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

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1 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

2 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

3 Figure 1 Street level retail shops

4 Outline 1 2 3 4 5 6 Background Research Questions & Objectives
Literature Review & Hypotheses 4 Research Design 5 Data and Sources 6 Expected Outcome

5 1 Background Tourism Industry Mainland China Visitors
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 A major part of HK economy. In 2009, it contributed to 3.3% of HK’s GDP. It employs over 193,200 persons, accounting for 5.5% of total employment. Visitor arrivals in 2011Q1&Q2 rose by 14.7% and reached 19.3 million, setting a new arrival record largest source market with 12.7 million, accounting for 65.7% of total visitor arrival 2011Q1&Q2 increases 19.43% annually from 1991 to 2010 The bulk of spending per capita for an overnight mainland Chinese visitor to Hong Kong is on shopping (73%), It’s mainly due to lower prices, quality assurance and better services, and strengthening RMB versus a weakening US dollar which HKD is pegged to. Tourism shopping or retailing rely a large part on this certain kind of tourists. HKTA (Hong Kong Tourist Association) takes Mainland China as one of its biggest growth markets, with ever-increasing visitor arrivals from the Mainland as the key to the long-term health of its tourism industry. Wang (2004) show that repeat visitation to Hong Kong from Mainland China has contributed greatly to shopping and local transportation.

6 Figure 2 Visitor Arrivals by Country/Territory of Residence (1993-2011)

7 Figure 3 Receipts from Visitors
( )

8 Figure 4 Consumption Expenditure of all Visitors ($million) (1998-2011)


10 Retail Industry in HK Retail Property
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

11 2 Research Questions & Objectives
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

12 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

13 3 Literature Review 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

14 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

15 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)

16 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

17 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

18 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)

19 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)

20 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

21 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

22 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

23 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.

24 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

25 4 Research Design 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

26 Variables 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 AC Numbers of hotels or guesthouse within 250m radius Number IVS equals 1 after implementation of the Individual visit scheme 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

27 5 Data and Sources Variables Description Data sources RP
Deflated transaction price per saleable area EPRC INDEX Retail price index Rating and Valuation Department MTR Distance to the nearest MTR station Survey and Mapping Office/ Google map AC Numbers of hotels or guesthouse within 250m radius Licensing Authority and Google map COR Located in corner Site visit AGE Building age SIZE Shop size FRON Length of frontage Site Measurement IVS Individual visit scheme Hong Kong Tourism Board

28 6 Expected Outcome Variables Expected sign Remark AGE +ve Control AGE2



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