ANTECEDENTS OF OLDER CONSUMERS' INTERNET SHOPPING FOR APPAREL PRODUCTS: PERCEIVED RISK AND BENEFITS AND SHOPPING ORIENTATION Except where reference is made to the work of others, the work described in this thesis is my own or was done in collaboration with my advisory committee. This thesis does not include proprietary or classified information. _______________________ Anjali Dabhade Certificate of Approval: _________________________ _______________________ Carol Warfield Wi-Suk Kwon, Chair Professor Assistant Professor Consumer Affairs Consumer Affairs _________________________ _______________________ Dr. Sandra Forsythe Dr. Sang-Eun Byun Wrangler Professor Assistant Professor Consumer Affairs Consumer Affairs _________________________ George T. Flowers Interim Dean Graduate School ANTECEDENTS OF OLDER CONSUMERS' INTERNET SHOPPING FOR APPAREL PRODUCTS: PERCEIVED RISK AND BENEFITS AND SHOPPING ORIENTATION Anjali Dabhade A Thesis Submitted to the Graduate Faculty of Auburn University in Partial Fulfillment of the Requirements for the Degree of Master of Science Auburn, Alabama August 9, 2008 iii ANTECEDENTS OF OLDER CONSUMERS' INTERNET SHOPPING FOR APPAREL PRODUCTS: PERCEIVED RISK AND BENEFITS AND SHOPPING ORIENTATION Permission is granted to Auburn University to make copies of this thesis at their discretion, upon request of individuals or institutions at their expense. The author reserves all publication rights. ______________________________ Signature of Author ______________________________ Date of Graduation iv VITA Anjali Dabhade was born August 27, 1978 to Subhash and Vijaylaxmi Shewalkar of Pune, India. She attended Fergusson College, Pune, India from 1997 to 1999 and completed her Bachelor in Science with major Chemistry. She attended Indira Institute of Management, Pune from the year 2000 to 2002 where she completed her Master in Computer Management. She entered Auburn University Graduate School in Spring, 2005. v THESIS ABSTRACT ANTECEDENTS OF OLDER CONSUMERS' INTERNET SHOPPING FOR APPAREL PRODUCTS: PERCEIVED RISK AND BENEFITS AND SHOPPING ORIENTATION Anjali Dabhade Master of Science, August 9, 2008 (Master in Computer Management, Pune University, India 2002) (B.Sc., Fergusson College, Pune University, India 1999) 111 Typed Pages Directed by Wi-Suk Kwon Despite the growth of the Internet, one segment which marketers have overlooked is older consumers. With the rapid growth of the older consumer population and the potential the Internet holds for them, it is a subject worth consideration. The purpose of this research is 1) to examine the relationship between older consumers? beliefs regarding online shopping risks and benefits and their attitude towards online purchase of apparel products, 2) to examine the relationship between older consumers? attitude and intention vi of online purchase of apparel products, 3) to explore the influence of older consumers? shopping orientation on their beliefs and attitudes about online shopping, and 4) to explore differences between baby boomers and elderly consumers in terms of the relationships proposed in objectives 1-3. Ajzen and Fishbein?s theory of reasoned action was used as a theoretical framework for this study. Data from a national sample of 293 baby boomer and elderly consumers were collected using a mail survey. Result from this study revealed support for the significant relationship between older consumers? convenience seeking orientation and perceived time and convenience risk, and that between their brand consciousness orientation and perceived hedonic enjoyment benefit of online apparel shopping. I addition, older consumers? time and convenience risk had a negative influence on attitude toward purchasing apparel online. This study also revealed differences between baby boomers and elderly consumers. Baby boomers? shopping orientation significantly influenced their perceived risk and benefits various ways, while such relationships were lacking among elderly consumers. In addition, no significant relationship was observed between perceived risk and attitude for elderly consumers, while for baby boomers, the more their perceived risk related to product performance, the less positive their attitude toward online apparel purchasing. For baby boomers, the benefit of convenience and comfort of shopping offered by online shopping was a significant predictor of their attitude, whereas elderly consumers? attitude was influenced by their perceived benefit associated with product and price offerings available online. vii Findings of this study are expected to offer strategic implications which retailers can use to develop their online services to potentially reduce risks and increase benefits that are specific to the current and the future older consumer. viii ACKNOWLEDGEMENT The author would like to sincerely thank Dr. Wi-Suk Kwon for her assistance, guidance, and unbounded patience during this research. Gratitude is also expressed to committee members Dr. Sandra Forsythe, Dr. Sang-Eun Byun, and Dr. Carol Warfield for their support and contribution to this thesis. The author would also like to express her sincere gratitude and appreciation to her Husband Jayendra Dabahde for his consistent encouragement and guidance. Many thanks are also due to the author?s family and friends for their support at all times. ix Style manual or journal used: Publication Manual of the American Psychological Association (5th ed.) Computer software used: Microsoft Word?, Microsoft PowerPoint?, Microsoft Excel?, Statistical Package for the Social Science (SPSS) x TABLE OF CONTENTS LIST OF TABLES ........................................................................................................... xiii LIST OF FIGURES ......................................................................................................... xiv CHAPTER 1. INTRODUCTION ........................................................................................1 Background and Purpose Statement ........................................................................1 Definition of Terms..................................................................................................4 CHAPTER 2. LITERATURE REVIEW .............................................................................7 Theoretical Framework and Hypotheses Development ...........................................7 Baby Boomers and Elderly Consumers .................................................................10 Perceived Risk .......................................................................................................12 Perceived Risk in Consumer Behavior ......................................................12 Perceived Risk in Online Shopping ...........................................................14 Financial Risk ................................................................................14 Product Performance Risk .............................................................15 Time Loss Risk ..............................................................................17 Psychological Risk .........................................................................18 Privacy and Security Risk ..............................................................18 Source Risk ....................................................................................19 Perceived Benefits .................................................................................................19 xi The Construct of Perceived Benefits .........................................................19 Perceived Benefits of Online Shopping .....................................................20 Shopping Convenience ..................................................................21 Information Availability ................................................................21 Variety............................................................................................22 Entertainment .................................................................................23 Shopping Orientation .............................................................................................23 CHAPTER 3. METHODOLOGY .....................................................................................27 Instrument Development ........................................................................................27 Data Collection ......................................................................................................29 Data Analysis .........................................................................................................30 CHAPTER 4. RESULTS ...................................................................................................33 Sample....................................................................................................................33 Principal Component Analysis Results ..................................................................38 Perceived Risk ...........................................................................................38 Perceived Benefits .....................................................................................40 Shopping Orientation .................................................................................43 Regression Analysis Results ..................................................................................47 CHAPTER 5. DISCUSSION .............................................................................................56 Summary ................................................................................................................56 Multidimentionality of Shopping Orientation, Perceived Risk, and Perceived Benefits .....................................................................................56 xii Relationships Between Online Shopping Constructs for Older Consumers .......................................................................................58 Implications............................................................................................................59 Managerial Implications ............................................................................59 Implications for Literature .........................................................................61 Limitations and Recommendations ........................................................................62 REFERENCES ..................................................................................................................63 APPENDICES Appendix A. Questionnaire ...................................................................................75 Appendix B. Correlations Between Items .............................................................87 xiii LIST OF TABLES Table 2.1. Dimensions of Perceived Risk in the literature ................................................16 Table 4.1. Demographic Information .................................................................................34 Table 4.2. General Information ..........................................................................................36 Table 4.3. Perceived Risk Principal Component Analysis Results ...................................39 Table 4.4. Perceived Benefits Principal Component Analysis Results .............................41 Table 4.5. Shopping Orientation Principal Component Analysis Results .........................45 Table B.1. Correlations Between Items of Perceived Risk ................................................87 Table B.2. Correlations Between Items of Perceived Benefits ..........................................89 Table B.3. Correlations Between Items of Shopping Orientation .....................................92 Table B.4. Correlations among Component Scores (All Respondents) .............................95 Table B.5. Correlations among Component Scores (Baby Boomers: 43-61 Years Old) ............................................................................................................................................96 Table B.6. Correlations among Component Scores (Elderly Consumers: >61 Years Old) ............................................................................................................................................97 xiv LIST OF FIGURES Figure 2.1. Theoretical Framework .....................................................................................8 Figure 4.1. Regression Results for All Respondents .........................................................50 Figure 4.2. Regression Results for Baby Boomers (43-61 Years Old) ..............................53 Figure 4.3. Regression Results for Elderly Respondents (> 61 Years Old) ......................54 1 CHAPTER 1. INTRODUCTION Background and Purpose Statement The Internet has been growing rapidly among consumers as a common mode of shopping. For example, according to Forrester Research Inc. report, online sales in the U.S. totaled approximately $175 billion, which was a 21 percent increase over the 2006 online sales of $144.6 billion. U.S (?2007 Online Retail Sales?, 2008). online sales are expected to reach $204 billion in 2008 (Rosencrance, 2008). Forrester Research projects the online retail industry to keep on increasing its total revenues for the next five years although at a decreasing rate as the industry becomes mature (?2007 Online Retail Sales,? 2008; Knight, 2008). For other countries? example, in UK, according to the BBC news, the Internet has been attracting consumers increasingly with the online buying growth rate of 27.4 percent in 2004 (?Online Shopping,? 2005). In the increasingly time-constrained world, the Internet provides consumers with great convenience, yet there is some hindrance which consumers are concerned about (Bhatnagar, Misra, & Rao, 2000; Forsythe, Liu, Shannon, & Gardner 2006; Fram & Grady, 1997). The hindrance can be the risk associated with online shopping such as consumers? apprehension about giving out credit card information and making a purchase without the touch and feel of the product (Bhatnagar et al., 2000; Torkzadeh & Dillion, 2002). Perceived risk is a function of uncertainties arising from any purchase process, 2 and electronic commerce amplifies such uncertainties leading to a higher perceived risk (Bhatnagar et al., 2000; Cox & Rich, 1964; Forsythe & Shi, 2003). However, despite the risks associated with online shopping, an increasing number of consumers are shopping online indicating that there are significant benefits of online shopping that may not be available in the traditional shopping (Alba, Weitz, Janiszewski, Lutz, & Wood, 1997; Bhatnagar & Ghose, 2004; Bhatnagar et al., 2006; Forsythe & Shi, 2003; Hoffman & Novak, 1996). Therefore, both perceived risk and benefits are important constructs to be researched in order to understand consumers? online shopping behavior. According to the United States Census Bureau (2006), 40% of the U.S. population is comprised of consumers aged 50+ who have control of 75% of the nation?s wealth and are accountable for 55% of the consumer spending power in the U.S. By 2010, the population of older people who are 65+ will grow to roughly 50 million (Polyak, 2000) as the ?baby boomer? generation will turn 65 beginning in 2011 (Miller, Kim, & Schofield-Tomschin, 1998; Sengupta, Velkoff, & DeBarros, 2005). According to the ClickZNetwork, although younger people drove the early stages of the Internet growth, new growth in the Internet adoption for the past few years has come from those aged 55 or older (McGann, 2004). Older customers have not been getting the attention they deserve by online marketers who have instead chosen to focus their attention on the age group 18-34 (?Baby Boomers,? 2006). In spite of the importance of this potentially lucrative market, little academic research has been conducted on older consumers who represent the fastest growing online consumer segment. The purpose of this study was to investigate consumers who are baby boomers (43-61 years old) or older (over 61 years old) ? combined called older consumers, 3 hereafter - in terms of their beliefs regarding risk and benefits of online shopping, attitudes towards the Internet purchase, and buying intention through the Internet in the context of apparel shopping. This study used the theory of reasoned action (Ajzen & Fishbein, 1980) as a framework to explain relationships among older consumers? beliefs (perceived risk and perceived benefits), attitudes, and purchase intentions in the online apparel shopping context. In addition, this study explored the influence of shopping orientation on the beliefs and attitude about online apparel shopping. Shopping orientation provides inner views of consumers with different shopping patterns, motivations to shop, and perceived importance of retail attributes (Gehrt & Shim, 1998; McKinney, 2004). This study explored relationships between shopping orientation and other variables addressed in this study. Furthermore, previous literature has predicted significant differences between the two sub-groups of older consumers ? baby boomers and the generation prior to them ? in their values, acceptance of innovations, and other social and consumer behaviors (?IT Facts Internet Usage,? 