The fundamental reasons of e-consumersõ loyalty to an online store

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1 Electronic Commerce Research and Applications 5 (2006) The fundamental reasons of e-consumersõ loyalty to an online store Dong-Mo Koo * School of Management, Kyungpook National University 1,370 Sankyuk-Dong, Buk-Gu, Daegu , Republic of Korea Received 13 June 2005; received in revised form 12 September 2005; accepted 18 October 2005 Available online 2 November 2005 Abstract Previous studies of online stores have concentrated on identifying various attribute and benefit dimensions important to customers and neglected delving into underlying motives of customers engaging in shopping online. The current study identified personal values as underlying motivations, which have received less attention but carry important meanings in explaining customersõ loyal behavior. From the perspective of means-end chain theory, a hierarchical cognitive structural model consisting of personal values, attribute evaluations, and loyal behavior has been proposed. 353 questionnaire data were collected from the experienced online shoppers in South Korea and put into structural equation model to investigate the hierarchical effects of personal values, evaluations of online store attributes, and loyalty. The results show that three customersõ values such as matured society, happiness, and esteem life are the underlying beliefs motivating and/or deterring customers to shop online. But their impacts were diverse. Even though esteem life value had a positive effect on attribute evaluations, values for matured life and happiness had negative influences on loyalty. In addition, the results also demonstrated that customersõ favorable evaluation of product assortment eventually guides customers to be loyal to an online store. Ó 2005 Elsevier B.V. All rights reserved. Keywords: Consumer behavior; Online shopping; Personal values; Means-end chain theory; Store loyalty 1. Introduction Consumer-based research orientation such as delving into relevant consumersõ underlying beliefs and subsequent loyal behaviors will enhance the efficiency of identifying and developing system requirements and new business models of online shopping stores. This orientation has been neglected in the previous studies of e-customersõ online shopping. Early researchers have noticed the great potential contribution of electronic commerce in business performance and attempted to identify factors related to the success of online shopping stores. These studies focused only on identifying important online store attributes and their psychometric properties [39,40,65,45,56]. The identified factors include system quality, information quality, on-time delivery, sale services, and external factors such as individual and organizational characteristics [8,56]. And recent research has focused on delving into the various * Tel.: ; fax : addresses: unlimited@knu.ac.kr, pearlkoo@chol.com. motives of individualõs engaging in shopping online and these higher level constructs include emotions and shopping benefits related to purchasing goods and services online or offline [24,49,55,9,43,60]. These studies added to our understanding on what online store attributes and benefits consumers consider important in choosing an online store and how managers can build and maintain associations of online stores in establishing attribute- or benefitbased positioning strategy. However, earlier investigations could not explicitly explain the fundamental reasons why these online store associations, i.e., online store attributes, are considered to be important, and subsequently used by customers in choosing online stores. Several studies in the context of off-line retailing have attempted to partially apply personal values as underlying motives which explain the reasons behind customersõ purchase behavior [61,18,6,35]. The current study attempts to give deeper insights into the fundamental reasons behind the customersõ online shopping behaviors. Accordingly, the current study approaches from the perspective of means-end chain theory, and attempts to /$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi: /j.elerap

2 118 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) introduce personal values as underlying motivations of an individual to evaluate online store features, which in turn foster customersõ loyalty to an online store. The current study approaches from the perspective of e- consumers and intends: (1) to introduce personal values as underlying beliefs to explain why customers positively or negatively evaluate certain online store attributes over others, and (2) in turn which online store attributes are important and relevant in explaining customersõ online store loyalty. The following sections provide the literature review on a means-end chain theory as a research framework and on concepts including personal values, online store attributes, loyalty, and their hypothesized relationships among themselves. The empirical tests of hypotheses and discussion of the results will follow. And the current study will conclude by addressing theoretical and managerial implications. 2. The conceptual model A theoretical model presented in Fig. 2 is proposed based on a framework of means-end chain theory, into which piecemeal studies on the relationships between personal values, online store attributes, and behavioral measures have been integrated [35,57,18]. The means-end chain theory assumes that beliefs, a link, or an association between two cognitions, form belief systems in human memory, and that such systems are hierarchical [20,21, p. 210]. A means-end chain is a chain of beliefs, where cognitions with an increasing degree of abstraction are linked to each other. These chains are used to describe consumersõ perceptions of objects and behaviors. The generic meansend chain consists of personal values, consequences, and attributes. The higher level of a means-end hierarchy contains abstract self knowledge about the consumerõs life goals and values, and the lower level carries relatively concrete knowledge about product/service attributes and their functional, psychological, and social consequences. Personal values are enduring motivations and desired endstates of existence. Terminal values proposed by Rokeach are related to preferred end states such as socialization, happiness, and security [54]. Consequences are benefits that a consumer can gain by consuming a product with certain attributes. Attributes are features or aspects of products or services. They can be physical, such as color, or abstract such as quality. An illustrative example is given as in Fig. 1, along with the core components of means-end chain hierarchy. A consumer in this example may choose a bottle of beer, i.e., Miller Lights, which carries characteristics such as less alcohol and filling (attributes) because this beer gives him/her benefits of avoiding getting drunk and having more time to socialize (consequences). These benefits are considered to be important to this consumer because he/ she considers sense of belonging as one of life goals (personal values). In this example, less alcoholic contents (attributes) and subsequent benefits of socialization are means, and personal value for sense of belonging is the end that this consumer pursues in life. The means-end chain theory explains that personal values of this consumer guide his/her evaluations of relevant attributes and their benefits of a product or service, and then these evaluations initiate goal-direct purchase behavior. However, benefit dimensions are not included in the present study because they represent higher level concepts such as ease of use and usefulness in the context of online shopping. The current study A means-end chain hierarchy End (Life Goals) Means (Attributes and Benefits) Purchasing Behavior An illustrative means-end chain hierarchy Personal Values pursued in life Benefits gained from consuming Miller Lights Attributes Miller Lights carries Buying a bottle of Miller Lights Components Sense of belonging as one of life goals More time to socialize Avoiding getting drunk Less alcohol Less filling Buying Behavior Fig. 1. An illustration of means-end chain model.

