The Study of Watch Sales Forecast Using Macroeconomic Variables for Taiwan

• Main Authors: Wong Yueh-Hua, 翁越華
• Other Authors: Goo Yeong-Jia
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/11582745998889008626

碩士 === 國立臺北大學 === 企業管理學系碩士在職專班 === 98 === The watch sales in Taiwan has been on steady growth in the past years despite global financial crisis in 2009. Swiss watch export to Taiwan suffered moderate decline which fair better than global industry average when comparing to drastic setback in the key markets. Although Swiss watch export began to see light at the end of the tunnel during the holiday season of 2009, but had the colossal financial crisis that casted grave consequences in the luxury goods sales altered methodology and business model from the independent to conglomerate? The five business studies include watch of different segments covering period of 7 years from 2003 to 2009, case studied include actual sales units and figures as prime examples based on 7 economic variables: TW Weighted Index, Unemployment Rate, Business Earnings, Currency Fluctuation, Interest Rate, Consumer Index Ratings & Cash Deposit Index as factors of general consensus, the indices are then calculated in one-month behind, one-quarter behind & six-month behind period as factors in comparison. In addition, classic models in seasonal change are also factored in predicting future trend in sales. The statistic of this study proved the following conclusions: 1.All 7 Macroeconomic Variables were vital in changing trend in sales as different price segments in successive period which evolved into different outcome. 2. Sales of entry-level sector definitely correlated to seasonal change, especially with holiday theme that were popular with loyal consumers, as fluctuation is very sensitive and rapid, it is the opposite with luxury watchs whereas sales are usually faster to rebound. 3. The narrower price elasticity of a brand proved easier for prediction of sales of the two brands studied, brand with slimmest room of price elasticity yielded the most accurate statistic.