2006; Guynn, 2002). Therefore, it was deemed worthwhile to explore differences between these two groups in terms of the proposed relationships between the variables. Specific objectives of this study, therefore, were 1. To examine the relationship between older consumers? beliefs regarding risk and benefits associated with online apparel shopping and attitude toward online purchase of apparel products. 2. To examine the relationship between older consumers? attitude and intention to purchase apparel products online. 4 3. To explore the direct influence of older consumers? shopping orientation on their attitudes toward purchasing apparel products online. 4. To explore the indirect influence of older consumers? shopping orientation on their attitudes toward purchasing apparel product online mediated by perceived risk and benefits. 5. To explore differences between baby boomers and the elderly in terms of the relationships proposed in objectives 1 through 4. Definition of Terms Attitude toward online purchase for apparel products: An individual?s disposition to respond favorably or unfavorably to the idea of purchasing apparel products online [adapted from the definition of ?attitude? by Ajzen (1989, p. 241)]. Baby boomers: People who were born between the years of 1946 and 1964. Brand Orientation: The importance a consumer places on brands in making his or her shopping and purchase decisions. Convenience and Comfort of Shopping: Perceived ease of Internet shopping related to being able to shop at any time and place with no trouble from salespeople or awkwardness of not purchasing. Convenience Seeking: The degree to which a consumer seeks convenience in deciding where to shop. Elderly consumers: Consumers who are aged 65 years or above (Polyak, 2000). However, elderly consumers in this study are defined as people who are aged over 61 years to distinguish them from baby boomers. 5 Financial Risk: Perceived potential loss of money or other resources as a consequence of an online purchase Hedonic Enjoyment: Perceived thrill and pleasure consumers expect from online shopping. Older consumers: Older consumers in this study are defined as people aged 43 or older including baby boomers (43-61 years old) and consumers who were older than them (over 61 years old) when data collection for this research occurred (2007). Online purchase intention for apparel products: The strength of the consumer?s intention to purchase apparel products online [adapted from the definition of ?behavioral intention? by Fishbein and Ajzen (1975, p. 288)]. Perceived benefits of online shopping: ?The consumer?s subjective perception of gain from shopping online? (Forsythe et al., 2006, p. 59). Perceived risk associated with online shopping: ?The consumer?s subjective perception of potential loss from shopping online? (Forsythe et al., 2006, p. 59). Price Consciousness: The extent to which a consumer shows concern for money and scout for good deals in shopping. Product Risk: Perceived likelihood that products purchased online fail to meet requirements desired by a consumer. Product and Price Offerings: Perceived variety of products and prices offered through the Internet. Shopping orientation: A shopper?s style that places particular emphasis on certain activities in shopping reflecting his or her view of shopping as a complex social, recreational, and economic phenomenon (Hawkins, Best, & Coney, 1989). 6 Shopping Enjoyment: The degree to which a consumer seeks pleasure in shopping. Shopping Confidence: The level of self-confidence a consumer shows in his or her ability as a good shopper Time/Convenience Risk: Perceived potential time or convenience loss due to browsing for and purchasing products online 7 CHAPTER 2. LITERATURE REVIEW Theoretical Framework and Hypothesis Development The Theory of Reasoned Action (TRA) (Ajzen & Fishbein, 1980) serves as the theoretical framework of this study. This theory states that individuals? attitude towards performing certain behavior is a powerful determinant of their intentions of performing the behavior, which then can be used to predict their future behavior (see Figure 2.1). Attitude can hold multiple components such as the cognitive, affective, and conative components (Rosenberg & Hovland, 1960). TRA views attitude as an affective dimension (i.e., overall favorable or unfavorable feelings toward an object) (Ajzen, 1989). However, constructs specified in TRA also reflect the other two components of attitude. The cognitive component of attitude is represented in this theory as a combination of beliefs that a behavior leads to certain outcomes and the evaluation of these outcomes. Specifically, according to Fishbein and Ajzen (1980), attitude is conceptualized as one score using the following equation: Ao = ? biei That is, for each belief (i) about an object, we take the weight or importance (bi) of that belief in determining one?s overall attitude towards the object and multiply it with the strength of the belief (ei). The sum of the product of all the belief weight-strength pairs represents the individual?s attitude towards the object (Ao). Behavioral intention refers 8 Figure 2.1 Theoretical Framework Shopping Orientation Perceived Risk of Online Shopping for Apparel Products Perceived Benefits of Online Shopping for Apparel Products Attitude Towards Online Purchase for Apparel Products Online Purchase Intention for Apparel Products Belief Behavioral Intention Attitude RQ1(a) RQ1(b) RQ2 H1 H2 H3 Note. RQ3 and RQ4 are not included in this figure. RQ3 addressed the indirect relation between shopping orientation and attitude mediated by perceived risk and perceived benefits. RQ4 addressed the differences between the baby boomers (43-61 years old) and the previous generation (over 61 years old) in the relationships suggested in this figure. 9 to individuals? decision of whether or not to perform a certain action, and is conceptualized in TRA to reflect the conative component of attitude. In the present study, the belief-attitude-behavioral intention link postulated by TRA was used to predict older consumers? attitude and purchase intention towards online purchase through the beliefs regarding risk and benefits they hold in their mind. According to the theoretical framework presented in Figure 2.1, older consumers? beliefs such as their perceived risk and benefits associated with online apparel shopping are conceptualized as possible antecedents of the consumers? attitude towards purchasing apparel products online, which in turn determines their online purchase intentions for apparel products. Therefore, based on this conceptual framework, the following hypotheses were developed. H1: Perceived risk associated with online shopping negatively predicts older consumers? attitude towards purchasing apparel products online. H2: Perceived benefits associated with online shopping positively predict older consumers? attitude towards purchasing apparel products online. H3: Attitude towards purchasing apparel products online positively influences older consumers? online buying intention for apparel products. Furthermore, the researcher explored the potential role of shopping orientation as a direct predictor for older consumers? attitudes toward online purchase of apparel products. Shopping orientation may also indirectly influence attitude of online purchase of the apparel product with a mediation of perceived risk and benefits. For this exploratory part of the research, the following research questions were developed. 10 RQ1: Is there a direct relationship between older consumers? shopping orientation and their perceptions of (a) risk and (b) benefits associated with online apparel shopping? RQ2: Is there a direct relationship between older consumers? shopping orientation and their attitude towards purchasing apparel products online? RQ3: Is the relationship between older consumers? shopping orientation and their attitude towards purchasing apparel products online mediated by their perceptions of risk and benefits associated with online shopping? The following sections in this chapter discuss literature on elderly consumers and baby boomers and the constructs proposed in the theoretical framework. Baby Boomers and Elderly consumers The older consumer market, including baby boomers who are future older consumers is gaining more attention among marketers due to the fast growth of this particular demographic segment. The number of people turning 60 was estimated to be 7,918 a day in 2006 (U.S. Census Bureau, 2006). By 2050, the number of people age 45+ is projected to be 1.7 times that in 2000 (U.S census Bureau, 2004). In the year 2004, there were 21.1 million older women and 15.2 million older men. The female to male sex ratio increases with age, ranging from 115 for the 45-69 age group to a high of 222 for persons 85 and over (Administration of Aging, 2006). According to U.S. Census Bureau projections, baby boomers accounted for 27 percent of the U.S. population in 2005 (Mature Market Institute Metlife, 2005). As the population of baby boomers and elderly consumers increases in the U.S., their spending power is also expected to grow. Elderly consumers who are of ages 11 between 65 and 85 have approximately twice the discretionary income of their children (Polyak, 2000). The poverty rate among senior citizens has dropped from 35 percent in 1960 to 10.2 percent in 2005 (Administration on Aging, 2006). These elderly consumers are also willing to spend the money and may not be as sensitive to price as younger consumers (Moschis, Lee, Mathur, & Strautman, 2000). On the other hand, speculations have been made that baby boomers may differ from their predecessors. Baby boomers, who are near future older consumers, are estimated to have one trillion dollars of spending power (?Marketing to Baby Boomers,? 2007); they have more income than their parents (Keister & Deeb-Sossa, 2001). Furthermore, they like to look good and be healthy, and are open-minded and aware of what they want and how they want to shop for it (Kharif, 2006). Baby boomers are expected to live a longer active life than any of their predecessors (Kharif, 2006), warranting increasing attention to this market segment from both the academia and practitioners. Recent research by marketers suggests that older consumers can be innovative purchasers as they are willing to use the Internet for a shopping purpose (Silvers, 1997). According to Administration of Aging (2006), 34.7 percent of households with elderly persons had a computer; this figure is somewhat more than half the figure for the general population which is 61.8 percent. Elderly households having Internet access was 6.8 million (29.4%) (as compared to 54.7% for the general population). Older consumers use the Internet mostly for email, searching for product/service and health information and making purchases (Administration on Aging, 2005). Baby boomers are increasingly adopting the Internet. For example, IT Facts reported that 195.3 million U.S. baby 12 boomers were current users of the Internet in 2006 (?IT Facts Internet Usage,? 2006). Consumers between ages 50 and 64 are expected to have three times more Internet access than those aged 65+ (Guynn, 2002). According to Jupiter Research, marketers spent close to $5 billion in advertisements targeting baby boomers or older consumers out of the total $13 billion spent on Web advertising in 2006. These statistics appear to indicate that although older consumers may not be as active on the Internet as younger generations, they are still taking part in the phenomenon of the Internet and that baby boomers especially are becoming a more and more important online consumer segment. These statistics also suggest that the relationships proposed in the hypotheses and research questions may differ for baby boomer and elderly consumers. Therefore, the following research question was added to this study. RQ4: Are there any differences between baby boomers (born between years 1946- 1964) and elderly consumers (born after 1964) with respect to the relationships described in H1 through H3 and RQ1 through RQ3? Perceived Risk Perceived Risk in Consumer Behavior The concept of perceived risk in relation with consumer behavior was first introduced by Bauer in 1960. Perceived risk was defined by Cox and Rich (1962) as ?the nature and the amount of risk perceived by a consumer in contemplating a particular purchase decision? (p. 33). Cunningham (1967) conceptualized perceived risk as the uncertainty of consequences. Researchers have generally agreed that perceived risk arises from perceived seriousness of the consequences when something goes wrong (Bettman, 1973; Taylor, 1974). A purchase decision a consumer makes will have consequences in 13 the future, so the consumer feels uncertainty of such consequences (Taylor, 1974). This uncertainty may be reduced by acquiring more information related to the product or the shopping environment (Taylor, 1974). For example, consumers associate more perceived risk with home shopping such as telephone shopping (Cox & Rich, 1962), catalog shopping (Festervand, Snyder, & Tsalikis, 1986; McCorkle, 1990), and mail-order shopping (McCorkle, 1990; Spence, Engel, & Blackwell, 1970) than in-store shopping where consumers can physically view the product. Perceived risk is a situational and personal factor that can negatively influence product purchase and store choice of the consumer (Dowling, 1986) in that as perceived risk decreases, purchase intention increases (Mitchell, 1999). Regardless of how perceived risk is defined, it is generally considered to be multidimensional (Bettman, 1973; Cunningham, 1967; Jacoby & Kaplan, 1972). The consequence or specific loss associated with perceived risk can be psychological/social or functional/economic or can be a combination of both (Taylor, 1974). Jacoby and Kaplan (1972) conceptualized four dimensions of perceived risk: financial risk, performance risk, psychological risk, and physical risk. Time loss risk was also studied by Roselius (1971) as a perceived risk dimension. According to Jacoby and Kaplan (1972) and Roselius (1971), financial risk refers to perceived potential loss of money or other resources as a consequence of purchase, while psychological risk is defined as perceived probability of the product purchase resulting in feelings of disappointment, frustration, and shame. These researchers also defined performance risk as perceived likelihood that the product purchased fails to perform as desired, whereas physical risk, which may be a sub- dimension of performance risk, refers to probability that the product purchased may be 14 dangerous for health and/or safety when the product fails. Finally, time loss risk refers to the perceived time lost in purchasing or retaining the product which the consumer intends to purchase. Perceived risk has been applied in recent online shopping research as an important variable that influences consumers? online purchase behavior. Perceived Risk in Online Shopping Internet stores are free from the boundaries of location, allowing consumers to shop from any remote locations (Bhatnagar et al., 2000). However, people may still be hesitant to shop from Internet stores due to the perceived risk associated with the online shopping process (Fram & Grady, 1997). Online shopping is considered to be riskier than in-store shopping since it is difficult to examine the product (Bhatnagar et al., 2000; Torkzadeh & Dillion, 2002), return the purchased product, and trust the integrity of the seller (Biswas & Biswas, 2004; Torkzadeh & Dillion, 2002). Researchers have tried to identify dimensions of perceived risk that are specific to the Internet shopping environment. In addition to the traditional perceived risk dimension as financial, product performance, psychological, physical, and time-loss risks, more dimensions such as privacy and security risk (Jarvenpaa & Todd, 1996) and source risk (Torkzadeh & Dillion, 2002) have been used to describe perceived risk in the online shopping context (see Table 2.1). Financial Risk. Financial risk in online contexts is related to the risk of losing money in online transactions by providing credit card or bank account information over the Internet (Fram & Grady, 1997; Lee, Park, & Ahn, 2001). Financial risk is more commonly associated with Internet shopping than with in-store shopping (Bhatnagar et al., 2000) because credit