目錄 5 MODEL BUILDINGS 致謝詞 1. China air conditioning market is growing at an annual average rate of 12.8% in 中文摘要 2

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1 C h a p t e r 2 MODEL BUILDINGS 致謝詞 1 China air conditioning market is growing at an annual average rate of 12.8% in quantity since 2000, according to Building Services Research and Information Association (BSRIA) from UK ( in its China 200 (Report 目錄 18768) (2). Household incomes, warmer summer each year, and a relatively low 表目錄 penetration (1% by 2004) of air conditioner helped sustain the growth. Of the 7 total 圖目錄 market size US$7.96 Billions (2004), 88.8% are residential and light commercial 8 unitary market (US$7.06B). Residential unitary market or RAC includes window units (through the wall), movable (or portable) units and mini split below kw 第一章緒論 9 (mostly single split). Light commercial unitary market or PAC includes package unit, 第一節研究背景 9 single and multiple split from kw to 17.8 kw, and US style rooftop, ductless split. 第二節研究動機與目的 10 第三節研究範圍與架構 11 Except window and package unit, the number of Out Door units (OD) is used for market size calculation, single or multiple split. Out door unit includes refrigeration compressor and condenser fan that consumed electrical power to produce cooling 第二章 during 文獻探討 hot season or heating during cold season. The number of Indoor Units 14 (ID) 第一節 for multiple 交易成本理論 split will not be considered as it contain only a fractional fan motor 14 (<1 第二節策略行銷 4C 理論 24 hp), to deliver cooled air, consumed very little electrical power while running. 第三節五力分析模型 The Dependent Factor: The dependent factor is the sum of RAC and PAC (RAC+PAC) in quantity of OD. 第三章台灣貿易商產業分析 34 The average size RAC is 3. kw unit (also called the cost control model for 第一節台灣貿易商結構分析 36 第二節 financial 台灣貿易商的困境與挑戰 model simulation purpose), 39 while PAC average size is 17.8kW unit. 第三節 China market 台灣中小型貿易業的五力分析 Window unit sale peaked 4 during 1997 to 1. millions sets. Taiwan - 4 -

2 目錄 market Window unit peak at 0.7 millions in the mid 90. China Window units continue to decline since 1997, replaced mainly by the equivalent size mini split. The reasons are: 1). Economy: Mini-split reached the scale economy much faster than Window unit due to competitive pricing; 2). Superior performance: Low noise and better appearance than window unit. China produced 42 millions ID in 200, is the 致謝詞 world s largest producer, from some 0 local and foreign brands. According 1 to 中文摘要 BSRIA, 9% of the total produced is for export market. Other than package 2 (self Abstract contain) unit, PAC also includes the Central residential unit system ( 3 ). This is a small central air conditioning system for residential and light 目錄 commercial application. Its capacity range is between 7kW to 40kW, can be applied to 60~00 square meter space, for large apartment or small stores. The US design roof top and Japanese design multiple split, and locally made small air-cooled water system are competing feverishly in this market. PAC application represents the most 第一章 growth 緒論 potential in China at least till The followings are data from BSRIA: 9 第一節 研究背景 9 第二節 Residential (RAC) / light commercial (PAC) unitary market, volume of outdoor units 研究動機與目的 10 第三節 199A 1996A 1997A 1998A 1999A 2000A 研究範圍與架構 11 第四節 研究流程 12 Annual % change Window 1,228,71 1,376,000 1,00,000 1,340, % Portable/Moveable 32,800 41,000 0,000 44, % Minisplits/ductless splits - 第一節 交易成本理論 14 第二節 Grand Total 策略行銷 4C 理論 24 第三節 五力分析模型 29 第三章 Table 台灣貿易商產業分析 2-1: Indicate 199~2000 RAC/PAC Market Actual from BSRIA. 34 第一節第二節第三節 <kw/rac 19.3% Cooling only 847, ,448 1,038,780 1,080, % Heat pump 1,977,920 2,17,712 2,423,820 2,20,61,004,300,698, % >kw/pac 21.3% Cooling only 11,93 127,12 1, , % Heat pump 269, , , , % Total ductless splits 19.% 台灣貿易商結構分析 36 台灣貿易商的困境與挑戰 39 台灣中小型貿易業的五力分析 % China GDP China Statistics Note: 1996~1998 window Source: BSRIA CHINA Both of data is from BSRIA, but the continual growth rate(yoy) is nearly 100%. Please refer it in care. 199~1998 mini/ductless sp Calculating according to corresponding percentage from 1999 to 2001 & from 2003 to Calculating according to the growth rate from 1999 to 2001 & from 2003 to 200