3 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) focuses on more basic features an online store carries. Accordingly, it is proposed in the current model that personal values represent the end that a consumer pursues as goals in life, and various online store attributes represent the means that he/she adopts to accomplish the goals when he/she buys goods and services online. More specifically, the research model shown in Fig. 2 postulates a hierarchical cognitive structural model consisting of personal values, online store attribute evaluations, and loyal behavior [6, p. 665]. Personal values are hypothesized to be the end that a consumer pursues in life and the underlying beliefs of customers, which can explain why these customers select certain online store attributes [59, p. 1069; 61,18,6]. Personal values are suggested to be the guiding principles of an individual shopper to evaluate various attributes of an online store. And the evaluations of various online store attributes are hypothesized to represent consumersõ means to achieve their desired end-states and eventually become the basis for selecting a specific online store [57]. These proposed hierarchical relationships are called top down route of information processing [6, p. 666] and were proved to be useful in explaining individual differences in underlying motivations of certain behaviors [21]. A study of [61] investigated the relationships between each items contained in the measures of personal values and mall visits. This study empirically showed that personal values can be predictors of mall visiting behavior. Another study of [18] empirically showed the direct and positive relationships between personal values and evaluations of store attributes. Two studies of [6,57] investigated the inter-relationships among personal values, attribute evaluations, and behavioral measures in an integrated perspective. For example, Brunso et al. [6], adopted a means-end chain theory and empirically proved the sequential effects of terminal values on lifestyle and then situation-specific product perceptions and behaviors. Shim and Eastlick [57] investigated the effects of personal values on aggregate measure of attributes and mall visits. These previous studies pose a research need to investigate the full pattern of relationships between personal values, attribute evaluations, and behavior. For example, [61] showed that there exist direct relationships between personal values and attribute evaluations. Additionally, [57] showed that personal values could be predictors of shopping behavior. However, these studies failed to show that which personal values are related with which attribute dimensions. Accordingly, the first agenda of the present study is raised in order to investigate the in-depth relationships among personal values and attribute evaluations: which constructs of personal values are related with which online store attributes. Meanwhile, [6,57] showed that customersõ attribute evaluations can be predictors of product purchase and/or mall visiting behavior. But they did not prove that what specific attributes are antecedents of behavioral measure. Therefore, the second research agenda is proposed to investigate the direct relationships between consumersõ evaluation of various online store attributes and loyalty. More detailed discussions on each agenda are shown in the literature review. 3. Literature review 3.1. Personal values Personal values are abstract goals or enduring motivational concerns [50]. Rokeach [54] identified two different kinds of values, instrumental and terminal values. Instrumental values represent general beliefs concerning desirable modes of conduct, whereas terminal values represent enduring beliefs concerning desirable end-states of existence. According to [54, p. 159], values are determinants End States of Existence Means (Online Store Attributes ) Behavior Personal Values Matured Society Safe World Happiness Esteem Life Online Store Associations Web Site Design Visual Appeal Hyperlinks Product Assortment Information Security Feature After-sale Services Online Store Loyalty Store Commitment + Re-patronage Intention Fig. 2. A hierarchical model of values-attributes-loyalty to an online store.

4 120 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) of attitudes and behavior that are substantially or logically related to them. Values are standards that guide and determine actions, attitudes toward objects, evaluations, comparisons of self with others, and attempt to influence others. The current study focuses on terminal values based on a suggestion that, even if instrumental values are related, terminal values are disproportionately predominant in predicting the importance of store attributes [18, p. 143]. Terminal values have been proven to be related with various consumer behaviors both directly and indirectly. In terms of relationships, [58,22,11,16] report that personal values are linked to various consumer behaviors. For example, [58] show that three global values have direct relationships with political behavior. However, [25,66, 41,62] empirically proved that values exert indirect impacts on behavior mediated by choice criteria, beliefs, perceived consequences of recycling, attitudes, and personal norms. An indirect relationship between personal values and behavioral measures is more generally accepted in the literature [41]. In addition, the means-end chain theory assumes that personal values could be end goals that a consumer pursues in his life. The theory implies that these end goals are principles and guidelines and directing customersõ evaluations of which attributes (means) are more relevant to achieve these end goals Online store associations Martineau defines store image as the way in which a store is defined in consumerõs mind, partly by its functional qualities and partly by an aura of psychological attributes [44]. More specifically, store associations are defined as beliefs a consumer holds for a certain store, and associations consist of concrete attributes, benefit values, and the overall attitude [29]. According to Chang et al. [7], who investigated 45 online shopping research published between 1986 and 2003, it is suggested that (1) although many antecedents of the adoption of online shopping have been investigated, most have only been studied once, (2) those that have been studied more showed their inconclusive impact, and (3) most studies have included variables on an ad hoc basis. Most of early studies linked to technology acceptance and innovation diffusion theory have delved into utilitarian dimensions such as ease of use, usefulness/relative advantage, and compatibility affecting usersõ acceptance of technology [15,52,63]. But these benefit dimensions are excluded from this study, because they represent higher level dimensions [31,7]. The current study focuses more on fundamental characteristics of online stores. The marketing theory proposes five stages of product purchase: need recognition, information search, evaluations of alternatives, purchase, and post purchase evaluation [37, pp ]. However, customer-oriented transaction process of shopping online consists of three major stages; information search, product ordering, and after sale services [1,67,51]. Previous online shopping studies lead us to following dimensions deemed to be important in customersõ selecting an online store to shop [40,65,56,45]. Important characteristics include online store atmospheric cues such as design and visual appeal, purchase-related services such as well-structured hyperlinks, information quality, product assortment, security, and after-sale services such as fast delivery, exchange, and return services. Based on previous studies [43,31,7], these seven different online store characteristics are selected as relevant dimensions in the current study. During search stage, visually attractive design and well organized web structure are considered as important attributes. Atmosphere in retail setting is defined as the intentional control and structuring of environmental cues [64, p. 193]. Atmosphere is generally conceptualized as three dimensional (social, design, and ambient factors in [19]) or five dimensional (external, interior, layout/design, people, and POP/decoration variables in [64]) concepts. Eroglo et al. [19] defined online store atmosphere as the sum of all the cues that are visible and audible to the online shopper, lacking sensory appeals derived from touch, smell, and taste. Mathwick et al. [43], Muylle and Despontin [45], and Kim and Steol [31] limit website atmosphere as visual appeal which include websiteõs display attractiveness, aesthetic