card fraud is a major concern to online consumers (Lee, Park, & 15 Ahn, 2001). Even though retailing on the Internet is increasing everyday and numerous surfers visit shopping websites, a very low proportion of the visits turns into sales partly because consumers are hesitant to provide credit card information (Bhatnagar et al., 2000). Researchers also have attributed financial risk associated with online shopping to the lack of trust in the retailer and fear of purchasing wrong products by mistake, not receiving the purchased product, personal information getting stolen, and credit card being overcharged (Forsythe et al., 2006). Financial risk may, however, be reduced with increased shopping experience on the Internet as the consumer acquires more knowledge about the e-tailer (Bhatnagar et al., 2000). Product Performance Risk. Product performance risk is defined as perceived risk associated with disappointment online buyers may experience when the product purchased online does not meet their expectations (Forsythe et al., 2006; Torkzadeh & Dillion, 2002). Higher product performance risk is created online due to the inability to physically examine the product and the lack of personal contact during the shopping process (Bhatnagar et al., 2000; Forsythe & Shi, 2003; Jasper & Ouellete, 1994; Torkzadeh & Dillion, 2002). The level of product performance risk associated with online shopping may also depend upon the type of the product. For example, it may be less risky to buy books, computers, or any electronic products which are more standardized (Bhatnagar et al., 2000) than products like fashion products which involve experiential value through fit, feel, fabric, and color of the product (Bhatnagar et al., 2000; Forsythe et al., 2006; Fram & Grady, 1997). Other product factors influencing 16 Table 2.1. Dimensions of Perceived Risk in the literature Risk Conceptual Definition Literature Traditional Shopping Context Online Shopping Context Financial Risk Risk related to the loss of money Derbaix (1983); Horton (1976) Lee, Park & Ahn (2001); Fram & Grady (1997); Forsythe & Shi (2003); Torkzadeh & Dillion (2002); Sweeney, Soutar, & Johnson (1999) Product Performance Risk Risk related to the functional aspect of the product Festervand, Synder, Tsalikis (1986); Horton (1976); Jacoby & Kaplan (1972); Spence, Engel, Blackwell (1970) Simpson, & Lakner (1993); Fram & Grady (1997); Torkzadeh & Dillion (2002); Forsythe et al. (2006) Psychological Risk Risk related to the dissatisfaction and mental stress caused due to purchase Jacoby and Kaplan (1972) Time loss risk Risk related time-lost in the buying or retaining the product Roselius (1971); McCorkle (1990) Forsythe et al. (2006); Forsythe & Shi (2003) Privacy Security risk Risk related to credit card and personal information being stolen Benassi (1999); Bhatnagar et al. (2000); Miyazaki & Fernandez (2001); Jarvenppa & Todd (1996) Source risk Risk related to the existence of the company Torkzadeh & Dillion (2002) 17 product performance risk may include the complexity of the product (e.g., technical complexity of electronic products), ego-related need of the product (e.g., Cologne), and the price of the product (Bhatnangar, Misra & Rao, 2004). The extent of product performance that is associated with this risk can vary depending on the context. For example, in traditional shopping, some researchers (e.g., Jacoby & Kaplan, 1972) used the term, physical risk to indicate a risk which causes harm to the health of an individual. The physical risk appears to be associated with the product performance risk in that such harm can be caused by the use of a product that does not function properly or has errors that can injure the user, which is an issue of product performance. Furthermore, recently, some researchers (e.g., Forsythe et al., 2006) have also extended the definition of product performance risk by including service performance issues such as shipping delay and shipping and handling payment issues under the umbrella of product performance risk. Product performance risk, however, also may be reduced with experience as the Internet user develops a sense of familiarity with the online shopping process and acquires more information on the products and the online retailer (Bhatnagar & Ghose, 2004). Time Loss Risk. In traditional shopping, Roselius (1971) suggested a risk associated with the loss of time during the purchase and retention of a product. The same time loss concept can be applied to online shopping contexts where consumers who are not familiar with online shopping might need to take time in browsing and navigating through a website (Forsythe & Shi, 2003; Forsythe et al., 2006). The downloading time 18 especially for high-pixel images and the time spent while waiting for the transaction to complete can also cause time loss risk (Forsythe et al., 2006). Psychological Risk. In traditional shopping, Jacoby and Kaplan (1972) defined psychological risk as dissatisfaction or mental stress caused due to the purchase of the product by an individual. The same concept of psychological risk can be applied to the online context assuming that consumers can be frustrated answering all the questions which a website asks before completing a transaction. Such frustration can cause mental stress due to delay in transaction. Mental stress may also be caused by the lack of clear directions on how to place an order while completing a transaction. Although it is feasible that online consumers may perceive some psychological risk when they predict such mental stress in online transactions, little research has addressed this type of risk in the online shopping context, warranting further research. Privacy and Security Risk. Privacy and security risk, which is specific to Internet shopping, arises due to the apprehension of the consumer about revealing his or her personal information online (Bhatnagar et al., 2000). Consumers fear that their personal information disclosed on the Internet might be stolen (Jarvenpaa & Todd, 1996). Apprehension about misuse of personal information can cause reluctance to shop through the Internet (Jarvenpaa & Todd, 1996). Many online retailers who address privacy and security concerns of the consumer are trying to build user friendly and secure websites which can enhance the overall Internet shopping experience of the consumer (Benassi, 1999; Miyazaki & Fernandez, 2001). 19 Source Risk. In previous research with catalog or mail-order shopping, source risk refers to the concern and discomfort consumers experience because they are not sure whether they should trust the catalog or mail-order retailer (McCorkle, 1990). The same concern also exists in the online shopping context. In the era where so many websites launch and close every day, consumers worry whether an online retailer from which they want to purchase a product is trustworthy and reliable (Torkzadeh & Dillion, 2002). Torkzadeh and Dillion (2002) argue that the main way for a retailer to achieve e- commerce success is through trust established in consumers? minds for the retailer. Perceived Benefits The Construct of Perceived Benefits Inherent needs as well as externally inspiring factors experienced by an individual are both considered to motivate his or her behavior (Westbrook & Black, 1985). Perceived benefits are possibly a function of the internal motives of consumers while shopping. Sheth (1983) argued that consumers? motives lead to their perception/evaluation of benefits of shopping, and divided consumer motives into functional versus non-functional motives. Functional (or utilitarian) motives can be related to the utilitarian needs such as convenience of time, place, variety of merchandise, quality of merchandise, and the price of merchandise (Sheth, 1983). Tauber (1972) argued that apart from the functional product needs, consumers? shopping behavior is also motivated by various non-functional needs such as diversion from the regular routine, self satisfaction of shopping, and learning new trends or physical activity. Non-functional (or hedonic) motives can be related to hedonic needs 20 such as social and emotional desires for an enjoyable and interesting shopping experience (Bellenger & Korgaonkar, 1980; Bhatnangar & Ghose, 2004; Eastlick & Feinberg, 1999; Menon & Kahn, 2002). Hedonic benefits of shopping address enjoyment and fun provided by shopping that satisfy these needs, and tend to be subjective and personal. Hedonic benefits do not focus on the task completion but on enjoyment, involvement, and impulsiveness of an individual or the experience (Bloch & Richin, 1983; Hirschman, 1983). Thus, analysis of shopping behavior cannot be completed without considering hedonic benefits obtained by the consumer during the shopping activity in addition to the utilitarian benefits provided by the purchased product (Tauber, 1972). Perceived Benefits of Online Shopping Internet shopping is considered to provide functional benefits since it provides consumers with the convenience of shopping from the comfort of their home at a given time of their choice (Bhatnagar & Gosh, 2004; Eastlick & Feinberg, 1999). Recent research shows the Internet can also provide non-functional or hedonic benefits to consumers by satisfying their emotional needs for enjoyment and providing an interesting shopping experience (Forsythe et al., 2006). However, most consumers have yet to recognize the hedonic benefits offered by Internet shopping (Dholakia & Uusitalo, 2002). Perceived benefits of online shopping are multidimensional and address a combination of utilitarian dimensions such as shopping convenience (Bellenger & Korgaonkar, 1980; Darden &Ashton, 1975; Stephenson & Willett, 1969; Westbrook & Black, 1985), information availability (Menon & Kahn, 1995), and variety (Bellenger & Korgaonkar, 1980; Menon & Kahn, 1995) and hedonic dimensions such as entertainment 21 (Forsythe et al., 2006; Hirschman & Holbrook, 1982; Jarvenpaa & Todd, 1996; Sherry, 1990). These benefit dimensions are examined in more detail next. Shopping Convenience. Many studies have been conducted to understand convenience as a shopping motive for consumers (Bellenger & Korgaonkar, 1980; Darden & Ashton, 1975; Stephenson & Willett, 1969; Torkzadeh & Dillion, 2002). More recently, researchers have suggested convenience due to the time or effort saved during online shopping thanks to the fact that physical location is irrelevant in the online context (Eastlick & Feinberg, 1999; Forsythe et al., 2006; Swaminathan, Lepkowska, & Rao 1999). Online shopping saves the effort of visiting retail stores (Bhatnagar & Ghose, 2004; Forsythe et al., 2006), appealing to consumers who prefer to purchase what they desire quickly without distraction from a salesperson. Internet shopping provides convenience for both consumers who are short of time and consumers who want to shop at their leisure. As Internet shopping allows consumers to quickly select the product and reduce time for payment, it also reduces the time pressure for those who want to shop with leisure. Recently, researchers also have viewed the comfortable and easy way of shopping without waiting for the assistance of the salesperson as a benefit of online shopping (Forsythe et al., 2006). This can lead to no-hassle shopping without any shame for not buying anything and just browsing for products (Forsythe et al., 2006). Information Availability. Online shopping enables the shopper to access a vast amount of information and subsequently empowers the consumer to search, review, and use this information more effortlessly and profoundly as compared to the bricks-and- mortar retail structure (Alba et al., 1997; Lynch & Ariely, 2000). Internet shoppers 22 perceive benefits of obtaining information directly from the website rather than from a salesperson (Van den Poel & Leunis, 1999). Online shoppers also receive more information from the Internet than from a catalog or any other offline channels (Venkatesh, 1998) with lesser amounts of money and effort (Alba et al., 1997; Lynch & Ariely, 2000). Information obtained from the Internet can be used to compare products and make the selection (Hoffman & Novak, 1996). This easy access and the vast amount of information consumers can receive on the Internet for a particular product that they intend to purchase has been one of the major reasons attracting customers to shop online (Swaminathan, Lepkowska, & Roa, 1999; Wolfinbarger & Gilly, 2001). Variety. Due to the boredom of using a single product, consumers often search for variety or novelty (Menon & Kahn, 1995). Search for variety or novelty may be accomplished better in the online setting as consumers have an opportunity to browse through a wide range of products provided by a virtually unlimited number of retailers at a given occasion in which consumers are not able to find elsewhere (Jarvenppa & Todd, 1996). As consumers browse through the wide variety of products on the Internet, they also can obtain competitive prices on merchandise and eye-catching promotional deals (Jarvenppa & Todd, 1996). Online shopping provides consumers with the flexibility to select and evaluate merchandise across stores. The broad selection of products from different brands and retailers with detailed information available may be viewed as a significant benefit of online shopping helping the consumer?s decision-making, which is likely to provide an important motive for online shopping (Forsythe et al., 2006; Menon & Kahn, 1995). 23 Entertainment. The entertainment dimension of benefits addresses online consumers? hedonic motive to seek pleasure and enjoyment by experiencing new things while shopping online (Forsythe et al., 2006). According to Sherry (1990), ?shopping is an adventure? (p. 27). Previously, researchers have discussed the concept of ?shopping adventure? as complete shopping entertainment and enjoyment which can result from playfulness arising but not from accomplishment of any decided end goal from experience (Hirschman & Holbrook, 1982; Sherry, 1990). Higher playfulness associated with adventure shopping behavior of an individual may result in more positive mood and greater shopping satisfaction which may further result in more impulse shopping as compared to the functional or goal focused shopping (Forsythe et al., 2006; Hoffman & Novak, 1996; Jarvenpaa & Todd, 1996). Recently, researchers have developed this construct of entertainment or enjoyment as a part of perceived benefits of shopping online (Forsythe et al., 2006). Shopping Orientation Stone (1954) introduced the concept of shopping orientation, which refers to the consumer?s shopping style while searching for products. Individual consumers? shopping orientation can be demonstrated in their shopping activities, interests, and opinions, reflecting their view of shopping as a complex behavior that may be a personal, economic, and social phenomenon (Darden & Howell, 1987). Jarboe and McDaniel (1987) highlighted that consumers? shopping orientation may refer not only to acquiring goods and services but also to diverse non-purchase motives such as the want for social interaction, diversion from regular routine activities, exercise, and the action of social 24 power (Bellenger & Korgaonkar, 1980). Shopping orientation, therefore, varies across individuals and different products, among individuals over time, and with changing situations (Girard, Korgoankar, & Silverblatt, 2003). For example, researchers such as Shim and Kotsiopulos (1992) and Moye and Kincade (2003) have investigated different shopping orientation dimensions specific to apparel products. Shim and Kotsiopulos (1992) performed cluster analysis on apparel consumers on nine orientation dimensions - confident/appearance (fashion conscious), brand conscious (loyal), convenience/time conscious, shopping mall conscious, local store conscious, apathetic towards ?Made-in- USA?, catalog oriented, economic/price conscious, and credit orientated - which resulted in three different consumer groups. The three groups included highly involved apparel shoppers, apathetic shoppers, and convenience-orientated catalog shoppers, and they differed in their use of resources, significance of store attributes, patronage behavior, lifestyle activities, and demographics. Similarly, Moye and Kincade (2003), in their study of apparel shoppers, adapted Shim and Kotsiopulos?s (1992) components of apparel shopping orientation and reorganized them into six dimensions including confidence, brand consciousness, appearance consciousness, convenience/time, bargain, and decisiveness. A main objective of shopping orientation research has been to examine whether consumers with different shopping orientations show differences in their shopping behavior (Gehrt & Shim, 1998). As stated earlier in the discussion of perceived benefits, consumers