有效的前進部署，能夠控制銷售中的投入以及降低損失，掌握產品以及物流的安排。對於季節性產品來說，他們本身具有銷售週期，而週期不全然是完全相同，有時也會受到外在條件的影響而提早或延後。此外，不單是季節時間影響銷售，進一步理解真正影響季節性的原因很重要，以便在進入市場的最佳時機前，做好前進部署。本研究以家用冷氣機的銷售為研究目標，將房屋交易和天氣因子作為探討影響銷售的因子。
本研究運用多元迴歸分析，分別採用虛擬變數和固定效果模型等方法，從不同觀點探討這些因子如何影響家用冷氣機的銷售。同時，特徵價格模型也在本研究中運用，分析異質性產品的特徵和價格的彈性。結果顯示，房屋交易和相關天氣因子對家用冷氣機的銷售具有影響力。另一方面，節能指標的產品特徵、年耗電量，以及機台樣式(窗型、分離式、一對多分離式)等特徵明顯地對家用冷氣機的價格有影響。這也反映出當今的節能政策，以及家用冷氣機的購買傾向。基於這些分析結果，在考量外部因子的變化後，可以建立前進部署策略，以便掌握家用冷氣機市場的銷售。

Taking effective preventive measures can control the cost and decrease the loss in sales to prepare the products and arrange the logistics properly. Seasonal products have own sales period, and the periods are not totally same. These periods sometimes happen early or late. Besides, the sales is not simply influenced by the season times. Figuring out what actually influences the sales to further execute preventive measures before entering the market is crucial. This study took the sales of room air-conditioners as the analysis target to explain how the external factors, which were the house transactions and weather factors, influence sales.
Multiple linear regression analysis was designed with dummy variables and fixed-effect model to be analyzed from different perspectives. Also, the hedonic price model was utilized to find out the elasticity between prices and product specifications. The results indicated that the room air-conditioners sales can be influenced by the house transactions and weather factors. In contrast, the energy-efficiency index, annual power consumption and different types (window, split, multi-split) of room air-conditioners influence room air-conditioners price more. This reflects the energy-saving policy nowadays and purchasing tendency. With the results, the preventive measures can be established considering the changes of external factors to seize the sales time.

Thesis Validation Letter i
Acknowledgement ii
Abstract iii
摘要 iv
Content Table v
Figures Table vi
Tables Table vii
Chapter 1. Introduction 1
Chapter 2. Literature Review 4
2.1. Seasonality 4
2.1.1. Measurement of seasonality 4
2.1.2. Seasonal Sales 5
2.2. Climate influences sales 6
2.3. Hedonic Price Model 8
2.3.1. Application of hedonic price model 9
Chapter 3. Methodology 11
3.1. Data source 12
3.1.1. Sales data 12
3.1.2. Meteorological data 12
3.1.3. House transaction data 12
3.2. Data Preprocessing 13
3.2.1. Sales data 13
3.2.2. Meteorological data 15
3.2.3. House transaction data 16
3.2.4. Control Variables 17
3.3. Analysis tools 20
3.3.1. Regression analysis 20
3.3.2. Regression analysis applying the fixed-effect model 22
3.3.3. Hedonic price model 23
Chapter 4. Results 25
4.1. Descriptive Analysis 25
4.2. Regression Analysis 30
4.2.1 Results of total RAC sales 30
4.2.2 Results of RAC sales of each brand 31
4.2.2.1. Regression with dummy variables 31
4.2.2.2. Regression analysis with the fixed-effect model 34
4.3. Seasonal Index 35
4.4. Hedonic Price Model 37
Chapter 5. Discussion 40
5.1. Analysis of regression model with total sales 40
5.2. Analysis of regression model with each brand 40
5.3. Analysis of hedonic price model 43
5.4. Limitation & Future development 45
5.5. Conclusion 46
Reference 47

