An Analysis on Rent Determinants of Retail Property ...
Transcript of An Analysis on Rent Determinants of Retail Property ...
Abstract— The Purpose of this study is to analyze the
determinants of rental price of retail properties. To be specific, the
study will look into more general rent determinants of stores by
expanding its spatial extent to 7 metropolitan cities in Korea, which is
relatively wide research range compared to precedent studies in the
country. Also, the study analyzes the differences in the determinants of
rental prices between the wholesale and retail services and other
businesses through estimating hedonic price model. For this, the data
holding the distance from nearest subway station and bus stop, the
types of business and others for each retail property is used. The result
of the analysis suggests interesting features of retail property’s
determining factors of rental price as follows. In general, an
improvement in horizontal accessibility raises store’s rental price, and
the vertical accessibility such as location floor develops different level
of rent. The growth of building age and the number of elevators
provokes the increase effect on the rent, while the gross area of parking
lot allocated to 1m2 of rent area has a negative effect on it with
increasing marginal effect. However, not all of these determinants
explain the difference between the rental price of stores occupied by
wholesale and retail services and that engaged in the other businesses.
Except for the factors related to the area of parking lot per rental unit,
all the other factors have been analyzed to account for the difference.
Keywords— Rent, Rent Determinants, Retail Property, Hedonic
Price Model, Wholesale and Retail Services
I. INTRODUCTION
OMMERCIAL activity is one of the elements that form
urban activity, so there are a variety of researches with
respect to commercial activity, such as the formation and the
range of business district, the scale of commercial facilities, and
consumer shopping behavior. However, only the study on rent
determinants has been undertaken restrictively on account of
the difficulty in collecting research materials. The factors that
influence the rental price of retail property have quite
piecemeal characteristics and their spatial extents are relatively
diverse and wide. On the other hand, data is not yet that
specifically constructed because both lessor and lessee show
repulsive attitudes toward making rental price and property’s
characteristics of every kind public.
Jihye. Han, is with the Dept. of Urban Engineering, Yonsei University,
Seoul, Korea. (corresponding author to provide phone: 82-10-4278-2289; fax:
82-2-393-6298; e-mail:[email protected]). Kabsung. Kim, was with University of Pennsylvenia, PA USA. He is now
with the Department of Urban Engineering, Yonsei University, Seoul, Korea as
a professor. (e-mail: [email protected] ).
Nevertheless, an analysis on rent determining factors of retail
property is worth studying in the way that it enables proper
planning of the business area based on understandings of micro
and macro commercial activities and helps directly to analyze
property’s profitability. Against this backdrop, this study
empirically analyzes determinants of retail property’s rental
price for the purpose of partially contributing to understand
value formation elements of the retail property. To be specific,
the major study objects are identifying general determining
factors of retail rent and on that basis analyzing difference in
the rent caused by whether the property is used for wholesale
and retail services or not.
The retail property is occupied by various types of business,
such as wholesale and retail services, food and lodging industry,
educational services, health services, and personal services, but
this study focuses only on one type of business, the wholesale
and retail services. This is because of the limitation the model
itself has. The model is designed to identify the difference in
rent determinants by dummy variables, which is quite distinct
from precedent studies. However, the design of the model with
dummy variables and its interaction terms costs the model’s
degrees of freedom by increasing number of independent
variables. Therefore, for the reliability of the model, it has to be
avoided to include all types of business as dummy variables. In
addition, the reason for focusing especially on wholesale and
retail services is that the industry is the end point of production
and distribution and the start point of consumption at the same
time. In other words, since it is the target of social interests, the
analysis of rent determinants of retail property focusing on the
wholesale and retail services is expected to play a pivotal role
for understanding commercial activities in both of micro and
macro dimensions.
II. LITERATURE REVIEW
In Korea, it is quite rare that research is on identifying
determining factors of the retail property, so is the study on
specific category of retail property. The previous studies have
in common that their spatial extents are strictly restricted within
commercial facilities in Seoul and in apartment complex.
Particularly, because the studies estimated the model in the way
of classifying the data into types of business, business districts,
and regions, they investigated only the structure of rental price
of each class not the difference in rental price and its
An Analysis on Rent Determinants of
Retail Property - Focusing on Wholesale and Retail Services -
Jihye, Han and Kabsung, Kim
C
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
135
determinants between the classes. In this respect, this study is
significant in the sense that it is looking for the difference in the
rent and its determinants driven from the property’s type of
business.
