Factors of Cosmetic Purchase Intention in Women Employees (Study in Jababeka Industrial Estate)

FACTORS OF COSMETIC PURCHASE INTENTION IN WOMEN EMPLOYEES (STUDY IN JABABEKA INDUSTRIAL ESTATE)

By: Pratiwi Citra Bella Lestari

014201400099

A Skripsi presented to the Faculty of Business President University in partial fulfilment of the requirements for Bachelor Degree in Management

May 2018

PANEL OF EXAMINERS APPROVAL SHEET

The Panel of Examiners declare that the skripsi entitled ―FACTORS OF COSMETIC PURCHASE INTENTION IN WOMEN EPLOYEES (STUDY IN JABABEKA INDUSTRIAL ESTATE)‖ that was submitted by Pratiwi Citra Bella Lestari majoring in Management from the Faculty of Business was assessed and approved to have passed the Oral Examination on May, 15th 2018.

Dr. Dra. Genoveva, M.M. Chair – Panel of Examiners

Siska Purnama Manurung S,Kom., MM.

Examiner 1

Dr. Ir. B.M.A.S. Anaconda Bangkara, MT., MSM.

Examiner 2

i DECLARATION OF ORIGINALITY

I, declare that this skripsi, entitled ―FACTORS OF COSMETIC PURCHASE INTENTION IN WOMEN EPLOYEES (STUDY IN JABABEKA INDUSTRIAL ESTATE)‖, is, to the best of my knowledge and beliefs, an original piece of work that has not been submitted, either in a whole or in a part, to another university to obtain a degree.

Cikarang, May 15th 2018

Pratiwi Citra Bella Lestari

ii ACKNOWLEDGEMENT

I would like to express my greatest gratitude to Allah SWT for the blessing, mercy, and opportunity as well as health and wellbeing that He has showered me throughout my life, especially during the period of skripsi completion,

The skripsi would not have been finished without the help and support of the people around me, therefore, I would like to express my appreciation to those who contribute to the making process of this research. Firstly, a very special gratitude goes to both my parents, Bambang Eko Wibisono and Oktavia, also my older sibling Billy and Hugo who always provide me with their never- ending love and support which motivate me to finish this venture.

Secondly, I send my sincere gratefulness to my skripsi advisor, Dr. Ir. B.M.A.S. Anaconda B, MT., MSM. who shared his valuable time, energy, knowledge, and expertise, as well as his life experiences to guide and encourage me throughout the research period patiently.

To my beloved friends, thank you for the support and help you all have given to me, and all the memories we created together during our life in university.

I also like to take this opportunity to thank all the lecturers, staffs and fellow students for the experiences and knowledge I obtained during my time as a President University student which I believe will be beneficial later in life.

Lastly, thank you for those people who lent their hands to contribute and participate, both directly and indirectly, in the completion of this skripsi, whom of which I could not mention individually. Hopefully, this skripsi will give benefits and inspirations for the society.

Sincerely,

Pratiwi Citra Bella Lestari

iii TABLE OF CONTENT

PANEL OF EXAMINERS APPROVAL SHEET ...... I

DECLARATION OF ORIGINALITY ...... II

ACKNOWLEDGEMENT ...... III

TABLE OF CONTENT ...... IV

LIST OF TABLES...... VII

LIST OF FIGURE ...... VIII

LIST OF EQUATION...... IX

ABSTRACT ...... X

CHAPTER I ...... 1

INTRODUCTION ...... 1

1.1 Background ...... 1 1.2 Problem Identification ...... 4 1.3 Research Questions ...... 5 1.4 Research Objective ...... 5 1.5 Significance Of Study ...... 6 1.6 Scope Of Limitation ...... 6 1.7 Organization Of Skripsi...... 7

CHAPTER II ...... 8

LITERATURE REVIEW ...... 8

2.1 Introduction ...... 8 2.2 Purchase Intention Theory ...... 8 2.3 Celebrity Endorsement ...... 9 2.4 Product Packaging ...... 10 2.5 Brand Image ...... 12 2.6 Price Fairness ...... 13

iv 2.7 Perceived Quality ...... 14 2.8 Research Gap ...... 15

CHAPTER III ...... 22

METHODOLOGY ...... 22

3.1 Introduction ...... 22 3.2 Theoretical Framework ...... 22 3.3 Research Framework ...... 23 3.4 Operational Definition Of Variables ...... 24 3.5 Questionnaire...... 28 3.6 Population And Sampling Design ...... 29 3.7 Research Instrument ...... 30 3.7.1 Data Collection Process ...... 30 3.7.2 Validity Test ...... 31 3.7.3 Reliability Test ...... 32 3.8 Normality Test ...... 33 3.9 Factor Analysis ...... 34 3.9.1 Correlation Matrix ...... 34 3.9.2 Factoring Extraction ...... 35 3.9.3 Factors Rotation ...... 37 3.9.4 Labeling The Established Factors ...... 37

CHAPTER IV ...... 38

DATA ANALYSIS ...... 38

4.1 Pre-Test ...... 38 4.1.1 Reliability Test ...... 38 4.1.2 Validity Test ...... 38 4.2 Normality Test ...... 42 4.3 Factor Analysis ...... 43 4.3.1 Preliminary Analysis ...... 43 4.3.2 Factor Extraction ...... 45 4.3.3 Factor Rotation ...... 49

v 4.3.4 Dominant Factor ...... 51 4.4 Discussion ...... 53

CHAPTER V...... 55

CONCLUSION AND RECOMMENDATION ...... 55

5.1 Conclusion ...... 55 5.2 Recommendation ...... 55

REFERENCE ...... 57

APPENDIX ...... 62

Appendix A – Questionnaire ...... 62 Appendix B – Normality ...... 66 Appendix C – Factor Analysis ...... 71

vi LIST OF TABLES

Table 1.1 Top Ten Largest Cosmetics Company In Indonesia ...... 1 Table 1.2 Top Eight Cosmetics Product On Sales In Indonesia ...... 2 Table 1.3 Registered Cosmetics Products In Bppom ...... 3 Table 2.1 The Previous Research ...... 19 Table 3.1 Operational Definition Of Variables ...... 24 Table 3.2 Example Of Likert Scale Questionnaire ...... 28 Table 3.3 Criteria Of Significance Factor Loading Based On Sample Size ...... 36 Table 4.1 Reliability Test Result ...... 38 Table 4.2 Validity Of Celebrity Endorsement ...... 39 Table 4.3 Validity Of Product Packaging ...... 39 Table 4.4 Validity Of Brand Image ...... 40 Table 4.5 Validity Of Price Fairness ...... 40 Table 4.6 Validity Of Perceived Quality ...... 41 Table 4.7 Kolmogrov-Smirnov With Adjusted Lilliefors Normality Test ...... 42 Table 4.8 Kmo And Bartlett's Test ...... 44 Table 4.9 Anti-Image Matrices ...... 44 Table 4.10 Communalities ...... 45 Table 4.11 Total Variance Explained ...... 47 Table 4.12 Rotated Component Matrix ...... 49 Table 4.13 Component Transformation Matrix ...... 50 Table 4.14 Factor Classification ...... 51 Table 4.15 Construction Of The First Factor ...... 51 Table 4.16 Construction Of The Second Factor ...... 52

vii LIST OF FIGURE

Figure 1.1 Indonesian Consumer Cosmetic Preference ...... 4 Figure 3.1 Theoretical Framework ...... 22 Figure 3.2 Research Framework ...... 23 Figure 4.1 Probability Plots Of Celebrity Endorsement...... 43 Figure 4.2 Factor Analysis Scree Plot ...... 48

viii LIST OF EQUATION

Pearson’ S Product-Moment.……...... 31

Cronbach’s Alpha……...... 33

ix ABSTRACT

Cosmetics become the primary needs for woman and men. Along with the development of science and technology, various types of cosmetics appear on the market. This study aims to specify factors in women employee cosmetics purchase intention by adopting Purchase Intention Theory which encompasses Celebrity endorsement, Product Packaging, Brand Image, Price Fairness, and Perceived Quality. The study is using purposive sampling method and conducted by distributing the questionnaires to 155 cosmetic users who work in Jababeka Industrial Estate, Indonesia. The Statistical Package for Social Science (SPSS) Version 24.0 is used to calculate the statistical analysis. This study adopted factor analysis factor which resulted in two dominant factors namely Performance of the Product and Attractiveness.

Keywords: Analysis Factor, Purchase Intention, Cosmetics, Performance of the Product, Attractiveness.

x CHAPTER I

INTRODUCTION

1.1 Background

In 2016 total population in Indonesia amounted to 261.1 million people (World Bank, 2017), making Indonesia a promising market for cosmetics companies. Currently the development of Indonesia cosmetics industry is quite solid (Kementrian Perindustrian RI, 2016). This can be seen from the increase of cosmetic sales in 2012 14% to 9.76 trillion (IDR) from 8.5 trillion, based on data from the Ministry of Industry Republic Indonesia. In the last six year (2009-2015). It is estimated that the market size of the cosmetic market is 46.4 trillion in 2017. In this amount, Indonesia is a potential market for beauty industry entrepreneurs both from local and even international enterprises (PT Sigma Research, 2017).

Dunia Industri conducted market research in October 2016, got top ten largest cosmetics company in Indonesia based on sales value, market segmented and brand name in Indonesia, Table 1.1 are the list of top ten largest cosmetic company in Indonesia.

Table 1.1 Top ten Largest Cosmetics Company in Indonesia

No Company Name Brand Sales 1 PT Unilever Indonesia Tbk Tresemme, Ponds, Rp 36.5 trilliun Citra, Vaseline, Clear, AXE, etc. 2 PT Loreal Indonesia Loreal Paris, Rp 27.99 trilliun Maybelline, Garnier, kerastase, The Body Shop, etc

1 3 PT P&G Indonesia Tbk SK-II, Pantene, Rp 14.87 trilliun Wella, Olay, Always, dan Head & Shoulders 4 PT Mandom Indonesia Tbk Pixy, Gatsby Rp 2.31 trilliun 5 PT Martina Bero Tbk Mirabella, Belia, Rp 694.7 miliar Caring colours, PAC, Cempaka, Sariayu, Biokos 6 PT Akasha Wira International Tbk Makarizo Rp 669.7 miliar 7 Oriflame Oriflame Rp 603 miliar 8 PT Mustika Ratu Tbk Mustika Ratu, Rp 428 miliar Biocell, Puteri, 9 PT Paragon Technology Wardah Rp 350 miliar 10 Revlon Revlon, Cutex, Rp 124 miliar PureICE

Source: Duniaindustri (2017)

In addition to the top ten cosmetics companies, Dunia Industri research also found eight cosmetics brands with the highest sales in Indonesia that can be seen on table 1.2. In the first position was occupied by L’Oréal with estimated sales in 2015 is amounting to 825 billion (IDR). In the second position is Oriflame, and then followed by Ponds, Citra, Gatsby, Pixy, Wardah and in the eighth position occupied by Sariayu.

Table 1.2 Top eight Cosmetics Product on Sales in Indonesia

NO Cosmetics Brand Company Sales 1 L’Oreal PT L’Oréal Indonesia Rp 825 miliar 2 Oriflame PT Oriflame Cosmetic Indonesia Rp 603 miliar 3 Ponds PT Unilever Indonesia Tbk Rp 358 miliar 4 Citra PT Unilever Indonesia Tbk Rp 347 miliar 5 Gatsby PT Mandom Indonesia Tbk Rp 335 miliar 6 Pixy PT Mandom Indonesia Tbk Rp 317 miliar 7 Wardah PT Paragon Technology Rp 300 miliar 8 Sariayu PT Martina Berto Tbk (MBTO) Rp 229 miliar

Source: Duniaindustri (2017)

2 The Indonesian cosmetics market is dominated by imported cosmetics product 60% of the total domestic market. About 5% of products are imported from ASEAN countries, while the remaining 55% are imported from Europe, The United States, China and some other countries. Based on the data of POM RI, the number of cosmetics that were notified in 2017 until September was 33,823 products. This number increased 11.57% from the previous year in the same period (Badan Pengawas Obat dan Makanan Republik Indonesia, 2017). Below are the details of the percentage of products registered in BPPOM.

Table 1.3 Registered Cosmetics Products in BPPOM

Country of Percentage of Product Origin Cosmetics Indonesia 40.52% Asean 4,69% Europe 28,58% Other countries 26,21%

Source: Kemenperin (2016)

Based on research results from Nielsen (2016), Indonesian consumers prefer to buy global cosmetics products rather than local products. Based on beauty product sales data in the third quarter of 2015, 48 percent of consumers liked global brand cosmetics 36 percent chose local products and the remaining 16 percent do not have any preferences. The demand for imported cosmetics Indonesia continues to increase in line with the growth will be the need for premium cosmetics brands from middle-class consumers in Indonesia.

Global Products Lokal Products note vote

16%

48%

36%

Figure 1.1 Indonesian Consumer Cosmetic Preference Source: Nielsen (2016)

1.2 Problem Identification

As there is an increase in people dependency on the usage of cosmetics to meet their daily needs, the growth of cosmetic market in the world is getting bigger and tighter, including Indonesia. According to PT Sigma Research (2017), the growth of this market in Indonesia averaged 9.67% per year in the last six years (2009-2015). It is estimated that the market size of the cosmetic market is 46.4 trillion (IDR) in 2017 of the total population reached over 260.1 million people. Therefore, it makes Indonesia as a potential market for cosmetics industry, both local and international enterprises.

The problem emerges when the majorities of Indonesians tend to purchase and use cosmetics product produced by foreign producers or prefer chose global or international cosmetic product, which described in Figure 1.1 above. It is also can be seen in the Table 1.2 top eight cosmetics product on sales in Indonesia, the first position was occupied by L’Oréal. L’Oréal is the largest French cosmetic company with estimated sales in 2015 reached over 825 million (IDR) in Indonesia. Other supporting data that Indonesia consumer prefer

4 global cosmetic product is the data from Ministry of Industry in Indonesia (2016) in the Table 1.3 that 60% of domestic market are dominated by imported cosmetic product which 4.69% from ASEAN, 28.58% is from Europe, and 26.21% came from other countries, Indonesia just take total amount 40% of domestic market in cosmetic industry. So, the money generated from the purchase is transferred to the foreign firms and increase their prosperities instead of local producers.

1.3 Research Questions

The purpose of this research is to identify the correlation between celebrity endorsement, product packaging, brand image, price fairness, perceived quality and consumer purchase intention on the global cosmetics product. The study is conducted by using purchase intention of cosmetics products model that developed by Chin and Harizan (2017) which encompasses celebrity endorsement, product packaging, brand image, price fairness, and perceived quality. Here are the several questions that the researcher is trying to answer by conducting the study.

1. What are the dominant factors from celebrity endorsement, product packaging, brand image, price fairness, and perceived quality that contribute to stimulate intention to purchase a global cosmetic product? 2. What are the dominant factors that can be developed from purchase intention theory in consumer of cosmetic product?