Anderson, J., Daultani, V., Muman, T., & Batran, M. (2019, December). The Importance of Weather for E-Commerce Orders Forecasting. In Proceedings of the 2019 International Conference on E-Business and E-commerce Engineering (pp. 15-19).
Badorf, F., & Hoberg, K. (2020). The impact of daily weather on retail sales: An empirical study in brick-and-mortar stores. Journal of Retailing and Consumer Services, 52, 101921.
Bahng, Y., & Kincade, D. H. (2012). The relationship between temperature and sales. International Journal of Retail & Distribution Management.
Bitran, G., Caldentey, R., & Mondschein, S. (1998). Coordinating clearance markdown sales of seasonal products in retail chains. Operations research, 46(5), 609-624.
Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2010). A basic introduction to fixed‐effect and random‐effects models for meta‐analysis. Research synthesis methods, 1(2), 97-111.
Bryant, W. K., & Gerner, J. L. (1978). The price of a warranty: The case for refrigerators. Journal of Consumer Affairs, 12(1), 30-47.
Thrane, C. (2005). Hedonic price models and sun-and-beach package tours: The Norwegian case. Journal of Travel Research, 43(3), 302-308.
Cheng, W. C. (2020, December 14) 2020台灣中小型空調市場展望Taiwan’s Air Conditioner Market Outlook 2020 from: https://ieknet.iek.org.tw/iekrpt/rpt_more.aspx?rpt_idno=688344567
Chien, C. C., Lee, C. F., & Wang, A. M. (2002). A note on stock market seasonality: The impact of stock price volatility on the application of dummy variable regression model. The Quarterly Review of Economics and Finance, 42(1), 155-162.
Courty, P., & Li, H. (1999). Timing of seasonal sales. The Journal of Business, 72(4), 545-572.
Gao, F., Demirag, O. C., & Chen, F. Y. (2012). Early sales of seasonal products with weather‐conditional rebates. Production and Operations Management, 21(4), 778-794.
Hylleberg, S. (2014). Seasonality in regression. Academic Press.
Koops, B. J. (2021). The concept of function creep. Law, Innovation and Technology, 13(1), 29-56.
McConnell, K. E., & Strand, I. E. (2000). Hedonic prices for fish: tuna prices in Hawaii. American Journal of Agricultural Economics, 82(1), 133-144.
Menezes, O. J. (1971). The dummy variable method for jointly estimating seasonal indexes and regression on non-seasonal variables. The American Statistician, 25(5), 32-36.
Monks, G. G. (1981). Seasonality studies. In Advances in archaeological method and theory (pp. 177-240). Academic Press.
Oh, J., Jo, Y. H., & Ha, K. J. (2021). The effect of anomalous weather on the seasonal clothing market in New York. Meteorological Applications, 28(2), e1982.
Osborn, D. R. (1988). Seasonality and habit persistence in a life cycle model of consumption. Journal of Applied Econometrics, 255-266.
Planas, C. (1998). The analysis of seasonality in economic statistics: a survey of recent developments.
Pongjit, C., & Chiaravutthi, Y. (2018). Brand and brand origin valuations: a case of the electrical appliance market in Thailand. International Journal of Business Innovation and Research, 17(2), 187-209.
Rapson, D. (2014). Durable goods and long-run electricity demand: Evidence from air conditioner purchase behavior. Journal of Environmental Economics and Management, 68(1), 141-160.
Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation in pure competition. Journal of political economy, 82(1), 34-55.
Steinker, S., Hoberg, K., & Thonemann, U. W. (2017). The value of weather information for e‐commerce operations. Production and Operations Management, 26(10), 1854-1874.
Štulec, I., Petljak, K., & Naletina, D. (2019). Weather impact on retail sales: How can weather derivatives help with adverse weather deviations? Journal of Retailing and Consumer Services, 49, 1-10.
Soysal, G. P., & Krishnamurthi, L. (2012). Demand dynamics in the seasonal goods industry: An empirical analysis. Marketing Science, 31(2), 293-316.
Wang, X., Sun, J., & Wen, H. (2019). Tourism seasonality, online user rating and hotel price: A quantitative approach based on the hedonic price model. International Journal of Hospitality Management, 79, 140-147.
Wildt, A. R. (1977). Estimating models of seasonal market response using dummy variables. Journal of Marketing Research, 14(1), 34-41.
Wolters, J., & Huchzermeier, A. (2021). Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment. Journal of Retailing.
Witte, A. D., Sumka, H. J., & Erekson, H. (1979). An estimate of a structural hedonic price model of the housing market: an application of Rosen's theory of implicit markets. Econometrica: Journal of the Econometric Society, 1151-1173.
Zhagina, S., & Pakhomova, O. (2019, July). The analysis of seasonality of tourist services in the European North of Russia. In IOP Conference Series: Earth and Environmental Science (Vol. 302, No. 1, p. 012040). IOP Publishing.
Zhang, Y., & Tao, W. (2020). Will energy efficiency affect appliance price? An empirical analysis of refrigerators in China based on hedonic price model. Energy Policy, 147, 111818.