窗簾產品網路銷售之環境、人口與經濟因素的影響～以美國市場為例

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(1)國立臺灣師範大學管理學院高階經理人企業管理碩士在職專班碩士論文 Program of Executive Master of Business Administration College of Management National Taiwan Normal University Master Thesis 窗簾產品網路銷售之環境、人口與經濟因素的影響～以美國市場為例 The Impact of Environmental, Demographic and Economic Factors on Online Sales of Window Covering in USA. 學生姓名：許基業 Name：Ko Chi-Yeh Jackson. 指導教授：邱皓政博士 Advisor：Chiou Hawjeng Ph.D.. 中華民國 105 年 5 月 May, 2016 0.

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(3) Abstract The introduction of the internet has increased the habits of online purchasing as consumers’ preference. This forces retailers to adapt and change their way of merchandising their products from the store shelf to the world of the internet. How do factors like the environmental, demographic, and economic affect online business? This research studies the online sales of the hard window covering industry within the United States. This research is a study of Company A’s customers’ online sales in 50 states within the country of United States. The first chapter gives a brief introduction to the Window Covering Industry and their background. The next chapter introduces different varieties of window coverings and explains their functionality including their features and benefits. Next is the introduction of Company A and its background. This research uses the data provided by Company A to analyze the correlations between online sales (dependent variables) and independent variables including environment, demography, and economics in the United States. Lastly, data are pooled and analytical tools; descriptive statistics, correlation coefficient, and multiple regression analysis; are used to emphasize the data and to search out their impact of each factor on the sales of different categories of hard window coverings. The results of the correlation analysis and regression analysis reveal that certain ethnic groups, Non-Hispanic White, Black and Asian affect the sales more than others. The data also suggest that Asians favor both Light Filtering and Room Darkening product categories and Blacks have a high preference of product categories in Light Blocking. Regional wise, the data also suggest that the best sales are in the South of United States. But the best testing ground for new products would be in the Northeast region of New York, Pennsylvania, and New Jersey. The average annual temperature is more influential on the overall sales of window coverings than the median household income. And yet, the number of clear days in the sky would decrease the sales of certain window coverings. This result is much more than anticipated and not only helps the sales on the internet, but also the sales in the retail stores. Keywords: Window treatment, window covering, correlation coefficient, multiple regression analysis, 窗飾, 窗簾, 相關係數, 回歸分析.. 2.

(4) 摘要隨著網際網路的普及，進而提升了消費者上網購物的偏好，迫使零售業者去適應並且改變從貨架到全球網際網路的產品銷售模式。本研究即針對美國境內的窗飾產業，在環境、人口和經濟等因素如何影響網路購物的銷售，進行實徵分析。本研究主要是對於Ａ公司在美國五十個州的網路銷售狀況進行分析研究。文中首先簡要介紹窗飾產業及其背景，再來則是說明各式窗飾產品的功能，其中包含產品特色與效益，接著則介紹Ａ公司與公司背景。本研究採用Ａ公司所提供的數據來分析網際網路銷售（依變數）與自變數的相關性，包含美國各州的環境、人口和經濟等變數，藉以了解這些預測因素對於不同類型窗飾產品銷售狀況的影響為何。最後，匯集數據並使用分析工具：描述性統計，相關係數和多元回歸分析，以強調數據並尋找每個因素對於不同類別窗飾產品所產生的影響。根據相關分析和回歸分析的結果，某些種族群體，非西班牙裔白人，黑人和亞洲人影響銷量比其他族群為多。此外，數據還顯示，亞洲人對於透光與不透光產品的喜好，而黑人則對於半透光的產品有高度的偏好。就區域性來看，數據顯示銷售最佳的區域屬美國南部，但對於新產品最佳試水溫的區域則是在紐約，賓夕法尼亞州和新澤西州的東北地區。然而，年平均氣溫比中產階級的家庭收入對於窗飾產品的整體銷售更有影響力，氣候晴朗的天數將減少一定的窗簾銷售。此研究的實徵分析結果不僅可以幫助網際網路的銷售，亦有助於零售商店的銷售。最後，除了深入討論本研究的發現之外，本研究也針對管理意涵與未來研究建議提出討論。. 3.

(5) Acknowledgements It is my pleasure to thank the people who have made this thesis possible. This research would not have been possible to complete without the support from my thesis advisor, Professor Hawjeng, Chiou, under whose guidance I chose this incredible topic. I would like to state what a privilege it was to be guided and supported all the way to put together a constructive report. It was this consistent assistance and advice that motivated me to keep moving ahead. His patience is well acknowledged and that is what led towards the completion of this significant research. I would like to highly thank my boss who provided and authorized me to use all the resources within the company to help and finish this thesis. Without his permission and assistance, I would have never collected the crucial data that was the heart of my thesis to complete it. I also wanted to thank my consultant in Canada who had encouraged me to take the study in EMBA and frequently checking up my status in school. His constant caring not only strengthens me to keep up but also my determination to finish courses. I also wish to express my gratitude to all the members of my thesis committee. I would like to thank Ms. Tsui-Chu, Pong and Ms. Yu-Giar, Chen who had provided me with valuable suggestions and help throughout the research, when I felt things were difficult and impossible at times. Most importantly, I am indebted to my wife and daughter who provided enough motivation and helped me to keep my spirit up. Last but not least, my loving parents who have always been there for me, giving me everything I needed in order to move forward. I want to thank them for their unlimited love and support which has shaped me into the hard working and responsible person I am now.. 4.

(6) Table of Contents Abstract ………………………………...……………….…………………………… 2 摘要 ……………………………………………………………………………….… 3 Acknowledgements ………………………………………………………………….. 4 Chapter 1 Introduction ……………………………………………………..….…… 7 1.1 Background of Research ……………………………….…………….…… 7 1.2 Motivation of Research ………………………………………………...…. 8 1.3 Purpose of Research ……………………………………………………. 10 1.4 Structure of Thesis …………………………………………………..…… 11 1.5 Research Method ………………………………………………....……… 12 Chapter 2 Literature Review …………………………………………………......… 13 2.1 Introduction to Hard Window Covering Industry .………………………. 13 2.1.1 Window Shutters or Plantation Shutters ………………………….....…… 14 2.1.2 Mini Blinds or Venetian Blinds …………………………………...…...… 16 2.1.3 Roman Shades ………………………………………......……………….. 17 2.1.4 Roller Shades ……………………………………………………….……. 18 2.1.5 Pleated and Cellular Shades ……………………………………………... 21 2.2 USA Market Share ……...……………………………………………… 23 2.3 Sales Channels and Distributions………………………………………… 25 2.4 Related Thesis of Window Covering Industry …………………...……… 27 Chapter 3 Research Methodology ……………………………………………......… 29 3.1 Introduction of Company A in Study …………..……………………...… 29 3.2 Market Share of Company A …………………………………………….. 30 3.3 Analytical Method …………………………………………….................. 34 3.4 Research Analysis ……………………………………………………….. 36 Chapter 4 Result ……………………………………………………………….…… 37 4.1 Descriptive Analysis of Key Factors ………….……………….………….... 37 4.1.1 Sales Data by State …………………………………….………………... 37 4.1.2 Weather Data by State …………………………………………………… 43 4.1.3 Demographic Data by State ……………………………………………... 45 4.1.4 Economic Data by State ……………………………………………….… 47 4.2 Correlation between Studied Variables ………..……………………………. 49 4.3 Multiple Regression Analysis …………………………………………...….. 55 4.3.1 Light Filtering Sales in Units and Dollars ………………………………. 55 4.3.2 Room Darkening Sales in Units and Dollars ………………………….… 56 4.3.3 Light Blocking Sales in Units and Dollars ……………………………… 58 4.3.4 Total Sales in Units and Dollars ………………………………………… 59 Chapter 5 Discussion and Conclusion …………………………………………….... 61 5.