1.4 Research Objective

The research entitled ―Factors of Cosmetic Purchase Intention in Women Employees (Study in Jababeka Industrial Estate)‖ with the subject of study is cosmetics users who work in Jababeka Industrial Estate. This research is conducted to answer the research question mentioned above.

5 1. To identify the dominant factors of celebrity endorsement, product packaging, brand image, price fairness, and perceived quality that stimulates intention to purchase cosmetic product. 2. To identify the dominant factors that developed from consumer purchase intention in cosmetic product.

1.5 Significance of Study

a. Society: For the society, this study is expected to be useful for disseminating a new knowledge about how society’s purchase intention in cosmetic products. Especially towards lipstick cosmetics products where there are products from overseas brands and domestic products. b. Local cosmetics producers: For local cosmetics manufacturers, this research can contribute to providing additional information and references to establish long-term business strategies that match with customer purchase intention to gain a higher probability of survival and generate more profits. c. Education: For education, this research can contribute to society by providing some new knowledge about Purchase Intention. Hopefully by reading this study, readers can also learn to use factor analysis to conduct social science research. d. Future research: For future research, the business market is constantly changing due to several factors. One such factor is characteristics and preferences of consumers. Therefore, further investigation in purchase intention factors can reduce the gap between previous and recent studies. It is hoped that this study also contributes in filling in previous research gaps and assisting in investigating factors in purchase intention

1.6 Scope of Limitation

The scope on this research is only focused on cosmetics user, especially for lip color product according to YouGov (2016) Indonesian 1st type cosmetic

6 product is lipstick. Therefore, the researcher focused to lipstick cosmetic in order to make it easier to understand the meaning of cosmetic in same perspective between researcher and respondent. Targeted female who worked in Jababeka Industrial Estate, which close to the industry due to Jababeka Industrial Estate in Cikarang is the biggest city of industries in Southeast Asia.

The limitation of this research is the researcher will not include the demographical factor, except Age. This research also conducted only based on Purchase intention to explore its correlation.

1.7 Organization of Skripsi

The first chapter of this skripsi covers the research background, problem identification, research objective, significance of the study, as well as scope and limitation of the research. Chapter 2 outlines literature review related to the research. Chapter 3 consists of research design, framework, and methodology that applied for this particular research. Chapter 4 contains data analysis and interpretation of the result. And Chapter 5 delivers the conclusion that obtained from the research and recommendations for future research. Questionnaire details, ordinal and interval data, and more detailed SPSS analysis can be found in the appendices.

7 CHAPTER II

LITERATURE REVIEW

2.1 Introduction

This chapter will contain literature and theories that related to the research. It also explains theoretical framework to examine five variables of Purchase Intention theory in which used to developed new factors.

2.2 Purchase Intention Theory

Based on term, intention is explained as the antecedents that stimulate and drive consumer’s purchases of product and service (Hawkins & Mothersbaugh, 2010). Purchase intention is composed from consumer’s feelings, thoughts, experience and external factors that considered before making any purchase (Bhakar, Bhakar, & Dubey, 2015). Purchase intention occur at evaluation stage of purchase or evaluation of alternatives (Kotler & Armstrong, 2017).

According to Kotler and Armstrong (2017) there are two factors can made purchase intention and purchase decision to choices most preferred brand. The factors are attitudes of others and unexpected situational factors. Attitudes of others mean when the important person around consumer think consumer should buy the lowest priced product, then the chances of us buying more expensive products are reduced because of that. Unexpected situational factor mean consumer may to purchase intention based on factors such as income, price and product benefit. But because of unexpected macroeconomic condition made the purchase intentions do not want that really actual purchase choice. The purchase intention was change because of the unexpected factor economic condition. The marketer usually should to know the consumer actual behavior through by their intention. Not the end until customer buy the

8 product, marketer will consider the satisfied or dissatisfied that call post- purchase behavior (Kotler & Armstrong, 2017).

Purchase behavior and purchase intention had the relationship (de Cannière, de Pelsmacker, & Geuens, 2010). According de Cannière et al. Purchase behavior could be predicted purchase intention with quality. Relationship of purchase behavior and purchase intention connected with quality (de Cannière et al., 2010). An individual's behavioral intention according on attitude towards the behavior and the subjective norms associated with the behavior (Asshidin, Abidin, & Borhan, 2016).

Asshidin, Abidin, and Borhan (2016) illustrate the concept of buying intentions reflects consumers’ foreseeable behavior in short term future buying decisions. They defined purchase intention is one of a very small set of variables that find routine application in consumer research investigations undertaken for a variety of different purposes and covering a broad range of products and services that make what products or brand the consumer will buy on next shopping trip and be a future projection of consumers’ behavior that will significantly contribute to the configuration of attitudes.

2.3 Celebrity Endorsement

Celebrity endorsement has been recognized as an important promotional tool by marketer (Chin & Harizan, 2017). Kotler and Armstrong (2017) explain endorsement same with testimonial evidence. Testimonial evidence or endorsement is one of the execution style that would be present the product for customer. It could be ordinary people saying how much they like a given product. For example, Whole Foods features a variety of real customers in its Values Matter marketing campaign. Or it might be a celebrity presenting the product (Kotler & Armstrong, 2017). Celebrities are a common feature in the contemporary marketplace, often becoming the face, or image, not only of consumer products and brands, but of organizations themselves (Ilicic & Webster, 2011).

9 Celebrity endorsements are effective for endorsement because several reasons according Hawkins and Mothersbaugh (2010). First reason is attention, celebrities may attract attention to the advertisement. Then, Consumers tend to be curious about celebrities and are drawn to ads in which they appear. Secondly reason is Attitude toward the ad. Likeability and popularity of celebrity often interpret into higher advertisement, which can enhance brand attitudes. Third reason is trustworthiness. Although the celebrity is being paid for the endorsement, celebrity can develop strong and credible public personas that consumer trust then that trust translated into purchase. Fourth reason is expertise. Celebrities are also experts like music and sport that are frequently occur. Companies in sport brand build whole lines around celebrity athletes. Then, aspirational aspects as the fifth reason. Consumers can identify or want to be like a celebrity. As a result, they can imitate celebrity behavior and style through purchases of similar brand and styles. The last reason is meaning transfer. Consumers may associate known characteristics of celebrities with product attributes that coincide with their own needs or desires (Hawkins & Mothersbaugh, 2010).

There are four items that indicate celebrity endorsement had influence purchase intention. Bhakar et al. (2015) mention that physical celebrity attractiveness, trustworthiness or credibility, expertise and celebrity popularity as a factor of celebrity endorsement in research which has credible.

2.4 Product Packaging

Packaging serves was a critical role in marketing and, in some product categories, such as bottled water the container carrying the consumable is inextricably linked to the consumption experience itself (Hess, Singh, Metcalf, & Danes, 2014). Package design not only increase the visibility of the product but also helps in easy recognition of the product (Bhakar et al., 2015). Packaging have ability to drive consumers physiological (unconscious) responses, as compared with verbal (conscious) responses (Vila-López &

10 Küster-Boluda, 2018). Packaging is all activity of designing and producing the container for product. Packaging was important because it is the buyer’s first encounter with the product. A good package draws the consumer in and encourages product choice (Kotler, Keller, Brady, Goodman, & Hansen, 2016).

According to Kotler et al., (2016), there were several factors that can made growing use of packaging for marketing tool. (1) Self-service. In an average supermarket, which may stock 15,000 items, the typical shopper passes some 300 products per minute. Given that 50 percent to 70 percent of all purchases are made in the store, the effective package must perform many sales tasks: attract attention, describe the product’s features, create consumer confidence, and make a favorable overall impression. (2) Consumer affluence or prosperity. Rising affluence means consumers were willing to pay a little more for the convenience, appearance, dependability, and prestige of better packages. (3) Company and brand image. Packages contribute to instant recognition of the company or brand. (4) Innovation opportunity. Unique or innovative packaging can bring big benefits to consumers and profits to producers. Companies are always looking for a way to make their products more convenient and easier to use—often charging a premium when they do so (Kotler et al., 2016).

After that company need made good packaging to various objectives for the products. packaging must achieve a number of objectives such as identify the brand, convey descriptive and persuasive information, facilitate product transportation and protection, assist at-home storage and aid product consumption (Kotler et al., 2016).

Bhakar et al. (2015) mention four indicators to measure product packaging. Which are the small package size, packaging attractiveness, soft packaging, and uniqueness of the package.

11 2.5 Brand Image

Kotler defines a brand consists of a name, term, sign, or symbol, or any combination of them, that attempts to represent the unique benefits a company can provide to consumers through a particular product or service, in terms of attributes, value, and culture (Kotler & Armstrong, 2017). Keller (2008) explain that an important role played by a brand is that it enables consumers to identify a firm’s products or services and can differentiate them from those of competitors. Certainly, consumers are facing an increasingly varied range of products on the market, while companies always know more about their products than do consumers. This asymmetric information availability may cause confusion or uncertainty in consumers’ minds when they make a purchase (Keller, 2008).

Brand image known as consumers' sense of the brand to stimulate consumers' purchase in the first conception of marketing considered "the brands" as well (Hu, Jou, & Liu, 2009). According Hawkins and Mothersbaugh noted brand image is a market segment or individual consumer’s schematic memory of a brand that contains the target market’s interpretation of the product’s attributes, benefits, usage situations, users, and manufacturer. marketer characteristics (Hawkins & Mothersbaugh, 2010). According Keller (2008) define brand image is consumers’ perceptions about a brand, as reflected by the brand associations held in consumer memory. Then, brand associations are the other informational nodes that connected with brand node in memory and contain the meaning of the brand for consumers. Associations come in all forms and may reflect characteristics of the product or aspects independent of the product (Keller, 2008).

Hu, Jou, and Liu (2009) define brand image could built by three main factors. There are three main factors that building the brand image are the image of product itself, the corporate image, and the image of competitor. From that three factors as the brand power measurement. Corporate image has dominance over brand strength and brand stature between others two factors.

12 Finally, according Keller (2008), brand image indicate measurement for creating a positive brand image are link of strong, favorable, and unique associations to the brand memory that make beliefs for the brand. Consumers form beliefs about brand attribute and benefits in different ways.

2.6 Price Fairness

Kotler and Armstrong (2017) are defining price as the total amount of value that consumer exchange for the benefits for having and using the product and service. While, Hawkins & Mothersbaugh (2010) define price is the amount of money one must pay to obtain the right to use the product. According to Xia, Monroe, and Cox (2004), price fairness is customers' perceptions and their related emotions about how fair, acceptable, and reasonable the difference is between two prices. The price fairness perceptions are usually derived from their antecedents and their consequences (Malc, Mumel, & Pisnik, 2016).

There are three major strategies that can use marketers to determine the price fairness. They are customer value–based pricing, cost-based pricing, and competition-based pricing. (1) Customer value–based pricing is using buyers' value perception for the basis to setting the price fairness for customer. Complete understanding of the value of goods or services made by the customer which is used as a benchmark in determining the good price. (2) Cost-based pricing considers pricing based on production cost, distribution cost and selling product plus rate of return for business and risk. Perception of customer value is usually the highest standard of price while cost as the lowest price of a product then added with profit as the value of corporate profits on the product made. (3) Competition-based pricing uses pricing based on competitor's strategy, cost, price, and market supply. Basic value based on the consumer through the value of the product at the price determined competitors to similar products. Companies can set a high price if the consumer feels that the company is delivering more value to the product. Likewise, the company should lower the price of the product if the consumer feels less value than the

13 competitor's product or changes the consumer's perception of the product so that the fair price is received (Kotler & Armstrong, 2017).

Keller mention price bands term that mean range of acceptable price from price level, that indicate flexibility and breadth marketers can adopt in pricing their brands within a tier (Keller, 2008).

According to Kotler and Armstrong (2017), there are external and internal factors that affecting a company to determine the price decisions. Internal factors that influence pricing decisions such as marketing strategy, objectives, marketing mix, and company considerations. Price decisions should be coordinated with product design, distribution, and promotional decisions to establish a consistent and effective marketing program. External factors in price considerations include market trait, demand and environmental factors such as economy, reseller needs, and government action. Economic conditions have a major impact on pricing decisions. Companies must understand the concept of demand curve (price demand relationship) and price elasticity (consumer sensitivity to price). The Great Recession causes consumers to rethink the price-value equation. Companies respond by increasing their emphasis on a value-for-money pricing strategy (Kotler & Armstrong, 2017).

Based on Xia, Monroe, and Cox (2004) there are indicators of measurement of this variable. They are reasonable, acceptable, and justifiable. These indicate of the measurement also a consumer’s assessment and associated emotions of whether the difference (or lack of difference) between a seller’s price and the price of a other party.

2.7 Perceived Quality

Perceived quality is customers’ perception of all quality or superiority of a product or service compared to alternatives and with respect to its intended purpose (Keller, 2008). Perceived quality as a cognitive response to a product which influences product purchase (Kumar, Lee, & Kim, 2009). Perceived

14 quality also provides value to consumers by providing them with a reason to buy and by differentiating the brand from competing brands (Asshidin et al., 2016).

Asshidin et al. (2016) define perceived quality as a consumer’s evaluation of a brand’s overall excellence based on intrinsic (performance and durability) and extrinsic cues (brand name). According them, Quality is defined as judgment about the overall excellence or superiority of a product or service. Quality can be defined in terms of the moment at which the consumer receives information or cues about the characteristics of the products while shopping for or consuming it. It also means that the perception of quality varies depending on a range of factors such as the moment at which the consumers make the purchase or consume a product, and the place where it is bought or enjoyed (Asshidin et al., 2016). Perceived quality influence purchase intention when consumers perceive higher product quality, it will lead to stronger repurchase intention (Ariffin, Yusof, Putit, & Shah, 2016). Consumers consider the product on quality in the purchase process on any product they want and on the other hand, purchasing decisions may depend on the perception of the quality of the consumer that distinguishes between local and imported products (Asshidin et al., 2016).

Perceived quality had indicated to measurement of the quality of product. According to Asshidin et al. (2016), there are four items that use for measurement, such as, performance, durability, brand name, and, purity.

2.8 Research Gap

Chin & Harizan (2017) found that celebrity endorsement and price fairness had influence on intention to purchase cosmetic product. But the other variables did not find the influence on intention to purchase cosmetic product, such as, brand image, product packaging, and perceived quality. The research conducted with quantitative method with do survey among 100 minimum sample working adults with measured on a 5-point Likert scale who are working in private

15 sectors within the northern region of Malaysia. Then, the data tested with a multiple regression analysis to examining the relationships between the independent variables (celebrity endorsement, product packaging, brand image, price fairness, and perceived quality) and dependent variables (consumers’ purchase intention). The result showed celebrity endorsement has a significant positive influence on purchase of cosmetic product. Then, product packaging and brand image did not impose any significant impact on purchase intention of cosmetic product. Therefore, they are not supported. Price fairness has a significant negative influence on purchase intention of cosmetic product and supported. Last variable, perceived quality did not show any significant influence on purchase intention of cosmetic products and not supported.