appeal, and general looking. In the current study, online store atmospheric cues are constrained to visual components and reflect two dimensions: web site design and visual appeal [9]. During ordering stage, customers perceive product assortment, information quality, and security as more important. Well-structured hyperlinks not just represent web-atmospherics, but also facilitate information search, order processes, and eventually save customersõ online shopping time. Additionally, easier navigation makes customers less price sensitive and purchase more expensive products [9]. Product assortment refers to the variety and a range of goods available from an online store [1]. Customers are more likely to visit an online store with varied high quality merchandise. And product information is referred to providing relevant information on the variety and features of products carried by an online store. Product information should be accurate, current, complete, timely, and understandable. Product information is likely to help customers compare shopping products, enhance shopping experience, take better purchase choices [1]. Perceived security, defined as an individualõs perception about his ability to control personal information about himself when logged onto an online shopping store [51], is also considered important in online shopping acceptance. Online stores use a number of mechanisms to gather information about their visitors: registration forms, web survey, and cookie files. Customers express their concerns over potential misuse of personal information [51,48]. So it is imperative for an online store to provide secured system and display privacy policy. When product ordering is completed, perceptions on after sale services such as safe packaging, fast delivery, and return/exchange services become more important

5 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) under online shopping environment. Reliable and timely delivery of products in safe package is one of the fundamental objectives of online shoppers, unlike offline retail shopping. Online shoppers make their orders at their office or home anticipating quicker, timely, and safe delivery on convenient time of choice. Return and exchange services are important if customers change their mind after delivery, or delivered product is damaged [36]. All these studies show that various attributes such as web site design, visual appeal, hyperlinks, product assortment, information, security, and after sale services form online store associations and are important in predicting customersõ purchase behavior. In an empirical study, Erdem et al. [18] show more direct relationships between personal values and various store attributes. Utilizing canonical correlations, they empirically prove that personal values such as personal gratification, social responsibility, and security are valid predictors of such store attribute dimensions as store status, merchandise, and price perceptions. Shim and Eastlick [57] and Homer and Kahle [26] showed that an individualõs values such as self-actualization and social affiliation have positive influences on an aggregate measure of attributes. These two studies consistently propose positive relationships between personal values and attribute evaluation. In addition, we saw in the previous section that indirect relationships between personal values and behavioral measures are more generally accepted, and that the means-end chain theory considers personal values as end goals and these end goals are principles and guidelines directing customersõ evaluations of which attributes (means) are more relevant to achieve these end goals. Accordingly, the current study postulates an agenda that personal values are positively associated with an individual customerõs evaluations of various online store attributes. To be precise, our interests are focused on which personal value dimensions are positively associated with which online store attribute dimensions. H1. Personal values are positively linked to an individual customerõs evaluations of web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale services Online store loyalty The generation of committed repeat purchasers has been a primary objective of marketers for decades because retaining customers requires less marketing resources than recruiting new ones [33]. Store loyalty has evolved from brand loyalty with respect to tangible goods [13]. Cunningham was the first to extend brand loyalty into store loyalty using the same measures [14]. A literature review by [27], indicates that much of initial research emphasizes the behavioral aspect of loyalty: exclusive purchase, two-thirds criterion, and three-in-a-row criterion. However, later studies stress the attitudinal measurement of psychological commitment, in which loyalty is assessed on the basis of responses to the statement of asking the favorite brand name regardless of price [33, pp ]. It is currently accepted that loyalty consists of two dimensions: both attitudinal and behavioral loyalties. The behavioral loyalty focuses on a measure of proportion of purchase of a specific brand, while attitudinal loyalty dimension is measured by psychological commitment to the target object [12, p. 813]. According to [5], when there is no store commitment in a consumerõs repeat visiting or buying behavior, the consumer becomes spuriously loyal, or a consumers with inertia repeat visiting behavior. Knox and Denison [34] defines store loyalty as the consumerõs inclination to patronize a given store or chain of stores over time (p. 34). Knox and Walker [33] similarly conceptualized brand loyalty with two measures; brand support index (a measure of brand buying behavior) and brand commitment. All these definitions suggest that a consumerõs commitment is a necessary condition for store loyalty to occur [5, p. 500]. Store loyalty in the current study can be defined as the biased behavioral re-patronage intention, expressed over time, of a customer with respect to an online store out of a set of online stores, which is a function of psychological decision-making and evaluative processes resulting in store commitment [27,33]. Loyalty has been used as a measure of consequences of strong brand associations and store attributes [46,29]. In terms of relationships between online store attributes and store loyalty, the results of previous studies have been mixed. In one situation, certain attributes are considered as important, but not if the situation changes. For example, Michon et al. [68], in traditional retail setting, empirically prove that ambient factor has a positive effect on product quality only at the medium retail density level. Wolfinbarger and Gilly [67] show in an empirical study that website design has a positive impact on loyalty intention. In case of product assortment, Elliot and Fowell [17] and Rohm and Swaminathan [53] show that product variety has a positive impact on internet purchase behavior. While Rohm and Swaminathan [53], Ahn et al. [1], Shih [56] and Ranganathan and Ganapathy [51] show that product information has positive relationships with online purchase, Shih [56] attests that perceived information quality does not adequately predict services purchase online (p. 361). Ranganathan and Ganapathy [51], Belanger and Kasper [3], and Elliot and Fowell [17] found that security and privacy are the most important predictors of intention to shopping online. But Wolfinbarger and Gilly [67] imply that privacy/security has no effect on loyalty intention and satisfaction. Shih [56], Ahn et al. [1], Koyuncu and Bhattacharya [32], Liang and Lai [36], Elliot and Fowell [17] show that fast and safe delivery, return, and exchange services generally increase customersõ buying online. These inconsistent results may be attributed to situational factors such as differences in consumer perceptions in different cultural contexts, or differences in products purchased. However, general maxim in the previous studies