(7) 5.1 Major Findings of the Study ………………………………………...……… 61 5.1.1 Environmental Factor ……………………...……………………….…… 61 5.1.2 Population Factor …………………………………………………...…… 62 5.1.3 Economic Factor ………………………………………………………… 63 5.2 Discussions and Conclusions ……...…………………………………….…. 63 5.3 Limitations and Recommendations ………..……………...………………... 64 Reference ………………………………………………………………………….... 65. 6.

(8) Chapter 1 Introduction 1.1 Background of Research Window Treatment or Window Covering is the name of this industry category. It is comprised of an interior decorating element that is placed on, in, around, or over the window. Often, the meaning of window treatment is to install the element which enhances the aesthetics of the window and the room in which it resides. This industry is further divided into two sub categories, hard and soft. Hard window treatments are made by hard material like wood or vinyl and soft window treatments are anything made by soft material like curtain or drapery. It is the hard window treatments that are mostly manufactured by the Taiwanese entrepreneurs and shipped from China to worldwide and mostly shipped to United States. Giant retailers like Home Depot, Lowes, Walmart, Target, JC Penney, Bed Bath & Beyond, etc. have sections in the retail store dedicated to the hard window treatments. It is a significant part of business for these home furnishing retailers and mass merchants. From figure 1, the industry is estimated at US 2.0 billion dollars in 2014 and has grown steadily in the past six years (see figure 1). However, since the world introduced the internet, online shopping has been a significant tool for consumers to shop. It changed the way people normally purchasing a product. For these giant retailers, they are forced to join this battle over the internet and their online business has become more important than ever.. Figure 1: Revenue of Blind & Shade Manufacturing (NAICS 33792) in United States from 2009 to 2014.Sourced:http://www.statista.com/statistics/292335/revenue-of-blind-and-shade-manufacturing-inthe-us/ 7.

(9) Windows alleviate interior thermal discomfort by reducing heat loss and/or heat gain and can lower heating, cooling, and electric lighting costs. Some new high-performance windows cost more but it is difficult to compete with “mainstream” or average window. (Peter, L., Dariush, A., & Charlie, H. 2000) Thus, a simple, low cost of window treatment solves the problem. In the conclusion of article “Manual control of window blinds and electric lighting: implications for comfort and energy consumption” by Newsham, G.R. (1999) that providing occupants with manually operable window treatments, and compared to providing no window shading devices, is likely to improve comfort. As a consumer buys window treatments, they need to consider the sizes of the windows. And no sizes are the same among different windows, some are big and some are small; some are wide in width and some are long in length. For a retailer to be successful in this industry, they need to carry as many sizes they can in a given retail floor in the store, this means if such store has more floor, such store can then carry more stock sizes or Stock Keeping Units (SKUS). But since the introduction of the internet, it is easy to carry these SKUS or stock sizes as it is inessential to have any physical rack or stand to display them. That is to say, there are limitless stock sizes or SKUS for online purchase. Another good thing about the internet is that it’s accessible anywhere with a mobile device and online shopping has become a major selling tool for these giant retailers. United States has been the country with the highest consumption of hard window treatments. There are 50 states within the continent and how can a giant retailer be successful with all the different window sizes in different regions or states? As my consultant who had over 50 years of knowledges and experiences in this industry had told me once before, windows tend to be larger in size in the west coast states such as California, but some window sizes are also big in south states like Florida and smaller sizes are located throughout the states like Pennsylvania, New York and others. Thus if any retailer is able to gather such information or discover the factors that affect the sales of these window treatments, they would excel in this industry. Window sizes are different in different houses even in the same state; the window size of a house is different with neighbor’s window size. So what elements may affect the online sales? Elements like geographic location, the average temperature, number of clear days, population, racial population, the number of home sales and the median household income could influence the sales of hard window treatments. 1.2 Motivation of Research Home furnishing stores like Home Depot, Lowes, Menards, JC Penney and mass merchants like Walmart, Target, etc. are the places for home owners to shop and 8.

(10) purchase “Do-It-Yourself” products during the early spring. It could be a summer project like putting on a new fresh coat of paint, or adding fixtures, remodeling or repairing of the house. Hard window treatment has been a significant section of business in home furnishing stores and mass merchants as they generate as much as 2.0 billion U.S dollars in annual sales. The topic is really intriguing as there are limited research studies in Hard Window Treatment and often times, ignored by the public because of its lack of excitement as the electronic gizmo such as iPhone. In this study, we will look at three factors and their impacts. First is the environmental factor. Since window size varies geographically, like urban versus rural area, or upstate vs downstate, it is difficult to categorize them into specific sizes. Instead, state sales data are studied to see the correlation between online sales and their geographic location. From previous research discovery, that weather has direct effects on the sales of window coverings. This study focuses on major weather indicators including both the average temperature and the number of clear days (Rea, 1984) in each state. In the United States, each state has different weather according to their geographic location. Secondly, this research also looks at the demographic factor. The population is another major factor since higher population would have higher sales. However, the United States is like a giant melting pot with different racial groups. According to United States Census Bureau, seven ethnic and racial categories are officially recognized. They are Non-Hispanic White, Hispanic or Latino, Black, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander and Mixed Race. This study looks at which ethnic groups affect the online sales of window coverings. Lastly, the economic factor in this study is taking to account as each state has different economic conditions. Even though the United States has the federal government but each state has each state’s governance. Thus, each state has its own economic condition. This research looks at two elements; 1) the number of home sales in a single year and 2) the median household income in each state. Household income is very important for the home owner. It determines their ability to shop which affects the sales of window coverings. Number of home sales is another element to study since it is a habit for Americans to remove all the window coverings after the house is sold. The windows of new homes are not covered by any window coverings. The new owner of the house would need to purchase these new windows coverings. In summary, this research only looks at these different factors as there are limited literatures on the study of sales of window coverings in the United States. This study focuses on these exploratory factors and the findings of this study will have lots of contributions for future research. This research may also serve as reference for this industry development. 9.