3 目錄 2001A 2002A 2003A 2004A 200A 2006E 致謝詞 1 Note: Source: BSRIA 目錄 Table2-2: Indicate 2001~200 RAC/PAC Actual and 2006 Estimate from BSRIA CHINA 第一章緒論 第一節 Minisplits/ductless 研究背景 splits - 9 第二節 研究動機與目的 10 第三節 研究範圍與架構 11 第四節 研究流程 12 第二章 Table 文獻探討 2-3: Indicate RAC/PAC Market Projection till 2010 from BSRIA. 14 第一節交易成本理論 14 第二節 Total number 策略行銷 of RAC+PAC 4C 理論 is shown on the following tables. Table 1-1 indicated 24 第三節 total number 五力分析模型 of RAC+PAC 29 from 199 to 2000 and the annual percentage change 第三章 (estimation) 台灣貿易商產業分析 at 12.8% annual percentage change. Table 1-3 is the BSRIA estimation 34 第一節 from 2006 台灣貿易商結構分析 to 2010 at 6.% annual 36 percentage change. 第三節 In summary: 台灣中小型貿易業的五力分析 CHINA Residential (RAC) / light commercial (PAC) unitary market, volume of outdoor units Annual % change Window 1,018, , , ,000 40,000 4, % Portable/Moveable 30,000 87,000 90,000 80,000 78,400 76, % Minisplits/ductless splits - <kw/rac 8,48,000 11,070,000 12,731,000 1,00,000 17,700,000 19,21, % Cooling only 2,992,000 3,321,000 3,819,300 4,00,000,200,000,14, % Heat pump,6,000 7,749,000 8,911,700 11,000,000 12,00,000 13,700, % >kw/pac 1,30,000 1,39,000 1,769,000 2,230,000 2,420,600 2,711, % Cooling only 47, ,700 30, , , ,00 9.3% Heat pump 848,000 1,077,300 1,238,300 1,0,000 1,700,600 1,930, % Total ductless splits (PAC) 9,83,000 12,609,000 14,00,000 17,730,000 20,120,600 21,926, % Grand Total (RAC+PAC) 10,901,000 13,633,000 1,480,000 18,22,000 20,739,000 22,48, % GDP China Statistics Residential (RAC) / light commercial (PAC) unitary market, volume of outdoor units 200A 2006E 2007E 2008E 2009E 2010E Annual % change Annual % change Window 40,000 4, ,00 291,600 20, , % -14.3% Portable/Moveable 78,400 76,800 7,300 73,800 70,000 67, % -2.2% <kw/rac 17,700,000 19,21,200 20,646,010 22,43,400 24,631,000 26,400, % 6.8% Cooling only,200,000,14,60,846,010 6,230,620 6,830,620 7,400, %.6% Heat pump 12,00,000 13,700,640 14,800,000 16,204,780 17,800,380 19,000, % 7.3% >kw/pac 2,420,600 2,711,20 3,01,000 3,226,120 3,336,120 3,90, % 6.6% Cooling only 720, ,00 839, , , ,000.%.4% Heat pump 1,700,600 1,930,70 2,211,700 2,320,000 2,400,000 2,600, % 7.1% Total ductless splits (PAC) 20,120,600 21,926,40 23,697,010 2,661,20 27,967,120 29,990, % 6.8% Grand Total (RAC+PAC) 20,739,000 22,48,90 24,136,810 26,026,920 28,287,120 30,267,000 6.% 6.4% GDP China Statistics Note: Source: BSRIA estimation during that period is 1.3%. Table 1-2 indicate the same from 2001 to 2006E

4 Period BSRIA: RAC+PAC Total OD (qty) 4,472,280 4,949,000,30,000,23,000 9,37,000 10,06,000 容 Period 頁次 2006 BSRIA: RAC+PAC Total OD (qty) 10,901,000 13,633,000 1,480,000 18,22,000 20,739,000 Table 2-4 RAC+PAC total in quantity 199~200 from BSRIA 致謝詞 The Independent Factors: 中文摘要 Factor that may have influenced the growth of RAC+PAC from 199 to in Abstract China includes the followings: 3 目錄 Gross Domestic Products (GDP) 表目錄 Floor Space of Buildings Under Construction and Completed 7 Per Capital Annual Disposal Income of Households Household Consumption Expenditure Retail Price Index 第一章 緒論 Ex-factory Price Indices of Durable Consumer Goods 9 第一節 Data from 研究背景 the National Bureau of Statistics of China ( Yearbook 9 (3) 第二節研究動機與目的 10 were adopted for the analysis. We will examine these factors one by one. 第三節研究範圍與架構 Gross Domestic Products (GDP): China experienced sharp GDP increase after the reform begins in GDP has risen from Rmb362.4 billion to Rmb trillions in 200 (both figures at current 第一節交易成本理論 14 prices), more than 0 times in 27 years. Per capital GDP rising from Rmb379 to 第二節策略行銷 4C 理論 24 第三節 Rmb10,61. 五力分析模型 29 The following are (from Wikipedia) scatter graph of the People s Republic of 第三章 China s 台灣貿易商產業分析 GDP from 192 to 200, based on nominal GDP data published 34 by the 第一節 People s 台灣貿易商結構分析 Republic of China and 36 compiled by Hitotsubashi University (Japan) and 第二節 confirm by 台灣貿易商的困境與挑戰 the economic statistic indicator 39 from the World Bank. (4) 第三節台灣中小型貿易業的五力分析 4-7 -

5 致謝詞 1 目錄 Chart 2-1: China GDP Growth from 192 to 200, excerpt from Wikipedia 第一章 Gross 緒論 Domestic Product (GDP) refers to the final products at market 9 prices 第一節 produced 研究背景 by all resident units in a country during a certain period of time. In 9 the 第二節研究動機與目的 10 practice of national accounting, gross domestic product is calculated with three 第三節研究範圍與架構 11 第四節 approaches, 研究流程 i.e. production 12 approach, income approach and expenditure approach, which reflect gross domestic product and its composition from different aspects. Air conditioning industry itself is a part of the GDP, we will examine the correlation between GDP and Per Capital GDP with the RAC+PAC growth. 第一節交易成本理論 14 第二節 In summary: 策略行銷 4C 理論 24 第三節五力分析模型 29 Period China Statistics: GDP (100 mm yuan) 8, , , , , ,468.1 Period 第三章台灣貿易商產業分析 34 China Statistics: 97, , , , ,879.0 第一節 GDP (100 mm 台灣貿易商結構分析 yuan) 36 第二節 Table 2- 台灣貿易商的困境與挑戰 Gross Domestic Products from 39 China Statistics Yearbook Chart 3-1. 第三節台灣中小型貿易業的五力分析 4-8 -

6 Per Capital GDP summary: Period China Statistics: Per Capital GDP (yuan/person) 4,84.00, , , ,1.00 7,08.74 Period China Statistics: Per Capital GDP (yuan/person) 致謝詞 1 7, , , , , Table 2-6 Per Capital Gross Domestic Products from China Statistics Yearbook Chart 3-1. 目錄 China s Bureau of Statistics made GDP Adjustment on Feb. 28, Year Historical 13.0% 12.60% 10.0% 9.60% 8.80% 7.80% 7.10% 8.00% 7.0% 8.30% 9.0% 9.0% Adjustment 14.00% 13.10% 10.90% 10.00% 9.30% 7.80% 7.60% 8.40% 8.30% 9.10% 10.00% 10.10% 第一章緒論 9 第一節 Table 2-7: 研究背景 China GDP Adjustment by the Statistics Bureau on Feb. 28, 第二節研究動機與目的 10 第三節研究範圍與架構 11 第四節 China Statistics: 研究流程 12 Period GDP (100 mm yuan) 8, , , , , ,468.1 Period China Statistics: GDP (100 mm yuan) 109, , , , ,321.0 第一節 Table 2-8: 交易成本理論 Revised Gross Domestic Products by the Statistics Bureau, Feb. 28, 第二節策略行銷 4C 理論 24 第三節 Floor 五力分析模型 Space of Buildings 29 Under Construction and Completed In the newly developed market such as China, the Air Conditioning businesses grow hand in hand with the construction industry. We will examine floor space of 第三章台灣貿易商產業分析 34 building both under construction and completed for its correlation with RAC+PAC 第一節台灣貿易商結構分析 36 growth. The time lags between building construction begin and installation of air 第三節 conditioners 台灣中小型貿易業的五力分析 should also be considered