Bhakar et al. 2015 had do research how the celebrity endorsement and product packaging can effected purchase intention to taking customer knowledge and perceived value on shampoo product. The study was causal in nature with survey method. With cause and efect relationship between variables such as, celebrity endorsement and product packaging on customer knowledge and perceived value, cause and effect relationship between celebrity endorsement, product packaging, customer knowledge and perceived value on purchase intention was identified. The samples size was 155 respondents in India with using sampling element non probability quota sampling technique. They used manova to identify the difference between all the continuous variables in case of categorical variables brand and gender. The result indicates celebrity endorser significantly effects purchase intention of shampoo directly as well as celebrity endorser, product packaging and customer knowledge effect perceived value as mediating variable in turn effecting purchase intention. While customer knowledge is a lesser important variable in case of shampoos purchase intention.

Kumar et al. (2009) investigate the purchase intention toward a United States versus local brand. This study demonstrates that Indian consumers' need for uniqueness, attitudes toward American products, and emotional value are direct and indirect antecedents of purchase intention. The study of Indian consumers

16 examines the effects of individual characteristic like consumer’s need for uniqueness and attitudes toward American products and brand-specific variables like perceived quality and emotional value on purchase intention toward a U.S retail brand versus a local brand. Sample size of this research was 411 college students in India. Measurement used Structural Equation Modeling (SEM) that found Indian consumers’ need for uniqueness positively influences attitudes toward American products. Attitudes toward American products positively affect perceived quality and emotional value for U.S brand while this is negative in the case of local brand in India. Emotional value is an important factor influencing purchase intention toward a U.S brand and a local brand as well.

Haque et al. (2015) found in their research that brand image and quality of foreign products carry significant positive influence on purchase intention of foreign products. They emphasize that the favorable match between country of origin image and brand image in the various marketing activities undertaken. Findings have also disclosed that Bangladeshi consumers pay much attention to the quality of foreign products. The results also indicated that ethnocentrism is unfavorably associated with foreign product quality when it comes to Bangladeshi consumers’ intention of buying imported products. The same as religiosity leaves a significant negative effect on the purchase intention of foreign products.

Asshidin et al. (2016) investigate the effects of perceived quality and emotional value that influence consumer’s purchase intention towards American and local products. Result shows moderate significant relationship between perceived quality and emotional value towards purchase intention. Then, perceived quality is a significant predictor of Malaysian consumers in purchasing process for both American and local products. This means that consumers emphasize on qualities in purchasing process on whichever products they encounter with and on the other side, decision on purchasing might depend on the perceive- ness of qualities if consumers were to distinguish between local and imported products. Asshidin et al. also found that emotional value is a good predictor in

17 predicting relationships with purchase intention among consumers. Perception of emotional value one could receive when purchasing, is in the same case with local and American product and could be concluded that the more pleasurable a consumer might experience, the more he or she would be likely to buy that product. This study clearly demonstrates that emotional value plays a critical role in forming Malaysian consumers’ purchase intention whether it is an American product or a local product.

The previous researches that elaborate above had measured purchase intention by implementing different methods and approaches. There are also few of them that developed new model based on the original theory such as perceived packaging quality by Hess et al., (2014) and conceptual framework price fairness perceptions by Xia et al., (2004) that influence on purchase intention. But none of the research were done and conducted to explore consumer behavior of cosmetic adoption in Indonesia, specifically Jababeka Industrial Estate. Therefore, this research is conducted in the hope to fill the gaps of previous research in the context of purchase intention theory which researcher adopt from Chin & Harizan (2017). There are five variables that implemented to this research, namely celebrity endorsement, product packaging, brand image, price fairness, and perceived quality. The highlights of the previous research in which the researcher used as foundation to conduct this particular research are presented in the Previous Research that shown on Table 2.1 in next page. The methods and data collection which applied for this research will further in next chapter.

Table 2.1 The Previous Research

AUTHOR(S) LOCATION SAMPLE THEORY VARIABLES METHOD RESULT NO (YEAR) 1 Teoh Khar Chin, Northern 100 working Purchase Celebrity Quantitative This research Siti Haslina Md Malaysia adults in private intention endorsement, showed celebrity Harizan, sector product endorsement and (2017) respondents packaging, price fairness brand image, significantly price fairness, influenced and perceive purchased intention quality of cosmetic products. 2 Shailja Bhakar, Shilpa India 150 Customers Purchase Celebrity Quantitative Indicate celebrity Bhakar, Abhay Dubey of different intention endorsement, endorser (2015) brand of product significantly effect shampoos packaging, purchase intention customer of shampoo then knowledge, product packaging perceived value and customer knowledge effect perceived values as mediating variable in turn effecting purchase intention 3 Archana Kumar, India 411 College Purchase Consumers’ Quantitative Indian consumers’ Hyun-Joo Lee, Youn- students were intention need for need for uniqueness Kyung Kim major consumer uniqueness, positively influence

(2009) groups of casual attitude toward attitudes toward

apparel and American American product. homogeneous in product, Then attitude nature perceived toward American quality, product positively emotional affect perceived value quality and emotional value for U.S brand while local brand was negative. While emotional was an important factor influencing purchase intention toward U.S brand and local brand. 4 Ahasanul Haque, Bangladesh 260 consumers Purchase Country of Quantitative Brand image and Naila Anwar, Farzana in 43 shopping intention origin image, quality of foreign Yasmin, Abdullah malls were religiosity, products carry Sarwar, Zariyah selected ethnocentrism, significant positive Ibrahim, Abdul randomly in two brand image, influence on Momen cities in foreign product purchase intention (2015) Bangladesh quality of foreign product but otherwise with religiosity that negative effect. Then image of the country of origin

carries a significant

positive effect on brand image but ethnocentrism carries a significant negative effect on perceptions about the quality of foreign products in purchase intention 5 Noor Hazlin Nor Malaysia 270 non- Purchase Perceived Quantitative The result shows Asshidin, Nurazariah international intention value, moderate Abidin, Hafizzah postgraduate and emotional significant Bashirah Borhan undergraduate value relationship (2015) students in between perceived higher learning quality and institution emotional value toward purchase intention.

Source: Developed by the Researcher (2018)

CHAPTER III

METHODOLOGY

3.1 Introduction

This chapter evaluates research methodology that used by the researcher to do the research. It consists of research framework, all the steps performed to implement the framework, data collection, and statistical analysis. In this particular research, quantitative method is used. The data used are primary data which were collected through spreading printed questionnaires to the target respondents directly. The software deployed to analyse the data is Statistical Package for the Social Science (SPSS) version 24.0, and the result will be explained thoroughly in Chapter IV.

3.2 Theoretical Framework

Celebrity Endorsement

Product Packaging

Brand Image Purchase Intention

Price Fairness

Perceived Quality

Figure 3.1 Theoretical Framework

Source: Chin (2017)

3.3 Research Framework

Problem Statement

Related Theories

Questionnaire Constructions

Pre-Test Distribution

Pearson Product Moment YES NO Validity

NO Reliability

YES Questionnaires Distribution

Data Collection

Succesive Interval Method

Normality

Analysis Factor

Data Interpretation

Conclusion & Recommendation

Figure 3.2 Research Framework Source: Developed by the Researcher (2018)

3.4 Operational Definition of Variables

Table 3.1 Operational Definition of Variables

Variables Definition Indicators Definition of Indicators Scale Celebrity Promotional tool of 1. Attractiveness 1. Attractive is for the how celebrity Ordinal Endorsement marketing that important 2. Trustworthiness act like to attract attention to the (Bhakar et al., nowadays and one of the or Credibility advertisement 2015; Chin & execution style that 3. Expertise 2. Trustworthiness is the celebrity Harizan, 2017) would product 4. Popularity strong and credible public presentation to customer. (Bhakar et al., 2015) personas that consumer trust to (Chin & Harizan, 2017; 3. Expertise is the experience of the Philip Kotler & people that come from the Armstrong, 2017) hobbies or the what they concern 4. Popularity is a liked or admired by many or by a particular group

or person that make enhance

brand attitude Product All activity of designing 1. Small package 1. Small packaging means the Ordinal Packaging and producing the pack size effectiveness the packaging that (Bhakar et al., that cover the product 2. Packaging easy to carry and minimalizing of 2015; Chin & (Phillip Kotler, Keller, attractiveness the product Harizan, 2017) Brady, Goodman, & 3. Uniqueness of the 2. Packaging attractiveness is the Hansen, 1990) packaging how the package act like to attract (Bhakar et al., 2015) attention from the color and design of packaging 3. Uniqueness of the packaging is the being different or the only one of its kind packaging and unlike anything else to attract interest or intention of product Brand Image Consumer’s sense of the 1. Strong brand 1. Strong brand is the value of the Ordinal (Chin & brand to stimulate 2. Favorable brand in the customer and their Harizan, 2017) consumer’s purchase and 3. Unique capability in the product

consists of name, term, They are must have of 2. Favorable is the expressing

sign, symbol, or any strong link of them approval or consent of brand in combination of them that (Keller, 2008) the society and to the advantage attempts to represent the of that brand unique benefit of 3. Unique is being the only one of company its kind of brand and unlike to be (Hu et al., 2009; Philip anything else Kotler & Armstrong, 2017) Price Fairness Price fairness is a 1. Reasonable 1. Reasonable is the how the Ordinal (Chin & customers’ perceptions 2. Acceptable consumer to receive the price Harizan, 2017; and their related 3. Justifiable with the fair and sensible from Xia et al., 2004) emotions about how fair, (Xia et al., 2004) 2. Acceptable is the measure of acceptable, and consumer able to accept and reasonable the difference satisfy of the product with that is between two price and price determined value that consumer 3. Justifiable is measure the price exchange for the benefits can be justified for the price

for having and using the consider of the ingredients or

product and service other aspect of the product (Philip Kotler & Armstrong, 2017; Xia et al., 2004) Perceived Perceived quality is 1. Performance of 1. Performance of the product is to Ordinal Quality customer’s perception of the product measure how that product can (Asshidin et al., all quality or superiority 2. Durability have good impact of the 2016; Chin & of a product compared to 3. Brand name consumer and suit with consumer Harizan, 2017) alternatives 4. Purity expectation (Keller, 2008) (Asshidin et al., 2016) 2. Durability is the strength of the cosmetic can stay along the use of the product 3. Brand name is the consideration of cosmetic customer to choose the product according the brand 4. Purity is the product to being pure after the product being package

Source: Developed by Researcher (2018)

3.5 Questionnaire

The questionnaire is divides into six parts. The first part is respondent identity which consists of age of respondent. Second part of the questionnaire is containing celebrity endorsement variable statements, which composed to understand the celebrity endorsement had influence in the purchase intention of the cosmetic product consumer. Product packaging statements are written in third part of the questionnaire, the purpose is to analyze on how consumers engage product packaging as the consideration of consumer intention in choose the product. Fourth part is containing statements that describe brand image of the product, it is used to observe whether the brand image have the ability to affect the consumers' intention in the cosmetic product. Then fifth part consists of price fairness variable statement to analyze whether the consumers' intention consist of the price fairness in consideration for the customers, such as reasonable that price of product, acceptable of the price had, etc. And the last part is about perceived quality statements where it was constructed to seek what certain customers' intention consideration by perceived quality of the cosmetic product. This research uses Likert scale to responds the questionnaire. Likert scale is a scale that used to measure the degree of agreement that symbolizes with five point anchors (Sekaran & Bougie, 2016).

Table 3.2 Example of Likert Scale Questionnaire

No. Statement Scale 1 2 3 4 5 1 2 3 4 5 6

Source: Sekaran & Bougie (2016)

Note:

1 = Strongly Disagree

2 = Disagree

3 = Neutral

4 = Agree

5 = Strongly Agree

Likert scale is used to answer each statement prepared by the researcher to represent the level of consumer approval. Responses are denoted by numbers from 1 to 5, where 1 is used when the respondent strongly disagrees with the statement, while 5 is used when they strongly agree with the statement.

Since the Likert scale is believed to be ordinal data, the researcher needs to transform the data using the Interval Success Method to convert data from ordinal to interval by using software called STAT97. Then, the rest of the statistical analysis is run using SPSS version 24.0.

3.6 Population and Sampling Design

The population is described as a group of people, events, or interesting things that researcher wants to examine. The population used in the study should relate to the object in which the research is conducted (Sekaran & Bougie, 2016).

The population of this research is the user of cosmetic product which narrows down to the consumer of lip color product cosmetic working in Jababeka Industrial Estate. The economic base of Cikarang is getting stronger as it has 4,000 multinationals from 35 countries. Since 1989, Jababeka City area has expanded to a total area of 5,600 hectares, making Jababeka City one of the largest in Southeast Asia. As a pioneer of private industrial area in Indonesia, the development of Jababeka Industrial Estate cannot be separated from the more complete infrastructure around Jababeka City. There are currently 1,650

multinational companies from 30 countries to tenants in Jababeka industrial estates in Cikarang, Bekasi, and 730,000 workers (Kompas.com, 2017).

Then, in that population researcher choose several samples for the respondents. According to Sekaran and Bougie (2016), the sample is a number of people who are part of a population or group of individuals representing a particular population that the researcher wants to explore. There are several reasons to conduct research using sampling rather than population, including time, cost, and limited human resources. The sampling system is also implemented to minimize errors while analyzing the data collected.

This research implements non-probability sampling method, especially purposive sampling technique. Based on the targeted population, the samples used for this study were users of lip color cosmetic products working in Jababeka Industrial Estate.

The total respondents for this study were 155 participants consisting of 155 female users of color lip color cosmetic products who worked in Jababeka Industrial estate and used it in their daily life. Questionnaires were prepared using Bahasa Indonesia, as all the targeted respondents were Indonesians, so the respondents and researchers would have the same interpretation of each statement written in the questionnaire.

3.7 Research Instrument

3.7.1 Data Collection Process

Primary Data

In this research, the data are primary data that collected with questionnaire. Questionnaire is a preformulated written set of questions to which respondents record their answers, usually within rather closely defined alternatives (Sekaran & Bougie, 2016). According the type of questionnaire, there are three types of questionnaire that distinguish the distributed of questionnaire, such as,

personally administered questionnaire or directly distribution questionnaire, mail questionnaires, and electronic and online questionnaires (Sekaran & Bougie, 2016). In this research, the researcher using personally administered questionnaire to distribute the questionnaire to the respondents. This method had advantage to make sure that the one that answers the questionnaire meet the criteria of targeted respondents. The period of questionnaires distribution started from 26th March 2018 until 7th April 2018.

3.7.2 Validity Test

Validity test is to measure the degree to which tests prepared for research or other measuring instruments actually measure what the researcher wants to measure (Lawrence et al., 2013). There are two results from validity test results, valid and invalid. Valid when the respondent understands well about the question and answers it according to what the researcher intends. Invalid is when the respondent misunderstands the question posed to them to answer the question in an unnecessary way (Greener, 2008). In this particular study, the researcher used the validity test to filter the prepared questionnaire, in which statements measured as invalid were omitted and changed from the questionnaire which was then distributed to the respondents.