(11) 1.3 Purpose of Research The purpose of this research is to identify the key factors that affect the overall sales of different product categories. Both correlation coefficient and multiple regression analysis tools are used for this purpose. Namely, this research uses correlation coefficient to explore the linear relationship between independent variable and depend variables, and to conduct the cross examination of the impact of the average temperature, number of clear days, state population, racial population, the median household income and the number of home sales in each state. The multiple regression analysis is used to determine the degree of contribution from each key factor toward the overall sales of different product categories. Product categories are differentiated by their light control as current industry standard. There are three types of light controls, Light Filtering, Room Darkening and Light Blocking. Light filtering is when the window covering is only covering the light but yet it is still transparent to see through. Room Darkening is when the light is gently filtered and still gives privacy, or the opaque visibility. Light Blocking is just blocking the light so the visibility is total blackout. Below table shows some examples of the type of products that would be considered under such categories. Table 1: Product Categories Definition. Light Control * Light Filtering. 全透光 Room Darkening. 半透光 Light Blocking. 全遮光. Visibility Transparent > 65.0% Opaque > 85.0% Blackout > 99.0%. Insulation Examples of Window Coverings Sun Screen Roller Shades, Bamboo Weak Roman Shades & Bamboo Roller Shades Fabric Roller Shades, Pleated Shades & Moderate Cellular Shades Venetian Blinds, Shadow Roller Shades Strong and Shutters. Note: Light Control refers to the day light being filtered by the window covering.. Every window covering has a certain quality of insulation which helps to save energy. It is very important as it may cut down the energy bills. It helps to maintain the room temperature by keeping the hot or cold air outside the window covering. The above table shows the relationship between the type of product category and its insulation quality. Light Filtering has low insulation quality because of its ability to filter the light and is less effective at keeping the hot or cold air out. Room Darkening has a medium insulation quality because it is better able to filter the light and better at keeping hot or cold air out. Light Blocking has a strong insulation quality as it blocks the light and is capable of keeping hot or cold air out better than the other two.. 10.

(12) 1.4 Structure of Thesis Chapter 1 of this thesis deals with the importance of hard window treatment in the home furnishing stores. It briefly describes the specific factors that are affecting the overall sales of hard window treatment in different states. In chapter 2, it includes a brief introduction to the Hard Window Covering Industry and a description of different product categories. Also it includes discussion of their market share in United States. Lastly, it includes literature reviews to understand the works that have been studied in the related researches. Chapter 3 gives an introduction of Company A and its market share. It then deals with the techniques and analytical tools used to develop the analysis of the data. Lastly, a brief discussion about the basics in correlation coefficient and introduces multiple regression analysis technique. In chapter 4 we use the methodologies in Chapter 3 to organize the collected data and analyze them through bar graphs, tables of correlation coefficient and multiple regression line analysis. This chapter also conducts correlation analysis to validate the reliability and fitness of the regression model. Based on our findings, recommended measures are suggested in Chapter 5 to help the Hard Window Covering industry to improve its online sales by understanding those factors.. 11.

(13) 1.5 Research Method Research method of this thesis is depicted in the following flowchart (see figure 2):. Define Research Problem. Literature Review. Collect and Organize Data. Data Analysis & Presentation. Result Analysis using Correlation Coefficient and Regression. Conclusion and Recommendation. Figure 2: Flowchart of Research.. In this research, we only collected the data from the online sales of Company A. Using correlation coefficient and by running tests between the independent and dependent variables through multiple regression analysis; and investigate the correlation between independent and dependent variables.. 12.

(14) Chapter 2 Literature Review 2.1 Introduction to Hard Window Covering Industry In the past, most of the medium size enterprises organized their own Industrial Association, for example, Taiwan Knitting Industry Association. However, the hard window blind industries had never organized their own industrial association. Their businesses were from nothing to plenty and from small to large. To count from 1985 to 1993, the blind industry had made a considerable amount of foreign exchange for the Taiwanese Government. Their advanced technological skills attracted both European and American manufacturers to move outside their continents, thus creating many special and professional Taiwanese manufacturers. At that time, this industry exported five hundred forty foot containers monthly with just one single item, and its exporting value exceeded 50 million U.S. dollars with an average of 10 million units. Before 2001, the export values kept on exceeding its previous year (張元蓉, 2006). Based on Taiwanese living and life style, it is difficult to imagine why there would be such a high demand of one single item for each year. In the early 1980s, Taiwanese manufacturers were importing both skills and machines from Japan and United States, both for producing and exporting. The majority of PVC mini blind was for United States, while Japan had a high demand of aluminum blind. Up to now, about 60% of the blind productions are still controlled by the Taiwanese. By the 1990’s, Taiwanese manufacturers were both specialized and professional in their field of manufacturing at low cost materials. As the government encouraged Taiwanese manufacturers to move into China with low cost labor and materials, many Taiwanese window covering manufacturers had moved to China by the late 1990’s (張元蓉, 2006). By the late 2000’s, the window covering industry had become diverse and broad selections, pleated shades, roman shades, roller shades, cellular shades, shutters and other specialized window coverings were introduced by these Taiwanese manufacturers whether they were coming from Taiwan, China or South East Asia. Based on 2014 year’s rough statistics, the total business value was about 2.0 billion U.S. dollars (See figure 1), but according to some suppliers’ estimation, the figure may be even higher due to new raw materials being continuously developed. It is another economic miracle in this window covering industry. Window covering is diverse and has a wide variety of products. It is often categorized into two types, soft and hard materials, soft materials would be drapery or fabric while hard is referring to blinds, shades, shutters, drapery hardware, etc. Operation includes from left to right, right to left, up or down, manual or mechanical, 13.

(15) electrical or remote controlled. Their functions are mostly home decorative, providing privacy or light filtering, sound-proofing, reflection of sun glare, interior temperature insulating, etc. Here we categorized some major types of hard window covering. 2.1.1 Window Shutters or Plantation Shutters Window Shutters or Plantation shutters are internal shutters conventionally made of wide wooden slats that are mounted in solid frames (see figure 3). The purpose of installing them is to facilitate the flow of fresh air through a building during the warm season and also to provide enough shade for keeping the interiors cool. Plantation shutters are also known as louvers or jalousies. You can find them in varying sizes and shapes, and you can get them installed to suit the shape and size of doors and windows of your house.. Figure 3: Window Shutters or Plantation Shutters (Example of Light Blocking). Shutters, in their basic design, have been in use since the middle ages. They formed a part of the structures having space for windows, but they were without glass. The shutters remained closed during inclement weather, but when weather became hot, they would be left open to admit fresh air for ventilation. When they arrived in South America and the Caribbean, the European colonists realized that this design ideally suited the prevailing climate. A number of older houses are provided with these typical interior shutters, and that possibly goes to explain why they are called plantation shutters. These shutters can pack a window completely, and a rod provided in the middle 14.

(16) is used for the opening or closing of the blinds. It's a normal practice to hinge shutters so as to pull them out for getting added ventilation. Some are made to include hinged panel sets that get folded crosswise over the window, enabling users to fold a part or the entire shutter back according to their requirement. Plantation shutters in café style go up to a part of the windows (see figure 4), thus creating privacy, but they do not obscure the window completely. They may also be styled and tailor-made to fit in irregular spaces, like circular or triangular windows. In the majority of homes, plantation shutters get separated from other elements by a glass window, though very old and more informal homes would not have glass in this position. They may also have detachable windows that may be stored when the weather is good, and fixed during winters for protecting the interiors of home from rain and wind.. Figure 4: Café Style Shutters (Example of Light Blocking). Though traditionally plantation shutters are made of wood, there are shutters made from other materials, like plastic and other synthetic compounds. For the consumers who have environment issues and simply don't like using natural wood, they may opt for recycled materials and get them painted or dyed, according to the material used for making them. Compared to traditional shutters made using wood, it is easier to clean the ones made from recycled material. They also last longer and are not so prone to getting cracked or faded when being exposed to the sun. 15.