7 目錄 Floor Space of Buildings under Construction refers to floor space of buildings under construction during the reference period, including newly started buildings, buildings started earlier and continued during the reference period, and buildings suspended earlier but restarted during the reference period, buildings completed during the reference period, and buildings under construction and then suspended 致謝詞 during the reference period. 1 中文摘要 In summary: 2 Period China Statistics: Floor 目錄 Space of Buildings Under Construction (10000 m²) 89, , , , , , Period 圖目錄 China Statistics: Floor 8 Space of Buildings Under Construction (10000 m²) 188, , , , , Table 2-9 Floor Space of Building Under Construction from China Statistics 第一章緒論 9 Yearbook Chart 第一節研究背景 9 第二節研究動機與目的 10 Floor Space of Buildings Completed refers to the floor space of buildings that are 第三節研究範圍與架構 11 第四節 completed 研究流程 in the reference 12 period in accordance with the requirements of the design, up to the standard for putting them into use, and have been checked and accepted by concerned departments as qualified ones. In summary: 第一節交易成本理論 14 第二節 China Statistics: 策略行銷 Floor 4C 理論 24 第三節 Space of 五力分析模型 Buildings 29 Period Completed (10000 m²) 3, , , , , , Period China Statistics: Floor Space of Buildings 97, , , , ,03.3 第三章 Completed 台灣貿易商產業分析 (10000 m²) 34 第一節 Table 2-10 台灣貿易商結構分析 Floor Space of Building 36 Completed from China Statistics Yearbook 第二節 Chart 台灣貿易商的困境與挑戰 39 第三節台灣中小型貿易業的五力分析

8 目錄 Per Capital Annual Disposal Income of Households In high land price countries such as Japan, Taiwan and Hong Kong, a large portion of the income is used for housing rental or loan, a relatively small portion of income is left for living standard improvement such as buying air conditioner. However, in China, most urban resident stay in the house provided by the government, therefore 致謝詞 a relatively high portion of the income can be used for non-housing expenditure. 1 中文摘要 Therefore, DPI may have more influence on purchasing power than GDP. 2 Comparing DPI between urban and rural household, the urban households is 2.71 目錄 times of the rural ones in 199, while in 2004, the ratio increases to 3.2 times. Urban 表目錄 household DPI has more correlation with the air conditioner market than the 7 rural 圖目錄 one. Therefore, DPI of the urban households is used for this analysis. 8 Disposable Income of Urban Households refers to the actual income at the disposal 第一章 of members 緒論 of the households which can be used for final consumption, other 9 non- 第一節 compulsory 研究背景 expenditure and savings. This equals to total income minus income 9 tax, 第二節 personal 研究動機與目的 contribution to social 10 security and sample household subsidy for keeping 第三節研究範圍與架構 11 diaries. Following formula is used: Disposable income = total household income - income tax - personal contribution to social security - sample household subsidy for keeping diaries 第二章 In summary: 文獻探討 14 第一節交易成本理論 14 第二節 China Statistics: 策略行銷 Per 4C 理論 24 Capital Annual Disposal 第三節五力分析模型 29 第三章台灣貿易商產業分析 34 第一節第二節第三節 Period Income of Urban Households (yuan) 4, ,838.90,160.30,42.10, , Period China Statistics: Per Capital Annual Disposal Income of Urban Households (yuan) 6, , , , , 台灣貿易商結構分析 36 台灣貿易商的困境與挑戰 39 台灣中小型貿易業的五力分析

9 目錄 Table 2-11: Per Capital Annual Disposal Income of Urban Households from China Statistic Yearbook Chart Household Consumption Expenditure: Household consumption expenditure represents the actual purchase on durable 致謝詞 goods items such as air conditioners. Similar to household DPI, urban household 1 consumption expenditure is 3.40 times of the rural ones in 199, while in 2004, the ratio increased to Therefore, the urban data are used for the analysis. 目錄 Consumption Expenditure of Urban Households refers to total expenditure of the sample households for consumption in daily life, including expenditure on eight categories such as food, clothing, household appliances and services, health care and medical services, transport and communications, recreation, education and cultural services, housing, miscellaneous goods and services. 第一章 In summary: 緒論 9 第一節研究背景 9 第二節 China Statistics: 研究動機與目的 Urban 10 Households Consumption 第三節 Expenditure 研究範圍與架構 (yuan) 11 Period ,874.00,430.00, , , , Period China Statistics: Urban Households Consumption Expenditure (yuan) 7, , , , , Table 2-12 Urban Households Consumption Expenditures from China Statistic 第一節交易成本理論 14 Yearbook Chart 3-18 第二節策略行銷 4C 理論 24 第三節五力分析模型 Retail Price Index Retail Price Indices reflect the trend and degree of change in retail prices of 第三章 commodities 台灣貿易商產業分析 during a given period. The change in retail prices of commodities 34 第一節 directly affect 台灣貿易商結構分析 the living expenditure 36 of urban and rural residents, government 第二節 revenue, 台灣貿易商的困境與挑戰 purchasing power of residents 39 and the equilibrium of market supply and 第三節台灣中小型貿易業的五力分析

