+-----------------------------------
0 | 192 67.84 67.84
1 | 91 32.16 100.00
------------+-----------------------------------
Total | 283 100.00
Mixed-use variable
Mixed_use | Freq. Percent Cum.
------------+-----------------------------------
0 | 171 60.42 60.42
1 | 112 39.58 100.00
------------+-----------------------------------
Total | 283 100.00
SW_qual variable SW_qual | Freq. Percent Cum.
------------+-----------------------------------
0 | 73 25.80 25.80
1 | 210 74.20 100.00
------------+-----------------------------------
Total | 283 100.00
SW_material variable
SW_material | Freq. Percent Cum.
------------+-----------------------------------
0 | 23 8.13 8.13
1 | 34 12.01 20.14
2 | 140 49.47 69.61
3 | 86 30.39 100.00
------------+-----------------------------------
Total | 283 100.00
SW_fur variable
SW_fur | Freq. Percent Cum.
------------+-----------------------------------
0 | 154 54.42 54.42
1 | 129 45.58 100.00
------------+-----------------------------------
Total | 283 100.00
Street variable
Street | Freq. Percent Cum.
------------+-----------------------------------
0 | 239 84.45 84.45
1 | 44 15.55 100.00
------------+-----------------------------------
Total | 283 100.00
Oneway variable
Oneway | Freq. Percent Cum.
------------+-----------------------------------
0 | 269 95.05 95.05
1 | 10 3.53 98.59
2 | 4 1.41 100.00
------------+-----------------------------------
Total | 283 100.00
Twoway variable
Twoway | Freq. Percent Cum.
------------+-----------------------------------
0 | 235 83.04 83.04
1 | 48 16.96 100.00
------------+-----------------------------------
Total | 283 100.00
Appendix E: Scatter histogram
Appendix F: Regression models
F.1 Correlation matrix between price and day-time and night-time activities
| price d_vend~g d_dome~c d_comm~l d_store d_tran~t n_vend~g n_dome~c n_comm~l n_store n_tran~t
-------------+---------------------------------------------------------------------------------------------------
price | 1.0000
d_vending | -0.0126 1.0000
d_domestic | -0.0766 -0.0492 1.0000
d_communal | -0.0232 0.0932 0.0640 1.0000
d_store | -0.0153 0.2064 0.0359 0.1580 1.0000
d_transport | 0.0486 0.2824 -0.0265 0.1653 0.1414 1.0000
n_vending | 0.0148 0.3643 0.0279 -0.0322 0.1450 0.2173 1.0000
n_domestic | -0.0970 -0.0343 0.2257 0.0925 0.1463 -0.0514 -0.0627 1.0000
n_communal | 0.0201 0.2292 0.0136 0.3623 0.1580 0.1263 0.0512 0.0546 1.0000
n_store | 0.0121 0.0502 -0.0303 0.0584 0.3359 0.1252 0.0434 0.0260 0.0739 1.0000
n_transport | 0.0768 0.1023 -0.1343 -0.0443 0.0038 0.2412 0.0498 -0.0642 0.0512 -0.0147 1.0000
F.2 Regression results (includes districts)
Variables Model 1 Model 2 Model 3 Model 4
Coef. Coef. Coef. Coef.
Constant -1.609***
(0.191)
-1.577***
(0.199)
-1.655***
(0.195)
-1.552***
(0.197)
Structural characteristics
Lot size (square meter) 0.644***
(0.057)
0.636***
(0.056)
0.659***
(0.055)
0.643***
(0.058)
Floor size (square meter) 0.201***
(0.033)
0.200***
(0.033)
0.192***
(0.033)
0.199***
(0.034)
Corner (1=corner) -0.086
(0.063)
-0.083
(0.062)
-0.062
(0.064)
-0.077
(0.067)
Width (meter) 0.006
(0.011)
0.008
(0.011)
0.004
(0.010)
0.005
(0.011)
Property use conditions
Rental property (1 = rental
property)
0.112**
(0.047)
0.120***
(0.046)
0.137***
(0.045)
0.110**
(0.046)
Mixed-use property (1 = using
house to business and shelter)
-0.106**
(0.046)
-0.112**
(0.046)
-0.124**
(0.048)
-0.104**
(0.047)
Shophouse neighborhood (the
number of houses)
0.047***
(0.007)
0.049***
(0.007)
0.051***
(0.008)
0.050***