(17) 2.1.2 Mini Blinds or Venetian Blinds A mini blind is a type of horizontal window blind made of long, narrow slats held together by string (see figure 5). Its slats are less than half the width of a regular venetian blind, and are often made of aluminum, measuring 15 millimeters (0.59 inches) or 25 millimeters (1 inch). The slats are opened and closed by rotating a rod or by directly pulling a string, and they are raised and lowered by pulling other strings. In the United Kingdom the term "venetian blind" also covers mini blinds.. Figure 5: Mini Blinds or Venetian Blinds (Example of Room Darkening). The long horizontal slats are held one above the other by the rungs of ladder cords shaped like a ladder. The lower ends of the legs of the ladder cords are secured to the long rail under the slats. Their upper ends are attached to the drive rod in the housing, the elongated box above the slats. As the drive rod rotates, one leg of each ladder cord moves up while the other moves down, causing the angle of the slats to change. In one design, this rotation is achieved by pushing up or pulling down on a long handle called a tilt wand connected to the drive rod by a lever. Lift cords along the ladder cords are also attached to the rail. They pass through holes in the slats and into the housing above, where they go over pulleys, come in and exit through the cord lock. For safety it's important that the lock always works. A downward pull on the 16.

(18) main lift cord raises the slats by the cords pulling up the rail below the slats. The cord lock holds the main lift cord to keep the slats up until the cord is pulled to release the lock. The safety lock made the cord lock easier to use. 2.1.3 Roman Shades Roman shade is a simple and practical window treatment to accent a room or to provide privacy from bright sun or nosy neighbors (see figure 6). A Roman shade is often a piece of fabric that is mounted at the top of a window. The fabric is pleated such that when the Roman shade's string is pulled, the fabric folds up in regular intervals. Not only does it look better than a boring plastic shade, it uses less fabric than other window treatments making it a less expensive alternative to ornate window treatments.. Figure 6: Fabric Roman Shades (Example of Light Filtering). Classic Roman shades have overlapping folds when the shade is lowered, but more different treatments do exist. Flat Roman shades have no folds when the shade is lowered. These shades, when made with sheer or light fabric, can soften bright southern lighting into a subtle, soothing light. Roman shades can be made using other materials like bamboo or paper which are also very specialized and decorative (see figure 7).. 17.

(19) Figure 7: Bamboo Roman Shades (Example of Light Filtering). 2.1.4 Roller Shades In America, window shades began appearing in homes and public buildings around 1780. Because these shades were made of translucent cloth or paper, their decorative designs could be seen by both the building’s inhabitants and those passing by outside. In the early nineteenth century, these shades were painted all over with romantic and imaginative landscapes. In the latter half of the century, these all-over landscapes were replaced with stenciled borders that often had a center medallion of floral or scenic imagery. While the all-over landscapes of the early nineteenth century exhibited primitive artistic technique, designs during the mid-nineteenth century were applied to the shades by copying, tracing, stenciling, or pouncing, producing imagery of a higher quality.. 18.

(20) Figure 8: Vinyl Roller Shades (Example of Light Blocking). In the modern days, roller shades have been innovated into several different styles and forms, and made with different materials like vinyl (see figure 8), fabric, paper, sun screen (see figure 9) and woven bamboo. Mechanism has transformed into a spring loaded bead chain which is used to raise and lower the shade. Color has trends of simplicity in solids or simple stripes. A new technology of fabric creating a unique design called “shadow shade” was introduced in the year 2000. (See figure 10). It features both privacy and light filtering to control the light coming through.. 19.

(21) Figure 9: Sun Screen Roller Shades (Example of Light Filtering). Figure 10: Shadow Shades (Example of Light Blocking) 20.

(22) 2.1.5 Pleated and Cellular Shades Pleated blinds are shades made from a pleated fabric (which helps to add texture to a room) that pull up to sit flat at the top of a window to hide from sight when open (see figure 11).. Figure 11: Fabric Pleated Shade (Example of Light Filtering). Honeycomb pleated blinds, or cellular blinds (actually cellular shades) are similar to pleated blinds except that they are made up of two or more layers joined at the pleats to form 'cellular' compartments that trap air, providing insulation (see figure 12). Due to their cellular construction, cellular blinds (aka energy saver) are known to the energy conscious as one of the highest energy-efficient and sound- absorbent 21.

(23) blinds of any window treatment. For greater insulation, cellular blinds are available in a variety of cell sizes, including 3/8" single cell, 3/4" single cell, 3/8" double cell and even triple cell. The more cells, the greater energy efficiency! All of the above can also be motorized, which is a great option for safety in homes with children and/or pets.. Figure 12: Cellular Shade (Example of Room Darkening). 22.

(24) 2.2 USA Market Share There are several major retailers who are selling window coverings in United States, retailers like Wal-mart, K-mart, Target, Home Depot and Lowes. Here is the data that was provided by the Company A and the data was from 2014. In figure 13, the bar graph is based on the number of linear footage of each different product displayed in different retail stores. Linear footage is a term that is used in this industry when it comes to merchandising the product. It is referring to the footage of displays or bays that have been used for merchandising the products. In another words, it is the number of feet that displays certain products visually for the consumer to shop. From this bar graph, we can see a couple things; one, both Lowes and Home Depot has most linear footage in total in store than the other three mass merchants, Wal-mart, K-Mart and Target. Two, both Home Depot and Lowes have the most product varieties (or number of products) when compared to mass merchants, Wal-mart, K-mart and Target. These differences are due to different types of stores and different types of customers. Home Depot and Lowes are Home Improvement stores which appeals to customers looking for more selection and specialized window coverings. Thus the product range offered by them is much more and the selected sizes offered are a lot more than the mass merchants. Mass merchants like Wal-mart, K-mart and Target have fewer sizes and less product variety because their customers are less specialized shoppers. Here is a pie chart that shows the market share of each different type of window coverings in United States. From figure 14, there is clear evidence of venetian blinds been the number one selling window covering from all the different categories. It consists of a total of 56%. The second place is the roman shades & Roll-up shades of 19% overall. The third place is the fabric & cellular shades which has 11%. It is amazing how many window coverings can be sold in a single year. It is estimated that Wal-mart sells their 1” mini blind (both LF & RD) by as much as 12 million pieces in a single year, Lowes sells their 1” mini blind at about 10 million pieces (both LF & RD) in a single year. This is just one single product in the window covering industry. The number would increase if we added everything up to an annual total of 2.0 billion dollars of window coverings in United States.. 23.

(25) Lowe's. THD. Wal-Mart. Target. K-Mart. 4 2 4 2 0. 16 2 2 8 8. 16 0 4. 6 0. 24. 10. 6. 0 2. 1" LF Blinds. 1" RD Blinds. FW & Vinyl Blinds. 0 0 8 8 0 1.5"/ 2" Shutters Real Wood Blinds. 16. Fabric/ Cellular Shades. 16. Bamboo/ PVC RS & RU. 0 3. 0 4 0 4. 8. Roller Shades. Verticals. Figure 13: Market Share of five major retailers in USA. Source: Retrieved from Company A. Bamboo/ PVC Roman Shades Verticals & Roll-Ups Roller Shades 6% 19% 4%. 1" RD Blinds 10%. 1" LF Blinds 14%. FW & Vinyl Blinds 27%. Fabric/ Cellular Shades Shutters 11% 4%. 1.5"/ 2" Real Wood Blinds 5%. Figure 14: Market Share of Different Types of Window Coverings in USA. Source: Retrieved from Company A.. 24.