10 demand, and the ratio of consumption to accumulation. Therefore, the retail price indices are useful to analyze the changes of the above economic activities. Since there is no index for household home appliance retail price before 2003, general index is used for the analysis. The following indices used preceding year as 100. Period 致謝詞 China Statistics: General 1 Retail Price Indices Period China Statistics: General Retail Price Indices Table General Retail price index from China Statistic Yearbook Chart 9-7 目錄 表目錄 Adjusting by using 199 as base at 100, the data is converted as follows: 7 Period China Statistics: General Retail Price Indices Period China Statistics: General Retail Price Indices 第一章緒論 第一節 Table 研究背景 General retail price index adjusted, using 199 as 第二節研究動機與目的 10 第三節 However, 研究範圍與架構 from the supply 11 and demand relationship, the price has an inverted relationship with dependent RAC+PAC, the lower the price the higher the number of air conditioner sold, adjusting by inverting the indices from above: Period China Statistics: General 第一節 Retail Price 交易成本理論 Indices 14 第二節策略行銷 4C 理論 24 第三節 China Statistics: 五力分析模型 General Period Retail Price Indices Table General retail price index inverted, using 199 as 1.0 第三章台灣貿易商產業分析 34 This study will review the retail price indices in various forms, of its correlation with 第一節台灣貿易商結構分析 36 the RAC+PAC air-conditioning market growth. 第三節台灣中小型貿易業的五力分析

11 Ex-factory Price Indices of Industrial Products Durable Consumer Goods: The ex-factory price indices of durable consumer goods are another indicator that may influence market changes. It may have a more direct impact on sales volume. Ex-factory Price Indices of Industrial Products reflect the trend and degree of 致謝詞 changes in general ex-factory prices of all industrial products during a given period, 1 including sales of industrial products by an industrial enterprise to all units outside the enterprise, as well as sales of consumer goods to residents. It can be used to analyze the impact of ex-factory prices on gross output value and value-added of the 目錄 industrial sector. The following indices used preceding year as 100. Period China Statistics: Ex- Factory Price Indices of Durable Consumer 第一章緒論 Goods 9 Period 第一節 China Statistics: 研究背景 Ex- 9 Factory Price Indices of 第二節研究動機與目的 Durable Consumer 第三節 Goods 研究範圍與架構 11 第四節 Table 2-14 研究流程 -1 Ex-factory 12 Price indices of Durable Consumer Goods from China Statistic Yearbook Chart 9-12 第二章 Adjusting 文獻探討 by using 199 as base at 100, the data is converted as follows: 14 第一節交易成本理論 14 China Statistics: Ex- 第二節策略行銷 4C 理論 24 Factory Price Indices of 第三節 Durable 五力分析模型 Consumer 29 Period Goods Period China Statistics: Ex- Factory Price Indices of 第三章 Durable 台灣貿易商產業分析 Consumer 34 Goods 第一節台灣貿易商結構分析 36 Table Ex-factory Price indices adjusted, using 199 as 100 第三節台灣中小型貿易業的五力分析

12 However, from the supply and demand relationship, the price has an inverted relationship with dependent RAC+PAC, the lower the price the higher the number of air conditioner sold, adjusting by inverting the indices from above: Period China Statistics: Ex- Factory Price Indices of Durable Consumer Goods Period China Statistics: Ex- 致謝詞 1 Factory Price Indices of Abstract Durable Consumer 3 Goods 目錄 Table Ex-factory Price indices inverted, using 199 as 1.0 Two more additional closely related independents factors were reviewed during the analysis: Urban population changes in percentage of total 第一章 緒論 Number of air conditioner owned by urban households 9 第一節研究背景 9 第二節 Urban 研究動機與目的 population changes 10 in percentage of total population: 第三節 Between 研究範圍與架構 198~2004, China urbanization 11 ratio increases steadily from 22% to 41.8%. The urbanization ratio is 0% on average for middle develop nation, while high income nation is 79%. From the urbanization development point of view, when the 第二章 ratio 文獻探討 is increase from 36% to 60%. The country is at the accelerating stage 14 of its 第一節 urbanization. 交易成本理論 China is at the stage of accelerating urbanization. It is estimated 14 that 第二節 the ratio 策略行銷 will reach 8.7% 4C 理論 by 2020, above the middle developed country level. 24 The 第三節五力分析模型 29 air conditioning market should be affected by this change greatly. Urban populations refer to all people residing in cities and towns, while rural 第三章台灣貿易商產業分析 34 populations refer to population other than urban population. 第一節台灣貿易商結構分析 36 第二節 In summary: 台灣貿易商的困境與挑戰 39 第三節台灣中小型貿易業的五力分析 4-1 -

13 Period China Statistics: Urban Population (%) 29.00% 29.40% 31.90% 30.40% 30.90% 36.10% Period China Statistics: Urban Population (%) 37.70% 39.00% 40.0% 41.80% 43.10% Table 2-1 Urban Population ratio from China Statistic Yearbook Chart 2-3: 致謝詞 1 中文摘要 Number of Air Conditioner Owned by Urban Households at Year-end: 2 Abstract Research indicated that there is a correlation between GDP and number 3 of air 目錄 conditioner owned per household. It is reported that when the per capital income reached US$4,000~$4,00., there will be one air conditioner per household. China has more population live in the subtropical zone any other nation in the world. This may represent higher than average number of air conditioner per household. Analysis by Professor Long, Wei Ding of Shanghai Tong ji University showed DPI 第一章 and 緒論 electrical power consumption have a correlation with the number of 9 air 第一節 conditioner 研究背景 per household. Accordingly, by 2010 there will be 12.8 number 9 of air 第二節 conditioner 研究動機與目的 per 100 households, 10 and the number will reach 190 by 第三節 In summary: 研究範圍與架構 11 Period China Statistics: Number of Air conditioner Owned Per 100 Urban Households at Year-end (qty) 第一節交易成本理論 14 Period 第二節策略行銷 4C 理論 24 China Statistics: Number 第三節五力分析模型 29 of Air conditioner Owned Per 100 Urban Households at Year-end (qty) 第三章 Table 台灣貿易商產業分析 2-16 Number of air conditioner owned per 100 urban households at year 34 end 第一節 from China 台灣貿易商結構分析 Statistic Yearbook Chart 第三節台灣中小型貿易業的五力分析