Chanho Kim et al.(2001) made a close inquiry into decision
principle of store usage by explaining location characteristics
and rental price. They identified determining factors using
hedonic price model and conducted integrated analysis on five
types of usage taking note of vertical location of commercial
facilities. To be concrete, the study reinterpreted determining
process of rental price in terms of the store’s accessibility and
space preference and willingness to pay for it. As results, the
rental price goes up as the area of property increases and as the
number of stores in the same industry on the same floor
increases. It also increases if the retail property is not on the
corridor, which is easy to approach, but if not, the rental price
decreases. In the aspect of vertical accessibility, the higher the
store is located on, the lower the rent is formed.
Jaewoo, Lee et al.(2006) carefully examined the structure of
retail property’s rental price in Seoul and that of each business
district in the capital on the basis of data collected from
buildings with more than three floors located in the heart of a
city. The study is unlike Kim’s in the way that it estimated the
model for each business district where the novelty comes from.
As a result of an analysis, the store’s located floor is the only
factor that affects rental price of the retail property in the same
direction in every business district analyzed. On the other hand,
the impact of conditions of location and building characteristics
on the rent is quite distinct from district to district.
The study, such as Kim’s that focus on local area and Lee’s
that restrict the research area only to downtown, is worth
researching because it catches otherness in the specific region
or business district. However, estimation of more general
model by expanding the range of spatial extent, for example,
the research of Jongeun, Lee et al.(2008), can be more helpful
to understand significant determining factors of rental price.
Jongeun, Lee et al.(2008) used the data collected from 16 cities
and provinces in Korea, thereby the study apprehended the
difference generated between two region(metropolitan area and
the rest). Moreover, it suggested that the general rent
determinants of the retail property are building coverage, ratio
of floor area to site, rentable space, land value, the number of
stories, the distance of the subway station from the store, the
width of the road the store bordered on, and the direction of the
window etc.
III. MODEL AND VARIABLES
A. Data
The analysis data used in this study is the Survey on Rented
Examples of Commercial Properties gone along by the
Ministry of Land, Transport and Maritime Affairs and Korea
Appraisal Board at the first quarter in 2011. The object of the
study is 12,559 stores located in 2,000 buildings in 7 regional
central cities in Korea.
B. Model and Variables
The examination of previous studies shows that the Hedonic
Price Model is widely being used in measuring real estate value
and in market analysis studies. The hedonic price model
focuses on investigating the factors that determine rent based
on a specific timeframe. The model is especially useful in
confirming the influence of new factors, which had previously
been unknown, such as the environment surrounding an office,
on the rental fee.
Hedonic price model is derived by using the nominally
observed price of goods and the quantity of characteristics. By
regressing the price of goods on the quantity of characteristics,
the hedonic price model is estimated. The estimated model can
be expressed as a functional formula as follows. The formula
classifies determining factors of retail rent into characteristics
of area(Aj), location(Lj), building( ), and rent unit( ).
What is important for the selection of location in the case of
retail shop is profitability and accessibility according to
Christaller’s Central Place theory and Nelson’s location theory.
Therefore, the elements that influence the selection of location
are how far from the rivals, the region’s population
composition, travel patterns of consumers, availability of
parking lot, residents attitudes and so on. Moreover, the
theories contend that lessees call for the retail properties with
high profitability and accessibility, whereupon high rental price
is formed. In this context, this study presumes that the factors
significant to retail property’s selection of location are the
factors that determine the level of rental price, so it used some
of elements proposed by the theories as explanatory variables.
Variable definitions for the data used in the analysis are
provided in Table I.
TABLE Ⅰ
VARIABLES FOR ANALYSIS
Category Variable Name Description
Dependent
Variable ln(rental price)
Log-transformed value of
rental price per ㎡
Characteristics of area
SEOUL If in Seoul = 1, if not = 0
Conditions of
location
SUB_INF
If located within subway influential
area(within 200m from the subway
station) = 1, if not = 0
FRTG_TYPE If frontage condition is greater than
middle-sized road = 1, if not = 0
BASE If located on basement = 1, if not = 0
2ND_FLR If located on second floor = 1, if not = 0
3RD_FLR If located on third floor = 1, if not = 0
4TH_ABOVE If located on fourth floor and above = 1,
if not = 0
Building
characteristics
AGE Building age (year)
N_ELEV The number of elevators
PKLOT_AREA The gross area of parking lot
divided by rent area
Characteristics
of rental unit IND_WHLS
If engaged in
wholesale and retail services
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
136
IV. ANALYSIS RESULTS
A. Descriptive Statistics of Variables
Descriptive statistics of variables are shown in Table Ⅱ.