(26) 2.3 Sales Channels & Distributions There are many sales channels for the window covering manufacturers but there are two major channels. One is thru the local retailers in the United States and another one is thru the online. From Company A’s sales data, it has been thirty years for them selling stock size window coverings thru local retailers like Wal-mart, JC Penney, Lowes, Home Depot and etc. It is until recent years that Company A has started to sell thru online. The stock sizes products are dealt in Free-On-Board (FOB) terms and the product are loaded in a container and shipped from China to the retailers in the United States. Depends on the type of product, each container can hold up to few thousands of units. The ownership of the product is transfer from the manufacturer to the retailers. The retailers take the products and distribute them into their own stores. The retailers would then sell to their customers who visit their store. For online sales, the product are manufactured and shipped from China and then storage in the warehouse in the United States. The customer orders online from the retailer’s website and the product is then shipped from the warehouse to the customer. Customer can order online from one unit to multiple units. The term is either freight prepaid or freight collect. The retailer does not take the ownership of the goods.. Figure 15: Revenue of Online of Company A. In figure 15, there is a huge increase in online sales from Company A in the first few years and there are double digit increases in the latter years. With this data, it clearly shows online sale is a significant business model to an industry. In figure 16 and 17, photos show difference between retail shopping and online shopping. 25.

(27) Figure 16: Lowes displays window coverings.. Figure 17: JC Penney’s website of online shopping.. 26.

(28) 2.4 Related Thesis of Window Covering Industry Window coverings are not only part of home living; they are an essential part of home décor. In addition to light filtering, sound-absorbing, landscaping and embellishment; a decorative window covering and its design style highlights each consumer’s preference and personality. From the historical point of view, in the early days mostly natural materials like bamboo and wood were used for the main materials of window treatments. It was not until the 17th century that it was replaced by textile materials. As late the 60’s and 70’s, it was replaced by the cheaper materials like Poly Vinyl Chloride or PVC. However, environment conservation protection awareness has caused the consumer to look for other safer and environmentally friendly materials. Such an increase in demand has led the industry to shift towards fire retardant, low cost and recycled materials which will be the next goal of development. (吳宗諭, 2009) Window covering is an industry led by the window covering manufacturers. Once in a while, new textile materials are provided by the fabric mills to be selected by these window covering manufacturers. As the technology of textile advances, newly innovative window coverings are presented in wide varieties with multiple aesthetics and functions. Not only covering and insulating interiors but others like sound reducing and electromagnetic resistance are added features. Other than the functions mentioned above, the biggest function of a window covering is that it changes the mood of the interior as the slats or draperies open and close. The lighting effects from the window change the context of the home furnishings. (林建良, 2010) Window covering has a multiple variety of products. It has soft (Ex.: drapery, roller shade, pleated shades, cellular shades, etc.) and hard (Ex.: aluminum made, steel made, wood made and PVC made mini blind, shutters and decorative rods.) as two categories, both have privacy and decorative features. At the end of 1979, the PVC mini blind was developed from zero to a revolutionary consumer product. It created a huge wave in the industry. The years between 1983 and 1989 created the heyday of Taiwanese plastic mini blind manufacturers as export numbers reached their highest peak. On October 6th, 1990, Taiwan's Ministry of Economic Affairs promulgated on the act of "Indirect Investment or Technical Cooperation Management in Mainland China ", which opened up both indirect investment and encouraged Taiwanese entrepreneurs to invest outside of their country. (張元蓉, 2009) This resulted in factories moving outside of Taiwan and orders shifted outside of the country. Plus both European and American consumer preference changed to more environmental friendly materials, PVC mini blinds were not welcome into the European market and the demand from North America decreased, causing more factories to move outside the country or go bankrupt and it was left with just a few 27.

(29) sizeable manufacturers that survived this ordeal. The reduction of export orders and the sever industry price competition resulted in a low profit margin. Window covering manufacturers were forced to turn to products that were high end products, unique products, or custom products such as roman shades, roller shades, etc. These new window coverings required higher skills in manufacturing, fabric material and multiple presentations, thus providing a higher profit margin and have become the main stream in the Taiwanese window covering market. (林建良, 2010). In terms of functionality, window covering, surrounding temperature and energy saving have a close relationship among one another. (林暐順, 2004). Matching room color is not an easy job! Coordinating colors not only makes a home appealing, but also allows the home owners to feel happy. Non-coordinating colors may cause and effect serious health issues. Some soft printed window coverings have colored dyes and chemical additives used during printing and post manufacturing process. These so called resins may contain formaldehyde, a type of carcinogen. (紀康寶, 2010). In the current living environment, window coverings have great impact on the human body’s psychological and physical health. However, in the current domestic market, it only recognizes “Fire-Retardant-Certified” window coverings (Fire Services Act Enforcement Rule Article 7). There are no other rules. As the technology of home furnishings advances and skills improve and with the opening of international trade, new window coverings are innovated every day. Different levels of imported fabrics by the trading companies have flooded the current market with untested window coverings and salespeople who have no knowledge of such an impact on health, directly or indirectly, leave the home owners situated in an unhealthy environment. So, the Industrial Development Bureau of Ministry of Economic Affairs is actively promoting “Soft Window Covering Made In Taiwan Smile Face Product Tested Quality Certificates”, lifting the good image of quality made products that are made in Taiwan protecting consumer health and providing safety. (蕭志舟, 2013). 28.

(30) Chapter 3 Research Methodology This research is by way of case study of Company A which collects data of their online sale history in a single year. This chapter reveals in four sections; First section gives introduction of Company A and covers its background; Second part of this chapter discusses Company A and its market share; Third section discovers the research procedure and; the Final section covers the analysis of this research. 3.1 Introduction of Company A in Study Company A is one of the leading window covering manufacturers in Asia, exporting a full line of mini blinds, roll up blinds, vertical blinds, shutters, roman shades and convolute rollers－all manufactured to their customers specifications as part of their private label program. Corporate headquarters and show room are located in Taipei close to the Taiwan World Trade Center and easily accessible to visiting buyers. Products are manufactured at our two factories in China. These facilities have more than 60,000 sq. meters of manufacturing space, equipped with up-to-date equipment and staffed by management with extensive experience in plastic technology, fabrication and assembly. Both are completely self-sufficient facilities directed from the company’s Taipei headquarters. All PVC products are manufactured in facility No. 1, while textile and woven wood products are produced in facility No. 2. A third facility will be located in North Vietnam which is one hour away from the Hanoi Airport with more than 90,000 sq. meters of manufacturing space. This company is strong and continues to grow in size. Company A is dedicated to continuous development of new products and improvements that respond to market demand. A continuous flow of new product is the life for a company to remain competitive in its industry. (Barczak, 1995) Company A stays in close contact with markets worldwide through their US and Canada liaison offices. This has contributed to company A leading in development of “Insulated Cellular” venetian blind slats; “Clear-View” room darkening blinds; a new “Luxer” gloss finish to give practical vinyl an aluminum look; and patented “Child-Safe” cordless systems for both blinds and roman shades. Other quality innovations are under development as part of a continuing program to supplement its basic assortment of high volume promotional products. Company A has been in this industry for over 30 years and stays in the top three major manufacturers in China and is a current vendor/supplier for major retailers in USA including but not limited to, Home Depot, Lowes, JC Penney, etc. Not only has their sale growth in the past 15 years doubled to over 75 million dollars, their number 29.