14 2.3 Data Examinations 目錄 Validity of the various independent factors will be examined here Comparing RAC+PAC correlation of with GDP and Per Capital GDP GDP reflected total output growth while per capital GDP has the effect of dilution 致謝詞 by the rural population. Using FX linear regression analysis, GDP R-square is higher, 1 therefore GDP is used for the analysis. RAC + PAC Total (OD (100 mm yuan) - (yuan/person) - Abstract Dates qty) - Forecast(Linear 3 Regression) 目錄 第一章緒論 9 第一節 Mean 研究背景 10,873, , , 第二節 Median 研究動機與目的 10 10,06, , ,08.74 第三節 Standard Deviation 研究範圍與架構 11,69, , ,19.43 Variance 32,03,406,868,94.0 1,614,769, ,819,90.43 Table : Comparing GDP with Per Capital GDP using linear regression analysis with FX. 第一節 Comparing 交易成本理論 floor space of buildings under construction versus completed: 14 第二節 Floor space 策略行銷 of buildings 4C 理論 under construction including newly started, buildings 24 第三節五力分析模型 29 started earlier, and buildings restarted during the reference period, buildings 第三章 reference 台灣貿易商產業分析 period. Standard office or apartment building takes 1~3 years to complete, 34 第一節 therefore 台灣貿易商結構分析 some of which may be 36 duplicated year to year. Building completed has 第二節 more correlation 台灣貿易商的困境與挑戰 with the installation 39 of air conditioner. It refers to the floor space 第三節台灣中小型貿易業的五力分析 Gross Domestic Product Forecast(Linear Regression) Per Capital GDP Forecast(Linear Regression) ,24, , , AIC BIC Mean Absolute Percentage Error (MAPE) 12.77% 9.76% 6.62% Sum Squared Error (SSE) 1,110,877,706, ,187,19, ,706, R-Square 9.28% 92.6% 92.31% Adjusted R-Square 94.76% 91.83% 91.46% Durbin Watson completed during the reference period, and buildings suspended during the

15 of buildings that are completed, up to the standard for putting them into use, for example, air conditioner installed and have been checked and accepted by concerned departments as qualified ones (i.e. permit issued). Analyzing both data with linear regression method indicated floor space of building 致謝詞 completed has a closer correlation with the air conditioning growth. R-square 1 (97.48%) for floor space of building completed is greater than the R-square (92.8%) for floor space under construction. Therefore, floor space of building completed is use for further analysis. 目錄 圖目錄 8 第一章 緒論 9 第一節研究背景 9 第二節 研究動機與目的 10 第三節 研究範圍與架構 11 第四節 研究流程 12 第二章 文獻探討 14 第一節交易成本理論 14 第二節 Table : 策略行銷 Comparing 4C 理論 Floor Space completed against under construction 24 using 第三節 linear regression 五力分析模型 analysis 29 with FX Retail price index 第三章 The 台灣貿易商產業分析 commodity retail price indices changes are useful to analyze the 34 living 第一節 expenditures 台灣貿易商結構分析 of urban and rural 36 residents, government revenue, purchasing power of resident and the equilibrium of market supply and demand, and the ratio of 第三節台灣中小型貿易業的五力分析

16 consumptions to accumulation. Since there is no index for air conditioner along, general index is used for the analysis. The chart below, using exponential smoothing method, shows the retail price index changes. 致謝詞 目錄 China Static: 9-7 Retail price index (199 = 100) Forecast of China Static: 9-7 Retail price index (199 = 100) Fitted Values Chart 2-2-1: Retail price index trend analysis using FX. 第一章緒論 Urban population 第一節研究背景 9 第二節 Urban populations 研究動機與目的 refer 10 to all people residing in cities or towns. Data are in 第三節 percentage 研究範圍與架構 of total population. 11 The number does not show strong correlation with 第四節 the conditioner 研究流程 market 12 change. R-square = 89.08%, Adjusted R-square = 87.86%. Using exponential smoothing method, the result is shown below: 第二章文獻探討 第一節交易成本理論 第二節 0.6 策略行銷 4C 理論 第三節 0.4 五力分析模型 第三章台灣貿易商產業分析 34 China Static: 2-3 Urban population in percentage of total () Forecast of China Static: 2-3 Urban population in percentage of total () Fitted Values 第一節台灣貿易商結構分析 36 Chart 2-2-2: Urban population trend analysis using FX. 第三節台灣中小型貿易業的五力分析

17 2.3. Number of air conditioner owned per 100 urban household at year-end The number of air conditioner owned is actually the result of all the independent factors that influenced the dependent RAC+PAC. Although the exponential smoothing method indicated a good correlation, R-square = 97.74%, Adjusted R- square = 97.49%, this factor will not be used due to its lagging character. 致謝詞 1 20 Abstract 目錄 China Statistics: 14-4 Number of Air conditioner Ow ned Per 100 Urban Households at Year-end (qty) Forecast of China Statistics: 14-4 Number of Air conditioner Ow ned Per 100 Urban Households at Year-end (qty) Fitted Values Chart 2-2-3: Number of air conditioner owned trend analysis using FX.. 第一章緒論 9 第一節 2.4 RAC+PAC 研究背景 forecast: Double-exponential versus Liner-regression method: 9 第二節 The results 研究動機與目的 of both methods 10 are shown here for future discussion and comparison. 第三節研究範圍與架構 RAC+PAC growth using double-exponential method: 第二章 文獻探討 第一節 交易成本理論 14 第二節 策略行銷 4C 理論 24 第三節 五力分析模型 BSRIA: RAC + PAC Total (OD qty) Forecast of BSRIA: RAC + PAC Total (OD qty) Fitted Values 第三章台灣貿易商產業分析 34 Chart 2-3-1: Double-exponential method forecast chart, using FX 第一節台灣貿易商結構分析 36 第三節台灣中小型貿易業的五力分析