From this, it can be confirmed that whether operational
defining is gone right, and the characteristics of the data can be
grasped. The stores that are engaged in the wholesale and retail
services are counted up to 2,003 and the stores engaged in other
industries are summed to 10,556. About 57% and 55% of
wholesale and retail services and other industries respectively
is analyzed to be located in Seoul.
The asking rental price per ㎡ is 52,718 won in average for
wholesale and retail services and as for other industries is
20,123 won, so the rental price of the property occupied by
wholesale and retail services are higher than other industries
averagely. It is also same for building age and the area of
parking lot. In case of the number of elevators, wholesale and
retail services show a tendency to locate in the building with
0.29 elevators on average and other industries does so in the
building with 0.39 elevators, so other industries seem to take
place in the buildings that are more convenient to use. In the
aspect of horizontal accessibility, the stores within 200m from
the subway station are 45% of wholesale and retail services and
43% of other industries. The number of cases that the size of
frontage is bigger than middle-sized road takes up 63% of
wholesale and retail services and 51% of other industries. As
for the aspect of vertical accessibility, 64% of the stores
engaged in wholesale and retail property analyzed to be
averagely located on the first floor, 11% on the second floor,
9% on the third floor, 9% on the fourth floor, and 7% on the
basement, and 19%, 19%, 20%, 29%, 13% of the stores
engaged in other industries are located on the first, second, third,
fourth, and basement respectively as listed in order.
Overall, all the mean values of the variables related to
wholesale and retail services present a contrast to those of other
industries. Therefore, it can be expected that the difference
between the rental price of wholesale and retail services and
that of other industries is caused by the difference in the
characteristics of the store for each group.
B. Result of Analysis of Variance
An analysis of variance has been conducted for the purpose
of confirming whether the difference in the characteristics of
the retail property and its rental price between the industries,
wholesale and retail services and other industries, which was
detected when descriptive statistics of variables are looked
through. The results are shown in Table Ⅲ. According to the
results, the difference in retail rent is statistically significant in
1% level, and the differences in all the factors included in the
model except for the variable that reflects whether the store is
located within station influence area or not are analyzed to be
statistically significant at 10% level.
C. Estimation results
Not classifying the stores into two groups, one for wholesale
and retail services and the other for other industries, the
model(Ⅰ) explains what the retail property’s general rent
determinants are and how much and in what direction they have
an impact on rental price. The results are presented in Table Ⅳ.
To be specific, in the aspect of regional characteristic, if the
store is located in Seoul, the rental price of the retail property is
estimated to enjoy 80.3% of synergistic effect more than the
one that is located in other than Seoul. As for the conditions of
location, if the retail property is situated within a radius of
200m from the nearest subway station, 8.6% higher rental price
is formed than if not. And if the width of the road bordered on
the store is larger than middle-sized road, the level of retail rent
is 3.0% higher than if otherwise.
The dummy variables that are defined to explain how vertical
accessibility has an effect on retail rent are estimated to most
powerfully influence the formation of the rent. Compared to the
store located on the first floor, the one on the second floor
TABLE Ⅱ
DESCRIPTIVE STATISTICS OF VARIABLES
Wholesale and Retail Services
Variable Name Sample
Size Mean
Standard Deviation
Min. Max.
Rental price
(won/㎡) 2,003 52,718.01 66,961.24 492.00
SEOUL 2,003 0.57 0.50 0 1
SUB_INF 2,003 0.45 0.50 0 1
FRTG_TYPE 2,003 0.63 0.49 0 1
BASE 2,003 0.07 0.25 0 1
2ND_FLR 2,003 0.11 0.32 0 1
3RD_FLR 2,003 0.09 0.28 0 1
4TH_ABOVE 2,003 0.09 0.29 0 1
AGE 2,003 28.76 12.69 4 83
N_ELEV 2,003 0.29 0.48 0 2
PKLOT_AREA 2,003 0.79 2.52 0 44
For the Rest
Variable Name Sample
Size Mean
Standard
Deviation Min. Max.