(31) of employees has been doubled with more than 1300 people today. Their gross profit has increased as much as 20% compared to 15 years ago. The key to its success lays in their fast development of new product innovation and acute sense of adaptation prior to the market change. A firm deals with the market intelligence to facilitate the customer needs and generate appropriate response to such needs is the key to success. (Borges, Hoppen, & Luce, 2009) As the technology advances throughout the years, Company A has been implementing a new management system from the inspiration of Toyota, the automaker; new automated machines for the manufacturing process; and new training programs for its employees to become more diverse and trained with multiple skills rather than single task work. However, both labor and material costs have increased over the years and the profit margin has been reduced. It is important to micromanage the business by more detailed analysis in its sales. 3.2 Product Portfolio of Company A It is estimated that there are over 100 million units of hard window coverings shipped from China to United States and Company A has about 10% of its market share. See below pie chart of an overall view.. Figure 18: Product Type Category in units of Company A.. 30.

(32) From figure 18, the pie chart shows that there is a significant quantity of mini blinds manufactured by Company A, it is over 50% which is more than half of what Company A has manufactured. The second highest product is the fauxwood blind which is another type of venetian blind but premium. The roller shade is in third place. However, the figures would be different in dollars, it is a different story.. Figure 19: Product Type Category in dollars of Company A.. In figure 19, the pie chart shows products in dollars of Company A, fauxwood Blind has a higher ratio than the mini blinds. Fauxwood blind is indeed a premium product which costs more to manufacture. Mini blind is a commodity product which is sold by bulk size. Thus dollar value of a mini blind is much lower than the fauxwood blind. Another very extreme product is the Shutters, it consists only 1% of units but 11% of dollars. That’s 11 times difference between dollars and units. Shutter is a very high premium product with extremely high costs to manufacture. For the purpose of this research, it is important to categorize them into different types of categories by their light control. It is difficult to analyze them by product type categories as it has no relationship with our three factors. It is important to review these products into three different product categories as specified in table 1 in both sales units and dollars. Those three product categories are Light Filtering, Room Darkening and Light Blocking. For the purpose of this research, comparison can be made between the sales of stock sizes and the online sales. Here is 31.

(33) the layout of all three based on the units and dollars.. Figure 20: Product Category in Units (top) and Dollars (bottom) of Company A.. The light filtering category has over 50% while light blocking only has 31% in units, but in dollars, the light blocking has over 50% and light filtering has 28%. The data clearly shows that light blocking is more expensive than the light filtering in cost. 32.

(34) It would be interesting to compare this with the online sales. See figure 21 for the online sales.. Figure 21: Product Category in Online Sales in Units (top) and Dollars (bottom) of Company A.. The data of online sales is telling a different story than the stock sizes. This data 33.

(35) clearly shows the online shopping focuses on more expensive and light blocking window coverings. Because of these differences between stock size sales and online sales, this research looks into the three factors that are affecting the online business. These factors are environment, economics and demographics in the United States. Table 2: Key Factors and Their Elements with Brief Descriptions. # Key Factors. Elements. Descriptions. Average Temperature. The average temperature of each state.. Number of Clear Days. The number of clear days of each state.. State Population. Population in each states.. Racial Population. Different racial groups' population in each state.. Home Sales. Number of Home Sales in each state.. Household Income. Median Household Income in each state.. 1. Environmental Factor. 2. Demographic Factor. 3. Economic Factor. The above table is a list of this research looking at the six elements that may affect the online sales. 3.3 Analytical Method Data are collected through Company A’s sales and marketing department by looking at their one specific business that they’ve managed in United States in the year 2014. Special Order Service (S.O.S.) is the definition of this specific business which means that the products are manufactured and shipped to vendor’s warehouse in United States. These products are sold through the retailers’ online business; and then courier delivered directly to the consumer. The original data consist of sales units and dollars of each state and filed by different retailers. The data also consist of product returns which were the result of incorrect orders or damaged during shipping and are removed from the data. Finally, these data of different retailers are then pooled together in one large organized data. However, as there are many different varieties of products in the pooled data, products are then categorized into three types by sharing the same common properties of light control. Please refer to table 1 in chapter 1. Geographic data are collected from the original data and further analysis is done by different regions in United States. United States Census Bureau defines four statistical regions, Northeast, South, Midwest and West. See below figure 22. This 34.

(36) would help to understand the different regions and their relationship with sales. These data are affiliated with other three factors, weather, demographic and economic.. Figure 22: Census Regions and Divisions of the United States; Source Census Bureau of United States of America. Source: www.census.com. Weather data are collected through “National Oceanic and Atmospheric Administration or NOAA” including the Average Temperature in 2014 and Number of Clear Days (the average number of days annually when cloud covers at most 30 percent of the sky during daylight hours) from the website of “Current Result”. Both the average temperature of each state and the number of clear days were collected from the same city in the same state. Demographic data are collected through Wikipedia website which consists of the population of each state in year 2014 and racial breakdown including Non-Hispanic White, Hispanic or Latino, Black, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander and Mixed Race in fifty different states. The ratios of different races were based on the year in 2010 as it is closest data to 2014. Economic data are collected from two web sites. The Home Sales (number of home sales in year 2014) in each state is collected from the Zillow web site and the household income by states of year 2014 is collected from the Wikipedia website. The 35.

(37) data from Zillow consist from June of 2008 to November of 2015, thus only the data collected from year of 2014 were used. 3.4 Research Analysis Every data set has a story, and if statistics are used properly, they do a good job of uncovering and reporting that story. In this research, descriptive statistic, correlation coefficient and multiple regressions are used as tools to analyze the data. Descriptive statistics is taking a set of data and boiling it down to a set of basic information. Correlation coefficient is used as a tool to see the strength and direction of the linear relationship between x and y. Then regression analysis is used to estimate the relationship among variables. As the researcher collects the data, the researcher arranged data accordingly by each state removing information that is not required such as the name of customer, address, telephone number, etc. Data is then rearranged accordingly into three categories in the format of sales units and dollars. Data are then organized to have all the independent variables including the average temperature, number of clear days, racial population (including Non-Hispanic White, Hispanic or Latino, Black, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander & Mixed Race) and the number of Home Sales and Median Household Income with dependent variables mixed into one data. Lastly, the researcher used both correlation coefficient and multiple regression analysis as tools on the data to provide the results in the next chapter.. 36.