18 Audit Trail - Statistics Accuracy Measures Value Forecast Statistics Value AIC Durbin Watson 1. BIC Mean 10,873, Mean Absolute Percentage Error (MAPE) 9.39% Median 10,06, Sum 容 Squared Error (SSE) 14,32,099,494,86.90 Standard Deviation 頁次,69, R-Square 9.2% Variance 32,03,406,868,94.0 Adjusted R-Square 9.02% Method Statistics Value Method Selected Double Exponential Smoothing-Holt Alpha 0.34 Gamma 1.00 致謝詞 Chart 2-3-2: Double-exponential method forecast audit trail, using FX 1 Forecast -- Double Exponential Smoothing-Holt Select Forecast Abstract Date Annual ,003, ,98, 目錄 ,193, ,789, ,384, 表目錄 ,979, ,74, ,169, 圖目錄 ,764, ,39, ,94, ,49, ,144, ,739, Avg 39,871, 第一章 Max 緒論 6,739, Min 23,003, 第一節研究背景 9 Chart 2-3-3: Double-exponential method forecast smoothing-holt, using FX 第二節研究動機與目的 10 第三節研究範圍與架構 RAC+PAC growth using Liner Regression method: 第二章 文獻探討 第一節 交易成本理論 第二節 策略行銷 4C 理論 第三節 五力分析模型 BSRIA: RAC + PAC Total (OD qty) Forecast of BSRIA: RAC + PAC Total (OD qty) Fitted Values 第三章 Chart 台灣貿易商產業分析 2-4-1: Liner Regression method forecast chart, using FX 34 第一節台灣貿易商結構分析 36 第三節台灣中小型貿易業的五力分析

19 Audit Trail - Statistics Accuracy Measures Value Forecast Statistics Value AIC Durbin Watson 1.02 BIC Mean 10,873, Mean 容 Absolute Percentage Error (MAPE) 12.77% Median 頁次 10,06, Sum Squared Error (SSE) 1,110,877,706, Standard Deviation,69, R-Square 9.28% Variance 32,03,406,868,94.0 Adjusted R-Square 94.76% Method Statistics Value Method Selected Linear Regression 致謝詞 Chart 2-4-2: Liner Regression method forecast audit trail, using FX 1 Forecast -- Linear Regression Selected Forecast Abstract Date Annual ,868, ,34,4.4 目錄 ,200, ,866, ,31, 表目錄 ,197, ,863, ,29, 圖目錄 ,19, ,861, ,26, ,192, ,88, ,24, Avg 31,696,2.4 第一章 Max 緒論 42,24, Min 20,868, 第一節研究背景 9 Chart 2-4-3: Liner Regression method forecast, using FX 第二節研究動機與目的 10 第三節研究範圍與架構 11 第四節 2. Building 研究流程 the best 12 fitting model of RAC+PAC growth in China Using multiple regression method, all of the above factors, the data from 199 to 200, total of 11 years of data, will be fit to the model set as below. 第一節 RAC + PAC 交易成本理論 Total (OD qty) = C(1) + ( (Gross Domestic Product (100 mm 14 yuan)) 第二節 * C(2) ) 策略行銷 + ( (Floor 4C Space 理論 of Buildings Completed (10000 sq.m)) * C(3) ) + 24 ( (Per 第三節五力分析模型 29 Capita Annual Disposable Income of Urban Households (yuan) ) * C(4) ) + ( (Urban Household Consumption Expenditure (yuan) ) * C() ) + ( (Retail price 第三章 index 台灣貿易商產業分析 (199 = 100 inverted)) * C(6) ) + ( (Ex-Factory Price Indices of Industrial 34 第一節 Products 台灣貿易商結構分析 Durable Consumer Goods 36 (199 = 100 inverted) ) *C(7) ) 第三節 The chart 台灣中小型貿易業的五力分析 below indicated the model present 4 a nice fit of the data available

20 致謝詞 1 RAC + PAC Total (OD qty) Forecast of RAC + PAC Total (OD qty) Fitted Values 中文摘要 Chart 2--1 Multiple Regression method forecast chart, using FX 2 Audit Trail -- Coefficient Table (Multiple Regression Selected) Series Included Standard Overall 目錄 Descritpion in Model Coefficient Error T-test F-test RAC + PAC Total (OD qty) Gross Domestic Product (100 mm yuan) Dependent -24,368, ,63, Yes Floor Space of Buildings Completed Yes Per Capita Annual Disposable Income of Urban Households (yuan) Urban Household Consumption Yes 6,93.6 2, Yes 1, , 圖目錄 Expenditure (yuan) 8 Retail price index (199 = 100 inverted) Ex-Factory Price Indices of Industrial Yes 217, , Yes -186, , Chart 2--2 Multiple Regression method forecast audit trail coefficient, using FX 第一章緒論 9 Audit Trail - Statistics 第一節 Accuracy Measures 研究背景 Value Value 9 AIC 第二節 BIC 研究動機與目的 ,873, Mean Absolute Percentage Error (MAPE) 3.49% 10,06, Sum Squared Error (SSE) 1,763,600,492,229.38,69, 第三節 R-Square 研究範圍與架構 % 32,03,406,868,94.0 Adjusted R-Square 98.62% Method Statistics Value Method Selected Multiple Regression Chart 2--3 Multiple Regression method forecast audit trail statistics, using FX Forecast -- Multiple Regression Selected Forecast 第一節 Date 交易成本理論 Annual ,080, ,122,1.80 第二節 2009 策略行銷 30,163, C 理論 ,204, 第三節 2011 五力分析模型 36,24, ,287, ,328, ,369, ,410, ,42, ,493, ,34, 第三章台灣貿易商產業分析 ,7, ,617, Avg 43,849, 第一節 Max 台灣貿易商結構分析 63,617, Min 24,080, Chart 2--4 Multiple Regression method forecast, using FX 第三節台灣中小型貿易業的五力分析

