The Impact of Implementation of Individual Visit Scheme on the Price of Street Level Retail Shops PhD Candidate: Liu Yan, Ivy Supervisor: Prof. K. W. Chau.

The Impact of Implementation of Individual Visit Scheme on the Price of Street Level Retail

Shops

PhD Candidate: Liu Yan, Ivy Supervisor: Prof. K. W. Chau

3rd , July, 2013

Definition of Keywords

• Individual Visit Scheme (IVS)– began on July 28, 2003, allowed travelers from

Mainland China to visit HK and Macau on an individual basis

• Street Level Retail Shops– ground floor shops within tenant-mixed buildings with

a street-faced frontage and are commonly found in the older parts of the urban area

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Figure 1 Street level retail shops

1 Background

2 Research Questions & Objectives

3 Literature Review & Hypotheses

4 Research Design

5 Data and Sources

Outline

6 Expected Outcome

• Tourism Industry– in 2009, it contributed to 3.3% of GDP, employed over

193,200 persons (5.5% employment)

– visitor arrivals in 2011 reached 41.9 million

• Mainland China Visitors– In 2011, largest source market with 28.1 million - 67%

– increases 19.43% annually from 1991 to 2011

– spend 73% expenditures on shopping on average

1 Background

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19931994

19951996

19971998

19992000

20012002

20032004

20052006

20072008

20092010

20110

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

45,000,000

Number of touristsNumber of Mainland touristsNumber of IVS

Figure 2 Visitor Arrivals by Country/Territory of Residence

(1993-2011)

1993 1994 1995 1996 1997 1998 1999 2000 20010

10000

20000

30000

40000

50000

60000

70000

80000

90000

YearReceipts from Visitors ($million)-Main-land ChinaReceipts from all Visitors ($million)

Figure 3 Receipts from Visitors(1993-2001)

Figure 4 Consumption Expenditure of all Visitors

($million) (1998-2011)

19981999

20002001

20022003

20042005

20062007

20082009

20102011

0

50000

100000

150000

200000

250000

YearConsumption Expenditure of Visitors ($million)-Mainland ChinaConsumption Expenditure of all Visi-tiors ($million)

• Retail Industry in HK– total retail sales: $325 billion (2010)

– HK$64 billion, or 20%, was directly attributed to shopping spending of Mainland Chinese tourists

• Retail Property– over 97% is in the private sector

– a large amount of very small retail business types and a rather small scale of huge retailers

– shopping malls, street-level retail shops, open air bazaars, markets and cooked food stalls

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• 2.1 Research Question– Shoppers can be classified into local-shoppers and

tourist-shoppers

– This study examines whether there is any relationship between changes on shopper mix and the implicit prices of street level retail shops attributes

– Makes use of the implementation of IVS in Hong Kong, which changed the shopper mix to undertake empirical tests

2 Research Questions & Objectives

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• 2.2 Research Objectives– Examine the differences in shopping behaviors between

local & tourist shoppers

– Identify factors that affect street level retail shops price in urban areas

– Identify attributes of street level retail shops which are likely to be affected by changes in local & tourist shopper mix

– Formulate and test hypotheses on the impact of IVS on the implicit prices of street level retail shops attributes

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• 3.1 Tourism Shopping– local-shoppers and tourist-shoppers have different

shopping behaviors (Christiansen & Snepenger, 2002)

– Heung and Qu (1998), tourism shopping: expenditure on goods purchased in HK, by international visitors, either for consumption in HK or for export but not including expenditure on food, drink or grocery items

– Law and Au (2000): visitors’ total expenditures on non-F&B items could have been consumed locally, or could have been taken abroad

3 Literature Review

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• 3.2 Retail Property• Macro view– Eppli and Benjamin (1994) : central place theory, retail

agglomeration economics, positive effects of large anchor-tenants and valuation of shopping centers

– Others: Sirmans and Guidry (1993), Benjamin, Boyle, and Sirmans (1990), O'Roarty, McGreal, and Adair (1997), etc

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• Micro view– Craig, Ghosh, and McLafferty (1984): area or market,

potential shops, optimal, physical features

– Sirmans and Guidry (1993) summarized four kinds of main factors: market condition, customer drawing power, building design and location

– Others: Yuo, Crosby, Lizieri, and McCann (2003), Gatzlaff, Sirmans, and Diskin (2001), etc. Teller (2008)

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• Hong Kong case– Richard S. Tay, Clement K. Lau, and Marie S. Leung

(1999)

– Chau, Pretorius, and Yu (2000) studied street level retail shops in Mong Kok

– Ning (2011) conducted a further research

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• 3.3 Property Price Determinants– Many studies have been done to study various factors that

affect property prices or rentals, say Archer, Gatzlaff, and Ling (1996), Gibbons and Machin (2008), Tsun (2010), etc