Rental price
(won/㎡) 10,556 20,122.55 22,237.07 273.40
SEOUL 10,556 0.55 0.497 0 1
SUB_INF 10,556 0.43 0.50 0 1
FRTG_TYPE 10,556 0.51 0.50 0 1
BASE 10,556 0.13 0.34 0 1
2ND_FLR 10,556 0.19 0.39 0 1
3RD_FLR 10,556 0.20 0.40 0 1
4TH_ABOVE 10,556 0.29 0.46 0 1
AGE 10,556 24.49 11.07 3 79
N_ELEV 10,556 0.39 0.55 0 2
PKLOT_AREA 10,556 0.67 1.94 0 64
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
137
shows 85.9% lower level of rental price, while the one on the
third floor presents 111.6%, the one on the fourth presents
130.8%, and the one on the basement presents 126.3% lower
level of retail rent. In other words, the rental price is formed
dissimilarly depending on how accessible the store is in a
vertical way. The first floor is the most vertically accessible to
consumers, so the store located on it shows highest rental price
compared to the one on the other floors, and in the order of
second floor, third floor, fourth floor, and basement, high-level
retail rent is built.
As one of the variables that represent building characteristics,
building age has a positive effect on rental price. Concretely,
one unit increment of building age increases 1.2% of rental
price. The number of elevators also influences the rent in a
positive way. If the variable increases as much as its one unit,
the level of the rental price rises in the extent of 22.7%.
However, being contradictory to the common sense, the
magnitude of the parking lot is estimated to have a negative
impact on the rent. Actually, in the range of its mean value, as
the size of the lot becomes large as much as its one unit, the
retail rent gets lower as much as 3.7%, but the absolute value of
its marginal effect diminishes as the size grows. It seems that
this is because in Korea parking along the street is still a daily
occurrence, so the magnitude of parking lot built in the building
may be not that significant determining factor of the retail
property. Actually, since too many cars are used when
compared to the size of parking lot, too much time is spent on
parking in Korea. Therefore people seem to prefer stopping by
to parking.
In order to see how the type of business causes the difference
in rent determinants of the retail property, the dummy variable,
which has the value of 1 if the business type is the wholesale
and retail services and the value of 0 if otherwise, is
additionally included in the model Ⅰ as an additive form and
multiplicative form(Model Ⅱ). The results can be seen in Table
Ⅳ. However, unfortunately, the interaction term that is the
multiplicative form of business dummy and building age could
not be included in the model Ⅱ, because it causes relatively
severe problem of multi-collinearity in the model. In fact, it is
estimated that all parts of the interaction term can be explained
by the other explanatory variables based on VIF.
According to the results of the estimation, except for the
variables related to parking lot(and building age), all the
variables are analyzed to play a role as factors that explain the
gap in the level of rental price between the types of business.
TABLE Ⅲ
ANALYSIS OF VARIANCE
Wholesale and Retail Services
Variable Name Sum of Squares Degrees of Freedom Mean Square F-Ratio P-Value
LN_rtprice
Between groups 1169.122 1 1169.122 1595.191 0.000
Residual 9203.080 12557 0.733
Covariate 10372.202 12558
For the Rest
Variable Name Sum of Squares Degrees of Freedom Mean Square F-Ratio P-Value
SEOUL
Between groups 0.949 1 0.949 3.843 0.050
Residual 3,102.486 12,562 0.247
Covariate 3,103.435 12,563
SUB_INF
Between groups 0.622 1 0.622 2.529 0.112
Residual 3,089.184 12,562 0.246
Covariate 3,089.806 12,563
FRTG_TYPE
Between groups 25.662 1 25.662 103.800 0.000
Residual 3,105.644 12,562 0.247
Covariate 3,131.306 12,563
BASE
Between groups 7.258 1 7.258 67.121 0.000
Residual 1,358.294 12,562 0.108
Covariate 1,365.552 12,563
2ND_FLR
Between groups 9.307 1 9.307 65.134 0.000
Residual 1,795.048 12,562 0.143
Covariate 1,804.355 12,563
3RD_FLR
Between groups 20.348 1 20.348 139.200 0.000
Residual 1,836.324 12,562 0.146
Covariate 1,856.673 12,563
4TH_ABOVE
Between groups 66.302 1 66.302 353.665 0.000
Residual 2,355.019 12,562 0.187
Covariate 2,421.321 12,563
AGE
Between groups 30,712.690 1 30,712.690 238.827 0.000
Residual 1,615,451.013 12,562 128.598
Covariate 1,646,163.703 12,563
N_ELEV
Between groups 18.547 1 18.547 64.832 0.000
Residual 3,593.725 12,562 0.286
Covariate 3,612.272 12,563
PKLOT_AREA
Between groups 24.416 1 24.416 5.857 0.016
Residual 52,366.982 12,562 4.169
Covariate 52,391.398 12,563
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
138
However, some of the variables are analyzed to be more
sensitive rent determinants for the retail property occupied by
wholesale and retail services. Those are on what nth floor the
store is located and whether it is within a radius of 200m from
the nearest subway station.