6 122 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) asserts that various store attributes elevate and enhance customersõ emotions and purchase behavior [44,38,2,47]. In addition, the means-end theory implies that consumersõ evaluations of store attributes are means to achieve their life goals and therefore initiate goal directed behavior. In other words, individual customerõs evaluations of attributes initiate goal-directed behavior in the context of shopping online. Accordingly, the second agenda is proposed that online store attributes are positively and directly linked to customer loyalty. This agenda focuses attention to which online store attribute dimensions are valid predictors of customer loyalty. H2. CustomersÕ favorable perceptions on web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale services are positively associated with online store loyalty. 4. Methodology and data analysis 4.1. Measurements Most items indicating personal values, online store attributes, and store loyalty were drawn from the previous literature, which renders more convincing content validity of the measures. 7-point Likert scales are adopted to measure the concepts. The 1 7 Likert type scales for measuring personal values were anchored for 1 not very important and for 7 very important. Other scales for measuring store attributes and other concepts were anchored for 1 strongly disagree and for 7 strongly agree. The items contained in the questionnaire were validated in a pilot test. The questionnaire used in the current study contained 18 items measuring terminal values, 25 items measuring online store associations, 2 items measuring commitment, and 4 items measuring re-patronage intention, and the remaining items measured respondentsõ online buying behaviors and demographics. Among them, 3 items each in the personal values and store associations, 1 item in the re-patronage intention scales were screened out during exploratory and confirmatory factor analyses. Eighteen terminal values are adopted directly from the Rokeach value inventory [62], because [18] have suggested that terminal values are disproportionately predominant in predicting the importance of store attributes (p. 143). Terminal values are defined as enduring beliefs concerning desirable end-states of existence. 15 items are found in Table 2 and the three items deleted were national security, comfortable life, and salvation. Online store associations are conceptualized as multidimensional concepts that a consumer perceives to be present in an online store, which can be physical or abstract [38, 10, p. 456]. Seven different attribute dimensions are identified. Atmospheric dimensions capture web site design and visual appeal, and adopted from [45,31]. Order-related characteristics reflect features such as hyperlink connotations adopted from [45,31], information quality from [1,56], product assortment from [1], perceived security from [67,51]. After-sale services dimension includes safe packaging, fast delivery, return, and exchange services and adopted from [36,1,40]. The individual measurement items contained in the online store attributes are found in Table 3. Online store loyalty has been defined as customersõ online store commitment in a consumerõs biased re-patronage intention and conceptualized with these two concepts. The 4-item intention to re-patronize to an online store are adopted from [42, p. 496], and store commitment, defined as the pledging or binding of an individual to his/her store choice [4], measures with two-item scales from [27, p. 80]. The specific items measuring online store commitment and re-patronage intention are found in Table 4. The average scores for each construct were put into as two separate scales measuring online store loyalty, consistent with the definition of [5]. Previous studies suggested that a consumerõs commitment is a necessary condition for loyalty to occur [5, p. 500] Characteristics of sample population As of April 2004, US billion dollars were traded online, accounting for about 16.7% of total trade volume in Korea. At the same time, there were 3242 online stores in Korea, a 37.1% increase compare to the figure of previous year. Among them, about US 6 billion dollars were traded through online shopping stores. 64.1% of total population in Korea use internet. The sample in the current study was a convenience sample. The sample was selected from users of internet with shopping experiences within the previous three month period. They live in a southern metropolitan city of Daegu, the third largest city in Korea with total population around 2.6 million. 12.6% of the sample used internet less than three years, 53.4% use internet more than three years and less than seven years. 34.8% of the sample used internet for communicating means such as and messenger, 32.4% for news and information search, 12.6% used for online shopping, and the remaining sample used for entertainment and community participation. 62.2% of the sample purchased products and services from five major online stores in Korea. About 22.7% of the sample purchased products/services from Auction owned by ebay, 16% from Daum Communications, 12.1% from Interpark, 6.3% from Naver, 5.5% from G-market, 3.1% from GSeShop, and so on. Respondents with online shopping experiences were approached by trained interviewers to respond. A gift worth two dollars was given at the end of the interview. Approximately 400 questionnaires were distributed. Among them, 363 questionnaires were redeemed, resulting in 90.8% response rate. By excluding problematic and unanswered questionnaires, 353 were used for analysis, resulting in a valid response rate of 88.3%. The profiles of respondents are shown in Table 1. It was revealed that 55.5% of the respondents were male, 51.6% were less than thirty, and 27.3% were in their thirties. 53.5% of the sample were married. 6.6% earned less than

7 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) Table 1 Profiles of the sample Measure Item Frequency Percentage (%) Gender Male Female Age Below Over Occupation Office and service workers Students Specialists Technicians Housewives Etc Education Below high school Junior college University Graduate Monthly income Below $ $ $ Over $ Etc Total two thousand dollars monthly income, 51.5% earned between two and three thousand dollars. 83% completed at least college education. 31% were office workers, 20.3% were homemakers, 16% were university students. 68% of the sample purchased US 165 dollars worth of products and services online for the last three month period. These demographics show that the sample represents the general online shoppers in South Korea Validity and reliability of the scales SPSS 10.0, a statistical software package, was adopted for exploring descriptive statistics and factor structures, and structural equation model [28] was also adopted for confirmatory factor analyses to verify the validity of the scales and structural relationships between exogenous and endogenous concepts. Two-stage analysis was utilized [23, p. 635]. The exploratory and confirmatory factor analyses are first analyzed and then structural model. Covariance matrix was used as input matrix and maximum likelihood estimation procedure was utilized in the analyses adopting LISREL 8.3, the most widely used structural equation modeling software. The confirmatory factor analyses for exogenous and endogenous factors were separately estimated. To assess the stability of online store associations and other constructs, the pilot survey was conducted employing one-to-one interview survey of approximately 98 students enrolled in senior and graduate level brand management courses during April More than 86 questions were given to the students. Based on the results of the pilot study, items in the current study were selected. Personal values are first analyzed for their psychometric properties. Exploratory factor analysis with eigen values over 1 has produced four factors: matured society, safe world, happiness, and esteem life. Adopting the KahleÕs nine-item measures of the List of Values (LOV), [30] identified self actualization, security/pleasure, and social affiliation, whereas [57] identified self actualization and social affiliation. Erdem et al. [18] used RokeachÕs eighteen terminal values and identified security, idealism, and personal gratification. Different value factor solutions may be attributed to situational factors [57,26]. From the exploratory factor analysis, two cross loaded items were deleted. The Table 2 Confirmatory factor analysis for personal values Construct Scales Internal consistency Convergent validity Cronbach Alpha Item-to-total correlation Standardized loadings (t-value) Standard error Composite reliability Matured society Mature love (spiritual and sexual intimacy) a Inner harmony (11.96) Wisdom (a mature understanding of life) (12.18) Social recognition (9.66) True friendship (12.41) Safe world World at peace a A world of beauty (14.74) Equality (11.83) Variance extracted Happiness Family security a Happiness (15.46) Freedom (13.25) Esteem life Self-respect (self-esteem) a Pleasure (an enjoyable, leisurely life) (11.46) A sense of accomplishment (11.42) An exciting life (8.13) Fit statistics: v 2 (d.f. = 84) = (P = 0.00), RMR = 0.070, SRMR = 0.055, GFI = 0.910, AGFI = 0.868, NFI = NNFI = 0.893, CFI = a Fixed at 1 to standardize.