with different shopping orientations, motivated by varying needs, may show different levels of sensitivity to diverse benefits provided by a product or service 25 (Forsythe et al., 2006; Hoffman & Novak, 1996). For example, Tauber (1972) explored why people shop and how consumers gain satisfaction from shopping activities and found that a large part of consumers? shopping motives are personal or social, beyond the economic basis. According to Stone (1954), not all consumers shop just for economic reasons, but rather different types of shoppers exist, such as economic shoppers, apathetic shoppers, ethical shoppers, and personalized shoppers. Economic/bargain shoppers are shoppers who are concerned about money, and thus they value the lower prices the large chain store can offer (also see Lumpkin, 1985), while apathetic shoppers are those who are least interested in shopping and have no inclination towards any store. Ethical shoppers are those who prefer to shop at small neighborhood stores, giving a chance for local merchants, whereas personalized shoppers appreciate the personal attention offered by sales associates and thus prefer to shop in a small store where such services can be more easily sought. Therefore, understanding target consumers? shopping orientations and how they are linked to their perceived benefits and risks of different shopping formats or products and attitude towards shopping them is important for marketers in order to provide the right mix of benefits to their target consumers. Different types of shopping orientation can reflect consumers? lifestyles, how they distribute their time and money, and thus how they perceive diverse risks and benefits of online shopping. Some shoppers may be highly price conscious and look for bargains (economic/bargain shoppers), so these consumers may more highly perceive economic benefits of online shopping through the abundance of products and price information provided online. Time orientated shoppers who are busy with household work or office 26 work may want more from the limited time available to them, and thus may value the time/convenience benefit provided by online retailers more than others might. Convenience seeking shoppers may perceive the physical benefits of shopping by sitting in the comfort of the house instead of visiting the store higher than they perceive other benefits. Experiential shoppers may be interested in trying new things with the Internet and thus enjoy the process of searching for new products online more than do other consumers. Recreational shoppers may intend to shop through the Internet largely for fun and entertainment. There have been some attempts to explore the relationship between the online consumer?s shopping orientation and online buying behavior. For example, Kim, Cho, and Rao (2000) examined the effects of price orientation and time orientation on online purchasing behavior, and found that price-orientated consumers perceive fewer risks and greater benefits of online shopping than do time-orientated consumers. Furthermore, Li, Kuo, and Russell (1999) found a significant difference between Web buyers and non- Web buyers in their experiential orientation although they did not differ in price, recreational, and convenience orientations. However, apart from the above few examples, little has been published about the relationships between online consumers? shopping orientation and perceived benefits and risks of online shopping or attitudes towards online purchase, warranting future exploration in this area of research. 27 CHAPTER 3. METHODOLOGY The researcher used a mail survey to collect data to achieve objectives of this study. Instrument Development For this study, a self-administrated questionnaire was developed using scales from previous research. This study was conducted as a part of a bigger project which dealt with older consumers? adoption of Internet shopping. The part of the questionnaire relevant to this study consisted of six sections: 1) shopping orientation, 2) apparel and Internet shopping information, 3) perceived risk, 4) perceived benefits, 5) attitude and purchase intention, and 6) demographics (see Appendix A for the questionnaire). First, the shopping orientation section included 28 questions regarding various dimensions of shopping orientation adapted from Moye and Kincade (2003), Choi and Park (2007), and Seock and Chen-Yu (2006). According to these researchers, the selected items addressed shopping confidence (e.g., ?I think I am a good shopper?), brand consciousness (e.g., ?I like to buy popular brands?), convenience orientation (e.g., ?I usually buy at the most convenient place?), time orientation (e.g., ?I shop from the store which saves time?), economic or price consciousness (e.g., ?I usually like to read advertisements regarding sale or deals?), and apathetic shopper orientation (e.g., ?I don?t like to spend much time shopping?). Each item was accompanied with a five-point Likert scale with 1 for ?strongly disagree? and 5 for ?strongly agree?. 28 Next, general information regarding apparel and Internet shopping related tendencies were collected such as amount spent on clothing for their family or themselves in a year, length of the Internet use, duration of Internet usage, purpose of using the Internet, and amount spent on clothing over the Internet. In the third section, perceived risk associated with online apparel shopping was measured using 19 items culled from existing literature such as Forsythe et al. (2006) and Torkzadeh and Dillion (2002). The items addressed multiple dimensions of perceived risk such as financial risk (e.g, ?I may not get what I want?), product performance risk (e.g., ?I can?t try on clothing?), time/convenience risk (e.g., ?It is difficult to find appropriate website order?), and source risk (e.g., ?I am concerned about the legitimacy of the Internet retailer?). The perceived risk items were again rated on a five-point Likert scale with 1 for ?strongly disagree? and 5 for ?strongly agree?. Twenty-six items addressing respondents? perceptions regarding benefits of online apparel shopping were adapted from existing literature (Forsythe et al., 2006; Ramus & Nielsen, 2005) for the fourth section. According to the literature, shopping convenience (e.g., ?I can shop in privacy of home?), product selections (e.g., ?Items from everywhere are available?), ease/comfort of shopping (e.g., ?I don?t have to be wait to be served?), price/bargains (e.g., ?It is easy to compare prices on the Internet?), and hedonic enjoyment (e.g., ?I can try new experience?) were potential dimensions these items addressed. The perceived benefit items were also accompanied rated on with a five-point Likert scale with 1 for ?strongly disagree? and 5 for ?strongly agree?. In section 5, attitude toward buying clothes through the Internet was measured using a five-point semantic differential scale consisting of three pairs of bipolar 29 descriptors: ?a good-bad idea?, ?pleasant-unpleasant?, and ?beneficial-not beneficial?. These bipolar descriptors were adopted from items used to measure various attitude constructs in the literature (e.g., Anand & Sternthal, 1990; Gill, Gossbart & Laczniak, 1988; Holbrook & Batra, 1987, MacKenzie & Lutz, 1989). In this section, purchase intention of buying clothes through the Internet was also measured using three five-point semantic differential scale items, ?unlikely-likely?, ?improbable-probable?, and ?impossible-possible? along with a uncompleted sentence, ?For me, buying clothes from the Internet in the next 6 months is ___________? (Chattopadhyay & Basu, 1990; Lim, Darley, & Summers, 1994; MacKenzie, Lutz, & Belch, 1986). For both the attitude and intention measures, a higher point indicated a more positive response. In the last section, demographic items such as gender, age, household income, current occupation, occupation before retirement, education, ethnicity, and their primary residence (for e.g., urban, suburban, or rural areas) were included. The demographic items were used to describe the sample characteristics along with the general apparel and Internet shopping information collected in the second section. Data Collection A pilot test of the questionnaire was conducted using a convenience sample of 18 people whose ages fit the target population for this study. They included 15 faculty and staff members in the College of Human Sciences and three employees working in a retail store. Through this pilot test, the readability and redundancy of the questionnaire items were checked. The questionnaire was refined based on the pilot test comments. The main survey was conducted in May through August 2007. The main mail survey procedure was designed according to the guidelines adapted from Dillman (2000). 30 A mailing list of 1000 potential respondents was purchased from a sampling company. This mailing list consisted of names and addresses of people aged 43-80 living in a variety of states in the U.S. Pre-notice postcards were sent to inform the sample that they would soon be receiving a packet consisting of the questionnaire regarding mature consumers? shopping behavior and to solicit their participation. A week after the pre- notice postcards had been sent, the first questionnaire packet was mailed out consisting of a cover letter which contained a brief description of the research and a confidentiality statement, a questionnaire, and a self-addressed stamped return envelope with an ID number. The cover letter also explained that this ID number was used only to differentiate respondents from non-respondents for future mailing purposes. To increase the response rate, non-respondents were mailed a postcard reminder in two weeks from the initial mailing. In addition, another packet of the questionnaire and return envelop was mailed out with a reminder letter to non-respondents two weeks after the postcard reminder had been sent. Data Analysis The data analysis consisted of descriptive statistics, correlation analysis, exploratory factor analysis, and regression analysis. After data cleaning, the researcher first conducted descriptive statistics mainly using frequencies to profile the sample characteristics. Then, exploratory factor analysis using a principal components analysis was executed for perceived risk, perceived benefits, and shopping orientation to check their dimensionality and reduce items. The principal components analysis was conducted using four steps. First, correlation analysis was carried out to examine whether correlations among the items measuring each construct were significant. Non-significant 31 correlations would indicate no relevance of the items with the other items within the construct, and thus the items with non-significant correlations with many of the other items should be deleted from further analysis (Bryman & Cramer, 1999). Second, a principal component analysis was run with items that showed significant correlations with other items for the corresponding construct. Concurring with the other researchers (Forsythe et al., 2006), several different criteria were adapted to determine the appropriate number of components to retain. The different criteria used by the researcher included 1) eigen value, 2) screeplot, and 3) the conceptual meaning of the items. Items finalized for each dimension (component) of the variable were then subjected to reliability tests using Cronbach?s alpha coefficients. Once the components and their items were determined, average scores of the multiple items finalized for each component were calculated for each respondent, so they could be used as variable scores representing the component. Descriptive statistics such as means and standard deviations were calculated for each component. Finally, the hypotheses and research questions were tested by using a series of multiple or simple regression analyses. Perceived risk and benefits have multiple dimensions and attitude towards online purchase has a single dimension. Therefore, multiple regression analyses were performed to test H1 and H2. For H3, a simple regression analysis was done as it had only one independent variable (attitude) and one dependent variable (purchase intention). RQ1(a) and RQ1(b) were tested using a series of multiple regression analyses with shopping orientation components as independent variables and each of the perceived risk and perceived benefits components as a 32 dependent variable. RQ2, which addressed the direct relationship between shopping orientation and attitude, was tested using a multiple regression analysis. To answer RQ3 (the mediation of perceived risk and benefits for the relationship between shopping orientation and attitude), four steps of regressions were planned. First, the relationship between shopping orientation and perceived risk and benefits should be significant (which was examined by RQ1(a) and (b) testing). Then, the relationship between perceived risk and benefits and attitude should be supported (which was examined by H1 and H2 testing). Next, the direct relationship between shopping orientation and attitude should be significant (which was examined by RQ2 testing). Provided the above three relationships being all significant, the last multiple regression would be run using all shopping orientation, perceived risk, and perceived benefit components as independent variables and attitude as a dependent variable. To support the complete mediating effect of perceived risk and benefits between shopping orientation and attitude, this final test should result in a non-significant effect for shopping orientation while perceived risk and benefits should still remain significant in their influence on attitude towards online purchase. Finally, RQ4 (comparison between baby boomers and the previous generation for the proposed relationships) was answered by testing all the hypotheses (H1,H2, and H3) and research questions (RQ1, RQ2, and RQ3) separately for the two groups of respondents. 33 CHAPTER 4. RESULTS Sample A total of 299 respondents returned their completed questionnaires, while 97 questionnaires were returned undeliverable. Among the 299 respondents, six were excluded from data analysis since these respondents reported that they were younger than 43 years. Therefore, overall, 293 usable responses were collected among the 903 who received the questionnaire packet, resulting in a usable response rate of 32.45%. The frequency statistics for each demographic item are presented in Table 4.1. Of 293 respondents, 170 were female and 122 were male. Respondents? ages ranged from 43 to 84 years, with a mean age of 59.4 years and a standard deviation of 10.62. Most respondents were non-Hispanic White (86%), followed by non-Hispanic Black (48%) and Hispanic (2%). About 26.9 percent of the respondents? annual household income ranged between $40,000 to $69,999, followed by $20,000 to $39,999 (23.6%) and greater than $100,000 (15.7%). Twenty nine percent of the respondents were retirees with no part-time job while retirees working part-time are accounted for about 10 percent of the respondents. Respondents who were currently working were mostly working in professional or technical fields (20.1%), followed by machine operators (7.8%), service workers or private household workers (5.5%), clerical worker (5.5%), managers or administrators for the non-farm businesses (5.1%), sales worker (3.1%), craft workers 34 Table 4.1. Demographic Information Characteristics Frequency Percent M SD Gender Female 170 58 Male Missing 122 1 41.6 .3 Age 59.38 10.62 43-50 76 26 51-55 56-61 62-64 65-70 >71 Missing 48 44 14 56 51 4 16.4 15 4.8 19.1 17.5 1.4 Annual Household Income <10,000 $10,000 to $19,999 $20,000 to $39,999 $40,000 to $69,999 $70,000 to $99,999 >100,000 Missing 16 23 69 79 40 46 20 5.5 7.9 23.6 26.9 13.7 15.7 6.8 Current Occupation Retired and no part-time job Retired but working part-time Professional or technical Manager or administrator(nonfarm) Sales worker Clerical worker Craftworker Machine operator/laborer Farmer, farm manager, or farm laborer Service worker or private house hold worker Homemaker Unable to work Other 84 29 59 15 9 16 7 23 6 16 8 12 6 28.7 9.9 20.1 5.1 3.1 5.5 2.4 7.8 2.0 5.5 2.7 4.1 2.0 (Continued) 35 Table 4.1. (Continued) Characteristics Frequency Percent M SD Occupation before Retirement (n =127) Professional or technical Manager or administrator Sales worker Clerical worker Craftworker Machine operator or laborer Farmer, farm manager, or farm laborer Service worker or private household worker Military Homemaker Other 36 14 6 10 10 15 3 13 4 8 8 28.3 11.0 4.7 7.9 7.9 11.8 2.4 10.2 3.1 6.3 6.3 Ethinicity Non-Hispanic White Non-Hispanic Black Hispanic Asian/Pacific Islander American Indian/Alaskan Native Other Missing Residence Urban Suburban Rural Missing 252 14 6 5 3 6 7 33 82 171 7 86 48 2.0 1.7 1.0 2.0 2.4 11.3 28.0 58.4 2.4 (2.4%), and homemakers (2.7%). Most of the respondents (58.4%) for this study were from rural areas, followed by suburban (28%) and urban (11.3%) areas. Thirty seven percent of the respondents said that they had spent less than $500 on clothing for themselves or their families over the past 12 months, followed by $501 36 Table 4.2. General Information Characteristics Frequency Percent M SD Spend on clothing from last 12 months $0 - $500 $501-$1000 $1001-$2000 $2001-$3000 $3001-$4000 $4001-$5000 > $5000 Missing 109 90 53 19 11 5 4 2 37.2 30.9 18.1 6.5 3.8 1.7 1.4 0.7 Internet Use History Never used Less than 6months 6 months to 1 year 1 year to < 2 years 2 years to 4 years Over 4 years 99 12 9 10 38 125 33.8 4.1 3.1 3.4 13.0 42.7 Internet used per week > 1 Hour 1 ? 