Pearson Product Moment (PPM) developed by Karl Pearson is a statistical tool used to measure the correlation between variables in which data must be in the form of intervals or ratios. This is denoted by r when measured in the sample and ρ when measured in the population. The PPM value is between -1 ≤ r ≤ 1. If the result of r is 0, it means that there is no correlation between the measured variables. While the positive (+) and negative (-) symbols indicate the direction of variable correlation (Lane, 2009). Below is the formula of Pearson Product Moment in statistic:

( ) ( )( ) ( ) √[ ( ) ]√[ ( ) ]

Source: Lane (2009)

Where:

= The number of paired observation

= Pearson r correlation coefficient

= The sum of x-values

= The sum of y-values

= The sum of squared x-values

= The sum of squared y-values

= The sum of x-values and y-valued

Validity test was carried out by distributing the questionnaire printed to 15 sample respondents at the pretest stage of the study, which was then calculated using SPSS version 24.0. To determine whether a valid or invalid statement is to compare the value of the item's correlation to the r-value in the distribution table, where the degrees of freedom (df) equals the sample size (N) minus 2. Thus, if N = 15, then df is 13, and the r-value will be equal to 0,514. Statements with correlations higher than 0.514 are measured as valid and lower ones will be measured as invalid.

3.7.3 Reliability Test

The reliability test is used to measure the consistency or repetition of the study over time, so that the same research methods can be held for several times and produce the same results as before (Greener, 2008). The ability to measure to keep the results remains the same over time and shows that this study is stable and low in situational change vulnerabilities (Sekaran & Bougie, 2016).

Reliability test is done in the pre-test phase of the research. Before the questionnaire is actually distributed to the respondent, the reliability of the

written statement must be tested. This test is performed using SPSS software, and the collected data is converted from ordinal to interval by applying the Microsoft Excel stats extension program first.

The results of the Alpha Cronbach coefficient in the reliability test are in the range of 0 to 1. If the items are not correlated to each other the coefficient will be 0, if all items tested contain high correlation then the coefficient will be close to 1. Generally, the reliability coefficient is less from 0.60 defined as poor, those with a range of 0.70 are considered acceptable and coefficients above 0.80 are good (Sekaran & Bougie, 2016).

Below is the formula of reliability measure developed by Cronbach:

( ) ( )

Source: Lane (2009)

Where:

= Instrument reliability’s coefficient

= Mean interitem correlation

= Number of items

3.8 Normality Test

Normal distribution refers to the frequency distribution of multiple events occurring at each variable value. In this study, researcher used two methods to evaluate the normality distribution of data. The first is to use the Shapiro-Wilk and Kolmogorov-Smirnov tests provided in the SPSS software. In both tests, the data is defined as normal when the significant number is greater than 0.05. Then, second method is by examining the histogram and plot of normal probability. Normal data shows a bell-shaped curve in its histogram. The X-axis histogram represents the value of the quantitative variable, while the Y-axis

represents the frequency of events. Probability plot is a graphical method represented by a plot that refers to a set of data and diagonal lines as the expected normal distribution. Normal data distribution is achieved when the plot is scattered and follows the diagonal line (Lawrence et al., 2013).

3.9 Factor Analysis

Factor analysis is a research method used to define relationships among a number of variables, and then convert them into smaller numbers by reducing or summarizing. It defines which variables are related and which variables are not. Researchers need to maintain these correlated variables by grouping them together and giving them a new label or name a new group formed from the analysis. Factor analysis is not only limited in determining correlation between variables but also among respondents (Hair, Black, Babin, & Anderson, 2010).

3.9.1 Correlation Matrix

The first step of factor analysis is to determine the correlation matrix between the factors analyzed. If one variable has a high dependency with other variables, it can be concluded that these variables can be grouped together because they have a high correlation. On the other hand, variables with a lower correlation would not be possible to form groups.

In this study, the correlation matrix was determined by analyzing KMO and Bartlett Test and Anti-image Correlation. Number of Kaiser-Meyer-Olkin (KMO) Adequacy Sampling Size ranges from 0 to 1, where KMO = 1 means that variables are predicted without error by other variables. KMO index range can be interpreted as the following criteria:

 KMO > 0.90 are excellent  KMO > 0.80 are good  KMO > 0.70 are decent  KMO > 0.60 are mediocre

 KMO > 0.50 are inadequate  KMO < 0.50 are unacceptable

Source: Hair et al., (2010)

The Bartlett Duration Test is a statistical test used to measure the presence of correlations between variables. The correlation between variables is higher if the number is significantly close to 0.

The final step of the correlation matrix is called the Anti-image Matrix, which also aims to predict the correlation between variables. The required index ranges of good correlation are those above 0.50. Variables with an Anti-Image Matrix index value below 0.50 will not be analyzed or eliminated further.

3.9.2 Factoring Extraction

Initial Eigenvalue

Initial Eigenvalue is a value that aims to measure how strong the correlation between data. Highly correlated data assumption is to evaluate its eigenvalues, where it should be greater than 1.00. Data with an eigenvalue of less than 1.00 will not be used further to assess the number of factors established (Lawrence et al ., 2013).

Percentage of Variance

The percentage of variants describes the percentage value of a variable against a given factor, in which each variable has 1 variance. The total variance is the total variable multiplied by 1 or 100%. And the cumulative variance is determined as the result of the accumulation of all variants. The formula for calculating the percentage variance is (eigenvalue ÷ total variance) × 100% (Lawrence et al., 2013).

Communality

Communality in the factor analysis defines the percentage variance of each variable classified in the number of factors extracted. The more communal means the correlation between the variables and the established factors becomes more intensive (Lawrence et al., 2013).

Factor Loadings

Factor loading determines the correlation between variables and components. This is the output of the calculated component matrix that is not rotated. This determines the level of correlation between variables and factors. The loading of a higher variable factor means that it is set to represent a factor, which describes the role of each variable in each factor (Hair et al., 2010). Researcher need to consider the factor of loading when interpreting factors. The following are significant criteria for evaluating correlations:

Table 3.3 Criteria of Significance Factor Loading Based on Sample Size

Factor Loading Sample Size Needed for Significance* 0.30 350 0.35 250 0.40 200 0.45 150 0.50 120 0.55 100 0.60 85 0.65 70 0.70 60 0.75 30

Source: Hair et al., (2010)

3.9.3 Factors Rotation

Rotated component factors showed a more detailed and clear factor distribution. Implementation of component factors to clarify the position of variables in the factors set. While un-rotated components extract factors based on variance, the rotated component matrix tries to distribute the variance of the predetermined factors (Hair et al., 2010). There are two methods of factor rotation, orthogonal rotation and oblique. The orthogonal rotation is assumed when the factor is rotated on a 90 degrees rotation, which results in each variable being strongly correlated with several factors while at the same time having a less strong correlation with other factors. Varimax rotation is widely used to calculate orthogonal methods. Another method is called skewed rotation where it allows factors to deviate from 90 degrees rotation. Factor correlation results are shown after the rotation process is complete. The most commonly used rotation for the oblique method is Promax rotation (Lawrence et al., 2013).

3.9.4 Labeling the Established Factors

In factor analysis, the factor contains some number of variables. When the factors are successfully classified by their value factor, the next step that the researcher needs to do is to label or name the factor according to the conceptual meaning of each factor seen from the group of variables that make up it (Hair et al., 2010). According to Yong & Pearce (2013), naming or labeling factors are the "art" method of factor analysis because there are no specific rules for naming the new factors generated as long as the names given best represent factors in the variables.

CHAPTER IV

DATA ANALYSIS

4.1 Pre-Test

4.1.1 Reliability Test

The reliability test will be considered to be accepted if the reliability coefficients are 0.70. In table 4.1 below shows the reliability test result for all variables.

Table 4.1 Reliability Test Result

Reliability Statistics Cronbach' Cronbach' N of s Alpha s Alpha Items Based on Standardiz ed Items .900 .910 31

Source: Primary Data and SPSS Version 24.00 (2018)

The reliability test in the table 4.1 above shown that the coefficient value of all variables is above 0.70 which means all variables that have been through reliability test are reliable. Hence, the variables are suitable for the future research.

4.1.2 Validity Test

The validity test will be considered as valid if the correlation value of each items greater than 0.514 with r table distribution for N=15 with the significance level of 0.05. And the invalid statement if each items correlation

value is below 0.514. And the invalid statement will be eliminated. The table 4.2 below shows the validity test result of each variable.

1. Celebrity Endorsement

Table 4.2 Validity of Celebrity Endorsement

Statement R Table R Value Result

Celebrity Endorsement 1 0.514 0.940 Valid Celebrity Endorsement 2 0.514 0.906 Valid Celebrity Endorsement 3 0.514 0.828 Valid Celebrity Endorsement 4 0.514 0.903 Valid Celebrity Endorsement 5 0.514 0.612 Valid Celebrity Endorsement 6 0.514 0.705 Valid Celebrity Endorsement 7 0.514 0.597 Valid

Source: Developed by the Researcher (2018)

According to the table 4.2 shows that there is no r value below 0.514 all Celebrity Endorsement statement are valid with r value greater than 0.514 which means all the statement still be used in the next step of the research.

2. Product Packaging

Table 4.3 Validity of Product Packaging

Statement R Table R Value Result

Product Packaging 1 0.514 0.623 Valid Product Packaging 2 0.514 0.426 Invalid Product Packaging 3 0.514 0.545 Valid Product Packaging 4 0.514 0.577 Valid Product Packaging 5 0.514 0.650 Valid Product Packaging 6 0.514 0.518 Valid Product Packaging 7 0.514 0.480 Invalid Source: Developed by the Researcher (2018)

According to the table 4.3 above shows Product Packaging statement, there are 2 statement that not valid because the r value below 0.514, thus the statement 2 and 7 will be eliminated and will proceed to the next step of the research.

3. Brand Image

Table 4.4 Validity of Brand Image

Statement R Table R Value Result

Brand Image 1 0.514 0.194 Invalid Brand Image 2 0.514 0.599 Valid Brand Image 3 0.514 0.671 Valid Brand Image 4 0.514 0.669 Valid Brand Image 5 0.514 0.655 Valid Brand Image 6 0.514 0.785 Valid Brand Image 7 0.514 0.633 Valid

Source: Developed by the Researcher (2018)

According to the table 4.4 above shows Brand Image Statement, only 1 statement that is not valid with r value 0.194 below 0.514, and the other six statement has r value Greater than 0.514 which mean the six statement will be used to the next step of research.

4. Price Fairness

Table 4.5 Validity of Price Fairness

Statement R Table R Value Result

Price Fairness 1 0.514 0.258 Invalid Price Fairness 2 0.514 0.721 Valid Price Fairness 3 0.514 0.836 Valid Price Fairness 4 0.514 0.523 Valid Price Fairness 5 0.514 0.590 Valid Price Fairness 6 0.514 0.746 Valid

Price Fairness 7 0.514 0.746 Valid

Source: Developed by the Researcher (2018)

According to the table 4.5 shows the first statement of the price fairness is invalid with the r value is 0.258 which is below 0.514, and the other six statement that has r value greater than 0.514 will be proceed to the next step of the research.

5. Perceived Quality

Table 4.6 Validity of Perceived Quality

Statement R Table R Value Result

Perceived Quality 1 0.514 0.326 Invalid Perceived Quality 2 0.514 0.676 Valid Perceived Quality 3 0.514 0.680 Valid Perceived Quality 4 0.514 0.750 Valid Perceived Quality 5 0.514 0.666 Valid Perceived Quality 6 0.514 0.841 Valid Perceived Quality 7 0.514 0.678 Valid

Source: Developed by Researcher (2018)

The table 4.6 shows all the six statement are valid which has r values greater than 0.514 and one statement will be eliminated cause has r value < 0.514 and will not proceed to next step of research.

The validity test for all statement are shown in the table above, there are 5 statement which considered invalid as the r value below 0.514 as its required. And all the five statement will be eliminated and will no longer include on the questionnaire that distributed to the respondents for further analysis processed.

4.2 Normality Test

By examining significance value of Lilliefors the normality data would be considered as a normal data when the data value is greater than 0.5. which means when the data is greater than 0.5 the data is eligible to the further analyzed. In the table 4.7 shows the all the data is normal since all the variable meet all required significance value of Lilliefors test which means all variables can be proceed to the next analyzed since all the variable is normal. Thus, multivariate analysis can be applied for this research and the researcher chooses to use factor analysis.

Table 4.7 Kolmogrov-smirnov with Adjusted Lilliefors Normality Test

Kolmogorov-Smirnova Statistic df Sig. Celebrity .044 100 .200* Endorsement Product Packaging .062 100 .200* Brand Image .069 100 .200* Price Fairness .072 100 .200* Perceived Quality .072 100 .200* Source: Primary Data and SPSS (2018)

In addition determining the significance value in Lilliefors test, can be done by examining the probability plots of the data, in the figure 4.1 showed that the one of the variable is normal as the plot are scattered and follow the diagonal line of probability plots.

Figure 4.1 Probability Plots of Celebrity Endorsement Source: Primary Data and SPSS (2018)

4.3 Factor Analysis

Factor analysis is used to analyze the data in this research. The detail explanation about factor analysis method can be read in the Chapter III in the research manuscript. The result that will be displayed in this chapter is limited to several data which is used to analysis this process. The complete result can be seen in the Appendix C.

4.3.1 Preliminary Analysis a. Correlation Matrix

The researcher put the correlation matrix table from SPSS in Appendix C, the result on the computation in SPSS for correlation matrix shows the determinant value is 1.000 which means it is close to zero. The value of correlation matrix define there is high correlation between variables. That is means one of the requirements of factor analysis already fulfilled.

b. KMO and Bartlett’s Test

Table 4.8 KMO and Bartlett's Test

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling .695 Adequacy. Bartlett's Test of Approx. Chi-Square 1050.06 Sphericity 5 df 435 Sig. .000

Source: Primary Data and SPSS (2018)

The table 4.8 above shows, the value of Kaiser Meyer Olkin Measure of Sampling Adequacy is 0.695 which is greater than the required value 0.5. Therefore, the analysis can be proceed to the next step and the sampling method is also acceptable. c. Anti-Image Matrices

In analyzing MSA of each manifest variable it is easier using the Anti-image Matrices. When the MSA value is greater than 0.5. the variables can be used to predict without any mistake by other variables and analyzed by using factor analysis. The table 4.9 below showed all the value of all variables are above 0.5. as required which is the factor analysis can be applied in this research.