• Building Age – Hottest variables: Knight and Sirmans (1996), Lee, Chung,

and Kim (2005), Rehm, Filippova, and Stone (2006), etc

– Depreciation & negative effect v.s. positive influence

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• Neighborhood Attributes– Rodriguez and Sirmans (1994), Wolverton (1997), Yiu,

Chau, and Wong (2008), Kestens, Theriault, and Rosiers (2004), Hui, Chau, Pun, and Law (2007) etc

– Parks, hospitals, banks or supermarkets, sea view, mountain view

– For retail properties, the most important issue is the power of generating potential customers (R.S. Tay, C.K. Lau, & M.S. Leung, 1999)

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• Transportation – bus, railway, MTR availability, distance to certain

stations or CBD

– positive effect: Chalermpong (2007), Shin, Washington, and Choi (2007), Tse (2002), Choy, Mak, and Ho (2007)

– negative effect: Poon (1978) and Forrest, Glen, and Ward (1996), Nelson(2008), Chau and Ng (1998)

– little has been done with reference to retail property: Damm, Lerman, Lerner-Lam, and Young (1980)

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• 3.4 Research Gap

– Previous research objectives focused mainly on shopping malls or shopping centers, nearly no studies on street-level retail shops

– There is no empirical study on the relationship of shopper mix and implicit prices of retail shops attributes

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• 3.5 Hypotheses– H1: Implementation of the Individual Visit Scheme will

increase the positive impact of building age on prices of street level retail shops, other things being equal

Rationale– Older street level shops occupy premier locations first

as the urban area develops

– AGE is a proxy for how well-known these locations are

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– H2: Implementation of the Individual Visit Scheme will increase the positive impact of upper level retail use on the prices of street-level retail shops, other things being equal

Rationale– Upper-level properties always carried out for other use;

– Different property type has different pedestrian drawing powers

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– H3: Implementation of the Individual Visit Scheme will increase the positive impact of proximity of the shops to tourist accommodation facilities, other things being equal

Rationale– Proximity to accommodation facilities is of value to

tourists but not local shoppers.

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– H4: Implementation of the Individual Visit Scheme will increase positive impact of proximity of the shops to MTR stations, other things being equal.

Rationale– Proximity to MTR is a measure of accessibility of

shops

– Accessibility of shops is more important to tourist than local shopper

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• Hedonic Price Model

ln(RP) =a0+a1AGE+a2AGE2+a3SIZE+a4SIZE2+a5FRON

+a6FRON2+a7COR+a8MTR+a9MTR2+a10AC

+a11AC2+a12IVS+a13IVS*AGE+a14IVS*FRON

+a15IVS*AC+a16IVS*MTR+ε– ln(RP) -natural log of the real price per saleable floor area– ai - coefficients – ε - error term

4 Research Design

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Variables DescriptionVariables Description Unit

RP Real price per saleable area $/M2

AGE Age of the shop Year

SIZE Saleable area of the shop M2

FRON Length of the frontage facing the street (equal zero if the shop is located inside a building

Meter

COR Shops located at the junction of 2 roads Dummy

MTR The distance to the nearest MTR station Meter

AC Numbers of hotels or guesthouse within 250m radius Number

IVS equals 1 after implementation of the Individual visit scheme Dummy

IVS*AGE Interaction between IVS and AGE  --

IVS*FRON Interaction between IVS and FORN  --

IVS*AC Interaction between IVS and AC  --

IVS*MTR Interaction between IVS and MTR  --

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5 Data and Sources

Variables Description Data sources

RPDeflated transaction price per saleable area

EPRC

INDEX Retail price index Rating and Valuation Department

MTR Distance to the nearest MTR stationSurvey and Mapping Office/ Google map

ACNumbers of hotels or guesthouse within 250m radius

Licensing Authority and Google map

COR Located in corner Site visit

AGE Building age EPRC

SIZE Shop size EPRC

FRON Length of frontage Site Measurement

IVS Individual visit scheme Hong Kong Tourism Board

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6 Expected OutcomeVariables Expected sign Remark

AGE +ve Control

AGE2 ? Control

SIZE +ve Control

SIZE2 ? Control

FRON +ve Control

FRON2 ? Control

COR +ve Control

MTR -ve Control

MTR2 ? Control

AC Insignificant Control

AC2 Insignificant Control

IVS +ve Control

IVS*AGE +ve H1

IVS*FRON +ve H2

IVS*AC +ve H3

IVS*MTR -ve H4

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THANK YOU