10 Hours 11 ? 20 Hours 21 ? 30 Hours 31 ? 40 Hours 41 ? 60 Hours Missing 14 109 37 10 3 4 95 4.7 44.5 12.4 3.4 1.0 1.2 32.4 Internet Use Purpose Checking email Searching for information Making reservations for travel Shopping Surfing the Internet for fun Paying bills online Listening to music or watching video clips Playing online video games Making donations to charity online Work/home office Networking/social 180 190 106 116 105 65 47 56 4 4 1 61.4 64.8 36.2 39.6 35.8 22.2 16.0 19.1 1.4 1.4 .3 (Continued) 37 Table 4.2. (Continued) Characteristics Frequency Percent M SD Spend on clothing online in last 12 months None $1 - $100 $101 - $300 $301 - $500 $501 - $1000 $1001 - $1500 $1501 - $2000 $2001 - $2500 Above $2500 184 42 24 19 9 5 3 1 6 67.8 14.3 8.2 6.5 3.1 1.7 1.0 0.3 2.0 -$1000 (30.9%) (see Table 4.2). The $1001-$2000 group accounted for 18.1 percent of the sample. Sixty-six percent of the respondents had Internet use experience, and 42.7 percent had been using the Internet for more than four years. The majority of those who were using the Internet reported that they usually spent less than 10 hours per week on the Internet. Searching for information was the most frequent reason for using the Internet (64.8%), followed by email checking (61.4%), shopping (39.6%), and making reservations for travel (36.2%). On the other hand, 35.8 percent of the respondents said they used the Internet for fun. Nineteen percent of the respondents particularly selected playing online video games, while 16 percent mentioned listening to music and watching video clips as a reason for them to be online, indicating that older consumers are adopting the Internet for various purposes. Among those who said they were using the Internet for shopping, 14.3 percent said they had spent $100 or less on clothing purchases on the Internet in the past year, while 14.7 percent spent $101-500. On the other hand, 5 percent 38 of the online shoppers spent more than $1000 on clothing purchases in the last year on the Internet. Principal Components Analysis Results Principal components analysis was used to determine underlying dimensions and reduce the number of items measuring perceived risk, perceived benefits, and shopping orientation. Perceived Risk Since all the 19 perceived risk items had significant correlations (see Appendix B.1), all the items were retained and subjected to a principal components analysis with varimax rotation. According to the eigenvalues (> 1.0) and the screeplot, it was clear that three components could be extracted. Three items, ?It is difficult to return items which I do not want to keep?, ?I am concerned about how much I can trust the Internet retailer?, and ?I am concerned about legitimacy of the internet retailer?, were deleted as a result of this initial principal components analysis since their component loadings were very similar for all the three components and they were not introducing different concepts than those already addressed by the other items that showed distinctively high loadings for one of the three components. Finally, another principal components analysis was run with the remaining 16 items, which clearly confirmed the three-component model (see Table 4.3). This 16-item, 3-component solution was consistent with Forsythe et al. (2006), exhibiting the construct validity of Forsythe et al.?s scale of perceived risk. Therefore, all the three components were labeled following the labels from Forsythe et al.?s original scale. The first component, Product Risk, consisted of six items with a Cronbach?s alpha of .91. The second component, Financial Risk, consisted of seven items with a Cronbach alpha of 39 Table 4.3. Perceived Risk Principal Components Analysis Results Component Label and Items Component Loading Component1 Component 2 Component 3 Product Risk I can?t try on clothing online I am not able to touch and feel the item I can?t examine the actual product Size may be a problem with buying clothes on the Internet I must pay for shipping and handling I must wait for merchandise to be delivered Cronbach?s alpha = .91 Variance explained = 47.35% .860 .805 .792 .786 .731 .714 Financial Risk I may not get what I want I may not get the product I may purchase something by accident I can?t trust online company My personal information may not be kept My credit card number may not be secure I might be overcharged Cronbach?s alpha = .89 Variance explained = 13.62% .768 .755 .746 .734 .689 .642 .632 Time/Convenience Risk It is difficult to find appropriate websites Pictures take too long to come up It is too complicated to place an order Variance explained = 7.14% Cronbach?s alpha = .88 .829 .793 .760 Items Excluded It is difficult to return items which I do not want to keep I am concerned about how can I trust Internet retailer I am concerned about legitimacy of the Internet retailer 40 .89. The last component, Time/Convenience Risk, consisted of three items with a Cronbach alpha of .88 (see Table 4.3). Respondents? scores on the multi-item average of each perceived risk component ranged between 1 and 5. Product Risk mean was 4.05 (SD = .84). The mean of Financial Risk was 3.24 (SD = .93), while that of Time/Convenience Risk was 2.99 (SD = 1.09). Perceived Benefits From the correlation analysis among the 26 items of perceived benefits, three items, which were reverse-coded, did not show significant correlations with many other items (see Appendix B). The reverse wording seemed to have confused the respondents while reading those questions, and thus these items were eliminated from further analysis to enhance the reliability of the scale. These three items included ?Internet shopping lacks personal service?, ?Internet shopping lacks social dimension in shopping?, and ?There is no physical place to complain?. The remaining 23 items were subjected to a principle components analysis with varimax rotation. The eigenvalue criterion (> 1.0) suggested four components while the screeplot suggested a possibility of five components. Since the eighenvalue and screeplot suggested different component numbers, the third criterion, the conceptual meaning of the items, was examined. From the four-component solution, eight items had similar loadings for all the four components. In addition, there was an item, ?There are no hassles?, which did not share a similar meaning with the other items falling under the same component. Thus, the above nine items were deleted for further analysis since their meanings were not clear, nor did they introduce different concepts than the retained items. Finally, principal components analysis was run again using varimax rotation with the remaining 14 items, which resulted in a final three-component 41 Table 4.4. Perceived Benefits Principal Components Analysis Results Component Labels and Items Component Loading Component 1 Component 2 Component 3 Convenient and Comfortable Shopping I can shop whenever I want I don?t have to leave home I don?t have to wait to be served I can save the effort of visiting stores I don?t have to deal with pushy salespeople on the Internet I can shop in the privacy of my home I can avoid the hassle of driving and parking I wont be embarrassed even if I don?t buy Variance explained = 33.16% Cronbach alpha = .91 .846 .813 .735 .731 .725 .715 .700 .631 Hedonic Enjoyment Internet shopping is good subject of conversation I can buy in impulse in response to ads It?s exciting to receive a package Variance explained = 5.16% Cronbach alpha = .66 .780 .739 .587 Product and Price Offerings Internet shopping is less expensive, providing the best prices I can get a broader selection of products I can find special products not available elsewhere Variance explained = 4.75% Cronbach alpha = .67 .759 .729 .645 (Continued) 42 Table 4.4. (Continued) Component Labels and Items Component Loading Component 1 Component 2 Component 3 Items Excluded Items from everywhere are available Internet shopping makes shopping fun I don?t get any busy signal I can custom-design products I can get good product information online I can try a new experience I can access many brands and retailers There are no hassles It is easy to compare prices on Internet solution (see Table 4.4). The first component, comprised of eight items with Cronbach?s alpha of .91, was labeled as Convenient and Comfortable Shopping since the items with high loadings on this component reflected the ease of Internet shopping at any time and place with no trouble from the salespeople or awkwardness of not purchasing. The second component consisted of three item, with a Cronbach?s alpha of .66, and was labeled as Hedonic Enjoyment which reflected the thrill consumers experience during or after online shopping. The third component consisted of three items, with a Cronbach?s alpha of .67, and was labeled as Product and Price Offerings since the items with high loadings on this component reflected a wide variety of products with best price offering enticing customers to shop through the Internet. This three-component solution for perceived benefits was different to some extent from what the previous researchers (Forsythe et al., 2006; Ramus & Nielsen, 2005) proposed originally. According to Forsythe et al. (2006), perceived benefits consisted of 43 four dimensions: shopping convenience, product selections, ease/comfort of shopping, and hedonic/enjoyment shopping. In addition, according to Ramus and Nielsen, (2005), perceived benefits consisted of seven components: convenience shopping, range of availability of products, information about product, enjoyment/fun of shopping, social aspect of shopping, personal service, price/bargains/costs, and technical systems/ homepage. However, the factor analysis results of the present study revealed that items addressing shopping convenience and ease/comfort of shopping from Forsythe et al. were combined as a single component. In addition, product selections (Forsythe et al., 2006), range of availability of products, information about product, and the bargain shopping (Ramus & Nielsen, 2005) were converted into a single component labeled as Product and Price Offerings. The component multi-item average of all three components ranged from 1 to 5 with a mean of 3.72 (SD = .73) for Convenience and Comfort of Shopping. The mean of Hedonic Enjoyment was 3.27 (SD = .70), while that of Product and Price Offerings was 3.47 (SD = .68). Shopping Orientation The result of correlation analysis showed that all the 28 items of shopping orientation were significantly correlated with each other (see Appendix B), and thus all the items were subjected to a principal components analysis with varimax rotation. The eigenvalues (> 1.0) and the screeplot showed that five components could be extracted. Then the analysis of conceptual meanings of the items showed that five items should be deleted since they demonstrated similar component loadings for all the components and they did not contain different meanings than those addressed by the other items. Finally, 44 another principal component analysis using varimax rotation was run with the remaining 23 items, which produced a clear five-component model (see Table 4.5). The first component of shopping orientation was labeled as Shopping Enjoyment since the nine items with high loadings for this component represented the degree to which consumers seek pleasure in shopping. Shopping Enjoyment items had a Cronbach?s alpha of .90. The second component had four items that addressed the extent to which consumers show concern for money and scout for good deals. Thus, this component was labeled as Price Consciousness. The four items showed a Cronbach alpha of .73. The third component was labeled as Convenience Seeking. This component had three items, with a Cronbach?s alpha of .63, which addressed the level at which consumers seek convenience while they shop online. The fourth component consisted of three items and was labeled as Shopping Confidence as the items showed the level of self-confidence a consumer felt as a good shopper. These items yielded a Cronbach?s alpha of .69. Finally, the last component, labeled as brand orientation, included four items that addressed how much importance consumers place on brands in their shopping and purchase decisions. The Cronbach?s alpha for this component items was .59, which was below .65 recommended for acceptable reliability (George & Mallery, 2003). However, since all four items for this component had component loadings that were above .50, the variance explained for this component was sizable, and the meaning for this component was unique, the researcher decided to retain this component in the scale. 45 Table 4.5. Shopping Orientation Principal Components Analysis Results Component Labels and Items Component Loadings Comp 1 Comp 2 Comp 3 Comp 4 Comp 5 Shopping Enjoyment I enjoy shopping I often like to shop even when I do not need anything For me, shopping is a form of recreation I enjoy spending time browsing Shopping puts me in a good mood I shop quickly as I can get it over with (R) Don?t like to spend much time shopping. (R)There are few things I would enjoy shopping for (R)I do not go shopping until I absolutely have to do it. Variance explained = 62.53% Cronbach?s alpha = .90 .825 .817 .778 .770 .770 .744 .740 .643 .539 Price Consciousness I shop a lot for special deals I can save a lot of money shopping around for bargain I tend to travel to several shopping places to compare prices I pay a lot of attention to prices Variance explained = 10.22% Cronbach?s alpha = .73 Convenience Seeking I put a high value on convenience when shopping I usually buy at most convenient place I shop where it saves time Variance explained = 4.75% Cronbach?s alpha = .63 .712 .693 .668 .663 .755 .709 .675 Note: (R) in front of items indicates that the items were reverse coded 46 (Continued) Table 4.5. (Continued) Component Labels and Items Component Loadings Comp 1 Comp 2 Comp 3 Comp 4 Comp 5 Shopping Confidence I think I?m a good shopper I feel confident in my ability to shop I?m able to choose the right product Variance explained = 2.97% Cronbach?s alpha = .69 .737 .708 .676 Brand Orientation I like to buy popular brand (R) I don?t pay much attention to brand names A well-known brand means good quality I try to stick to certain brands and stores Variance explained = 4.80% Cronbach?s alpha = .59 .823 .725 .572 .541 Items excluded I don?t mind paying high prices for what I like When I find what I like, I usually buy it without hesitation Once I find a brand I like, I stick with it I read or watch advertisements for sale I tend to examine product attributes carefully when making a purchase decision Note: (R) in front of items indicates that the items were reverse coded 47 The shopping orientation dimensions found in this study were similar to the conceptualization of shopping orientation of previous researchers (Choi & Park, 2006; Moye & Kincade, 2002; Seock & Chen-Yu, 2007) who included such dimensions as price consciousness, convenience/time consciousness, and confidence in shopping. However, previous researchers? shopping enjoyment items (Seock & Chen-Yu, 2007; Choi & Park, 2007) and apathetic shopping orientation items (Choi & Park, 2007) were combined to constitute one component (Shopping Enjoyment) in this study, indicating that shopping enjoyment and apathetic shopping orientation may be the opposite ends of a continuum, conceptually. In addition, unlike Seock and Chen-Yu (2007) and Moye and Kincade (2002) who suggested two brand related shopping orientation dimensions (brand consciousness and brand loyalty), this study found these two dimensions were converged into a single component, Brand Orientation. The summated multi-item score average of the first component, Shopping Enjoyment, ranged from 1 to 5 with a mean of 2.82 (SD = .88). Price Consciousness?s multi-item score average ranged from 1 to 5 with a mean 3.50 (SD = .80). The third component, Convenience Seeking, which ranged from 1 to 5, showed a mean of 3.39 (SD = .74). The fourth