21 容 頁次 63,617, , , , , AIC BIC Mean Absolute Percentag 3.49%.21% 7.60% 3.20% 2.79% 1.90% 1.28% Sum Squared Error (SSE 1,763,600,492, ,769, ,78, , , R-Square 99.4% 97.23% 9.88% 98.48% 97.09% 34.43% 98.91% Adjusted R-Square 98.62% 93.07% 89.69% 96.21% 92.73% 0.00% 97.28% Durbin Watson Mean 10,873, , ,13.7 6, , Median 10,06, , , , , Standard Deviation,69, , , , , Variance 32,03,406,868,94.0 1,614,769, ,141,248, ,00, ,686, 致謝詞 1 目錄 Chart 2-- Multiple Regression method statistics summary, using FX 圖目錄 The Multiple Regression Model: 8 RAC + PAC Total (OD qty) = -24,368, ( (Gross Domestic Product (100 mm yuan)) * ) + ( (Floor Space of Buildings Completed (10000 sq.m)) * - 第一章 緒論 ) + ( (Per Capita Annual Disposable Income of Urban Households (yuan) 9 ) * 第一節 6,93.6 ) 研究背景 + ( (Urban Household Consumption Expenditure (yuan) ) * 1, ) 第二節研究動機與目的 10 + ( (Retail price index (199 = 100 inverted)) * 217, ) + ( (Ex-Factory Price 第三節研究範圍與架構 11 第四節 Indices of 研究流程 Industrial Products 12 Durable Consumer Goods (199 = 100 inverted) ) * -186, ) 第二章 This 文獻探討 model has R-sq = 99.4% and Adjusted R-sq of 98.62% (Chart 2--3), which 14 is 第一節 adequate 交易成本理論 for business forecasting purpose. Regarding the coefficient 14 of the 第二節 independent 策略行銷 factors, 4C the 理論 different scale of each coefficient does not imply the 24 level 第三節五力分析模型 29 of their impact to the output variable. The contribution of each independent factor to the trend can not be drawn directly here. Some T-test values may indicate low 第三章 eminency 台灣貿易商產業分析 that can be regarded as insignificant. (E.g. T-test for GDP = Chart 第一節 2--2). However, 台灣貿易商結構分析 the R-Sq of 36 Retail price index is 34.79%, indicating weak 第二節 correlation. 台灣貿易商的困境與挑戰 39 第三節台灣中小型貿易業的五力分析

22 2.6 Building the best fitting model of RAC+PAC growth in China using logarithm data with the Multi-regression method Taking logarithm of dependent RAC+PAC and all the independent factors Period (year) RAC + PAC Total (OD qty) Log Gross Domestic Product (100 mm yuan) Log Floor Space of Buildings Completed (10000 sq.m) Log 致謝詞 (yuan) Log 1 目錄 Table 2-18 Dependent and independent factors in logarithm Using pro-cast to examine data after logarithm 第一章緒論 9 RAC + PAC Total Gross Domestic Buildings Retail price index 第一節研究背景 of Urban Consumption (OD qty) Log - Product (100 mm Completed (10000 (199 = Households (yuan) Expenditure (yuan) Dates Forecast(Double yuan) Log - sq.m) Log - inverted) Log - Log - Log - 第二節研究動機與目的 Exponential Forecast(Holt- 10 Forecast(Double Forecast(Exponent Forecast(Double Forecast(Holt- Smoothing-Holt) Winters) Exponential ial Smoothing) Exponential Winters) 第三節研究範圍與架構 11 Smoothing-Holt) Smoothing-Holt) 第一節 交易成本理論 14 第二節 策略行銷 4C 理論 24 第三節 五力分析模型 29 Chart Logarithm Pro-cast method statistics summary, using FX The retail price indices remain the one with weaker correlation as indicated by the 第三章台灣貿易商產業分析 34 low R-sq value. 第一節台灣貿易商結構分析 36 第三節 Using 台灣中小型貿易業的五力分析 linear regression method to examine 4 data after logarithm: Per Capita Annual Disposable Income of Urban Households Urban Household Consumption Expenditure (yuan) Log Retail price index (199 = 100 inverted) Log Ex-Factory Price Indices of Industrial Products Durable Consumer Goods (199 = Floor Space of Ex-Factory Price Per Capita Annual Indices of Disposable Income Urban Household Industrial Products Durable Consumer Goods (199 = 100 inverted) Log - Forecast(Double Exponential Smoothing-Holt) 2020 Forecast AIC BIC Mean Absolute Per 0.8% 0.36% 0.7% 0.31% 0.31% 0.41% 0.2% Sum Squared Erro R-Square 94.61% 97.76% 90.31% 98.40% 97.66% 33.98% 98.86% Adjusted R-Square 94.01% 97.20% 89.24% 98.22% 97.07% 33.98% 98.73% Durbin Watson Mean Median Standard Deviation Variance

23 Dates RAC + PAC Total (OD qty) Log - Forecast(Linear Regression) Gross Domestic Product (100 mm yuan) Log - Forecast(Linear Regression) Floor Space of Buildings Completed (10000 sq.m) Log - Forecast(Linear Regression) Per Capita Annual Urban Household Disposable Income Retail price index Consumption of Urban (199 = 100 Expenditure (yuan) Households (yuan) inverted) Log - Log - Log - Forecast(Linear Forecast(Linear Forecast(Linear Regression) Regression) Regression) Ex-Factory Price Indices of Industrial Products Durable Consumer Goods (199 = 100 inverted) Log - Forecast(Linear Regression) Forecast AIC BIC Mean Absolute Percentage Error (MAPE) 0.40% 0.37% 0.61% 0.27% 0.22% 0.1% 0.11% Sum Squared Error (SSE) R-Square 97.08% 97.8% 94.20% 98.96% 98.87% 29.10% 99.82% Adjusted R-Square 96.76% 97.61% 93.% 98.8% 98.7% 21.23% 99.80% Durbin Watson 致謝詞 Mean Median Standard Deviation Variance Chart Logarithm Linear Regression method statistics summary, using FX 目錄 Using multiple regression method, include all of the factors above, the data 表目錄 from 199 to 200, will be fit to the model set as below: 7 圖目錄 第一章緒論 第一節研究背景 第二節研究動機與目的 10 RAC + PAC Total (OD qty) Log Forecast of RAC + PAC Total (OD qty) Log Fitted Values 第三節研究範圍與架構 11 第四節 Chart 研究流程 Logarithm 12 Multiple Regression method forecast chart, using FX 第二章 文獻探討 14 第一節 交易成本理論 14 第二節 策略行銷 4C 理論 24 第三節 五力分析模型 29 第三章 台灣貿易商產業分析 34 第一節 Chart 台灣貿易商結構分析 Logarithm Multiple 36 Regression method forecast, using FX 第三節台灣中小型貿易業的五力分析