8 124 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) remaining sixteen items were included in the confirmatory factor analysis. The final measurement scales and fit statistics are shown in Table 2. The v 2, shown at the bottom of Table 2, is with degrees of freedom 84 and significant at v 2 is sensitive to the number of individuals in the sample and unreliable when the sample exceeds 200 [23]. The GFI, AGFI, NFI, NNFI, and CFI values approach or exceed the recommended level of The goodness of fit index (GFI) is a measure of absolute fit and represents the overall degree of fit (the squared residuals from prediction compared with the actual data). The adjusted goodness fit index (AGFI) is an extension of GFI adjusted by the ratio of the degrees of freedom for the proposed model to the degrees of freedom for the null model [23, p. 684]. The null model represents the simplest model that can be theoretically justified [23, p. 620]. The normed fit index (NFI) is a measure comparing the proposed model with the null model, and the non-normed fit index (NNFI) and the comparative fit index are also known as comparative indices between the proposed and null models [23, p. 686]. These statistics suggest that the data reasonably fit the model. Table 3 Confirmatory factor analysis for online store associations Construct Scales Internal consistency Convergent validity Cronbach Alpha Item-to-total correlation Std loadings (t-value) Standard error Composite reliability Variance extracted Design Store structure is confusing b a Well designed for convenience (18.43) Clearly structured (18.22) Visual appeal Visually pleasing a Store has visually appealing design (8.40) Hyperlink The meaning of hyperlink is unclear b a Tell me clearly what can I find behind them (21.03) Assortment Carries a variety of products not easily found a Offers products with unique characteristics (16.49) Updates often with new products (16.12) Sells various assortments (14.33) Information Store provides reliable information a Provides accurate information (25.15) Provides detailed information (24.03) Provides comparative information (20.73) Sufficient contents that I expect to find (20.00) Security Not give my information without permission a Provides security measures to remove overall (33.90) concern about security Will not misuse my personal information (26.35) After-sale services Has easy exchange policy a Easy to return harmed products (23.11) Delivers products at promised time (18.11) Delivers the right product ordered (20.99) Fit statistics: v 2 (d.f. = 209) = (P = 0.00), RMR = 0.055, SRHR = 0.032, GFI = 0.90, AGFI = 0.864, NFI = 093, NNFI = 0.951, CFI = a Fixed at 1 to standardise. b Reverse coded. Table 4 Confirmatory factor analysis for store loyalty Construct Scales Internal consistency Convergent validity Commitment Plan to maintain my shopping habits at this online store Am committed to maintaining my purchasing at this online store Cronbach Alpha Item-to-total correlation Std loadings (t-value) Standard error Composite reliability Variance extracted a (16.18) 0.53 Re-patronage intention Will be very probable ( a ) Will be very Likely (40.32) 0.15 Will be very possible (30.65) 0.39 Fit statistics: v 2 (d.f = 4) = (P = 0.00), RMR = 0.025, SRMR = 0.012, GFI = 0.98, AGFI = 0.91, NFI = 0.99 NNFI = 0.97, CFI = a Fixed at 1 to standardize.