component, Shopping Confidence, had the mean score 4.12 (SD = .58) with the scores ranging between 1 to 5. Finally, the multi-item score average of the fifth component, Brand Orientation, ranged between 1 to 5 with a mean of 3.13 (SD = .69). Regression Analysis Results For testing the relationships proposed in the hypotheses and research questions, the researcher performed a series of regression analyses to identify the best combination of independent variables explaining variances in the dependent variables. Before 48 conducting the research analyses, the research questions and hypotheses were refined along with the conceptual model using components from each construct as the variable names (see Table 4.6). Table 4.6. Refined Research Questions and Hypotheses H1 Older consumers? perceived risk associated with online shopping negatively predicts their attitude towards purchasing apparel products online. H2 Older consumers? perceived benefits associated with online shopping positively predict their attitude towards purchasing apparel products online. H3 Older consumers? positive attitude towards purchasing apparel products online can lead to online buying intention for apparel products. RQ1(a) Does older consumers? shopping orientation directly explain their perceived (i) product risk, (ii) financial risk, and (iii) time/convenience risk associated with online shopping for apparel products? RQ1(b) Does older consumers? shopping orientation directly explain their perceived benefits related to (i) convenience and comfort of shopping, (ii) hedonic enjoyment, and (iii) price and product offerings provided by shopping online for apparel products? RQ2 Does older consumers? shopping orientation directly explain their attitude towards purchasing apparel product online? RQ3 Is the relationship between older consumers? shopping orientation and attitude towards purchasing apparel products online mediated by their perceptions of risk and benefits of online apparel shopping? RQ4 Are there any differences between baby boomers (43-61 years old) and current older consumers (over 61 years old) with respect to the relationships described in H1 through H3 and RQ1 through RQ3? Analysis for RQ1 through RQ3 and H1 through H3 used the data from the entire sample. First, the stepwise multiple regression analyses for both RQ1(a) - i and ii, which addressed shopping orientation as a direct predictor of perceived Product Risk and 49 Financial Risk, respectively, showed that none of the independent variables (i.e., five dimensions of shopping orientation) had a regression coefficient that was significant (p > .05). Therefore, no direct relationships between shopping orientation and product or financial risk perceptions were observed. RQ1(a)-iii, which explored the direct influence of the five shopping orientation components on Time/Convenience Risk, was tested using a stepwise multiple regression. The regression model that included only Convenience Seeking (?* =.17, p = .01, Adj. R2 = .03) as the independent variable was resulted as the best model (Adj. R2 = .03), whereas the other independent variables (Shopping Enjoyment, Price Conscious, Shopping Confidence, and Brand Orientation) could not meet the criteria for the stepwise entrance. Therefore, partial support for the relationship between shopping orientation and perceived benefits was found due to the significant positive relationship between Convenience Seeking and Time/Convenience Risk. This implies that older consumers who have a greater tendency to seek convenience in their shopping are more likely to perceive time/convenience risk when shopping online for apparel products (see Figure 4.1). The stepwise multiple regression analysis results for RQ1(b)-i, which addressed the five shopping orientation components as direct predictors of the perceived benefit of online apparel shopping as a convenient and comfortable shopping venue, revealed a non-significant result (p > .05). That is, no shopping orientation components were significantly related to perceived benefit of convenience and comfort of online shopping. 50 Attitude Purchase Intention .61*** Convenience Comfort of Shopping Hedonic Enjoyment Product Risk Shopping Enjoyment Price Consciousness Convenience Seeking Shopping Confidence Time/Convenience Risk Financial Risk Product and Price Offerings Brand Orientation Perceived Benefits Perceived Risk Shopping Orientation .13* .17*** .17** .25* .17** * p < .05 ** p < .01 *** p < .001 Figure 4.1. Regression Results for All Respondents - .18** 51 The relationship between shopping orientation and perceived hedonic enjoyment of online apparel shopping, addressed by RQ1(b)-ii, was partially supported (R2 = .04). Two shopping orientation variables - Shopping Enjoyment (?* =.17, p = .01) and Brand Orientation (?* =.13, p = .05) - significantly explained the perceived hedonic enjoyment benefit of online shopping. This result implies that older consumers who tend to seek more enjoyment and place more importance on brands in their shopping are more likely to perceive the potential hedonic pleasure online apparel shopping could provide. The RQ1(b)-iii, which addressed shopping orientation as a direct predictor of perceived benefits of product and price offerings from the Internet, resulted that none of the independent variables (i.e., five dimensions of shopping orientation) had a regression coefficient that was significant (p > .05) in the stepwise regression analysis. Therefore, no direct relationships between shopping orientation and product and price offerings were noticed. Next, the stepwise multiple regression analysis testing the direct influence of shopping orientation on the older consumer?s attitude toward purchasing apparel on the Internet, which was addressed by RQ2, yielded a non-significant result (p > .05). All shopping orientation variables failed to meet the criteria for inclusion in the regression model. To test whether a relationship between shopping orientation and attitude is mediated by perceived risk and benefits (RQ3), first the direct relationship between shopping orientation and attitude should be significant. However, this relationship was revealed to be non-significant (RQ2). Therefore, no further analysis for RQ3 was possible within the scope of this research. 52 The hypothesized direct influence of perceived risk and benefits, respectively, on attitude toward online apparel purchase (H1 & H2), were both partially supported (R2 = .20). Time and Convenience Risk showed a negative influence on attitude (?* = -.18, p = .01), while perceived benefits regarding Hedonic Enjoyment (?* = .17, p = .01) and Price and Product Offerings (?* = .25, p = .05) positively predicted attitude. This result suggests that if the older consumer perceives less risk of losing time or convenience, and more benefits of hedonic enjoyment and price and product offerings about shopping online, he or she is more likely to have a positive attitude toward making apparel purchases online. H3, which predicted older consumers? attitude toward online apparel purchase as a predictor of their intention to purchase apparel products online, was supported (?* = .61, R2 = .37, p < .001). This positive relationship means that the more positive older consumers? attitudes, the more likely they are to purchase apparel products online in the next six months. All the significant regression coefficients from RQ1-RQ2 and H1-H3 testing results are presented in Figure 4.1. Finally, RQ4 was answered by splitting up the sample into two sub-groups - baby boomers (43-61 years old) and elderly respondents (> 61 years old) - and run the regression analyses for RQ1-RQ2 and H1-H3 separately for these two groups. Figures 4.2 and 4.3 show significant regression coefficients for the baby boomer and elderly groups, respectively. As demonstrated in the figures, the positive relationship between attitude and intention of purchasing apparel online was significant consistently for both baby boomers and elderly consumers. However, the other regression analysis results varied greatly between the two groups. For example, for baby boomers, two shopping 53 Attitude Purchase Intention Convenience and Comfort of Shopping Hedonic Enjoyment Product Risk Shopping Enjoyment Price Consciousness Convenience Seeking Shopping Confidence Time/Convenience Risk Financial Risk Product and price Offerings Brand Orientation Perceived Benefits Perceived Risk Shopping Orientation .39*** .18* .20** .18** .19** .20** .20* .62*** .33*** * p < .05 ** p < .01 *** p < .001 Figure 4.2. Regression Results for Baby Boomers (43-61 Years Old) -.25** 54 Attitude Purchase Intention Convenience and Comfort of Shopping Hedonic Enjoyment Product Risk Shopping Enjoyment Price Consciousness Convenience Seeking Shopping Confidence Time/Convenience Risk Financial Risk Product and Price Offerings Brand Orientation Perceived Benefits Perceived Risk Shopping Orientation .21* .39*** .56*** * p < .05 ** p < .01 *** p < .001 Figure 4.3. Regression Results for Elderly Respondents (> 61 Years Old) 55 orientation components (Price Consciousness and Convenience Seeking) positively predicted two perceived risk components (Time/Convenience Risk and Product Risk). On the contrary, there were no significant relationships between the shopping orientation variables and the perceived risk variables for elderly consumer group. Furthermore, the baby boomer group showed significant positive influences of shopping orientation related to Shopping Enjoyment and Brand Orientation on perceptions of Hedonic Enjoyment of online shopping, whereas no such relationships were found from the elderly group. Instead, the elderly group showed a significant positive influence of the Convenience Seeking orientation on perceived benefits of Convenience and Comfortable Shopping on the Internet, which was not significant for the baby boomer participants. In terms of the influence of perceived risk and benefits on attitude toward online purchasing, the only significant independent variable for the elderly group was perceived benefits of Product and Price Offerings. However, for baby boomers, Product Risk and Convenience and Comfort of Shopping significantly influenced their attitude. Moreover, a significant direct relationship between a shopping orientation variable (Shopping Enjoyment) and attitude was also detected for baby boomers, which was not significant for either the elderly group or when the total sample was considered. 56 CHAPTER 5. DISCUSSION Summary This study contributes to the literature by providing insight on the variables that lead to online purchase intention of current and near future older consumers. The older consumer segment, though important, has been less researched in the past in the context of online shopping. Therefore, findings from this study are may offer strategic implications which retailers can use to develop their online services to potentially reduce risks and increase benefits that are specific to this important consumer segment. Findings of this study are summarized below in terms of the multidimensionality of the constructs used in this study and the relationships between them. Multidimensionality of Shopping Orientation, Perceived Risk, and Perceived Benefits The factor analyses revealed the multidimensionality of the shopping orientation, perceived risk, and perceived benefit constructs. First, perceived risk was divided into three components - Product Risk, Financial Risk, and Time/Convenience Risk. The three dimensions of perceived risk associated with online apparel shopping found in this study were consistent with Forsythe et al.?s (2006) conceptualization of perceived risk, confirming the validity and reliability of their scale. Among the three perceived risk dimensions, the mean score for Product Risk was the highest, followed by Financial Risk, and Time/Convenience Risk. 57 On the other hand, some of the dimensions conceptualized in existing perceived benefits scales (Forsythe, et al., 2006; Ramus& Nielsen, 2000) were merged in the present study, resulting in only three components of perceived benefits associated with online apparel shopping ? Convenience and Comfort of Shopping, Hedonic Enjoyment, and Price and Product Offerings. For example, the price and product offering benefits combined a few constructs from existing scales such as price, bargains, and costs from Ramus and Nielsen (2000) and information availability or merchandise variety related constructs from Menon and Kahn (1995) and Bellenger and Korgaonkar (1980), addressing older consumers? perceptions about the availability of a variety of product and price information and offerings on the Internet. The hedonic enjoyment dimension in this study combined the pleasure older consumers may perceive from online shopping (Forsythe, et al., 2006) and some additional aspects such as perceptions regarding how much Internet shopping makes shopping in general fun and how Internet shopping makes a good subject of conversation (Ramus & Nielsen, 2000). According to the component mean scores, the participants rated highest the Convenience and Comfort of Shopping benefit of online shopping, followed by Product and Price Offerings and Hedonic Enjoyment. Finally, the factor analysis revealed five components of Shopping Orientation - Shopping Enjoyment, Price Consciousness, Convenience Seeking, Shopping Confidence, and Brand Orientation. Again, some dimensions of shopping orientation from existing scales (Choi & Park, 2006; Moye & Kincade, 2002; Seock & Chen-Yu, 2007) were combined in this study. For example, a variety of items addressing shopping enjoyment to apathy towards shopping appeared to represent the range of a single construct, 58 shopping enjoyment. Among the five components of shopping orientation, the participants showed the highest rating on shopping confidence, followed by price consciousness, convenience seeking, and brand orientation, which were all above the neutral point (3.0). However, the mean of shopping enjoyment was below the neutral point, rated lowest among the participants. Relationships Between Online Shopping Constructs for Older Consumers For older consumers, support was found for the relationship between their convenience seeking orientation and perceived product risk, and that between their brand orientation and perceived hedonic enjoyment benefit of online apparel shopping. In addition, older consumers? perceived time/convenience risk had a significant influence on their attitude toward purchasing apparel online. Furthermore, the separate analysis for the baby boomer and elderly participants? data revealed differences between these two groups. For example, no relationship was found among shopping orientation variables and perceived risk variables for elderly consumers, whereas the baby boomer group demonstrated significant positive relationships between two shopping orientation dimensions (price consciousness and convenience seeking) and two perceived risk dimensions (product risk and time/convenience risk). On the other hand, the interconnection between shopping orientation and perceived benefits of online shopping was evident in the domain of hedonic shopping for baby boomers, while it was significant in the convenience shopping term for the elderly. That is, while baby boomers? shopping enjoyment and brand orientations were significant positive predictors of their perceptions of hedonic enjoyment benefits for online shopping: for the elderly, their convenience seeking 59 tendency had a positive influence on their perceptions of convenience and comfort benefit of online shopping. In addition, although the relationship between attitude and intention of purchasing apparel online was consistently significant for both baby boomers and the elderly, the predictors of the attitude differed to a great extent. Baby boomers? attitude was explained by their time/convenience risk and convenience and comfort benefit perceptions, while the elderly participants? attitude was significantly determined by only their price and product offering benefit perception. Implications Managerial Implications This research was conducted to understand perceptions of baby boomers and elderly consumers related to risk and benefits associated with online apparel shopping and their influence on attitude and intention of online apparel buying. This study also explored shopping orientation as a potential antecedent of older consumers? perceived risk and benefits of online shopping, and found a few types of orientation that warrant more investigation. The baby boomer group is of great importance to e-tailers since it is perhaps the most affluent generation in US history. Furthermore, this generation is also technology savvy (?Boomers Are the Wealthiest?, 2007). Findings from this study can help online retailers understand perceived risk and benefits of shopping online for apparel products with respect to their perceived risk and benefits. Findings related to shopping orientation suggest these twp grips differ with respect to how they may deal with the perceived risk and benefits of online shopping in forming their attitude and further purchase intention to buy apparel products online. 