24 目錄 容 頁次 致謝詞 1 中文摘要 Chart Logarithm Multiple Regression method audit trail coefficient, using 2 FX Abstract 3 目錄 表目錄 7 Chart Logarithm Multiple Regression method audit trail statistics, using FX RAC + PAC Total (OD qty) Log = ( (Per Capita Annual Disposable 第一章緒論 9 Income of Urban Households (yuan) Log ) * 1.6 ) + ( (Urban Household 第一節研究背景 9 第二節 Consumption 研究動機與目的 Expenditure 10 (yuan) Log ) * 2.26 ) + ( (Retail price index (199 = 100 第三節 inverted) 研究範圍與架構 Log) * 3.48 ) + ( (Ex-Factory 11 Price Indices of Industrial Products Durable Consumer Goods (199 = 100 inverted) Log ) * -3.0 ) The purpose of taking logarithm is to reduce the influence due to different scale. However, converting the forecast results (Chart 2-7-2), total RAC+PAC forecast by 第一節交易成本理論 will be 210,310,209 in quantity. This equals to 16.7% CAGR for the next 1 第二節策略行銷 4C 理論 24 第三節 years. This 五力分析模型 is unrealistically 29 high. The actual growth from 199 to 2000 is 1.3%, and 12.8% from 2000 to 200 on average. The trend should slow down together with most other leading indicators such as GDP, building floor space, and DPI. 第三章台灣貿易商產業分析 34 第一節 2.6. Differencing 台灣貿易商結構分析 to induce stationarity: 36 第二節 Differencing 台灣貿易商的困境與挑戰 is a simple transformation 39 to remove trend from the data. 第三節台灣中小型貿易業的五力分析

25 目錄 Since t = a + bxt + Ut, t = a + b Xt + Ut RAC + PAC Total (OD qty) Log 容 Year Differencing 頁次 致謝詞 中文摘要 Abstract 目錄 Table Differencing the logged data Using linear regression to analyze the result as follows: 第一章 0.03緒論 第一節 0.02 研究背景 第二節 0.01 研究動機與目的 10 第三節 0.01 研究範圍與架構 第四節 研究流程 RAC+PAC Log Forecast of RAC+PAC Log Fitted Values 第二章 Chart 文獻探討 2-7- Linear regression of the differencing data 14 第一節交易成本理論 14 第二節 Converting 策略行銷 linear regression 4C 理論 result after differencing, the 2020 RAC+PAC 24 total 第三節 become 189,29,686 五力分析模型 (Table ). It has a reducing effect of the trend by about 10% at the end of the 1 years forecast. However, it remains far exceeded the more realistic forecast number of 63,617,613 which will be 7.7% CAGR from 2006 to 第三章台灣貿易商產業分析 第一節台灣貿易商結構分析 36 第三節台灣中小型貿易業的五力分析

26 Linear Regression 目錄 致謝詞 ,331,9 1 中文摘要 ,668,940 2 目錄 圖目錄 ,011,489 8 第一章 緒論 ,233,823 9 第一節研究背景 ,937,490 第二節 研究動機與目的 ,,12 第三節 研究範圍與架構 ,742,689 第四節 研究流程 ,29, Multiple Regression method taking out Retail Price Index, and DGP using 第一節交易成本理論 14 logarithm data: 第二節策略行銷 4C 理論 24 第三節 Chart 五力分析模型 indicated Retail 29 Price and GDP are not included in the model, to find influence: 第三章台灣貿易商產業分析 34 第一節第二節第三節 Year Convert to RAC+PAC in log 台灣貿易商結構分析 36 台灣貿易商的困境與挑戰 39 台灣中小型貿易業的五力分析 Forecast RAC+PAC total ,973, ,919, ,029, ,864, ,798, ,316, ,298, ,83, ,038, ,042, ,143, ,682, ,924, ,0,308 Table Converting linear regression results out the forecast using multiple regression logarithm data without retail price index

27 致謝詞 RAC + PAC Total (OD qty) Log Forecast of RAC + PAC Total (OD qty) Log Fitted Values Abstract Chart Logarithm Multiple Regression Chart w/o Retail Price and GDP factor, 3 using FX 目錄 Forecast -- Multiple Regression Selected Forecast Date Annual 圖目錄 第一章 2014 緒論 第一節 2016 研究背景 第二節 2018 研究動機與目的 第三節 2020 研究範圍與架構 Avg 7.88 Max 8.34 Min 7.42 Chart Logarithm Multiple Regression forecast w/o Retail price and GDP 第二章 factor, 文獻探討 using FX 14 Audit Trail -- Coefficient Table (Multiple Regression Selected) 第一節交易成本理論 14 RAC + PAC Total (OD qty) Log 第二節策略行銷 4C 理論 24 Floor Space of Buildings Completed (10000 sq.m) Log Yes Per Capita Annual Disposable Income of Urban Yes 第三節 Households (yuan) 五力分析模型 Log 29 Urban Household Consumption Expenditure (yuan) Log Ex-Factory Price Indices of Industrial Products Durable Consumer Goods (199 = 100 inverted) Log Series Included Standard Overall Descritpion in Model Coefficient Error T-test Elasticity F-test Dependent Yes Yes Chart Logarithm Multiple Regression coefficient w/o Retail price and GDP 第三章台灣貿易商產業分析 34 factor, using FX 第一節台灣貿易商結構分析 36 第三節台灣中小型貿易業的五力分析

28 Audit Trail - Statistics Accuracy Measures Value Forecast Statistics AIC Durbin Watson BIC Mean Mean Absolute Percentage Error (MAPE) 0.43% Median Sum Squared Error (SSE) 0.02 Standard Deviation R-Square 97.12% Variance Adjusted R-Square 9.20% Method Statistics Value Method Selected Multiple Regression 致謝詞 Chart Logarithm Multiple Regression statistics w/o Retail price and 1 GDP 中文摘要 factor, using FX 2 Neither Retail price index nor GDP will influence the result of the forecast. 目錄 In this Chapter, we have examined different method of quantitative forecasting, using various independent factors that influence the outcome of the dependent: the air conditioner market growth in China. We will follow by comparing forecast against other statistic data for its validity. 第一章緒論 9 第一節研究背景 9 第二節研究動機與目的 10 第三節研究範圍與架構 11 第一節 交易成本理論 14 第二節 策略行銷 4C 理論 24 第三節 五力分析模型 29 第三章 台灣貿易商產業分析 34 第一節 台灣貿易商結構分析 36 第二節 台灣貿易商的困境與挑戰 39 第三節 台灣中小型貿易業的五力分析