(38) Chapter 4 Results This chapter displays the results of this research. The first section of this chapter looks at the independent variables of three factors: environmental, demographic and economic. This section uses descriptive analysis to analyze these key factors. Second section examines the correlation between independent variables and dependent variables. Finally, the last section uses multiple regression analysis as a tool to look at each independent variable and its effects on the dependent variables. 4.1 Descriptive Analysis of Key Factors 4.1.1 Sales Data by State For the environmental factor, this research studies two independent variables, both the average temperature and the number of clear days. For the geographic, sales data are organized by the sales units and dollars of each state in all three total product categories. The researcher also looked at each three different product categories’ sales units and dollars of each state. The bar graph in figure 23 is showing both sales units and dollars in total of all three categories in each state. It shows New York has the top ranking in sales units (4479 units) and dollars ($173,806.15), while Pennsylvania is in second place in both sales units (4201 units) and dollars ($173,541.56). Florida has the third place in sales dollars ($166,199.59) but fifth place in sales units (2835 units). Massachusetts is in the fourth place of sales dollars ($152,897.69) but has third place in sales units (3785 units). New Jersey is in fifth place in sales dollars ($130,142.88) but in fourth place in sales units (3072 units). The bar graph in figure 24 is showing both sales units and dollars in Light Filtering product category of each state. It shows that New York has the top ranking again in both sales units (747 units) and dollars ($16,270.25) while California is in second top position in both sales units (567 units) and dollars ($13,470.19). Illinois is the third ranking in both sales units (549 units) and dollars ($12,120.77). New Jersey is in fourth place in both sales units (513 units) and dollars ($11,121.80). Pennsylvania is the fifth position in both sales units (486 units) and dollars ($10,603.83). The bar graph in figure 25 is showing both sales units and dollars in Room Darkening product category of each state. It shows that New York yet again has the top ranking in both sales units (1002 units) and dollars ($25,286.93) while Pennsylvania is in second top position in both sales units (744 units) and dollars ($18,920.41). Illinois is the third ranking in sales units (541 units) but fourth place in 37.

(39) sales dollars ($13,834.01). Massachusetts is in fourth place in sales units (521 units) but rank fifth in sales dollars ($13,348.01). California is in fifth place in sales units (513 units) but third place in sale dollars ($14,259.30). The bar graph in figure 26 is showing both sales units and dollars in Light Blocking product category of each state. It shows that Pennsylvania has the top ranking in sales units (2971 units) but second in sales dollars ($144,617.32). Massachusetts is in second position in sales units (2816 units) but fourth place in sales dollars ($129,998.73). New York is the third ranking in both sales units (2730 units) and dollars ($132,248.97). Florida is the fourth places in sales units (2266 units) but number one rank in sales dollars ($151,979.38). New Jersey is the fifth position in sales units (2266 units) but Texas is in fifth place in sale dollars ($113,412.40). New Jersey is in sixth place in sales dollars ($105,815.30) and Texas is in eighth place in sales units (1529 units). The researcher also looked at the average dollars per unit of these states in the top rankings of Light Filtering, Room Darkening, Light Blocking and Total categories. Their data are organized in the below table 3. Table 3: Average Dollars per Unit in Light Filtering, Room Darkening, Light Blocking and Total.. California Florida Illinois Massachusetts New Jersey New York Pennsylvania l Texas. LF Avg. $$/Unit $23.76 $23.23 $22.08 $21.32 $21.68 $21.78 $21.82 $23.27. RD Avg. $$/Unit $27.80 $27.47 $25.57 $25.62 $26.20 $25.24 $25.43 $26.62. LB Avg. $$/Unit $62.13 $67.07 $57.65 $46.16 $51.49 $48.44 $48.47 $74.17. Total Avg. $$/Unit $43.72 $58.62 $39.26 $40.40 $42.36 $38.80 $41.31 $59.67. The data clearly shows these three states, California, Florida and Texas are in the top three average dollars per unit in all four different categories. The data suggest that under the same categories, their average window sizes are larger than other states as larger window covering size is more expensive than the smaller size.. 38.

(40) Figure 23: Total of all three product categories and its sales units and dollars of each state of USA.. 39.

(41) Figure 24: Light Filtering product category and its sales units and dollars of each state of USA.. 40.

(42) Figure 25: Room Darkening product category and its sales units and dollars of each state of USA.. 41.

(43) Figure 26: Light Blocking product category and its sales units and dollars of each state of USA. 42.

(44) 4.1.2 Weather Data by State In the Weather factor, this study looks at two variables; average temperature of each state and their number of clear days in a single year. In figure 27, the average temperature data shows that Florida is in second highest rank. The rest of the four best sales states: New Jersey (27th), Pennsylvania (30th), Massachusetts (32nd) and New York (39th); are nowhere on top ten lists. In the number of clear days, their ranking is as follows: Florida is in 23rd place, Massachusetts is in 28th place, New Jersey is in 33rd place, Pennsylvania is in 40th and New York is in 46th. From the graph, there is not enough to suggest relationship between weather and sales units and dollars.. 43.

(45) Figure 27: Average Temperature and number of clear days of each state of USA.. 44.

(46) 4.1.3 Demographic Data by State Demographic Factor is referring to the population in each state. However, the researcher also looked at the racial groups in each state. First, a brief look at the population in each state compared to the total sales units and dollars. In figure 28, the bar graph shows the population in each state and California has the highest population. In second place is Texas, third place is Florida and New York is in fourth place. Pennsylvania is in sixth place, New Jersey is in eleventh place and Massachusetts is in fourteenth place. The data suggest weak relationship between population and sales units and dollars.. 45.

(47) Figure 28: Population of each state in USA.. 46.

(48) 4.1.4 Economic Data by State Economic factor consist of two independent variables which include the number of home sales in a single year in each state and the median household income in a single year in each state. In figure 29, the bar graph shows that Florida has the top in Home Sales but is in 37th place in Median Household Income. Pennsylvania ranks 6th place in Home Sales and 23rd place in Median Household Income, while New York has 9th place in Home Sales and 16th place in Median Household Income. New Jersey is at 15th position in Home Sales and 10th position in Median Household Income and Massachusetts has 28th place in Home Sales and 6th place in Median Household Income.. 47.

(49) Figure 29: Number of Home Sales and median Household Income of each state of USA.. 48.

(50) 4.2 Correlation between Studied Variables In this section is the study of correlation coefficient between independent variables (average temperature, clear days, population in seven different race groups, number of home sales and median household income) and eight dependent variables (sales units and dollars in three categories and total of three categories). Table 4: Correlation Coefficients between Weather Factors & Sales Variables. Avg. Temp 2014 (°F). Sales Variables Category 1 Light Filtering (Units) Light Filtering (Dollars) Category 2 Room Darkening (Units) Room Darkening (Dollars) Category 3 Light Blocking (Units) Light Blocking (Dollars) Total Three Categories Total (Units) Total (Dollars). Clear Days. 0.032 0.045. -0.162 -0.151. -0.023 -0.006. -0.212 -0.197. 0.122 0.227. -0.174 -0.117. 0.086 0.195. -0.186 -0.131. Clearly from the data, the environmental variables (both average temperature and number of clear days) do not have a strong relationship with dependent variables, from the table 4, the correlation coefficients are of +0.032, +0.045, -0.023, -0.006, +0.122, +0.227, +0.086 & +0.195 in average temperature and the correlation coefficients are -0.162, -0.151, -0.212, -0.197, -0.174, -0.117, -0.186 and -0.131 in clear days respectively. Note two highest correlation coefficients are Light Blocking in dollars with 0.227 and Room Darkening in units of -0.212. This suggests that the higher the average temperature would have a weak positive linear relationship with sales dollars of Light Blocking category. Also, the higher the number of Clear Days would have a weak negative linear relationship with the sales unit of Room Darkening category.. 49.