60 In addition, this study compared elderly consumers with baby boomers in terms of the proposed relationships. Unlike the elderly group who showed few significant relationships among the variables investigated in this study, baby boomers revealed a possibility of becoming major online shoppers. Baby boomers who liked shopping and who cared about brands perceived more positively about the hedonic benefit of online shopping. Besides, shopping enjoyment orientation directly influenced baby boomers? attitude toward online purchasing. On the other hand, baby boomers? convenience seeking and price conscious orientations influenced their product risk, which in turn explained their attitude toward online purchasing. In addition, their perception of convenience and comfort of online shopping significantly influenced their attitude. Therefore, it appears that e-retailers need to promote among baby boomer consumers the hedonic enjoyment from online shopping, the convenience of avoiding pushy salespeople or parking problem, and shopping in privacy, and the time saving aspect of online shopping to encourage their online shopping participation. For example, online retailers might use virtual mannequins to demonstrate a more real visual feel for the garment to enhance hedonic enjoyment. The retailers might expedite the delivery process, charge reasonable shipping and handling fees, and enhance their websites by enabling faster loading of pictures and making it more user-friendly when it comes to placing an order so as to alleviate baby boomer consumers? time/convenience risk. This is because baby boomers who seek convenience and are price conscious seem to believe that shopping online wastes their time while looking for a reliable e-tailer, browsing the retail web site, and waiting for product deliveries. In addition, baby boomers who are brand-conscious seem to perceive more pleasure of 61 online shopping possibly because they know the apparel they are purchasing and thus believe things are less likely to go wrong in terms of the product quality and fitting. Therefore, for e-tailers who target baby boomers, enhancing brand image is an important step to encourage their customers to visit their web site. Implications for Literature The present study is based on the theory of reasoned action (TRA) (Fishbein & Ajzen, 1980) which stated that individuals? attitude towards performing certain behavior is a powerful determinant of their intentions of performing the behavior. This study examined this theory with respect to older consumers? belief, attitude, and purchase intention related to online apparel shopping, and demonstrated the validity of the belief-attitude-behavioral intention link postulated by the theory. In this study, older consumers appeared to form their attitude and behavioral intention towards online purchase through the beliefs they perceive of online shopping. Beliefs about online shopping such as their perceived risk and benefits were found to be significant antecedents of older consumers? (especially baby boomers?) attitude towards purchasing apparel products online, which in turn led to their online purchase intentions for apparel products. Furthermore, the researcher explored shopping orientation as an indirect predictor of older consumers? attitude towards online purchasing, whose impact may be mediated by beliefs such as perceived risk and benefits. In doing so, the researcher expanded the discussion of older consumers? online shopping behavior beyond the TRA framework, and provided a rationale for further investigation of the role of shopping orientation in online consumer behavior. 62 Limitations and Recommendations Listed below are a few of the limitations which need to be taken into consideration in understanding the findings of this study. First, there was a statistical limitation to this study. Each hypothesis and research question was tested separately using linear regression analyses. In doing so, the researcher was unable to examine the structural relationships among the variables or test the fit of the entire model. Therefore, future researchers should use structural equation modeling to test the hypotheses and research questions to understand the structural relationships among the variables. 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I enjoy shopping. 1 2 3 4 5 6. I enjoy spending time browsing. 1 2 3 4 5 7. I don?t like to spend much time shopping. 1 2 3 4 5 8. For me, shopping is a form of recreation. 1 2 3 4 5 Level of Agreement STRONGLY DISAGREE STRONGLY AGREE 4 76 9. I often like to shop even when I do not 1 2 3 4 5 need anything. 10. I shop a lot for special deals. 1 2 3 4 5 11. I pay a lot of attention to prices. 1 2 3 4 5 12. I can save a lot of money shopping around for 1 2 3 4 5 bargains. 13. When I find what I like, I usually buy them 1 2 3 4 5 without hesitation. 14. I don?t mind paying high prices for what I like. 1 2 3 4 5 15. I read or watch advertisements for sales. 1 2 3 4 5 16. I tend to examine product attributes carefully 1 2 3 4 5 when making a purchase decision. 17. I tend to travel several shopping places 1 2 3 4 5 to compare prices. 18. I usually buy at the most convenient place. 1 2 3 4 5 19. I shop where it saves time. 1 2 3 4 5 20. I put a high value on convenience when 1 2 3 4 5 shopping. 21. I feel confident in my ability to shop. 1 2 3 4 5 22. I think I?m a good shopper. 1 2 3 4 5 23. I?m able to choose the right product. 1 2 3 4 5 24. Once I find a brand I like, I stick with it. 1 2 3 4 5 25. I try to stick to certain brands and stores. 1 2 3 4 5 Level of Agreement STRONGLY DISAGREE STRONGLY AGREE 77 26. I shop as quickly as I can to get it over with. 1 2 3 4 5 27. I do not go shopping until I absolutely have 1 2 3 4 5 to do it. 28. There are very few things I would enjoy 1 2 3 4 5 shopping for. Section 2 In this part, we would like to learn about your use of different shopping places. We are also interested in learning how the Internet has been used in your life. Please answer each question below to your best knowledge. 1. Over the last 12 months, approximately how much have you spent on clothing for you and your family? (Check (?) one that best represents your response). ________ $0-$500 ________ $501-$1,000 ________ $1,001-$2,000 ________ $2,001-$3,000 ________ $3,001-$4,000 ________ $4,001-$5,000 ________ ABOVE $5,000 2. Have you used the Internet? ________ YES (if ?Yes?, please go to question 4.) ________ NO (if ?No?, please skip to Part 3). 3. How long have you been using the Internet? ________ LESS THAN 6 MONTHS ________ 6 MONTHS TO 1 YEAR ________ MORE THAN 1 YEAR BUT LESS THAN 2 YEARS ________ 2 YEARS TO 4 YEARS ________ OVER 4 YEARS Level of Agreement Strongly Disagree Strongly Agree 78 4. On average, how many hours do you spend per week using the Internet? _____________ HOURS 6. For what purposes have you used the Internet? Please check (?) all that apply. ________ CHECKING EMAIL ________ SEARCHING FOR INFORMATION ________ BUYING OR MAKING RESERVATION FOR TRAVEL ________ SHOPPING ________ SURFING THE INTERNET FOR FUN ________ PAYING BILLS ONLINE ________ LISTENING TO MUSIC OR WATCHING A VIDEO CLIP ________ PLAYING ONLINE GAMES ________ MAKING A DONATION TO A CHARITY ONLINE ________ WORK HOME/OFFICE ________ NETWORKING / SOCIAL ________ OTHER (Please specify the use _____________________________) 7. Over the last 12 months, approximately how much have you spent on the Internet for clothing purchases? ________ $0-$100 ________ $101-$300 ________ $301-$500 ________ $501-$1,000 ________ $1,001-$1,500 ________ $1,501-$2,000 ________ $2,001-$2,500 ________ Above $2, 500 Section 3 The following set of statements relates to the different risks that consumers may associate with online shopping. Please indicate your level of agreement with each of the statements using the following scale. Please circle the number that best matches your response to each statement. SCALE: STRONGLY DISAGREE DISAGREE NEITHER AGREE NOR DISAGREE AGREE STRONGLY AGREE 1 2 3 4 5 79 Example: Level of Agreement Shopping from the Internet is risky 1 2 3 4 1. I can?t trust the online company. 1 2 3 4 5 2. I may not get the product 1 2 3 4 5 3. I may purchase something by accident 1 2 3 4 5 4. My personal information may not be 1 2 3 4 5 kept. 5. I may not get what I want. 1 2 3 4 5 6. My credit card number may not be 1 2 3 4 5 secure 7. I might be overcharged 1 2 3 4 5 8. I can?t examine the actual product. 1 2 3 4 5 9. I am not able to touch and feel the item 1 2 3 4 5 10. I must pay for shopping and handling 1 2 3 4 5 11. I must wait for merchandise to be 1 2 3 4 5 delivered. 12. Size may be a problem with clothes 1 2 3 4 5 13. I can?t try on clothing online 1 2 3 4 5 14. It is too complicated to place order 1 2 3 4 5 15. It is difficult to find appropriate 1 2 3 4 5 websites 16. Pictures take too long to come up 1 2 3 4 5 5 Strongly Disagree Strongly Agree 80 Level of Agreement 17. I am concerned about the legitimacy 1 2 3 4 5 of the Internet retailer 18. I am concerned about how much I can 1 2 3 4 5 trust the Internet retailer. 19. It is difficult to return items which I do 1 2 3 4 5 not want to keep Section 4 The following set of statements relates to the different benefits consumers seem to associate with using the Internet for shopping. Please indicate your level of agreement with each of the statements using the following scale. Circle the number that best matches your response to each statement. SCALE: STRONGLY DISAGREE DISAGREE NEITHER AGREE NOR DISAGREE AGREE STRONGLY AGREE 1 2 3 4 5 Example: Level of Agreement The Internet provides benefits while shopping 1 2 3 4 5 1. I can shop in privacy of home 1 2 3 4 5 2. I don?t have to leave home 1 2 3 4 5 3. I can shop whenever I want 1 2 3 4 5 4. I can save the effort of visiting stores 1 2 3 4 5 Strongly Disagree Strongly Agree Strongly Disagree Strongly Agree 81 Level of Agreement 5. I can avoid the hassle of driving and 1 2 3 4 5 parking 6. Items from everywhere are available 1 2 3 4 5 7. I can get good product information online 1 2 3 4 5 8. I can get a broader selection of products 1 2 3 4 5 9. I can access many brands and retailers 1 2 3 4 5 10. I can find special products not available 1 2 3 4 5 elsewhere 11. I don?t have to wait to be served 1 2 3 4 5 12. There are no hassles 1 2 3 4 5 13. I won?t be embarrassed even if I don?t buy 1 2 3 4 5 14. I don?t get any busy signal 1 2 3 4 5 15. I don?t have to deal with pushy salesperson 1 2 3 4 5 on the Internet 16. I can try new experience 1 2 3 4 5 17. It?s exciting to receive a package 1 2 3 4 5 18. I can buy in impulse in response to ads 1 2 3 4 5 19. I can custom-design products 1 2 3 4 5 20. Internet shops make shopping fun 1 2 3 4 5 21. Internet shopping is good subject of 1 2 3 4 5 conversation 22. Internet shopping is less expensive providing 1 2 3 4 5 best prices Strongly Disagree Strongly Agree 82 Level of Agreement 23. It is easy to compare prices on Internet 1 2 3 4 5 24. Internet shopping lacks the social dimension 1 2 3 4 5 of shopping 25. Internet shopping lacks personal 1 2 3 4 5 customer service 26. There is no physical place to complain 1 2 3 4 5 Section 5 Now we would like to learn your opinion about buying clothes or groceries on the Internet. Please circle the number that best matches your response to complete each sentence. 1. Buying clothes from the Internet is _____________. Bad 1 2 3 4 5 Good Unpleasant 1 2 3 4 5 Pleasant Unfavorable 1 2 3 4 5 Favorable 2. I ____________ buying clothes from the Internet. dislike 1 2 3 4 5 like 3. For me, buying clothes from the Internet in the next 6 months is ______________. unlikely 1 2 3 4 5 likely improbably 1 2 3 4 5 probably Impossible 1 2 3 4 5 possible Strongly Disagree Strongly Agree 83 Section 6 The following set of questions asks demographic information. Please check the appropriate box or write in a better description. 1. Please select your gender. MALE FEMALE 2. What is your age? _____________ YEARS OLD 3. Which of the following ranges include your total annual household income from all sources before taxes in 2006? Under $5,000 $5,000 to just under $9,999 $10,000 to $14,999 $15,000 to $19,999 $20,000 to $24,999 $25,000 to $29,999 $30,000 to $39,999 $40,000 to $49,999 $50,000 to $59,999 $60,000 to $69,999 $70,000 to $79,999 $80,000 to $99,999 $100,000 to $124,999 $125,000 to $149,999 $150,000 to $199,999 $200,000 to $249,999 $250,000 and over 4. Which of the following best describes your current occupation? ________RETIRED ________RETIRED AND WORKING PART-TIME ________PROFESSIONAL OR TECHNICAL (for example, accountant, artist, computer specialist, dentist, engineer, nurse, physician, scientist, teacher, writer) 84 ________MANAGER OR ADMINISTRATOR (NON-FARM) ________SALES WORKER (for example, bank teller, bookkeeping, office clerk, postal worker, secretary, teacher's aide) ________CRAFTSWORKER (for example, baker, carpenter, electrician, foreman, jeweler, mechanic, plumber, tailor) ________MACHINE OPERATOR OR LABORER (for example, bus driver, conductor, factory worker, truck driver) ________FARMER, FARM MANAGER, OR FARM LABORER ________SERVICE WORKER OR PRIVATE HOUSEHOLD WORKER (for example, barber, bartender, cook, dishwasher, firefighter, nursing aide, police officer, waiter) ________MILITARY ________HOMEMAKER ________STUDENT ________UNABLE TO WORK ________OTHER (PLEASE SPECIFY: _______________________________) 5. If you chose ?RETIRED BUT WORKING PART TIME? for question 4, which of the following best describes your current part time job? (If you did NOT choose ?Retired but working part time?, please skip to question 9.) ________PROFESSIONAL OR TECHNICAL (for example, accountant, artist, computer specialist, dentist, engineer, nurse, physician, scientist, teacher, writer) ________MANAGER OR ADMINISTRATOR (NON-FARM) ________SALES WORKER (for example, bank teller, bookkeeping, office clerk, postal worker, secretary, teacher's aide) ________CRAFTSWORKER (for example, baker, carpenter, electrician, foreman, jeweler, mechanic, plumber, tailor) ________MACHINE OPERATOR OR LABORER (for example, bus driver, conductor, factory worker, truck driveR) ________FARMER, FARM MANAGER, OR FARM LABORER ________SERVICE WORKER OR PRIVATE HOUSEHOLD WORKER (for example, barber, bartender, cook, dishwasher, firefighter, nursing aide, police officer, waiter) ________OTHER (PLEASE SPECIFY: ____________________________________) 6. What group do you consider yourself to be a member of? (Please click on one of the following options.) 