Table 4.9 Anti-Image Matrices

Variables MSA Variables MSA

Celebrity Endorsement 1 0.699 a Brand Image 4 0.768 a

Celebrity Endorsement 2 0.703 a Brand Image 5 0.637 a

Celebrity Endorsement 3 0.725 a Brand Image 6 0.685 a

Celebrity Endorsement 4 0.648 a Price Fairness 1 0.664 a

Celebrity Endorsement 5 0.707 a Price Fairness 2 0.613 a

Celebrity Endorsement 6 0.652 a Price Fairness 3 0.729 a

Celebrity Endorsement 7 0.778 a Price Fairness 4 0.720 a

Product Packaging 1 0.657 a Price Fairness 5 0.855 a

Product Packaging 2 0.602 a Price Fairness 6 0.716 a

Product Packaging 3 0.697 a Perceived Quality 1 0.579 a

Product Packaging 4 0.677 a Perceived Quality 2 0.654 a

Product Packaging 5 0.582 a Perceived Quality 3 0.792 a

Brand Image 1 0.731 a Perceived Quality 4 0.650 a

Brand Image 2 0.645 a Perceived Quality 5 0.774 a

Brand Image 3 0.659 a Perceived Quality 6 0.786 a

Source: Primary Data and SPSS (2018)

4.3.2 Factor Extraction a. Communalities

Table 4.10 Communalities

Communalities Initial Extracti on CE1 1.000 .331 CE2 1.000 .267 CE3 1.000 .256 CE4 1.000 .280 CE5 1.000 .215 CE6 1.000 .152 CE7 1.000 .271 PP1 1.000 .231 PP2 1.000 .374 PP3 1.000 .456 PP4 1.000 .281 PP5 1.000 .207

BI1 1.000 .507 BI2 1.000 .359 BI3 1.000 .172 BI4 1.000 .278 BI5 1.000 .249 BI6 1.000 .229 PF1 1.000 .170 PF2 1.000 .176 PF3 1.000 .199 PF4 1.000 .301 PF5 1.000 .310 PF6 1.000 .255 PQ1 1.000 .291 PQ2 1.000 .270 PQ3 1.000 .234 PQ4 1.000 .260 PQ5 1.000 .378 PQ6 1.000 .502 Source: Primary Data and SPSS (2018)

Communalities describes the variance of each manifest variable in the amount of factors that being extracted. Initial communalities define the variance of each variable before extraction, which why initial value of all variables are 1. Variables with higher value of communalities after extraction showed that the variables are highly correlated with the extracted factors. b. Total Variance Explained

According to the table 4.11, there nine factors which eigenvalue are greater than 1. So, in order to simplify the number of factors that formed from the analysis, the researcher changes the eigenvalue to 2.6 which establishes two factors instead of nine. Meanwhile, the percentage of variance describes the percentage value of variable on established factors. The variance of each variable is 1. Therefore, since there are 30 variables used in this research, the total variance will be 1 × 30 = 30. So, the percentage of variance that can be explained by one variable can be calculated dividing Eigenvalue with the total

variance, then multiply the result by 100%. For example, factor 1 with Initial eigenvalue of 5.587, thus, the calculation will be (5.587÷ 30) × 100% = 18.625%.

Table 4.11 Total Variance Explained

Total Variance Explained Extraction Sums of Rotation Sums of Initial Eigenvalues Squared Loadings Squared Loadings Com % of % of Cumul % of Cumul pone Varian Cumulative Varian ative Varian ative nt Total ce % Total ce % Total ce % 1 5.587 18.625 18.625 5.587 18.625 18.625 4.946 16.487 16.487 2 2.874 9.579 28.204 2.874 9.579 28.204 3.515 11.717 28.204 3 2.532 8.442 36.646 4 1.934 6.448 43.094 5 1.747 5.823 48.917 6 1.385 4.615 53.532 7 1.319 4.397 57.928 8 1.208 4.027 61.955 9 1.064 3.545 65.500 10 .970 3.234 68.734 11 .890 2.965 71.699 12 .835 2.783 74.482 13 .756 2.520 77.002 14 .715 2.382 79.384 15 .661 2.205 81.589 16 .616 2.053 83.642 17 .575 1.916 85.557 18 .545 1.815 87.373 19 .537 1.790 89.162 20 .456 1.520 90.682 21 .412 1.373 92.056 22 .396 1.321 93.376 23 .348 1.159 94.536 24 .327 1.091 95.626 25 .291 .971 96.598 26 .270 .900 97.498

27 .237 .789 98.287 28 .192 .640 98.927 29 .169 .564 99.492 30 .153 .508 100.000 Source: Primary Data and SPSS (2018)

Figure 4.2 Factor Analysis Scree Plot Source: Primary Data and SPSS (2018)

Figure shows in 4.2 above graphs component number in X-axis against eigenvalue in Y-axis. The graph can used to determine how many factors are there to be extracted. It can be seen from the curve first Factor plot to second and third factor is decline slightly as the range of Eigenvalue between those factors are quite far. And then start from fifth factor plot the curve is getting flatter through the last factor. The scree plot also showed that there are actually nine factors which eligible to be used further in factor analysis since the Eigenvalue of those factors are above. However, the factoring process is stopped at 5th factor since the Eigenvalue is changed to 2.6. The attempt is done in order to simplify the number of extracted factors.

4.3.3 Factor Rotation

In the table 4.12 shows the rotated factor loading of each manifest variable under four extracted factors. The factor loadings are used to classify the distribution of each variable into generated factors. The classification process is done by comparing the correlation value of each column in each item. The higher value of factor loading, the correlation between the variable and the factor is also higher.

Table 4.12 Rotated Component Matrix

Rotated Component Matrixa Component 1 2 CE1 .043 .574 CE2 .275 .438 CE3 .210 .460 CE4 .285 .446 CE5 .227 .404 CE6 .319 .225 CE7 .262 .450 PP1 -.006 .480 PP2 -.067 .608 PP3 -.229 .635 PP4 -.074 .525 PP5 .001 .455 BI1 .711 -.032 BI2 .595 -.070 BI3 .403 .097 BI4 .470 .238 BI5 .497 -.042 BI6 .432 .204 PF1 .392 .128 PF2 .419 .021 PF3 .365 .256 PF4 .402 .373

PF5 .542 .127 PF6 .358 .357 PQ1 .528 -.106 PQ2 .422 -.303 PQ3 .477 -.080 PQ4 .495 .125 PQ5 .574 .218 PQ6 .690 .162 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.a a. Rotation converged in 3 iterations. Source: Primary Data and SPSS (2018) The rotation is needed since there are a lot of manifest variables with high loading. It also makes the analysis become easier the correlation is acceptable if the loading facto of each variable is equal to or above 0.5. The correlation degree of variables with loading factor below 0.5 is considered weak, therefore will be eliminated for the next step of factor analysis. The classification of each variable will be shown in table 4.14 below.

Table 4.13 Component Transformation Matrix

Component Transformation Matrix Component 1 2 1 .874 .486 2 -.486 .874 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Source: Primary Data and SPSS (2018)

Tables 4.13 of component transformation matrix represent the correlation between the extracted factors by examine the value diagonally. The correlation between the factors is considered high since the value of each variable is more than 0.5.

Table 4.14 Factor Classification

Factor Manifest 1 BI 2 PF 5 PQ 1 PQ 5 PQ 6 2 CE 1 PP 2 PP 3 PP4 Source: Developed by the Researcher (2018) Notes: BI: Brand Image PF: Price Fairness PQ: Product Quality CE: Celebrity Endorsement PP: Product Packaging

4.3.4 Dominant Factor

From the test by implementing factors analysis method there are new factors that generated from 30 manifest variables, the new factor shows 28.204% cumulative value which means that the factor are able to represent 28.204% variability of all variables. a. First Factor The first new factor formed from extraction has variance value 16.487% after the rotation. This factor formed from the combination of variables, brand image, price fairness, and three of them are from perceived quality. Below are the table 4.14 shows five variables that construct the first factors.

Table 4.15 Construction of the First Factor

No Variables Statement 1 Brand image 2 Global cosmetics products always gave a

performance as promised 2 Price Fairness 5 The global brand price of cosmetic products is always equivalent to the benefits they are offered 3 Perceived quality 1 Lipstick global brand always lasted 24 hours on my lips 4 Perceived Quality 5 Global cosmetics products always have superior quality 5 Perceived Quality 6 The global lipstick brand has a variant selection of colors

Source: Developed by the Researcher (2018) According to the all statement that already constructed above on the table, the first factor is combine by Brand image, Price Fairness, and Perceived Quality, which more dominant into the ability global cosmetic product serve a quality product with the worth price. Thus the first factor can be referred as ―performance of the product‖. According to (Asshidin et al., 2016) Performance of the product is to measure how that product can have good impact of the consumer and suit with consumer expectation. And global cosmetic product gives them good performance of the product as the consumer expectation. b. Second Factor

The second factor which generated from factor analysis are constructed by four manifest variables, one from celebrity endorsement and three product packaging, the new factor extraction has variance value 28.204% after the rotation. The table 4.16 shown the second factor constructed.

Table 4.16 Construction of the Second Factor

NO Variables Statement 1 Celebrity Endorsement 1 I always look at celebrity reviews about cosmetic products when wanting to buy

cosmetics 2 Product Packaging 2 full information about the function of the product on the packaging always help me to choose cosmetic products 3 Product Packaging 3 I tend to buy glamorous glass-packed products 4 Product Packaging 4 I often choose favorite colors on product packaging when I want to buy cosmetics

Source: Developed by the Researcher (2018)

As can be seen in table 4.16 the second factor showed, the factor that stimulates purchase intention in cosmetic product is the enough information given by the product throughout the endorsement and their product packaging also well packaged product. The researcher named this as ―Attractiveness‖ Attractive is for how celebrity act like to attract attention to the advertisement and how product packaging like to attract attention from the color and the design (Bhakar et al., 2015), with well attractive advertisement people will tend to get attracted easily and it is also defined the quality of product itself if it is good or not.

4.4 Discussion

According to the result from all the processed that the researcher been through purchase intention can be used to product innovation and development in the cosmetic industries, the previous study from Chin & Harizan (2017) did found that from five variables, celebrity endorsement and price fairness has significance impact in stimulating purchase intention in cosmetic product on intention to purchase cosmetic product. But the other variables did not find the influence on intention to purchase cosmetic product, such as, brand image, product packaging, and perceived quality.

The first new factor called performance of the product it is formed by the variables that dominantly represent the consumer needs for quality of the product. And nowadays people intention to purchase cosmetics is because of the performance of the quality, whether it is as they are expected and even worth to purchase.

The second new factor is generated from celebrity endorsement and product packaging. All of the manifest variable are indicate the attractiveness of the product. The attractiveness is always being the first sight reason why we wanted to buy the product. For instance, we buy the product because of the product has glamour packaging or because the product having an attractiveness on the advertising by using world top public figure (celebrity).

CHAPTER V

CONCLUSION AND RECOMMENDATION

5.1 Conclusion

This research assesses the factors of women employees’ consumer of cosmetic product in Jababeka Industrial Estate by adopting purchase intention theory, with five variables used to the analysis namely Celebrity Endorsement, Product Packaging, Brand Image, Price Fairness, and Perceived Quality. The research is conducted to 155 female consumers who work in Jababeka Industrial Estate. The analysis was done by adopting factor analysis method. The result of the study showed that there are two dominant factors which generated from the Purchase Intention, namely performance of quality and attractiveness. Based on the percentage variance after rotation of each factor, performance of product is the most dominant one among the other factors with 16.487% and the second factor is 11.717%. These four new factors can be implemented to further explore consumer purchase intention of cosmetic product adoption or other innovative products.

5.2 Recommendation

The results of present study have some practical implications. For academic purposes, this research contributes in providing knowledge of purchase intention which particularly applied in cosmetic consumer. While for the local cosmetic producers, this research can be used as reference when developing new product cosmetics by considering the quality given trough the product.

Although this study contributes for certain implications, there are limitations that need to be addressed for future research. Firstly, the subjects of this study is only limited to a small number of cosmetics users who work in Jababeka Industrial Estate.

Whereas, those consumers are not the only one who have the access to adopt the product, and consumer behaviour in other places may be different from those participated in this study. Therefore, it is suggested for future research to be conducted in different places with different types of respondents.

Purchase intention is a wide concept which is applicable for different types of product. Hence, it still needs further exploration to develop new knowledge by using different approach modelled in this study which certainly give contributions academically and for practical implementations.

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APPENDIX

Appendix A – Questionnaire

Questionnaire in Bahasa Indonesia

Berilah tanda sesuai pendapat Anda, dengan ketentuan skala Likert sebagai berikut:

5 = Sangat Setuju; 4 = Setuju; 3 = Netral; 2 = Tidak Setuju; 1 = Sangat Tidak Setuju

Apakah anda menggunakan Lip color cosmetic (lipstick dan liptint) dalam keseharian? (Jika YA silahkan lanjutkan)

TIDAK

QUESTIONARE 1 2 3 4 5

Celebrity saya selalu melihat ulasan selebrity Endorsement mengenai produk kosmetik saat ingin membeli kosmetik saya lebih sering memilih kosmetik yang di endors oleh selebriti Saya cenderung memilih produk yang digunakan oleh selebritis terkenal saya selalu beranggapan selebriti terkenal pasti meng endorse barang yang ber- kualitas Saya akan membeli lipstick yang di endorse oleh selebriti cantik Saya selalu membeli kosmetik yang di endorse oleh selebriti top dunia

saya selalu membeli produk yang di endorse (direkomendasikan melalui iklan) oleh selebriti favorit saya

Product Kemasan berbahan plastik selalu saya Packaging pilih saat membeli kosmetik saya cenderung membeli produk yang berkemasan kaca saya sering kali memilih warna kesukaan pada kemasan produk saat ingin membeli kosmetik saya selalu memilih kemasan dengan tutup yang rapat informasi lengkap mengenai fungsi produk dikemasan selalu membantu saya untuk memilih produk kosmetik Brand Image Lipstick merek global membuat saya percaya diri Global kosmetik produk selalu memberikan peforma sesuai dengan yang dijanjikan Saya selalu cocok menggunakan merek global kosmetik Saya cenderung membeli kosmetik produk yang disarankan teman teman saya