(51) Table 5: Correlation Coefficients between State Populations & Sales Variables. Sales Variables. Population. Category 1 Light Filtering (Units) Light Filtering (Dollars) Category 2 Room Darkening (Units) Room Darkening (Dollars) Category 3 Light Blocking (Units) Light Blocking (Dollars) Total Three Categories Total (Units) Total (Dollars). 0.749 0.776 0.663 0.688 0.577 0.655 0.642 0.688. Table 5 shows that there is a strong correlation between state populations and the sales units and dollars in different categories of the product. Table 5 shows correlation coefficients are +0.749, +0.776, +0.663, +0.688, +0.577, +0.655, +0.642 & +0.688 separately. This means that the correlation between population and the dependent variables has a moderate linear relationship and both sales units and dollars of Light Filtering have strong linear relationships. Thus, the result supported that the population has positively correlated to the sales of the product in both units and sales. Racial groups including Non-Hispanic White, Hispanic or Latino, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander and Mixed Race are examined with the dependent variables (Light Filtering, Room Darkening, Light Blocking and Total Sales in sales units and dollars).. 50.

(52) Table 6: Correlation Coefficients between Racial Populations & Sales Variables.. Sales Variables Category 1 Light Filtering (Units) Light Filtering (Dollars) Category 2 Room Darkening (Units) Room Darkening (Dollars) Category 3 Light Blocking (Units) Light Blocking (Dollars) Total Three Categories Total (Units) Total (Dollars). Non-Hispanic White. Hispanic or Latino. Black. American Indian or Alaskan Native. Asian. Native Hawaiian or Pacific Islander. Mixed race. 0.824 0.844. 0.511 0.545. 0.702 0.709. 0.187 0.214. 0.576 0.605. 0.110 0.139. 0.590 0.623. 0.767 0.784. 0.404 0.435. 0.643 0.661. 0.109 0.130. 0.478 0.508. 0.031 0.057. 0.489 0.518. 0.680 0.738. 0.319 0.410. 0.698 0.796. 0.002 0.052. 0.310 0.341. -0.034 0.010. 0.360 0.419. 0.745 0.774. 0.377 0.436. 0.716 0.799. 0.050 0.075. 0.394 0.390. -0.001 0.025. 0.433 0.458. 51.

(53) In table 6, most races have strong and modest linear relationship with three different product categories (Light Filtering, Room Darkening and Light Blocking) and Total Sales in units and dollars. There are two races; American Indian or Alaskan Native and Native Hawaiian or Pacific Islander; showing very weak correlation coefficients, they are +0.187, +0.214, +0.109, +0.130, +0.002, +0.052, +0.050 and +0.075; +0.110, +0.139, +0.031, +0.057, -0.034, +0.010, -0.001 and +0.025 respectively. Both Non-Hispanic White and Black have the strongest linear relationship with three different product categories (Light Filtering, Room Darkening and Light Blocking) and Total of three categories in Sales units and dollars. Their correlation coefficients are +0.824, +0.844, 0.767, +0.784, +0.680, +0.738, +0.745 and +0.774 for Non-Hispanic White and Black has correlation coefficients; they are +0.702, +0.709, +0.643, +0.661, +0.698, +0.796, +0.716 and +0.799. While Hispanic or Latino, Asian and Mixed race have modest linear relationship with different product categories (Light Filtering, Room Darkening and Light Blocking) and Total of three categories in Sales units and dollars. Their correlation coefficients are +0.511, +0.545, +0.404, +0.435, +0.319, +0.410, +0.377 and +0.436 for Hispanic or Latino; +0.576, +0.605, +0.478, +0.508, +0.310, +0.341, +0.394 and +0.390 for Asian; +0.590, +0.623, +0.489, +0.518, +0.360, +0.419, +0.433 and +0.458 for Mixed Race. Table 7: Correlation Coefficients between Economic Factors & Sales Variables. Sales Variables Category 1 Light Filtering (Units) Light Filtering (Dollars) Category 2 Room Darkening (Units) Room Darkening (Dollars) Category 3 Light Blocking (Units) Light Blocking (Dollars) Total Three Categories Total (Units) Total (Dollars). Home Sales. Median Household Income. 0.592 0.616. 0.296 0.293. 0.484 0.509. 0.274 0.281. 0.539 0.641. 0.246 0.182. 0.558 0.645. 0.268 0.207. In table 7, the data is showing some interesting relationships between Economic variables and dependent variables. The number of Home Sales has modest linear relationship with different product categories (Light Filtering, Room Darkening and Light Blocking) and Total of three categories in Sales units and dollars. Their correlation coefficients are +0.592, +0.616, +0.484, +0.509, +0.539, +0.641, +0.558 and 0.645. For the Median Household Income, it has a weak linear relationship with 52.

(54) different product categories (Light Filtering, Room Darkening and Light Blocking) and Total of three categories in Sales units and dollars. Their correlation coefficients are +0.296, +0.293, +0.274, +0.281, +0.246, +0.182, +0.268 and +0.207. Further analysis on all the studied variables includes the Average Temperature of each state; number of Clear Days in each state; population of Non-Hispanic White, Hispanic or Latino, Black, American Indian or Alaskan Native, Asian, Native Hawaiian or Pacific Islander and Mixed Race in each state; number of Home Sales in each state; and the median household income in each state. From the Table 8, both Non-Hispanic White and Black have the strongest linear relationship with all three different categories and Total Sales in Units and Dollars as their correlation coefficients are above +0.60. Asian and Mixed Race have the second strongest linear relationship as their correlation coefficients are close to 0.50. Hispanic or Latino is in third place with the three categories and the Total Sales in Units and Dollars. Both American Indian or Alaskan Native and Native Hawaiian or Pacific Islander have a very weak linear relationship with three different categories and Total Sales in Units and Dollars as their correlation coefficients are closer to zero. Home Sales has stronger linear relationship than Household Income in all three different categories and the Total of three categories. The Average Temperature has a weak linear relationship with all three different categories and the Total of three categories. While Clear Day has a moderate negative linear relationship with all three different categories and the Total of three categories.. 53.

(55) Table 8: Correlation Coefficients between Independent Variables & Sales Variables. Sales Variables Category 1 Light Filtering (Units) Light Filtering (Dollars) Category 2 Room Darkening (Units) Room Darkening (Dollars) Category 3 Light Blocking (Units) Light Blocking (Dollars) Total Three Categories Total (Units) Total (Dollars). Avg. Temp 2014 (°F). Clear Days. Non-Hispanic White. Hispanic or Latino. Black. American Indian or Alaskan Native. Asian. Native Hawaiian or Pacific Islander. Mixed race. Home Sales. Median Household Income. 0.032 0.045. -0.162 -0.151. 0.824 0.844. 0.511 0.545. 0.702 0.709. 0.187 0.214. 0.576 0.605. 0.110 0.139. 0.590 0.623. 0.592 0.616. 0.296 0.293. -0.023 -0.006. -0.212 -0.197. 0.767 0.784. 0.404 0.435. 0.643 0.661. 0.109 0.130. 0.478 0.508. 0.031 0.057. 0.489 0.518. 0.484 0.509. 0.274 0.281. 0.122 0.227. -0.174 -0.117. 0.680 0.738. 0.319 0.410. 0.698 0.796. 0.002 0.052. 0.310 0.341. -0.034 0.010. 0.360 0.419. 0.539 0.641. 0.246 0.182. 0.086 0.195. -0.186 -0.131. 0.745 0.774. 0.377 0.436. 0.716 0.799. 0.050 0.075. 0.394 0.390. -0.001 0.025. 0.433 0.458. 0.558 0.645. 0.268 0.207. 54.