1. Non-Hispanic White 2. Non-Hispanic Black 3. Hispanic 85 4. Asian/Pacific Islander 5. American Indian/Alaskan Native 6. Other (please specify _________________________________) 7. Which of the following best describes the location of your primary residence? (Please click on one of the following options.) Urban Suburban Rural 86 APPENDIX B: CORRELATIONS BETWEEN ITEMS 87 Table B.1. Correlations Between Items of Perceived Risk R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 I can't trust the online company (R1) 1.00 I may not get the product (R2) .65** 1.00 I may purchase something by accident (R3) .55** .64** 1.00 My personal information may not be kept (R4) .47** .48** .53** 1.00 I may not get what I want (R5) .52** .61** .68** .58** 1.00 My credit card number may not be secure (R6) .41** .45** .40** .40** .45** 1.00 I might be overcharged (R7) .49** .58** .56** .56** .58** .59** 1.00 I can't examine the actual product (R8) .25** .36** .34** .34** .36** .46** .53** 1.00 I am not able to touch and feel the item (R9) .22** .33** .30** .30** .33** .36** .49** .84** 1.00 I must pay for shipping and handling (R10) .27** .26** .27** .26** .26** .45** .43** .59** .52** 1.00 I must wait for merchandise to be deleivered (R11) .23** .29** .28** .29** .29** .32** .44** .51** .55** .69** 1.00 Size may be a problem buying clothes on the Internet (R12) .17** .28** .30** .28** .28** .36** .38** .62** .58** .56** .56** 1.00 I can't try on clothing online (R13) .14** .19** .18** .19** .19** .31** .32** .60** .65** .59** .62** .78** It is too complicated to place an order (R14) .40** .44** .47** .44** .44** .43** .58** .42** .41** .43** .44** .42** It is difficult to find appropriate website (R15) .46** .50** .50** .50** .50** .41** .53** .41** .40** .38** .48** .38** Picture takes too long to come up (R16) .38** .50** .46** .50** .50** .34** .44** .32** .34* .34** .39** .34** I am concerned about the legitimacy of the Internet retailer (R17) .44** .53** .47** .53** .53** .48** .58** .51** .47* .46** .45** .49** I am concerned about how much I can trust the Internet retailer (R18) .47** .55** .50** .55** .55** .51** .68** .53** .51** .50** .49** .47** It is difficult to return items that I do not want to keep (R19) .37** .46** .43** .46** .46** .46** .52** .49** .42** .51** .50** .49** * p < .05 ** p < .01 *** p < .001 (Continued) 88 Table B.1. (Continued) R13 R14 R15 R16 R17 R18 R19 I can't trust the online company (R1) I may not get the product (R2) I may purchase something by accident (R3) My personal information may not be kept (R4) I may not get what I want (R5) My credit card number may not be secure (R6) I might be overcharged (R7) I can't examine the actual product (R8) I am not able to touch and feel the item (R9) I must pay for shipping and handling (R10) I must wait for merchandise to be delivered (R11) Size may be a problem buying clothes on the Internet (R12) I can't try on clothing online (R13) 1.00 It is too complicated to place an order (R14) .35** 1.00 It is difficult to find appropriate website (R15) .32** .77** 1.00 Picture takes too long to come up (R16) .28** .61** .72** 1.00 I am concerned about the legitimacy of the Internet retailer (R17) .43** .58** .58** .58** 1.00 I am concerned about how much I can trust the Internet retailer (R18) .45* .61** .64** .61** .87** 1.00 It is difficult to return items that I do not want to keep (R19) .44** .53** .54** .44** .53** .59** 1.00 * p < .05 ** p < .01 *** p < .001 89 Table B.2. Correlations Between Items of Perceived Benefits B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 I can shop in the privacy of my home (PB1) 1.00 I can find special products not available elsewhere (PB2) .56* 1.00 Internet shopping makes shopping fun (PB3) .39** .43 1.00 Internet shopping lacks personal customer service (PB4) .05 .02 -.15* 1.00 I don't get any busy signal (PB5) .47** .34** .36** .18** 1.00 I can custom design products (PB6) .31** .33** .35** .09 .39** 1.00 Internet shopping lacks the social dimensional of shopping (PB7) .03 -.06 -.19** .54** .10 -.03 1.00 I don't have to leave home (PB8) .60** .38** .29** .06 .43** .25** .03 1.00 Items form everywhere are available (PB9) .52** .51** .38* .06 .43** .35** -.04 .69** 1.00 I don't have to deal with pushy salespeople on the Internet (PB10) .44** .32** .20** .08 .46** .24** .15* .53** .48** 1.00 I can shop whenever I want (PB11) .57** .31* .25* .06 .48** .23** .07 .67** .55** .58** I can get good product information online (PB12) .36** .38** .37** -.10 .32** .28** -.09 .42** .42** .31** I dont have to wait to be served (PB13) .52** .34** .37** .06 .53** .32** .04 .62** .57** .57** I can try a new experience (PB14) .40** .21** .38** .03 .41** .39** .06 .49** .42** .43** Internet shopping is good subject of conversation (PB15) .24** .17* .47** -.02 .23** .34** .08 .21** .21** .26** There is no physical place to complain (PB16) .05 .04 -.14* .32** .01 .05 .31** .17** .15* .21** I can save the effort of visiting stores (PB17) .56** .36** .24** .08 .38** .23** .04 .56** .49** .48** I can get broader selection of products (PB18) .38** .48* .39** -0.11 .30** .32** -.22** .43** .61** .34** Internet shopping is less expensive, providing the best prices (PB19) .19** .25** .41** -.20** .17** .26** -.25** .16** .31** .09 I can aviod hassle of driving and parking (PB20) .54** .34** .32** -.01 .39** .25** -.02 .63** .58** .47** I can access many brands and retailers (PB21) .54** .42** .43** -.01 .38** .27** -.08 .61** .60** .42** I won't be embarrassed even if I don't buy (PB22) .45** .37** .32** -.09 .33** .13* -.04 .57** .46** .45** I can buy on impulse in response to ads (PB23) .26** .20** .21** -.04 .20** 0.10 .16* .30** .27** .29** There are no hassles (PB24) .23** .17** .31** -.19** .28** .20** -.06 .33** .26** .29** It's exciting to receive a package (PB25) .37** .33** .44** -.09 .39** .27** .04 .38** .34** .34** It is easy to compare prices on the Internet ((PB26) .40** .30** .49** -.15* .39** .36** -.12 .47** .51** .33** * p < .05 ** p < .01 *** p < .001 (Continued) 90 Table B.2. (Continued) B11 B12 B13 B14 B15 B16 B17 I can shop in the privacy of my home (PB1) I can find special products not available elsewhere (PB2) Internet shopping makes shopping fun (PB3) Internet shopping lacks personal customer service (PB4) I don't get any busy signal (PB5) I can custom design my products (PB6) Internet shopping lacks the social dimensional of shopping (PB7) I don't have to leave home (PB8) Items form everywhere are available (PB9) I don't have to deal with pushy salespeople on the Internet (PB10) 1.00 I can shop whenever I want (PB11) .53** 1.00 I can get good product information online (PB12) .67** .59** 1.00 I dont have to wait to be served (PB13) .53** .50** .69** 1.00 I can try a new experience (PB14) .19** .22** .29** .45** 1.00 Internet shopping is good subject of conversation (PB15) .14* .02 .20** .18** .09 1.00 I can save the effort of visiting stores (PB16) .59** .33** .54** .40** .26** .23** 1.00 I can get broader selection of products (PB17) .39** .48** .44** .31** .26** .04 .37** Internet shopping is less expensive, providing the best prices (PB18) .13* .25** .23** .15* .28** -.08 .17** I can aviod hassle of driving and parking (PB19) .56** .28** .46** .38** .21** .06 .62** I can access many brands and retailers (PB20) .66** .50** .60** .53** .23** .08 .57** I won't be embarrassed even if I don't buy (PB22) .50** .35** .53** .44** .27** .19** .51** I can buy on impulse in response to ads (PB23) .20** .16* .27** .34** .40** .09 .32** There are no hassles (PB24) .32** .38** .43** .34** .35** -.03 .35** It's exciting to receive a package (PB25) .33** .32** .41** .38** .42** .08 .35** It is easy to compare prices on the Internet ((PB26) .51** .51** .47** .42** .41** .01 .42** * p < .05 ** p < .01 *** p < .001 (Continued) 91 Table B.2. (Continued) B18 B19 B20 B21 B22 B23 B24 B25 B26 I can shop in the privacy of my home (PB1) I can find special products not available elsewhere (PB2) Internet shopping makes shopping fun (PB3) Internet shopping lacks personal customer service (PB4) I don't get any busy signal (PB5) I can custom design my products (PB6) Internet shopping lacks the social dimensional of shopping (PB7) I don't have to leave home (PB8) Items form everywhere are available (PB9) I don't have to deal with pushy salespeople on the Internet (PB10) I can shop whenever I want (PB11) I can get good product information online (PB12) I dont have to wait to be served (PB13) I can try a new experience (PB14) Internet shopping is good subject of conversation (PB15) I can save the effort of visiting stores (PB16) I can get broader selection of products (PB17) 1.00 Internet shopping is less expensive, providing the best prices (PB18) .48** 1.00 I can aviod hassle of driving and parking (PB19) .44** .26** 1.00 I can access many brands and retailers (PB20) .52** .23** .64** 1.00 I won't be embarrassed even if I don't buy (PB22) .40** .19** .55** .61** 1.00 I can buy on impulse in response to ads (PB23) .25** .26** .35** .33** .37** 1.00 There are no hassles (PB24) .35** .32** .34** .35** .37** .37** 1.00 It's exciting to receive a package (PB25) .43** .29** .40** .41** .38** .38** .44** 1.00 It is easy to compare prices on the Internet ((PB26) .55** .44** .42** .53** .41** .31** .46** .50** 1.00 * p < .05 ** p < .01 *** p < .001 92 Table B.3. Correlations Between Items of Shopping Orientation SO1 SO2 SO3 SO4 SO5 SO6 SO7 SO8 SO9 I feel confident in my ability to shop (SO1) 1.00 I do not go shopping until i absolutely have to do it (SO2) .01 1.00 I like to buy popular brands (SO3) .03 .05 1.00 I dont like to spend much time shopping (SO4) -.17** .38** .07 1.00 I can save a lot of money shopping around for bargains (SO5) .28** .08 .05 .04 1.00 There are very few thing i would enjoy shopping for (SO6) -.13* .41** .02 .44** -.02 1.00 I tend to travel to several shopping places to compare prices (SO7) .17** -.07 .07 -.24** .41** -.15** 1.00 I think i am a good shopper (SO8) .45** -.04 -.06 -.14* .32** -.03 .30** 1.00 I dont pay much attention to brand names (SO9) .07 .06 -.45** .06 .11 .12* .05 .05 1.00 Shopping puts me in a good mood (SO10) .23** -.21** .14* -.47** .23** -.36** .23** .20** .04 I don't mind paying high prices for what I like (SO11) -.04 .05 .19** .02 -.05 .05 -.12* -.09 -.11 I usually buy at the most convenient place (SO12) -.09 .14* .14* .25** -.11 .07 -.27** .14* -.00 A well-kwon brand means good quality (SO13) .09 -.01 .33** -.10 .13* -.07 .14* .09 -.12* For me, shopping is a form of recreation (SO14) .16** -.24** .09 -.52** .22** -.42** .23** .16** -.04 When I find what I like, I usually buy it without hesitation (SO15) -.00 -.11 .15** .04 .02 .03 -.11 -.02 -.08 I shop a lot for special deals (SO16) .34** .00 .07 -.15* .52** -.11 .42** .38** .10 I am able to choose the right product (SO17) .37** .07 .08 .06 .29** .03 .22** .48** .01 Once i find a brand I like, I stick with it (SO18) .04 .03 .14* .10 .09 -.04 .11 .03 -.15* I enjoy shopping (SO19) .25** -.28** .19** -.57** .26** -.35** .22** .29** -.05 I often like to shop even if I do not need anything (SO20) .15* -.34** .11 -.61** .21** -.42** .31** .18** -.04 I read or watch advertisements for sales (SO21) .07 -.17** .09 -.18** .21** -.09 .23** .29** -.07 I shop where it saves time (SO22) .11 .15* .08 .18** .12 .07 -.09 .06 .07 I try to stick to certain brands and stores (SO23) .02 .07 .27** .13* -.00 .07 -.05 .00 -.14* I put a high value on convenience when shopping (SO24) .03 .20** .12 .26** -.00 .15** -15** .01 .02 I shop as quickly as I can to get it over with (SO25) -.14* .40** -.00 .51** -.09 .42** -19** -.22** .09 I enjoy spending time browsing (SO26) .22** -.32** .01 -.54** .21** -.41** .32** .23** -.12 I pay a lot of attention to prices (SO27) .22** .04 -.02 -.11 .30** -.05 .36** .31** .09 I tend to examine product attributes carefully when making a purchase decision (SO28) .19** .06 -.01 .06 .20** -.07 .21** .33** -.02 * p < .05 ** p < .01 *** p < .001 (Continued) 93 Table B.3. (Continued) SO10 SO11 SO12 SO13 SO14 SO15 SO16 SO17 SO18 SO19 I feel confident in my ability to shop (SO1) I do not go shopping until i absolutely have to do it (SO2) I like to buy popular brands (SO3) I dont like to spend much time shopping (SO4) I can save a lot of money shopping around for bargains (SO5) There are very few thing I would enjoy shopping for (SO6) I tend to travel to several shopping places to compare prices (SO7) I think i am a good shopper (SO8) I dont pay much attention to brand names (SO9) Shopping puts me in a good mood (SO10) 1.00 I don't mind paying high prices for what I like (SO11) .06 1.00 I usually buy at the most convenient place (SO12) -.04 .09 1.00 A well-kwon brand means good quality (SO13) .17** .19** .13* 1.00 For me, shopping is a form of recreation (SO14) .64** .06 .01 .30** 1.00 When I find what I like, I usually buy it without hesitation (SO15) .09 .43** .15** .18** .16** 1.00 I shop a lot for special deals (SO16) .25** -.16** -.08 .21** .25** -.04 1.00 I am able to choose the right product (SO17) .11 .09 -.01 .12* .10 .03 .32** 1.00 Once I find a brand I like, I stick with it (SO18) -.00 .13* .10 .19** .04 .20** .09 .16** 1.00 I enjoy shopping (SO19) .72** 09 -.05 24** .67** .13* .32** .18** .08 1.00 I often like to shop even if I do not need anything (SO20) .61** .04 -.17** .23** .69** .09 .31** -.01 .08 .69** I read or watch advertisements for sales (SO21) .26** -.06 .02 .15* .27** .00 .37** .12* -.02 .33** I shop where it saves time (SO22) .02 .04 .30** .11 .00 .09 .17** .29** .17** .09 I try to stick to certain brands and stores (SO23) .00 .13* .22** .27** .01 .22** .06 .09 .33** .00 I put a high value on convenience when shopping (SO24) -.01 .02 .42** .04 -.03 .15** .04 .15** .18** -.01 I shop as quickly as I can to get it over with (SO25) -.48** -.04 .20** -.05 -.44** .02 -.19** -.07 .03 -.57** I enjoy spending time browsing (SO26) .57** -.02 -.13* .12* .58** -.05 .30** .12 -.01 .64** I pay a lot of attention to prices (SO27) .10 -.31** -.07 .10 .17** -.21** .43** .21** .04 .13* I tend to examine product attributes carefully when making a purchase decision (SO28) .03 -.10 .08 .12* .02 -.06 .28** .29** .23** .06 * p < .05 ** p < .01 *** p < .001 (Continued) 94 Table B.3. (Continued) SO20 SO21 SO22 SO23 SO24 SO25 SO26 SO27 SO28 I feel confident in my ability to shop (SO1) I do not go shopping until i absolutely have to do it (SO2) I like to buy popular brands (SO3) I dont like to spend much time shopping (SO4) I can save a lot of money shopping around for bargains (SO5) There are very few thing i would enjoy shopping for (SO6) I tend to travel to several shopping places to compare prices (SO7) I think i am a good shopper (SO8) I dont pay much attention to brand names (SO9) Shopping puts me in a good mood (SO10) I don't mind paying high prices for what I like (SO11) I usually buy at the most convenient place (SO12) A well-kwon brand means good quality (SO13) For me, shopping is a form of recreation (SO14) When I find what I like, I usually buy it without hesitation (SO15) I shop a lot for special deals (SO16) I am able to choose the right product (SO17) Once i find a brand I like, I stick with it (SO18) I enjoy shopping (SO19) I oftem like to shop even if I do not need anything (SO20) 1.00 I read or watch advertisements for sales (SO21) .26** 1.00 I shop where it saves time (SO22) -.11 .15* 1.00 I try to stick to certain brands and stores (SO23) -.10 .13* .22** 1.00 I put a high value on convenience when shopping (SO24) -.13* .06 .39** .29** 1.00 I shop as quickly as I can to get it over with (SO25) -.56** -.22** .12* .22** .27** 1.00 I enjoy spending time browsing (SO26) .66** .26** -.06 -.07 -.12* -.63** 1.00 I pay a lot of attention to prices (SO27) .14* .23** .08 -.00 -.08 -.06 .25** 1.00 I tend to examine product attributes carefully when making a purchase decision (SO28) .01 .16** .19** .09 .09 -.05 .19** .42** 1.00 * p < .05 ** p < .01 *** p < .001 95 Table B.4. Correlations among Component Scores (All Respondents) ShO1 ShO2 ShO3 ShO4 ShO5 PR1 PR2 PR3 PB1 PB2 PB3 ATT PI Shopping Enjoyment (ShO1) 1.00 Price Consciousness (ShO2) .29** 1.00 Convenience Seeking (ShO3) -.18** -.08 1.00 Shopping Confidence (ShO4) .39** .45** .08 1.00 Brand Orientation (ShO5) .26** .04 .20** .27** 1.00 Product Risk (PR1) .03 .11 .09 .02 -.03 1.00 Financial Risk (PR2) -.05 .06 .06 .02 .03 .52* 1.00 Time/ Convenience Risk (PR3) .03 .08 .17** -.00 .11 .52** .64** 1.00 Convenience/Comfort shopping (PB1) -.02 -.01 .08 .05 .04 .19* -.04 -.14* 1.00 Hedonic Enjoyment (PB2) .15* .06 .07 .10 .12 .11 -.00 -.02 .66** 1.00 Price Product Offering (PB3) .04 .06 .07 .08 .03 -.03 -.18** -.22** .68** .65** 1.00 Apparel Attitude (ATT) .07 -.05 .02 -.07 .05 - .16** -.20** -.25** .34** .34** .40** 1.00 Purchase Intention (PI) .09 .02 .04 .01 .06 - .17** -.30** -.33** .33** .27** .38** .61** 1.00 * p < .05 ** p < .01 *** p < .001 96 Table B.5. Correlations among Component Scores (Baby Boomers: 43-61 Years Old) ShO1 ShO2 ShO3 ShO4 ShO5 PR1 PR2 PR3 PB1 PB2 PB3 ATT PI Shopping Enjoyment (ShO1) 1.00 Price Consciousness (ShO2) .27** 1.00 Convenience Seeking (ShO3) -.09 -.24** 1.00 Shopping Confidence (ShO4) .44** .49** -.09 1.00 Brand Orientation (ShO5) .31** -.09 .12 .29** 1.00 Product Risk (PR1) .04 .16* .14 -.03 -.01 1.00 Financial Risk (PR2) -.06 .09 .15 .00 -.01 .42* 1.00 Time/ Convenience Risk (PR3) .04 .10 .29** -.01 .01 .43* .57** 1.00 Convenience/Comfort shopping (PB1) .02 -.00 -.05 -.04 .08 -.02 -.22** -.33* 1.00 Hedonic Enjoyment (PB2) .13 .06 .10 .08 .14 -.08 -.13 -.11 .60** 1.00 Price Product Offering (PB3) .09 .00 .03 .07 .07 -.21* -.29* -.30 .70 .61* 1.00 Apparel Attitude (ATT) .14 -.04 -.04 -.05 .05 -.25* -.26** -.30 .41* .36** .39** 1.00 Purchase Intention (PI) .19* -.00 -.06 .03 .12 -.17* -.40 -.33** .38** .32* .38* .64** 1.00 * p < .05 ** p < .01 *** p < .001 97 Table B.6. Correlations among Component Scores (Elderly Consumers: >61 Years Old) ShO1 ShO2 ShO3 ShO4 ShO5 PR1 PR2 PR3 PB1 PB2 PB3 ATT PI Shopping Enjoyment (ShO1) 1.00 Price Consciousness (ShO2) .40** 1.00 Convenience Seeking (ShO3) -.19 .09 1.00 Shopping Confidence (ShO4) .40 .39** .26** 1.00 Brand Orientation (ShO5) .43** .30 .21 .31** 1.00 Product Risk (PR1) .03 .04 03 .08 -.1 1.00 Financial Risk (PR2) -.02 .04 -.05 .05 .05 .64** 1.00 Time/ Convenience Risk (PR3) .04 .14 .06 .03 .16 .68** .73* 1.00 Convenience/Comfort shopping (PB1) -.03 -.09 .21* .18 .08 .41* .22 .19 1.00 Hedonic Enjoyment (PB2) .22 .02 .02 .12 .07 .30 .16 .14 .72** 1.00 Price Product Offering (PB3) .01 .03 .06 .08 -.02 .10 -.03 -.02 .61** .70** 1.00 Apparel Attitude (ATT) -.02 -.11 .07 -.12 .00 -.09 -.11 -.15 .21* .31** .38** 1.00 Purchase Intention (PI) -.14 -.012 .18 -.06 -.02 -.23 -.17 -.28** .17 .18 .31** .56** 1.00 * p < .05 ** p < .01 *** p < .001