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


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


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


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


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

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TABLE Ⅳ

REGRESSION MODEL ESTIMATION OF RETAIL PROPERTY’S RENT


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


139

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