Merek global kosmetik cenderung memiliki reputasi diatas merek kosmetik lokal Kosmetik merek global lebih mudah

di temukan di pasaran Price Saya selalu membeli produk kosmetik Fairness dengan harga sesuai anggaran yang saya tentukan Manfaat yang di dapat dari global kosmetik produk selalu sesuai dengan harga beli Merek global kosmetik produk cenderung terjangkau oleh semua kalangan Saya akan selalu memilih global kosmetik produk walaupun harga yang ditawarkan lebih tinggi Harga merek global kosmetik produk selalu setara dengan manfaat yang ditawarkan Global kosmetik produk menawarkan harga yang bervariasi tergantung kualitas dan ketahanan produk nya. Perceived Lipstick merek global selalu bertahan Quality 24 jam dibibir saya kualitas kosmetik global cenderung memiliki mutu yang baik dari waktu ke waktu produk kosmetik global bertahan sesuai dengan tanggal kadaluarsa Global kosmetik produk terbuat dari bahan alami sesuai janji produk Global kosmetik produk selalu memilik kualitas yang lebih unggul Merek lipstick global lmemiliki

pilihan warna yang beragam

Appendix B – Normality

Histogram and Normal Q-Q Plots

1. Celebrity Endorsement

2. Product Packaging

3. Brand Image

4. Price Fairness

5. Perceived Quality

Appendix C – Factor Analysis

Correlation Matrix

C C C C C C C P P P P P P P P P P P P P P P P P E E E E E E E P P P P P B B B B B B F F F F F F Q Q Q Q Q Q 1 2 3 4 5 6 7 1 2 3 4 5 I1 I2 I3 I4 I5 I6 1 2 3 4 5 6 1 2 3 4 5 6 1. ------Cor C 0 .2 .2 .3 .3 .0 .3 .0 .2 .3 .1 .1 .0 .0 .0 .0 .1 .0 .0 .1 .1 .1 .0 .2 .0 .0 .0 .1 .2 rela E 0 6 0 9 7 2 2 4 2 1 6 8 7 5 2 4 1 6 4 3 4 1 1 4 0 4 9 2 6 tion 1 0 8 7 3 9 5 8 5 2 6 1 7 8 5 3 5 3 7 1 4 9 5 7 3 6 6 9 6 4 . 1. - - - - 2 0 .6 .6 .1 .2 .1 .0 .0 .0 .1 .1 .2 .1 .0 .1 .1 .0 .0 .1 .1 .1 .1 .2 .0 .0 .1 .0 .3 .2 CE 6 0 3 2 9 9 8 2 0 5 5 7 0 1 6 3 0 7 3 4 3 5 4 3 9 0 3 5 2 2 2 8 0 0 4 7 7 8 7 5 5 4 2 8 3 5 7 6 2 2 8 8 6 6 4 0 2 4 3 2 2 . 1. - - - - 2 .6 0 .6 .2 .2 .2 .0 .1 .1 .0 .1 .1 .1 .0 .0 .1 .0 .0 .1 .0 .1 .0 .1 .1 .0 .0 .0 .2 .2 CE 0 3 0 1 4 4 4 1 3 0 0 5 0 0 1 9 3 4 4 1 8 6 6 1 6 7 1 3 3 2 3 7 0 0 6 8 6 7 8 2 1 5 4 0 5 2 6 9 7 5 4 1 1 9 8 0 5 0 1 7 3 . 1. - - - - - 3 .6 .6 0 .3 .2 .1 .0 .0 .0 .0 .1 .2 .1 .0 .0 .2 .2 .0 .2 .2 .1 .1 .2 .1 .0 .0 .0 .2 .2 CE 9 2 1 0 4 0 2 6 0 2 2 1 0 4 0 8 2 1 6 0 1 8 2 3 2 9 5 8 6 2 4 3 4 6 0 1 3 5 0 7 2 3 6 6 4 4 7 9 6 4 6 8 0 3 0 0 1 8 1 0 6

CE . .1 .2 .3 1. .1 .3 .0 .1 .1 - - .1 .0 .0 .1 .2 .0 .1 .0 .1 .2 .0 .1 .0 .0 .0 .1 .2 .1

5 3 9 4 4 0 2 5 9 9 1 .0 .0 7 3 4 3 2 4 5 1 4 0 4 8 9 1 0 1 9 6 7 7 8 1 0 9 8 1 9 0 3 5 0 1 6 3 2 3 2 8 2 9 6 7 4 7 3 9 6 1 9 0 0 5 . 1. - 0 .2 .2 .2 .1 0 .2 .0 .0 .0 .1 .0 .2 .3 .1 .1 .0 .1 .1 .2 .0 .1 .1 .1 .0 .0 .0 .0 .1 .1 CE 2 9 4 0 2 0 2 8 3 5 3 4 6 1 8 6 4 7 2 8 7 0 3 4 5 8 6 1 3 9 6 5 7 6 3 9 0 1 4 9 6 7 1 8 2 9 9 7 9 1 5 7 3 8 4 4 2 9 7 8 2 . 1. - 3 .1 .2 .1 .3 .2 0 .2 .2 .2 .0 .1 .1 .1 .1 .1 .0 .0 .0 .1 .1 .1 .1 .2 .2 .0 .1 .2 .3 .2 CE 2 8 4 2 5 2 0 1 0 0 5 8 4 7 4 4 8 1 5 5 5 5 2 7 2 7 4 4 6 0 7 8 8 7 5 8 1 0 5 5 7 2 1 2 5 4 7 4 6 9 1 8 1 3 1 3 7 4 1 6 5 . - - 1. - - - - - 0 .0 .0 .0 .0 .0 .2 0 .5 .3 .2 .1 .0 .0 .0 .1 .0 .2 .0 .0 .1 .2 .1 .1 .0 .0 .0 .1 .0 .0 PP 4 2 1 6 9 8 1 0 5 0 7 5 2 6 8 0 0 5 9 7 0 5 0 0 9 9 3 6 6 8 1 5 7 8 0 1 4 5 0 6 2 2 3 3 4 0 3 2 6 7 2 6 6 1 5 7 0 7 0 0 3 . - 1. - - - - - 2 .0 .1 .0 .1 .0 .2 .5 0 .4 .2 .3 .0 .0 .0 .1 .0 .2 .1 .0 .0 .1 .0 .1 .0 .0 .0 .0 .1 .1 PP 2 0 3 0 9 3 0 5 0 1 5 2 7 1 0 3 3 7 7 1 7 5 7 3 0 6 1 8 1 0 2 2 5 2 7 9 9 5 6 0 7 3 6 0 5 2 9 4 7 6 0 2 1 2 0 6 3 9 4 0 4 . 1. ------3 .0 .1 .0 .1 .0 .2 .3 .4 0 .3 .2 .1 .1 .0 .0 .0 .0 .0 .1 .0 .1 .0 .0 .1 .1 .1 .0 .0 .0 PP 1 5 0 2 1 5 0 0 1 0 3 4 0 3 1 8 9 9 8 6 7 6 3 6 3 8 0 0 7 2 3 6 5 1 2 0 6 7 2 7 0 0 4 1 9 6 1 4 7 3 4 0 8 7 7 4 4 4 1 0 9 . - - 1. ------1 .1 .0 .0 .0 .1 .0 .2 .2 .3 0 .3 .0 .0 .1 .2 .0 .1 .0 .0 .0 .1 .1 .2 .1 .1 .0 .0 .0 .0 PP 6 5 0 2 3 3 5 7 5 3 0 7 1 9 4 1 8 2 8 9 0 8 3 2 8 8 7 8 1 0

4 1 4 5 3 0 7 2 2 3 0 0 9 1 1 7 0 8 8 0 0 9 8 1 0 2 4 2 7 8 5

. - 1. ------1 .1 .1 .1 .0 .0 .1 .1 .3 .2 .3 0 .0 .1 .1 .1 .0 .2 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .1 .1 PP 8 7 5 1 5 4 8 5 2 4 7 0 2 4 6 3 1 0 1 1 4 2 7 5 8 6 7 3 2 2 5 7 2 4 6 5 1 1 3 6 4 9 0 9 6 6 6 9 1 6 3 0 3 4 5 5 7 6 5 7 2 . - - - - 1. 0 .2 .1 .2 .1 .2 .1 .0 .0 .1 .0 .0 0 .6 .2 .2 .3 .2 .1 .2 .0 .1 .3 .3 .3 .2 .2 .1 .4 .4 7 0 0 0 7 6 4 2 7 0 1 2 0 6 6 3 1 8 2 6 5 6 1 1 0 4 7 7 2 3 BI1 8 8 0 6 0 8 2 3 0 1 1 9 0 4 1 6 8 2 3 9 1 1 3 6 6 4 0 6 0 6 . - - - 1. 0 .1 .1 .1 .0 .3 .1 .0 .0 .1 .0 .1 .6 0 .2 .0 .1 .2 .0 .0 .0 .0 .2 .2 .1 .2 .2 .2 .3 .3 5 1 0 4 3 1 7 6 1 3 9 4 6 0 2 7 3 5 4 8 5 2 5 5 8 9 5 3 2 6 BI2 5 3 5 4 1 2 5 4 5 9 1 6 4 0 5 5 2 6 1 3 7 7 2 4 7 8 5 2 2 0 . - - - - 1. - 0 .0 .0 .0 .0 .1 .1 .0 .0 .0 .1 .1 .2 .2 0 .4 .1 .3 .1 .1 .0 .2 .1 .1 .0 .0 .1 .1 .2 .3 2 6 1 0 4 8 4 8 0 1 4 6 6 2 0 2 4 7 9 9 3 3 9 0 3 7 1 2 2 0 BI3 3 5 2 4 6 9 4 0 2 6 7 6 1 5 0 3 0 5 7 3 9 5 7 9 9 2 8 0 1 1 . 1. 0 .1 .0 .0 .1 .1 .1 .1 .1 .0 .2 .1 .2 .0 .4 0 .3 .3 .2 .2 .0 .2 .2 .3 .0 .1 .1 .2 .2 .3 4 3 9 8 3 6 4 0 3 8 1 3 3 7 2 0 2 7 6 5 9 8 1 0 9 7 4 1 4 4 BI4 5 7 6 7 3 9 7 3 9 1 0 6 6 5 3 0 2 3 6 7 0 4 3 5 9 2 7 4 4 4 . ------1. 1 .1 .1 .2 .2 .0 .0 .0 .0 .0 .0 .0 .3 .1 .1 .3 0 .2 .0 .1 .0 .0 .1 .0 .4 .2 .1 .1 .2 .2 1 0 3 2 2 4 8 0 3 9 8 1 1 3 4 2 0 5 3 6 5 0 7 7 1 1 5 9 8 9 BI5 3 6 9 9 2 7 4 2 4 4 8 9 8 2 0 2 0 9 4 8 0 9 4 8 6 9 2 4 5 1 - - .0 .2 .0 .1 .0 .2 .2 .0 .1 .2 .2 .2 .3 .3 .2 1. .1 .3 .1 .2 .2 .1 .1 .0 .1 .1 .1 .3 . .0 4 1 4 7 1 5 7 9 2 0 8 5 7 7 5 0 8 0 3 3 3 4 3 4 1 6 3 4

BI6 0 7 7 6 3 9 6 6 7 7 8 1 2 6 5 3 9 0 6 6 8 7 4 2 9 7 8 3 2 1

6 2 0 7 - . - - 1. - 0 .0 .0 .0 .1 .1 .0 .0 .1 .0 .0 .0 .1 .0 .1 .2 .0 .1 0 .5 .3 .3 .4 .0 .1 .0 .1 .2 .0 .2 PF 4 3 4 6 5 2 5 9 7 8 8 1 2 4 9 6 3 8 0 2 6 9 1 9 0 1 6 4 1 1 1 1 2 5 4 2 1 9 7 6 3 0 6 3 1 7 6 4 6 0 2 1 2 2 9 2 1 1 3 9 2 - . - - - 1. - 1 .1 .1 .2 .0 .2 .1 .0 .0 .1 .0 .0 .2 .0 .1 .2 .1 .3 .5 0 .2 .2 .2 .1 .0 .0 .0 .0 .0 .2 PF 3 4 1 0 1 8 5 7 1 6 9 1 6 8 9 5 6 0 2 0 2 5 8 1 0 8 7 1 1 3 2 4 8 4 6 8 5 1 2 0 4 0 3 9 3 3 7 8 6 2 0 6 8 3 6 9 4 1 3 4 7 . 1. 1 .1 .0 .2 .1 .0 .1 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .3 .2 0 .4 .3 .1 .1 .0 .1 .3 .3 .2 PF 4 3 8 1 4 7 5 0 7 7 0 4 5 5 3 9 5 3 6 2 0 2 7 1 2 0 3 2 2 7 3 9 8 1 8 2 7 8 6 2 0 9 0 1 7 9 0 0 8 1 6 0 8 7 5 5 2 6 5 8 6 . - 1. - 1 .1 .1 .1 .2 .1 .1 .2 .1 .1 .1 .1 .1 .0 .2 .2 .0 .2 .3 .2 .4 0 .3 .3 .1 .0 .1 .2 .2 .2 PF 1 5 6 8 0 0 5 5 5 6 8 2 6 2 3 8 0 3 9 5 2 0 5 8 9 0 6 6 7 2 4 5 6 1 0 9 3 1 6 1 8 8 3 1 7 5 4 9 7 2 8 8 0 8 2 5 9 7 2 0 0 . - 1. 0 .1 .0 .1 .0 .1 .1 .1 .0 .0 .1 .0 .3 .2 .1 .2 .1 .2 .4 .2 .3 .3 0 .1 .1 .0 .3 .3 .1 .3 PF 1 4 6 2 4 3 2 0 7 3 3 7 1 5 9 1 7 3 1 8 7 5 0 3 4 2 1 6 4 7 5 7 6 9 3 6 8 3 1 2 7 1 4 3 2 7 3 4 4 2 3 7 8 0 4 6 9 8 7 7 3 . .2 .1 .2 .1 .1 .2 .1 .1 .0 .2 .0 .3 .2 .1 .3 .0 .1 .0 .1 .1 .3 .1 1. .1 .0 .0 .1 .3 .1 PF 2 3 1 3 8 4 7 0 3 6 2 5 1 5 0 0 7 4 9 1 1 8 3 0 4 7 3 9 6 2

6 4 4 8 0 7 4 1 5 0 7 0 5 6 4 9 5 8 2 9 6 5 2 4 0 9 6 2 6 5 8

3 0 - . - - - - - 1. 0 .0 .1 .1 .0 .0 .2 .0 .0 .1 .1 .0 .3 .1 .0 .0 .4 .1 .1 .0 .1 .1 .1 .1 0 .3 .3 .1 .2 .3 PQ 0 9 6 2 9 5 2 9 0 3 8 8 0 8 3 9 1 3 0 0 2 9 4 4 0 5 1 9 6 6 1 6 0 0 0 4 4 3 7 6 4 2 5 6 7 9 9 6 9 2 9 5 5 6 9 0 9 9 5 4 3 - . ------1. 0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .1 .0 .2 .2 .0 .1 .2 .0 .0 .0 .0 .0 .0 .0 .3 0 .1 .0 .2 .1 PQ 4 0 7 9 1 8 7 9 6 8 8 6 4 9 7 7 1 4 1 8 0 0 2 7 5 0 7 9 3 8 2 6 2 5 1 7 2 7 0 3 4 4 7 4 8 2 2 9 7 1 4 2 9 9 6 9 0 9 0 2 1 - . - - 1. 0 .1 .0 .0 .0 .0 .1 .0 .0 .1 .0 .0 .2 .2 .1 .1 .1 .1 .1 .0 .1 .1 .3 .0 .3 .1 0 .2 .2 .3 PQ 9 3 1 5 0 6 4 3 1 0 7 7 7 5 1 4 5 1 6 7 3 6 1 3 1 7 0 9 0 0 3 9 4 0 8 3 9 4 7 9 4 2 6 0 5 8 7 2 8 1 1 6 7 8 2 9 9 0 2 3 2 . - - - 1. 1 .0 .0 .0 .1 .0 .2 .1 .0 .0 .0 .0 .1 .2 .1 .2 .1 .1 .2 .0 .3 .2 .3 .1 .1 .0 .2 0 .3 .5 PQ 2 5 3 8 1 1 4 6 8 0 8 3 7 3 2 1 9 6 4 1 2 6 6 9 9 9 9 0 8 0 4 6 3 1 1 9 7 1 0 4 1 7 5 6 2 0 4 4 3 3 3 5 2 7 6 5 0 2 0 3 8 . - - - - - 1. 2 .3 .2 .2 .2 .1 .3 .0 .1 .0 .0 .1 .4 .3 .2 .2 .2 .1 .0 .0 .3 .2 .1 .3 .2 .2 .2 .3 0 .3 PQ 6 2 3 6 9 3 6 6 1 7 1 2 2 2 2 4 8 3 1 1 2 7 4 6 6 3 0 8 0 6 5 4 2 7 0 6 8 6 0 0 0 8 7 0 2 1 4 5 2 9 4 8 0 7 5 4 2 3 3 0 6 . .2 .2 .2 .1 .1 .2 .0 .1 .0 .0 .1 .4 .3 .3 .3 .2 .3 .2 .2 .2 .2 .3 .1 .3 .1 .3 .5 .3 1. PQ 1 2 2 2 6 9 0 8 0 2 0 2 3 6 0 4 9 4 1 3 7 2 7 2 6 8 0 0 6 0