In the aspect of wholesale and retail services, if the store is
located in Seoul, the rental price is 74.9% higher than the one in
the other region, which is 6.5% lower than the case of other
industries. And if the distance from the nearest subway station
is less than 200m, the retail rent is estimated to rise up to 12.5%,
which is higher than the one worked for the other businesses.
The type of frontage also influences differently to the rental
price of wholesale and retail services and to that of other
industries, specifically having a negative impact(-7.4%) on the
rent in the case of retail business and a positive impact(2.6%) in
the case of other industries.
The rental price of wholesale and retail services notably
elastically reacted to the vertical accessibility so that the rent is
formed 89.0%, 117.6%, 136.7%, 141.4%, and 152.4% lower if
the store is located on the second floor, third floor, fourth floor,
and the basement respectively than on the first floor. Lastly,
one unit increase in the number of elevators causes 10.8%
increase in the rental price of the retail property engaged in
wholesale and retail services compared to that engaged in the
other industries.
V. CONCLUSION
This study casts a long shadow to us in the respects of
analyzing rent determinants, which is the field of the research
studied not enough, and particularly looking into the
differences in the rental prices between the types of business
and that in the characteristics of the property the lessees have in
favor of. However, the study has several restrictions. The
model used in the study has its limit that it cannot make detailed
analysis for each type of business because the number of
dummy variables and interaction terms that were going to be
included in the model would increase exponentially only to cost
the degrees of freedom. Luckily, the size of the sample is
sufficiently large so that using the model with only one dummy
variable for the types of business and its interaction terms is
acceptable in the aspect of reliability of the model. Another
limitation of the study is that it doesn’t bother to investigate the
cause of the results of empirical analysis thoroughly.
The empirical results of the study implies that first, when
selecting the retail property for the purpose of investing or
operating retail business, conditions of location is the most
important factor the investor or operator should consider.
Notably, vertical accessibility of the store should be come up
for in priority based on the results that the location of the store,
specifically on what nth floor the store is located on, causes a
large margin on rental prices. Second, the study suggests that
since each type of business has dissimilar structure of rent
determining process, understanding and analyzing determining
factors of rental price for each of them is surely required.
REFERENCES
[1] K. Y. Byun, “A Comparative study on the office rent determinants of Seoul’s large office market”, Ph. D. dissertation, Kyungwon University
2004.
[2] C.H. Kim, J. S. Song, “A Research on the Use Determination Based upon the Location Characteristics Analysis on Commercial Facilities in
Apartment Complex”, Journal of the Korean Planner Association, vol.36,
2001, pp.113-129. [3] Y. K. Hur, S. J. Kim, “The Estimation of Spatial Effects of the Office rent
in Seoul”, Journal of the Korean Planner Association, vol.58, 2008, pp.
195-208. [4] S. Y. Jeong, J. N. Kim,” A Cross-sectional Model of Retail Property
Rents in Seoul, Korea”, Journal of Korea Real Estate Analysis
Association, vol.12, nm 2, 2006, pp. 27-49.
