Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/184100
Title: LOCATIONAL & PHYSICAL CHARACTERISTICS & THE PERFORMANCE OF SHOPPING CENTRES : A MULTIPLE REGRESSION ANALYSIS APPROACH
Authors: CHAN WAI LUEN
Issue Date: 1996
Citation: CHAN WAI LUEN (1996). LOCATIONAL & PHYSICAL CHARACTERISTICS & THE PERFORMANCE OF SHOPPING CENTRES : A MULTIPLE REGRESSION ANALYSIS APPROACH. ScholarBank@NUS Repository.
Abstract: The retail industry has not been doing well since the boom in the early 1990s. Giant retailers CK. Tang, Isetan and Metro continue to report losses. The whittling demand is partly due to the effects of the full day Area Licensing Scheme (ALS) and the Goods and Services Tax imposed on 1st of April 1994. The increasing labour cost has also eaten into the profit margins of retailers. In addition, the proliferation of sophisticated shopping alternatives in the regional countries, together with a strong Singapore dollar, has affected tourist spending in Singapore. In contrast, the locals, equipped with a higher purchasing power, are well placed to shop abroad. Taken together, the lacklustre performance of the retail industry is expected to continue. With more retail space coming onto the market, will the market be saturated with too many retailers competing for a dwindling share of the consumer dollar? This dismal situation prompted this study to identify the key factors that are associated with the success of shopping centres in Singapore. In the past, several types of analyses have been used to evaluate retail trading and shopping centre performance. These techniques range from simple "rules of thumb" and ratio methods to trade methods and market penetration techniques. Using a multiple linear regression model and occupancy rate as a measure of performance, this study postulates that the performance of shopping centres can be explained by a few site and location characteristics. Based on a sample of 28 shopping centres drawn from the Orchard Road area, it was found that 68.7% of the variation in the occupancy rate of shopping centres can be accounted for by the presence of anchor tenants and foodcourts, the availability of resting seats and the nearness to bus stops and Mass Rapid Transit (MRT) stations.
URI: https://scholarbank.nus.edu.sg/handle/10635/184100
Appears in Collections:Bachelor's Theses

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