75 6 5 2 3 6 1 2 5 3 4 9 5 2 6 0 1 4 1 1 2 7 6 0 3 8 3 1 2 8 6 0

4 0

Anti – Image Matrices

C C C C C C C P P P P P P P P P P P P P P P P P E E E E E E E P P P P P B B B B B B F F F F F F Q Q Q Q Q Q 1 2 3 4 5 6 7 1 2 3 4 5 I1 I2 I3 I4 I5 I6 1 2 3 4 5 6 1 2 3 4 5 6 Anti - ima ge ------Cov C .5 .0 .0 .1 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 aria E 3 1 7 3 7 2 8 5 8 1 4 3 1 0 5 3 4 3 2 4 1 1 2 3 3 2 6 5 0 nce 1 2 0 3 8 6 5 0 8 8 0 6 5 6 5 0 4 8 2 1 1 8 1 5 8 0 6 6 4 5 . ------0 .3 .1 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 1 5 3 3 4 9 1 2 0 0 5 4 4 4 6 4 1 2 1 0 2 0 1 2 4 4 9 3 4 1 2 0 1 3 5 9 4 4 2 7 8 0 5 3 9 3 2 3 8 3 4 1 5 9 2 8 9 4 1 6 3 . ------0 .1 .4 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 7 3 1 1 0 3 7 3 7 2 5 2 5 3 0 0 2 4 0 2 7 5 1 6 4 7 4 2 3 3 3 3 3 5 1 1 0 4 3 8 4 6 6 5 7 6 8 0 9 5 6 8 7 2 4 8 5 4 2 8 5 ------. .1 .1 .2 .0 .0 .0 .0 .0 .0 .0 9, .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 1 3 1 8 9 2 3 1 6 4 0 0 2 3 3 4 3 5 0 1 6 0 1 4 1 6 5 9 1 2

4 3 5 1 8 0 4 4 5 4 7 4 9 3 1 7 0 9 1 4 3 7 1 1 4 3 3 7 9 4 8

8 E- 0 2 - . ------0 .0 .0 .0 .6 .0 .1 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 7 4 0 9 0 7 2 0 0 3 3 7 6 7 2 0 9 4 8 4 3 4 5 2 8 1 1 0 7 0 5 6 9 1 0 0 1 7 2 4 7 6 9 5 3 5 6 1 6 1 9 4 5 2 4 2 3 2 5 6 9 . ------0 .0 .0 .0 .0 .6 .1 .0 .0 .0 .0 .1 .0 .1 .0 .0 .1 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 2 9 3 2 7 3 0 2 3 5 9 0 2 2 5 4 3 5 3 3 2 6 1 3 5 0 4 2 1 1 6 5 4 0 4 1 8 7 0 3 9 1 6 0 7 9 9 0 2 4 7 1 9 1 7 8 4 3 9 1 4 - . ------0 .0 .0 .0 .1 .1 .5 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 CE 8 1 7 3 2 0 7 9 1 5 5 6 2 0 6 1 2 4 3 8 2 5 3 9 7 0 4 2 5 1 7 0 4 4 4 7 7 6 4 5 0 1 0 2 9 5 2 7 2 6 5 3 2 8 2 0 5 8 3 5 9 . ------0 .0 .0 .0 .0 .0 .0 .5 .2 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 PP 5 2 3 1 0 2 9 4 1 3 6 1 2 4 4 3 0 3 8 5 2 6 0 2 7 4 4 7 4 3 1 8 2 3 5 2 0 4 8 4 1 2 1 6 4 7 8 2 8 7 8 2 6 8 7 8 4 3 6 6 8 - .0 - .0 - .0 .0 - .4 - .0 - .0 - .0 - .0 - - .0 - .0 .0 - .0 - - .0 .0 - PP . 0 .0 6 .1 3 1 .2 2 .1 0 .1 4 .0 8 .0 0 .1 .0 3 .0 1 0 .0 2 .0 .0 3 8 .0

2 0 7 7 4 0 3 5 1 6 0 9 0 4 4 3 1 6 0 8 5 0 0 8 6 7 4 2 7 6 3

8 8 4 4 4 5 9 5 4 6 3 6 1 8 3 8 - . ------1 .0 .0 .0 .0 .0 .0 .0 .1 .5 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 PP 1 0 2 4 3 5 5 3 0 8 9 3 2 5 8 1 1 4 3 7 1 9 2 5 7 4 5 7 5 5 3 0 8 4 7 7 9 0 1 4 3 9 1 1 4 7 5 0 9 2 8 5 1 0 5 2 4 1 3 6 8 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .5 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 PP 4 5 5 0 3 9 5 6 0 9 8 9 2 7 3 3 0 0 0 1 5 5 3 9 5 4 7 5 4 3 4 6 0 6 4 6 1 1 2 9 9 1 1 4 4 1 0 0 4 4 0 7 7 1 9 4 3 4 2 9 8 - 9, - 0 . - - 9 ------0 .0 .0 E- .0 .1 .0 .0 .1 .0 .1 .5 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 PP 3 4 2 0 7 0 6 1 0 3 9 7 4 7 7 2 5 5 0 2 3 6 2 4 1 3 1 4 8 0 5 5 5 6 2 9 6 0 1 5 1 1 1 8 4 1 9 3 9 2 5 7 2 9 0 7 8 7 3 3 2 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .3 .2 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 1 4 5 2 6 2 2 2 4 2 2 4 4 0 0 1 4 1 0 7 8 0 6 3 5 5 1 8 8 6

BI1 6 3 5 3 5 0 2 6 4 1 4 8 8 6 2 3 0 9 6 7 1 5 5 5 8 4 2 7 8 6

. ------0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .2 .3 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 0 4 3 3 7 2 0 4 4 5 7 7 0 6 3 8 2 2 0 7 1 2 2 7 6 2 5 6 1 1 BI2 5 9 7 1 3 7 9 4 9 4 4 4 6 9 3 8 0 9 3 3 0 0 0 4 4 1 4 8 5 1 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .5 .1 .0 .0 .0 .0 .0 .1 .0 .0 .1 .0 .0 .0 .0 .1 5 6 0 3 2 5 6 4 8 8 3 7 0 3 6 1 4 9 6 2 7 0 0 5 2 0 0 9 6 0 BI3 0 3 6 7 5 9 5 7 3 7 1 1 2 3 5 8 5 4 5 9 9 9 2 1 6 8 4 6 9 6 . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .5 .1 .0 .0 .0 .0 .0 .0 .1 .0 .1 .0 .0 .0 .0 3 4 0 4 0 4 1 3 1 1 3 2 1 8 1 4 4 8 7 2 3 3 1 3 7 0 0 0 0 8 BI4 4 2 8 0 6 9 2 8 5 5 0 9 3 8 8 3 6 6 7 6 3 9 7 2 6 2 9 8 2 1 - . ------0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .5 .0 .0 .1 .0 .1 .0 .0 .1 .0 .0 .0 .0 .0 4 1 2 3 9 3 2 0 0 1 0 5 4 2 4 4 3 5 8 0 1 2 7 6 8 1 0 7 4 6 BI5 8 3 0 9 1 0 7 2 6 0 0 3 0 0 5 6 4 0 3 5 8 3 6 1 9 0 3 4 0 5 . ------1 .1 .0 .1 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .4 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 3 2 4 5 4 5 4 3 0 4 0 5 1 2 9 8 5 6 4 5 1 3 0 2 1 1 1 4 1 2 BI6 2 8 9 1 6 2 2 8 4 9 4 9 9 9 4 6 0 8 1 3 5 7 1 0 5 8 1 7 6 3 PF . .0 .0 - - .0 - .0 - .0 .0 .0 - .0 - - .0 .0 .4 - - - - .0 - .0 - - .0 .0

1 0 1 0 .0 .0 3 .0 8 .0 3 0 0 .0 0 .0 .0 8 4 7 .2 .0 .0 .0 4 .0 3 .0 .0 7 5

2 3 5 0 8 4 3 7 8 2 4 2 0 3 6 7 3 1 4 0 8 5 9 3 8 5 0 9 4 9 1 4 1 6 6 6 5 7 7 7 3 3 0 1 4 . ------0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .2 .4 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 PF 4 0 2 1 4 3 8 5 3 7 1 2 7 7 2 2 0 5 0 4 5 3 1 5 2 8 0 7 3 8 2 1 4 6 3 9 7 5 8 5 8 0 5 7 3 9 6 5 3 7 8 3 6 6 7 4 4 7 3 8 0 7, - 8 . ------9 - - - 0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .5 .1 .1 .0 .0 .0 E- .0 .1 .0 PF 1 2 7 6 3 2 2 2 0 1 5 3 8 1 7 3 1 1 8 5 5 2 0 6 0 1 0 2 4 4 3 8 1 8 7 4 1 3 2 3 5 7 7 1 0 9 3 8 5 7 3 7 0 9 1 7 9 2 9 5 2 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .1 .0 .1 .0 .0 .0 .1 .4 .0 .1 .0 .0 .0 .0 .0 .0 PF 1 0 5 0 4 6 5 6 1 9 5 6 0 2 0 3 2 3 5 3 2 4 8 2 9 1 4 1 4 4 4 1 5 7 1 5 9 2 6 0 1 7 2 5 0 9 9 3 7 3 6 0 5 5 2 3 6 1 9 2 9 . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .5 .0 .0 .0 .0 .0 .0 .0 PF 2 1 1 1 5 1 3 0 0 2 3 2 6 2 0 1 7 0 9 1 0 8 8 1 4 2 8 6 7 4 5 5 9 2 1 2 1 8 8 8 0 1 9 5 0 2 7 6 1 3 6 9 5 7 9 8 0 3 8 5 2 - - .0 - .0 .0 - .0 - .0 - .0 - - .0 - .0 .0 .0 - .0 - .0 .5 - .0 .0 - - .0 PF . .0 6 .0 2 3 .0 2 .0 5 .0 4 .0 .0 5 .1 6 2 4 .0 6 .1 1 7 .0 3 9 .0 .0 8

6 0 2 4 4 4 7 9 7 6 5 9 0 3 7 1 3 1 0 3 5 1 2 9 2 6 6 4 4 8 1

3 2 4 2 6 9 5 4 2 7 2 0 2 8 8 . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .1 .0 .0 .1 .0 .0 .0 .0 .4 .1 .1 .0 .0 .1 PQ 3 4 4 1 8 5 7 7 2 7 5 1 5 6 2 7 8 1 8 2 0 9 4 6 7 6 1 5 0 2 1 0 8 8 3 2 8 0 8 7 2 4 7 8 4 6 6 9 5 0 4 7 3 8 0 4 3 6 4 1 9 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .1 .6 .0 .0 .0 .0 PQ 2 4 7 6 1 0 0 4 4 4 4 3 5 2 0 0 1 1 3 8 1 1 2 3 6 7 0 4 8 0 2 6 9 5 3 3 4 5 4 1 4 3 8 4 1 8 2 0 8 5 4 9 6 0 6 3 4 4 6 2 1 7, 8 . ------9 ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 E- .0 .0 .0 .1 .0 .6 .0 .0 .0 PQ 6 9 4 5 1 4 4 4 2 5 7 1 1 5 0 0 0 1 0 0 0 4 8 9 1 0 8 3 1 2 3 6 4 4 7 2 3 8 3 8 1 4 7 2 4 4 9 3 1 1 7 2 1 3 4 6 4 8 0 8 3 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .4 .1 .1 PQ 5 3 2 9 0 2 2 7 3 7 5 4 8 6 9 0 7 4 9 7 2 1 6 4 5 4 3 5 1 9 4 4 1 2 9 5 9 3 6 7 3 2 3 7 8 6 8 4 7 4 3 9 9 8 2 4 6 0 4 1 6 PQ - - - .0 - .0 - .0 .0 - .0 - - .0 - - - - .0 .0 - - .0 - - - - - .4 .0

5 . .0 .0 1 .0 1 .0 4 8 .0 4 .0 .0 1 .0 .0 .0 .0 7 3 .1 .0 7 .0 .0 .0 .0 .1 1 1

0 4 3 4 7 1 5 6 6 5 9 8 8 5 6 0 4 1 4 8 4 4 5 8 0 8 1 1 0 5 0 6 8 6 5 6 3 8 9 2 0 6 5 2 8 1 2 8 1 5 - . ------0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .1 .0 .4 PQ 3 1 3 2 0 1 1 3 3 5 3 0 6 1 0 8 6 2 5 8 4 4 4 8 2 0 2 9 1 2 6 3 3 5 8 9 4 9 8 3 8 8 2 6 1 6 1 5 3 9 0 2 9 2 1 9 1 3 6 5 9 Anti - ima ge .6 ------Cor C 9 .0 .1 .3 .1 .0 .1 .1 .1 .1 .0 .0 .0 .0 .0 .0 .0 .2 .0 .0 .0 .0 .0 .0 .0 .0 .1 .1 .0 rela E 9 2 5 5 3 4 4 0 8 9 8 6 3 1 9 6 9 6 4 8 3 2 4 6 6 4 0 1 1 tion 1 a 4 5 2 4 3 5 8 4 7 4 4 8 1 1 4 1 4 2 4 3 3 4 9 0 4 9 1 0 . .7 ------0 0 .3 .4 .1 .1 .0 .0 .0 .0 .1 .1 .1 .1 .1 .0 .0 .3 .0 .0 .0 .0 .0 .0 .1 .1 .1 .0 .1 .0 CE 2 3 4 2 0 9 3 5 1 1 1 0 2 3 4 9 3 1 3 0 4 1 4 5 1 0 9 7 2 3 2 4 a 8 4 7 8 1 0 7 9 0 0 3 7 2 5 0 6 1 9 7 2 1 0 8 0 2 7 1 3 . - .7 ------1 .3 2 .3 .0 .0 .1 .0 .1 .0 .1 .0 .1 .0 .0 .0 .0 .1 .0 .0 .1 .1 .0 .1 .1 .1 .0 .0 .0 .0 CE 5 4 5 2 0 5 5 6 8 4 1 5 4 9 1 1 4 1 1 6 6 3 2 3 0 4 8 5 9 8 3 5 8 a 0 2 8 1 8 6 8 4 2 5 4 3 7 2 0 0 0 3 2 5 2 9 1 2 0 2 3