(0.007)
Location characteristics
Distance to CBD (kilometer) -0.058***
(0.008)
-0.058***
(0.009)
-0.053***
(0.009)
-0.056***
(0.009)
Distance to School (kilometer) -0.062
(0.038)
-0.069*
(0.040)
-0.047
(0.038)
-0.069*
(0.040)
Distance to School_squared
(square kilometer)
0.016***
(0.005)
0.017***
(0.005)
0.013***
(0.005)
0.016***
(0.005)
Distance to Hospital (kilometer) 0.181***
(0.055)
0.198***
(0.057)
0.176***
(0.054)
0.181***
(0.057)
Distance to Hospital_squared
(square kilometer)
-0.037***
(0.011)
-0.039***
(0.011)
-0.036***
(0.010)
-0.036***
(0.011)
Distance to Market (kilometer) 0.039
(0.049)
0.019
(0.051)
0.026
(0.049)
0.034
(0.049)
Sidewalk
Sidewalk width (meter) 0.047**
(0.021)
0.061**
(0.025)
0.047*
(0.027)
0.047*
(0.026)
Distance to sidewalk (meter) -0.002***
(0.000)
-0.002***
(0.000)
-0.002***
(0.000)
-0.002***
(0.000)
Sidewalk surface (1 = paved
sidewalk)
0.104*
(0.062)
0.115*
(0.062)
0.116*
(0.066)
0.120*
(0.066)
Sidewalk width*surface -0.037
(0.027)
-0.042
(0.028)
-0.036
(0.029)
-0.040
(0.031)
Sidewalk furniture (1 = sidewalk
has furniture)
0.139***
(0.037)
0.137***
(0.036)
0.132***
(0.035)
0.138***
(0.037)
Street width (meter) 0.086
(0.052)
0.096*
(0.053)
0.074
(0.055)
0.082
(0.055)
Liveliness index
Liveliness index (number) -0.029*
(0.015)
Day-time activities
D sidewalk vending (people) -0.003
(0.017)
D domestic use (people) -0.056*
(0.031)
D communal (people) -0.059***
(0.012)
D spillover store (people) 0.014
(0.013)
D transportation (people) -0.025
(0.026)
SW width*D sidewalk vending -0.002
(0.006)
SW width*D domestic use 0.030**
(0.015)
SW width*D communal 0.006
(0.004)
SW width*D spillover store -0.008*
(0.004)
SW width*D transportation 0.015*
(0.008)
Night-time activities
N sidewalk vending (people) 0.005
(0.014)
N domestic use (people) -0.019
(0.024)
N communal (people) -0.014
(0.033)
N spillover store (people) -0.005
(0.004)
N transportation (people) -0.043**
(0.020)
SW width*N sidewalk vending -0.001
(0.003)
SW width*N domestic use 0.004
(0.010)
SW width*N communal 0.001
(0.013)
SW width*N spillover store 0.001
(0.000)
SW width*N transportation 0.016*
(0.009)
Districts (Base: Binh Tan district)
Distrist 1 0.340***
(0.091)
0.347***
(0.093)
0.365***
(0.090)
0.347***
(0.092)
Distrist 3 0.357***
(0.105)
0.330***
(0.108)
0.391***
(0.103)
0.339***
(0.112)
Distrist 5 0.299***
(0.089)
0.325***
(0.085)
0.402***
(0.079)
0.298***
(0.090)
Distrist 10 0.291***
(0.074)
0.288***
(0.075)
0.323***
(0.075)
0.288***
(0.077)
Distrist 11 0.249***
(0.073)
0.250***
(0.073)
0.254***
(0.072)
0.260***
(0.076)
Phu Nhuan Distrist 0.331***
(0.068)
0.340***
(0.069)
0.335***
(0.072)
0.351***
(0.071)
Tan Binh Distrist 0.244***
(0.060)
0.259***
(0.062)
0.261***
(0.059)
0.236***
(0.060)
R_squared 0.8488 0.8518 0.8625 0.8523
F (Prob > F) 47.85
(0.000)
48.31
(0.000)
49.34
(0.000)
36.26
(0.000)
Mean VIF 4.13 4.07 4.72 4.85
AIC 102.04 98.34 95.24 115.38
BIC 200.47 200.41 230.12 250.26
F3. F test
Model 2
(1) livelinessindex = 0
F( 1, 255) = 3.59
Prob > F = 0.0592
Model 3
( 1) d_vending = 0
( 2) d_domestic = 0
( 3) d_communal = 0
( 4) d_store = 0
( 5) d_transport = 0
( 6) sw_dvending = 0
( 7) sw_ddomestic = 0
( 8) sw_dcommunal = 0
( 9) sw_dstore = 0
(10) sw_dtransport = 0
F( 10, 246) = 6.96
Prob > F = 0.0000
Model 4
( 1) n_vending = 0
( 2) n_domestic = 0
( 3) n_communal = 0
( 4) n_store = 0
( 5) n_transport = 0
( 6) sw_nvending = 0
( 7) sw_ndomestic = 0
( 8) sw_ncommunal = 0
( 9) sw_nstore = 0
(10) sw_ntransport = 0
F( 10, 246) = 5.06
Prob > F = 0.0379