Compared with local shoppers, tourist shoppers have very different shopping behaviors and preferences, which in turn influence the location selection decisions of retailers and the pricing of retail spaces. The implementation of "Individual Visit Scheme" (IVS) policy since July, 2003 which allows Mainland Chinese tourists to visit Hong Kong on an individual basis has significantly increased the proportion of tourist shoppers. This policy provides us with an invaluable opportunity to examine how changes in tourist-local shopper mix affect the pricing of retail spaces in Hong Kong.
There have been very few empirical studies on the pricing of street level retail shops (or "shops") due to lack of transaction data and difficulties in identifying and measuring price-influencing location attributes of shops. Shops in Hong Kong have been more actively transacted compared to most markets around the world, which helps to solve the data availability problem. In this study, transactions of the shops in Causeway Bay, a major shopping area for both local and tourist shoppers in Hong Kong, during the period 1993 to 2011 has been used for empirical analysis. The difficulty of modeling the unknown location attributes of shops is tackled with use of spatial auto-regressive modeling techniques.
The significances of this study are threefold. First, we find that the shopping behaviors of tourists are influenced by their hometown shopping experiences. This is evidenced by the reversal of the impact of building age on shop’s transaction price after the implementation of IVS policy. Before this policy, when local shoppers were the majority, the effect of age on shop prices was positive as it captures some of the preferential location attributes of shops that were well known to local shoppers. When the proportion of Mainland Chinese tourist shoppers increased after the implementation of IVS, the impact of age on shop prices becomes negative as their hometown experiences suggest that new shops provide better shopping environment and are more preferred than old ones.
The second contribution is to show how tourist shopper’s shopping behaviors are affected by the cost of stay. Compared with local shoppers, tourist shoppers have a much higher cost of stay. Shop location attributes that can reduce the shopper’s idle time (e.g. travelling and shopping around time) would be more valuable to tourist shoppers than local shoppers. This implies that the proximity to Mass Transit Railway (MTR) station and the accommodation facilities around the retail units are preferred by tourist shoppers. Empirical evidence shows that the value of proximity to MTR station has increased significantly after the implementation of IVS, which is consistent with the prediction from tourist shoppers’ high cost of stay.
Finally, the third contribution of this study is improvement of empirical analysis method. A major problem in analyzing shop prices is the difficulty in measuring and modeling the specific price-influencing location factors, which give rise to misspecification of the hedonic price model. This study resolves this problem by adopting spatial econometric models. Our empirical results also show strong evidence of spatial auto-correlation in shop prices. / published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/206733 |
| Date | January 2014 |
| Creators | Liu, Yan, 刘燕 |
| Contributors | Chau, KW |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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