TABLE Ⅳ
REGRESSION MODEL ESTIMATION OF RETAIL PROPERTY’S RENT
Wholesale and Retail Services
Explanatory
Variables Model Ⅰ Model Ⅱ
constant 9.687*** (0.021)
9.544*** (0.023)
SEOUL 0.803***
(0.012
0.814***
(0.012)
SUB_INF 0.086*** (0.011)
0.074*** (0.012)
FRTG_TYPE 0.030***
(0.012)
0.026**
(0.012)
BASE -1.263***
(0.019) -1.097***
(0.021)
2ND_FLR -0.859***
(0.017)
-0.719***
(0.019)
3RD_FLR -1.116***
(0.017) -0.967***
(0.019)
4TH_ABOVE -1.308***
(0.016)
-1.158***
(0.018)
AGE 0.012*** (0.001)
0.011*** (0.001)
N_ELEV 0.227***
(0.013)
0.244***
(0.013)
PKLOT_AREA -0.037***
(0.005) -0.032***
(0.005)
PKLOT_AREA2 0.001***
(0.0001)
0.001***
(0.0001)
IND_WHLS - 0.544*** (0.038)
SEOUL
X IND_WHLS -
-0.065**
(0.030)
SUB_INF
X IND_WHLS -
0.051*
(0.030)
FRTG_TYPE
X IND_WHLS -
-0.100***
(0.031)
BASE
X IND_WHLS -
-0.427***
(0.058)
2ND_FLR
X IND_WHLS -
-0.171***
(0.048)
3RD_FLR
X IND_WHLS -
-0.209***
(0.052)
4TH_ABOVE
X IND_WHLS -
-0.256*** (0.051)
AGE
X IND_WHLS - -
N_ELEV
X IND_WHLS -
-0.136*** (0.033)
PKLOT_AREA
X IND_WHLS -
-0.013
(0.012)
PKLOT_AREA2
X IND_WHLS -
0.0001 (0.0004)
R2 0.543 0.560
Adj.R2 0.543 0.559 F-value 1,355.843 725.737
Sig. 0.000 0.000
Note: *, **, *** are statistically significant at 10%, 5%, 1%, respectively
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
139
[5] K. Y. Kim, C. G. Kim, “An Empirical Study on the Determinants of
Office Rent”, Journal of Korea Real Estate Analysis Association, vol.12, 2006, pp.115-137.
[6] J. S. Kim, C. W. Suh, “A Study on the Spatial Autocorrelation in
Estimation of Office Rentals in Seoul”, Journal of the Korean Planner Association, vol. 44, no. 2, 2009, pp. 95-110.
[7] K. Lancaster, “A New Approach to Consumer Theory”, Journal of
Political Economy, vol.74, 1966, pp. 132-157. [8] H. S. Lee, S. K. Park, “An Analysis of Office Rent Determinants by
Grades and Regions Considering Spatial Autocorrelation”, Journal of the
Korean Planner Association, vol. 45, no. 2, 2010, pp.165-177. [9] J. E. Lee, J. H. Cho, “A Study on Rent Determinants of Retail Property”,
Korea Real Estate Review, vol. 18, 2008, pp.63-102.
[10] J. W. Lee, “Rental Market Structure of the Commercial Real Estate in Korea”, Ph. D. dissertation, Hanyang University 2005.
[11] J. W. Lee, C. M. Lee, “Rent Determinants of Retail Properties in Seoul”,
Journal of the Korean Planner Association, vol. 41, no. 1, 2006, pp. 75-90.
[12] Y. M. Lee, “A Review of the Hedonic Price Model”, Journal of Korea
Real Estate Analysis Association, vol. 14, no. 1, 2008, pp. 81-87. [13] Y. H. Noh, “A Study on the Determining Factors of Office Rental Rate &
Management Process – Focused on the Kangnam, CBD and Yeouido
Districts– ”, Journal of the Korean Regional Development Association, vol. 20, no. 4, 2009, pp. 283-300.
[14] S. Rosen, “Hedonic Prices and Implicit Markets: Product Differentiation
in Pure Competition”, Journal of Political Economy, vol. 82, 1974, pp. 34-55.
[15] S. C. Yang, “A Study on the influence of type of business of tenant to the office building rents in Seoul”, Journal of Korean Real Estate Research
Institute, vol. 18, no. 1, 2008, pp. 49-69.
[16] S. C. Yang, S.W. Lee, “A Study on the Determinants of Non-residential Property Value”, Journal of Korean Real Estate Research Institute.
[17] J. K. Cho, “A Study on the Comparison of Change in Rent Determinants
between Office and Retail Properties”, Ph. D. dissertation, Seokyung University 2013.
3rd International Conference on Management, Behavioral Sciences and Economics Issues (ICMBSE'2014) Feb. 11-12, 2014 Singapore
140