9 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) The internal consistency refers to an instrumentõs ability to attribute the effects that was observed to the measured variables and not to other factors. The internal consistency reliability of personal values is assessed by the Cronbach alphas and item-to-total correlations presented in the middle of Table 2. One item in safe world value was additionally deleted due to low item-to-total correlation. Values for item-to-total correlations ranged from to Correlations above 0.6 are considered as appropriate. The Cronbach alpha values ranged from to The Cronbach alpha values above 0.60 are considered as acceptable. The Cronbach alpha is a statistic that summarizes the extent to which a set of items making up a measure intercorrelate. All values show that internal consistency reliability of personal values is deemed adequate. The convergent validity of personal values was assessed based on factor loadings, composite reliabilities, and variances extracted [23]. The convergent validity refers to confirmation of the existence of a construct determined by the correlations exhibited by independent measures of the construct. The results of the convergent validity are shown in the right hand side of Table 2. Factor loadings of all items in each construct ranged from to 0.879, which all exceeded the recommended level of And all t-values corresponding to the paths between the scales and their respective factors were significant at 0.01 or less. The composite reliability values, which depict the degree to which the construct indicators indicate the latent construct, ranged from and 0.660, all of which fell short of the recommended level of The variances extracted, which reflect the overall amount of variance in the indicators accounted for by the latent construct, were in the range between and 0.608, two constructs fell below the recommended level of All these figures show that the convergent validity of personal values is less convincing. However, by considering admissible values of Cronbach alphas and item-to-total correlations, it was decided to keep all four personal value constructs. Because the sample is relatively high, above 350, and they also bear important implications in explaining customersõ underlying shopping motives [30, p. 243]. The fit statistics of the measurement model of online store associations found at the bottom of Table 3 show that the data fit the model well. The final measurement scales are also presented in Table 3. The internal consistency and convergent validity of online store associations is similarly assessed. The alpha coefficients and item-to-total correlations of measurement items for each construct are presented in the middle of Table 3. The values for item-to-total correlations ranged from to 0.963, all of which are above the cutoff level of 0.6. The Cronbach alpha values ranged from to The Cronbach alpha values above 0.60 are considered as good and acceptable. The convergent validity of online store associations was assessed based on factor loadings, composite reliabilities, and variances extracted. The results of the convergent validity are also shown at the right hand side of Table 3. Factor loadings Table 5 Discriminant validity tests Construct Commitment (1) 1.00 Patronage intention (2) 0.74 (0.15) 1.00 Atmosphere (3) 0.60 (0.11) 0.45 (0.11) 1.00 Interior and design (4) 0.70 (0.13) 0.59 (0.13) 0.62 (0.10) 1.00 Facilities (5) 0.59 (0.12) 0.61 (0.12) 0.60 (0.09) 0.63 (0.11) 1.00 Employee services (6) 0.48 (0.11) 0.63 (0.12) 0.52 (0.09) 0.54 (0.10) 0.53 (0.09) 1.00 Product assortment (7) 0.56 (0.10) 0.68 (0.11) 0.52 (0.08) 0.66 (0.10) 0.72 (0.10) 0.60 (0.09) 1.00 Hedonic benefit (8) 0.62 (0.13) 0.49 (0.12) 0.57 (0.10) 0.58 (0.11) 0.62 (0.11) 0.36 (0.09) 0.75 (0.11) 1.00 Utilitarian benefit (9) 0.54 (0.11) 0.53 (0.12) 0.53 (0.09) 0.58 (0.11) 0.61 (0.10) 0.47 (0.09) 0.77 (0.10) 0.74 (0.12) 1.00 Self-actualization (10) 0.03 (0.08) 0.10 (0.08) 0.13 (0.06) 0.10 (0.07) 0.08 (0.07) 0.08 (0.07) 0.28 (0.07) 0.03 (0.07) 0.16 (0.07) 1.00 Safe world (11) 0.04 (0.07) 0.13 (0.08) 0.06 (0.06) 0.17 (0.07) 0.13 (0.06) 0.15 (0.06) 0.29 (0.06) 0.01 (0.07) 0.11 (0.07) 0.81 (0.08) 1.00 Maturity (12) 0.22 (0.09) 0.31 (0.10) 0.24 (0.07) 0.33 (0.09) 0.37 (0.08) 0.29 (0.08) 0.48 (0.08) 0.19 (0.08) 0.32 (0.08) 0.73 (0.08) 0.80 (0.08) 1.00 * Phi estimates with standard errors in parentheses. Each phi indicates discriminant validity because each phi plus or minus two standard errors does not include 1.

10 126 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) of all items in each construct ranged from to 0.895, all of which exceeded the recommended level of 0.60 but one. And all t-values corresponding to the paths between the scales and their respective factors were significant at the significance level of 0.01 or less. The composite reliabilities ranged from and 0.796, most of them fell short of the recommended level of The variance extracted measures were in the range between and 0.765, all of which exceeded the recommended level of All these figures show that the convergent validity of online store associations is marginally acceptable. The measurement model of online store loyalty shows that the data fit the model well. The final measurement scales and fit statistics are presented at the bottom of Table 4. The internal consistency and convergent validity of online store loyalty is similarly assessed. The alpha coefficients and item-to-total correlations of measurement items for each construct are presented in the middle of Table 4. The values for item-to-total correlations ranged from to 0.970, all of which are above the cutoff level of 0.6. The Cronbach alpha values were and 955. The Cronbach alpha values above 0.60 are considered as good and acceptable. The convergent validity of online store associations was assessed based on factor loadings, composite reliabilities, and variances extracted. The results of the convergent validity are also shown at the right hand side of Table 4. Factor loadings of all items in each construct ranged from to 0.821, all of which exceeded the recommended level of And all t-values corresponding to the paths between the scales and their respective factors were significant at 0.01 or less. The composite reliabilities were and 0.753, which were above the recommended level of The variance extracted measures were and 0.697, all of which exceeded the recommended level of All these figures show that the convergent validity of online store loyalty is generally acceptable. The discriminant validity is assessed comparing correlation coefficients (phis) plus and/or minus two standard errors. The discriminant validity refers to a criterion imposed on a measure of a construct requiring that it not correlate too highly with measures from which it is supposed to differ. Table 5 shows that correlations coefficients and standard errors in parentheses. Constructs have discriminant validity if each phi between two constructs plus or minus two standard errors does not include a plus/ minus one or above [42, p. 491]. Calculated values do not contain 1, which verify the discriminant validity of the constructs adopted in the current study. 5. Hypotheses testing and discussion After assessing the reliability, convergent, and discriminant validity, the overall fit of the structural model is confirmed. In case of loyalty, commitment and intention to revisit and make purchases at an online store were averaged, respectively, and put into the structural model as two separate scales forming online store loyalty, consistent with [5, p. 504]Õs definition. The fit statistics are summarized at the bottom of Table 6. The model shows that the v 2 value 1, with degrees of freedom 699 with p value Table 6 The results of structural model Paths Constructs Standardized coefficients (std. error) t-values Constructs Standardized coefficients (std. error) t-values Beta fl Web site design! Loyalty.124(0.078) Happiness! Web site design 0.152(0.054) * Visual appeal! Loyalty.093(0.069) Happiness! Visual appeal 0.164(.053) * Hyperlink! Loyalty.166(0.07) * Happiness! Hyperlink 0.165(.054) * Product assortment! Loyalty.473(0.105) ** Happiness! Product assortment 0.163(.057) * Information! Loyalty.075(0.105) Happiness! Information 0.154(.056) * Security features! Loyaliy.072(0.058) Happiness! Security features 0.162(.057) * After-sales servies! Loyalty.045(0.09) Happiness! After-sales services 0.161(.051) * Gamma fl Matured society! Web site design.160(0.07) * Esteem life! Web site design 0.169(.049) * Matured society! Visual appeal.158(0.07) * Esteem life! Visual appeal 0.168(.052) * Matured society! Hyperlink.160(0.06) * Esteem life! Hyperlink 0.169(.047) * Matured society! Product assortment.170(0.06) * Esteem life! Product assortment 0.168(.051) * Matured society! Information.172(0.06) * Esteem life! Information 0.171(.058) * Matured society! Security features.162(0.06) * Esteem life! Security features 0.170(.038) * Matured society! After-sales services.162(0.061) Esteem life! After-sales services 0.171(.049) * Safe world! Web site design 0.101(.053) Safe world! Visual appeal 0.106(0.052) Safe world! Hyperlink 0.109(0.067) Safe world! Product assortment 0.114(0.058) Safe world! Information.113(0.064) Safe world! Security features.122(0.047) Safe world! After-sales services 0.119(0.067) Fit statistics: v 2 (d.f. = 699) = (p = 0.00) RMR = 0.12, RSMR = 0.066, GFI = 0.83, AGFI = 0.80 NFI = 0.86, NNFI = 0.91, CFI = * Significant at ** Significant at 0.01.