CE - - - .6 - .0 .0 .0 .1 .1 .0 .0 .0 - .0 .1 ------.1 .1 .2 .0 -

4 . .4 .3 4 .2 5 8 3 8 1 1 0 7 .0 9 0 .0 .4 .0 .0 .1 .0 .0 .1 .0 4 2 7 4 .0 3 2 2 8a 1 6 5 7 2 5 1 0 3 9 3 1 9 1 1 3 6 0 2 0 3 2 9 4 2 8 5 4 0 7 5 8 1 0 6 8 3 8 9 4 0 2 - . - .7 ------1 .1 .0 .2 0 .1 .2 .0 .2 .0 .0 .1 .1 .1 .0 .0 .1 .0 .1 .0 .0 .0 .0 .0 .1 .0 .0 .0 .1 .0 CE 3 0 0 1 7 1 1 0 0 6 6 3 4 5 4 1 6 8 5 9 5 8 8 4 5 2 1 1 5 1 5 4 7 2 7 a 4 6 3 6 3 0 6 2 6 3 0 0 7 2 4 9 8 8 0 4 1 8 0 4 8 . - - - .6 ------0 .1 .0 .0 .1 5 .1 .0 .0 .0 .1 .1 .0 .2 .0 .0 .2 .0 .0 .2 .0 .1 .0 .0 .1 .0 .0 .0 .0 .0 CE 4 9 5 5 1 2 7 3 6 9 4 7 4 6 9 8 2 9 6 5 3 2 1 6 0 0 6 5 2 2 6 3 8 8 6 4 a 6 3 3 6 9 5 2 2 7 3 2 6 2 6 4 9 8 1 5 7 5 3 1 8 - . - - - .7 ------1 .0 .1 .0 .2 .1 7 .1 .0 .0 .0 .1 .0 .0 .1 .0 .0 .0 .0 .1 .0 .1 .0 .1 .1 .0 .0 .0 .1 .0 CE 4 3 5 8 1 7 8 6 3 8 8 0 5 2 1 2 4 8 6 6 4 0 6 6 3 0 7 4 1 3 7 5 1 1 5 6 6 a 8 1 6 8 4 0 0 4 1 9 1 9 7 0 3 5 0 4 8 6 4 2 8 . - - - .6 ------1 .0 .0 .0 .0 .0 .1 5 .4 .0 .1 .0 .0 .0 .0 .0 .0 .0 .1 .1 .0 .1 .0 .0 .1 .0 .0 .1 .0 .0 PP 0 5 6 3 0 3 6 7 4 5 0 2 6 9 8 6 0 7 7 1 3 3 1 4 5 7 7 5 9 7 1 8 0 8 7 3 3 8 a 3 4 9 0 0 7 4 9 4 5 1 7 9 3 5 9 3 2 0 2 7 9 PP - .0 - .1 - .0 .0 - .6 - .0 - .1 - .1 - .0 - - .0 - .0 .0 - .0 - - .0 .2 -

2 . 1 .1 8 .2 6 3 .4 0 .2 1 .2 1 .1 6 .0 1 .2 .1 7 .0 2 1 .1 5 .0 .0 8 0 .0

1 7 8 2 0 3 1 4 2 1 7 1 5 2 8 3 2 3 9 9 0 4 5 3 9 7 5 3 5 7 8 6 6 3 a 0 2 3 0 2 1 7 4 6 2 7 4 - . - - - - - .6 ------1 .0 .0 .1 .0 .0 .0 .0 .2 9 .1 .0 .0 .1 .1 .0 .0 .0 .0 .1 .0 .1 .0 .0 .1 .0 .0 .1 .1 .1 PP 9 1 4 1 6 9 8 5 1 7 6 5 4 1 5 2 1 9 6 5 2 7 3 9 3 7 8 4 1 1 3 7 9 8 5 3 6 6 4 0 a 9 3 6 7 1 7 7 4 1 2 6 9 4 5 6 1 1 1 6 5 - . - - - - .6 ------0 .1 .1 .0 .0 .1 .0 .1 .0 .1 7 .3 .0 .1 .0 .0 .0 .0 .0 .0 .1 .1 .0 .1 .1 .0 .1 .1 .1 .0 PP 8 1 1 1 6 4 8 0 1 6 7 3 5 6 5 5 0 0 0 2 0 1 5 7 0 6 1 0 0 7 4 4 0 4 1 0 9 8 9 7 9 a 1 4 0 4 4 1 8 8 0 0 1 4 2 3 8 8 1 0 7 - . ------0 .1 .0 .0 .1 .1 .1 .0 .2 .0 .3 .5 .1 .1 .1 .0 .0 .1 .0 .0 .0 .3 .0 .0 .0 .0 .0 .0 .1 .0 PP 6 0 5 0 3 7 0 2 1 5 3 8 0 6 2 5 9 1 0 5 6 2 5 6 3 6 2 8 7 0 5 4 0 2 0 6 5 4 0 2 3 1 2a 7 1 5 3 6 3 3 0 6 1 0 9 3 0 6 5 1 4 - . - - - - - .7 ------0 .1 .1 .0 .1 .0 .0 .0 .1 .0 .0 .1 3 .5 .0 .0 .0 .0 .0 .1 .1 .0 .1 .0 .1 .1 .0 .2 .2 .1 3 2 4 7 4 4 5 6 1 4 5 0 1 7 0 3 9 4 1 9 8 1 4 7 4 1 2 1 3 7 BI1 8 3 5 3 2 2 0 0 5 6 4 7 a 4 4 1 3 8 5 6 4 3 5 9 3 1 5 9 2 0

BI2 . .1 - - .1 - - .0 - .1 .1 - - .6 - .1 .0 - .0 .1 - .0 - - .1 - - - .0 -

0 3 .0 .0 5 .2 .0 9 .1 1 6 .1 .5 4 .0 9 4 .0 0 7 .0 4 .0 .1 5 .2 .1 .1 3 .0 1 7 9 9 6 6 2 7 2 7 0 6 7 5 7 7 5 7 6 9 2 8 4 6 4 4 0 6 8 2 1 4 5 2 0 3 1 4 a 3 0 1 3 2 2 7 6 7 - . ------.6 ------0 .1 .0 .0 .0 .0 .1 .0 .1 .1 .0 .1 .0 .0 5 .2 .0 .1 .1 .0 .1 .2 .0 .0 .2 .0 .0 .1 .1 .2 9 4 1 9 4 9 1 8 6 5 5 2 0 7 9 1 8 8 2 5 4 1 0 9 4 1 0 9 4 1 BI3 1 2 3 3 3 7 4 4 8 1 4 5 4 3 a 2 2 4 5 7 0 7 4 0 3 3 7 0 3 4 . ------.7 ------0 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .2 6 .2 .1 .1 .0 .0 .0 .0 .2 .1 .1 .0 .0 .0 .1 6 9 1 0 1 8 2 6 3 2 5 5 3 9 1 8 7 7 5 5 6 7 2 3 5 6 1 1 0 6 BI4 4 5 7 1 0 3 1 9 0 7 4 3 1 7 2 a 2 0 2 3 0 9 9 6 0 9 4 6 4 7 - . ------.6 ------0 .0 .0 .0 .1 .2 .0 .0 .0 .0 .0 .0 .0 .0 .0 .2 3 .1 .1 .2 .0 .2 .1 .1 .3 .0 .0 .1 .0 .1 9 3 4 9 6 2 4 0 1 1 0 9 9 4 8 7 7 0 6 1 3 5 3 1 7 1 0 5 8 3 BI5 1 0 2 8 0 2 9 4 2 7 1 6 3 5 2 2 a 0 5 5 3 2 6 1 6 7 5 0 6 5 . ------.6 ------2 .3 .1 .4 .0 .0 .0 .0 .2 .0 .0 .1 .0 .0 .1 .1 .1 8 .0 .1 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 6 1 1 1 8 9 8 7 3 9 0 1 4 7 8 7 0 5 8 1 2 8 0 3 3 3 2 0 3 5 BI6 4 6 0 1 7 6 1 5 2 4 8 3 8 0 4 0 0 a 6 5 9 1 2 9 3 3 0 3 7 0 . .0 .0 - - .0 - .1 - .0 .0 .0 - .0 - - .1 .0 .6 - - - - .0 - .0 - - .1 .1 PF 0 3 1 .0 .1 6 .0 7 .1 6 0 0 .0 0 .1 .1 6 8 6 .4 .1 .1 .1 8 .1 6 .0 .2 6 3

1 4 1 0 1 5 2 6 1 9 1 8 3 1 6 2 5 5 6 4 4 6 1 7 2 6 2 0 0 7 1

2 0 2 9 1 5 5 2 a 9 9 5 7 9 2 2 . ------.6 - - - - - 0 .0 .0 .0 .0 .2 .1 .1 .0 .1 .0 .0 .1 .1 .0 .0 .2 .1 .4 1 .1 .0 .0 .1 .2 .1 .0 .1 .0 .1 PF 8 0 6 3 9 5 6 1 7 5 2 5 9 7 5 5 1 1 4 3 0 8 3 1 7 5 1 6 8 8 2 4 9 0 6 4 6 7 7 9 2 0 0 6 9 7 3 5 5 9 a 5 1 1 3 0 4 3 2 9 2 - . ------0 .0 .1 .1 .0 .0 .0 .0 .0 .0 .1 .0 .1 .0 .1 .0 .0 .0 .1 .1 .7 .2 .1 .1 .0 .0 .0 .0 .3 .0 PF 3 4 6 6 5 3 4 3 0 2 0 6 8 2 4 6 3 2 6 0 2 4 9 0 1 3 0 5 0 8 3 3 7 3 8 9 4 0 9 7 6 0 6 4 1 0 0 3 9 9 5 9a 1 1 8 4 0 0 8 3 6 - . ------.7 ------0 .0 .1 .0 .0 .1 .1 .1 .0 .1 .1 .3 .0 .0 .2 .0 .2 .0 .1 .0 .2 2 .1 .2 .2 .0 .0 .0 .0 .1 PF 2 1 3 0 8 2 0 3 2 7 1 2 1 4 1 7 5 8 1 8 4 0 6 4 0 2 7 4 9 1 4 3 2 2 3 8 9 3 3 4 9 1 1 3 8 7 9 2 1 5 1 1 a 6 2 3 9 4 3 8 1 . ------.8 - - - 0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .0 .1 .0 .0 .0 .1 .0 .1 .0 .1 .1 5 .0 .0 .0 .1 .1 .1 .0 PF 4 4 2 2 8 1 6 1 1 3 5 5 4 4 0 2 3 0 7 3 9 6 5 3 9 3 3 3 5 8 5 4 1 5 8 8 8 5 5 5 4 4 0 5 3 4 9 6 2 7 1 1 6 a 3 0 2 1 1 2 4 - . ------.7 - - - 0 .0 .1 .1 .0 .0 .1 .0 .1 .0 .1 .0 .0 .1 .0 .2 .1 .0 .0 .1 .1 .2 .0 1 .1 .0 .1 .0 .1 .1 PF 6 5 3 0 4 6 6 4 3 9 7 6 7 6 9 3 1 3 8 1 0 4 3 6 1 5 5 8 8 6

6 9 0 2 9 0 1 0 9 4 5 2 9 9 2 0 6 1 9 2 3 8 2 3 a 5 9 0 3 2 3

. ------.5 - - - - 0 .1 .1 .0 .1 .1 .1 .1 .0 .1 .1 .0 .1 .1 .2 .1 .3 .0 .1 .2 .0 .2 .0 .1 7 .2 .2 .1 .0 .2 PQ 6 1 0 3 5 0 3 5 5 3 0 3 4 5 4 5 7 3 6 7 1 0 9 1 9 8 0 1 0 8 1 0 8 9 4 4 5 4 3 9 6 3 3 3 4 3 0 6 3 9 0 4 3 0 5 a 8 3 6 1 6 - . ------.6 - 0 .1 .1 .1 .0 .0 .0 .0 .0 .0 .0 .0 .1 .2 .0 .1 .0 .0 .0 .1 .0 .0 .0 .0 .2 5 .0 .0 .1 .0 PQ 4 0 4 4 2 0 0 7 7 7 6 6 1 4 1 6 1 3 6 5 3 2 3 5 8 4 0 8 5 0 2 4 0 1 2 1 7 8 2 6 1 8 0 1 2 3 9 7 3 2 4 0 9 2 9 8 a 6 4 6 2 . ------1 .1 .0 .1 .0 .0 .0 .0 .0 .0 .1 .0 .0 .1 .0 .0 .0 .0 .0 .0 .0 .0 .1 .1 .2 .0 .7 .0 .0 .0 PQ 0 9 8 2 1 6 7 7 5 8 1 2 2 0 0 1 0 2 0 1 0 7 3 5 0 0 9 5 3 4 3 9 2 2 9 8 5 6 0 2 1 8 6 5 7 7 4 5 0 2 3 0 4 1 0 3 6 2a 3 4 2 - . ------.6 - - 1 .0 .0 .2 .0 .0 .0 .1 .0 .1 .1 .0 .2 .1 .1 .0 .1 .1 .2 .1 .0 .0 .1 .0 .1 .0 .0 5 .2 .4 PQ 1 7 5 7 1 5 4 5 8 4 0 8 1 6 9 1 5 0 0 6 5 4 3 8 1 8 5 0 5 4 4 1 7 0 4 0 3 4 2 3 1 1 5 9 6 0 6 0 3 2 2 8 3 1 3 6 4 3 a 7 4 - . ------.7 0 .1 .0 .0 .1 .0 .1 .0 .2 .1 .1 .1 .2 .0 .1 .0 .0 .0 .1 .0 .3 .0 .1 .1 .0 .1 .0 .2 7 .0 PQ 1 2 9 4 5 2 1 9 0 1 0 7 3 3 4 0 8 3 6 8 0 9 5 8 0 5 3 5 4 3 5 0 1 2 2 4 1 2 7 5 6 0 1 2 8 3 4 6 7 7 9 3 8 2 2 1 6 4 7 a 5

PQ - - - - - .0 .0 .0 - - .0 .0 - - - - .1 - .1 - - .1 - .1 - .0 - - .0 .7

6 . .0 .0 .0 .0 2 3 7 .0 .1 7 0 .1 .0 .2 .1 3 .0 3 .1 .0 1 .0 6 .2 0 .0 .4 3 8 0 3 8 8 1 8 8 9 7 1 7 4 7 2 1 6 5 5 1 8 8 1 8 3 8 2 4 4 5 6 7 3 3 0 8 7 5 0 7 4 7 0 2 6 4 6 2 4 a 0 a. Measures of Sampling Adequacy(MS A)