11 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) significant at Even though the p-value is significant, the ratio of the v 2 to degrees of freedom is 2.095, which is considered to be acceptable when it is less than 3 [23, p. 687]. RMR (the root mean square residual) and SRMR are 0.12, and 0.066, respectively. The recommended level of RMR and SRMR (the standardized root mean square residual) is RMR is an average of the residuals between the observed and estimated input matrices and measures the overall fit of the model. SRMR is standardized form of RMR adjusted by the degrees of freedom. The GFI and AGFI were 0.83 and These fit statistics are lower than the recommended level of The poor GFI and AGFI statistics may be attributed to several constructs representing personal values and attribute dimensions with low composite reliability scores and variances extracted. However, NNFI is 0.91, which is acceptable and above the recommended level of NNFI suggests that the model is significantly improved compared to the null model. In addition, the CFI value is 0.92, exceeding the recommended level of Based on these facts, it is concluded that even though the data does not fit the model perfectly, the overall statistics imply that the model is marginally acceptable. These arguments lead us to test the hypotheses proposed in the current study. Having assessed the overall and measurement models, the estimated coefficients of the causal relationships are examined. The overall model tests globally support the proposed conceptualization. The results are summarized in Table 6. To test the hypothesized relationships, the estimated standardized coefficients, signs, and their associated t-values are examined. H1 predicted that personal values are positively linked to an individual customerõs evaluations of web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale services. Major attention for this agenda was given to which personal value dimensions are positively associated with which online store attribute dimensions. The results are found in Table 6. It was shown at the left hand side of Table 6 that matured society value had a statistically significant negative effect on all seven online store associations such as web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale service. But our hypothesis predicted positive effects. In case of safe world value, it had a positive impact on online store associations, but the impacts were not statistically significant. Happiness value had a statistically significant effect on all seven online store attributes, but the impact was negative. In case of esteem life value, it had a statistically significant and positive effect on all seven online store attributes including web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale services. It is summarized that: (1) two values including matured society and happiness had statistically significant effects on attributes, but their impacts were negative; (2) while safe world value had no impact on attribute evaluations, esteem life value had statistically significant and positive effects on attribute evaluations. These results revealed that only esteem life value had positive influences on online store attribute dimensions, partially supporting Hypothesis 1. The results imply that while customers with strong values for matured society and happiness tend to evaluate online store associations negatively, customers with strong value for safe world have no interest at all in online store attributes. Only customers with strong value for esteem life tend to evaluate online store associations positively and have favorable interest in buying products and services online. From these results, one thing should be noted. Previous studies [18,35,57] consistently attest that positive relationships exist between personal values and store attributes. For example, Erdem et al. [18] demonstrate that personal gratification, social responsibility, and security are positively correlated with store status, merchandise, and price perceptions. However, the results of the current study indicate that more diverse relationships may exist in the causal links from personal values to online store attributes. Value for esteem life is the only value that is strongly and positively associated with online store attributes. H2 predicted that customersõ favorable perceptions on web site design, visual appeal, well organized hyperlinks, information quality, product assortment, and after-sale services are positively associated with online store loyalty. This agenda leads our attention to which online store attributes are valid predictors of customer loyalty. The results found at the top left of Table 6 show that only one attribute, product assortment, is strongly and positively associated with online store loyalty. Even though hyperlink had a statistically significant effect, the direction was reversed, contrary to the proposed direction. These results imply that H2 is partially supported. The results suggest that customers who have favorable inclination toward product assortment or variety tend to have strong commitment toward online stores and intention to re-patronize. While customers who have unfavorable inclination towards hyperlink, web site design, and after-sale services tend to have negative behavioral direction, customers who rated visual design, information, and security favorably have no interest at all in forming store commitment and re-patronizing behavior to an online store. These results imply that it is necessary to stock variety of products in an online store in order to attract and maintain previous customers and form store commitment. With one exception of product assortment, these results of the present study contradict with the previous studies. In terms of web atmosphere, for example, [31] show that web appearance has a positive impact on satisfaction, and [67] empirically show that website design has a positive impact on loyalty intention. The current study included two atmospheric cues, website design and visual appeal. The results show that neither website design nor visual appeal had statistically significant effects on loyalty. Among product order related factors, well-structured hyperlinks in the previous studies not just represent web-atmospherics, but also

12 128 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) facilitate information search, order processes, save customersõ online shopping time, eventually makes customers less price sensitive, and purchase more expensive products [9]. But the current study showed that hyperlink had a negative effect on loyalty. In terms of effects of information, [53,1,56,51] stipulated that product information has positive relationships with online purchase. But the present study show no statistically significant effect of information on loyalty, which is consistent with the results of [56], who attested that perceived information quality does not adequately predict services purchase online (p. 361). With regards to security, while [51,3,17] found that security is the most important predictor of intention to shopping online, [67] implied that privacy/security has no effect on loyalty intention and satisfaction. Our results show that security had no effect. The current study show that aftersale services had no effect on forming customersõ re-patronage intention and commitment. These results contradict the previous studies, which empirically proved that after-sale services such as fast and safe delivery, return, and exchange services generally increase customersõ buying online [56,1,32,36,17]. In terms of product assortment, the results in the present study showed that product assortment had a positive and statistically significant effect on loyalty, which is consistent with the previous studies, in which customers are more likely to visit an online shopping store with varied high quality merchandise [1,17,53]. All these discrepancies may be attributed to situational and customersõ characteristics in different cultural backgrounds. For example, the results of the present study may imply that online stores have failed to differentiate themselves against competitors in terms of web site design, visual appeal, information presentation, security features, and after-sale services. Currently, there are about 3242 online stores rivaling each other to capture some share of US 6 billion dollar trade volume. The results suggest that more unique and differentiated attribute-based positioning strategies will appeal online purchasers in South Korea. As additional tests, paths from personal values to loyalty had been inserted one by one. However, it was revealed that the effects of personal values to loyalty were negligible. No v 2 difference test and related path coefficients were statistically significant. These results show that there are no direct influences of personal values on online store loyalty. 6. Conclusions, implications, and future research 6.1. Summary The current study introduced personal values as the underlying motives of an individual online shopperõs to evaluate seven different attributes, which in turn may lead them to be committed to and re-patronize an online store. The results show that three customersõ values such as matured society, happiness, and esteem life are the underlying beliefs motivating/deterring customers to shop online. But their impacts were different. Even though personal value for strong esteem life had a positive effect on attribute evaluation, values for matured life and happiness had negative influences on loyalty. In addition, the results also demonstrated that customersõ favorable evaluation of product assortment eventually guided customers to be loyal to an online store. The results imply that customers with strong values for matured society and happiness have negative perceptions on all seven online store attributes. However, some of these customers still do shopping online, due to product assortment. Meanwhile, a group of customers with strong value for esteem life tend to have positive perceptions on online store attributes, and product assortment is the only one and most attractive feature enticing customers in this group. They think that security may harm them when purchasing products online Research implications There are several important theoretical implications of the current study. First, the current study showed that personal values are not automatically translated into customersõ loyal intention to shop online. Previous studies consistently predicted that there are positive relationships between personal values and store attribute evaluations [18,57,26]. However, the current study showed that while matured society and happiness values are negatively related, customersõ esteem life value is positively associated with online store attribute evaluations. Second, most previous studies attested that most attribute dimensions online stores carry are positively associated with loyalty. However, the current study showed that only product assortment had a positive impact on online store loyalty. More thorough investigations in different contexts will add out understanding of the effects of online store attributes on loyalty. Third, the current study may contribute, to some extent, to extending the means-end theory by empirically testing the roles of personal values. The means-end chain theory implies that personal values could be the enduring, situation-free, underlying beliefs explaining why customers select certain store attributes among others [18,6]. The current study empirically showed that personal values could be underlying belief system, which guides customers to evaluate various online store attributes positively and/or negatively and leads to be loyal to an online store Managerial implications The results of the current study provide several important managerial insights to managers of online stores. The current study identified three important customer groups and strategies for these consumer groups can be recommended. The first managerial strategy is to mitigate or neutralize thoughts that cynical customers with safe world and happiness values have. Customers with strong value for matured society tend to evaluate all seven attribute dimensions negatively. In addition, customers with strong value for happiness also tend to evaluate attribute dimen-

13 D.-M. Koo / Electronic Commerce Research and Applications 5 (2006) sions negatively. To attract customers in these two groups, managers should implement strategies to convert these cynical customers into true loyal customers, or at least to neutralize their tendency to evaluate store attributes negatively. A positioning strategy emphasizing that shopping at an online store can contribute to customersõ inner harmony, social recognition, family security, and happiness, will appeal to these groups. Another strategy is also needed for the group with strong value for esteem life. The group with esteem value tends to evaluate all seven attribute dimensions positively. A positioning strategy showing that shopping online may enhance self-oriented life goals such as self-respect, exciting/pleasure life, and accomplishment will appeal to customers in this group Future research and limitations Future studies will investigate more thoroughly the effects of personal values on various attributes and behavior related to online shoppers. Previous studies predicted the positive impact of personal values, but the current study shows that personal values may not be automatically translated into positive evaluations of attributes of online stores. Cross-cultural and/or replication studies of the effect of personal values on customersõ evaluations of online store associations and loyalty will enhance our understanding. Second, it may also be useful to study how consumers with varying degrees of tasks differ in their evaluations between various online store characteristics. Eroglo et al. [19] imply that task-oriented customers and fun-directed customers will differ in their selections of attributes. It is proposed that customers with low task duty may consider atmospheric cues as important, but customers with high task-related duty may prefer utilitarian attributes. Investigation on customers with varying degrees of duty completion tasks will deepen our insights. Third, some researchers have suggested that expert consumers are likely to use more abstract elements in their evaluations. This suggests that consumersõ experiences and/or knowledge about online shopping may impact their online store purchase behavior. Clearer investigations of expert/novice consumersõ use of concrete versus abstract attributes will enhance our understanding. Fourth, more research on attribute-related associations of online shopping stores will also be useful. Including associations such as product price, search cost, and other entertainment and social interaction will provide greater insight into online shopping behavior. Like many others employing survey methods, this study has limitations. The first limitation pertains to measurement. The personal values are shown to have low composite reliability values and variances extracted, resulting in low fit statistics of the structural model. This poor validity may be attributed to subjectsõ time constraint during the survey and/or burdensome numbers of questions contained in the survey. Accordingly, researchers should interpret the effects of these dimensions with caution. Second, even if the sample is relatively large, the sample in the current study does not adequately represent the general population. Accordingly, another caution should be excised when interpreting and generalizing the results. References [1] T. Ahn, S. Ryu, I. 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