Mass customization, which is a combination of mass production and customization, refers to a business strategy that provides tailored products or services, allowing individual consumers to create these based on their specific needs and wants (Fiore, Lee, & Kunz, 2004). According to Pine and Gilmore (1999), consumer demand for apparel products decreased in the 1990s owing to mass production, wherein large volumes and the standardization of products were emphasized. However, consumers’ desire for unique products has since increased, and mass customization began to be considered as a strategy to satisfy these more demanding consumers (Pine & Gilmore, 1999). In apparel mass customization programs, consumers are offered options in terms of color, size, fabric, and design components, which enable them to create a pair of shoes or an item of clothing. This process of customization has become more efficient with the introduction of Internet technology (Randall, Terwiesch, & Ulrich, 2005). A number of apparel companies, such as Nike, Adidas, and Land’s End now offer well-established customization programs, and industry reports (Roumeliotis, 2013; Technavio, 2015) indicate that the popularity of this online retailing format has increased (see also Randall et al., 2005). Thus, retailers now enjoy stronger relationships with their customers and benefit from opportunities to learn about their customers’ preferences (Simonson, 2005).

Mass customization not only provides uniqueness of design but also increases consumer involvement in shopping through the codesign process and interactive features (Fiore et al., 2004). A key value of mass customization is the hedonic and creative achievement value gained during the customizing process (Merle, Chandon, Roux, & Alizon, 2010). As Pine and Gilmore (1998) pointed out, in today’s experience economy—which emphasizes consumers’ shopping experiences rather than shopping outcomes, e.g., a shopping mall with an amusement park—hedonic and creative achievement experiences are considered significant.

To date, researchers have focused primarily on the efficiency of the mass customization process from an organizational management perspective (e.g., Hedge, Kekre, Radiv, & Tadikamalla, 2005; Yue, Xia, Tran, & Chen, 2009) and consumer benefits that will lead to behavioral intentions (e.g., Fiore et al., 2004; Merle et al., 2010), but product and self-image enhancing positive consumer responses have not been studied in the context of mass customization (Sirgy, Grewal, & Mangleburg, 2000). Thus, in the current study we proposed the concept of self-congruity (Sirgy, 1986), which has previously been used to explain the nature of the process through which a consumer chooses a product. According to Zhang and Bloemer (2008), a consumer’s feeling of connection with an object can be explained by its perceived fit, relevance, and congruity. Although there has been a great deal of research conducted separately on mass customization and on self-congruity (Fiore et al., 2004; Franke, Keinz, & Steger, 2009; Merle et al., 2010), the effects of the congruence between a customized product and a consumer’s self-image on consumer responses in online mass customization remain largely unknown (Sirgy, 1986; Sirgy & Su, 2000); further, research on functional congruity between consumers’ expectations and customized products is limited. Given the growing importance of personalization in both marketing and retailing, we focused on examining how self-congruity and functional congruity derived from customized products affect emotional product attachment and perceived quality, and how these variables, in turn, influence behavioral intentions. In addition, we examined how individual differences in self-monitoring affect consumers’ interest in customizing a product. The empirical findings we obtain in this study are expected to contribute to the literature on online mass customization and self-congruity theory. From a managerial perspective, our findings will also help online retailers to understand how self-congruity and functional congruity can be used to develop more effective strategies for their target markets.

Theoretical Development and Hypotheses

Self-Congruity

Self-congruity is the “cognitive matching between value-expressive attributes of a given product (brand or store) and consumer self-concept” (Sirgy, Johar, Samli, & Claiborne, 1991, p. 363), and the terms self-image congruence, image congruence, and self-congruence are used interchangeably in the literature (Sirgy, 1986; Sirgy & Su, 2000). Self-concept is multidimensional (Sirgy et al., 2000), being composed of actual self-concept, ideal self-concept, social self-concept, and ideal social self-concept, and self-congruity involves the process of matching these four types of self-concept with a product, brand, or store. According to Sirgy et al. (2000), actual self-congruity occurs when a consumer tries to match his or her actual self-concept with a product, brand, or store, and ideal congruity occurs when a consumer tries to match his or her ideal self-concept with a product, brand, or store. Social congruity refers to the match between a consumer’s social self-concept and a product, brand, or store, whereas ideal social congruity pertains to the match between a consumer’s ideal social self-concept and a product, brand, or store (Sirgy et al., 2000). According to Hosany and Martin (2012), among the four types of self-concept, actual and ideal congruity have been well supported as predictors of various types of consumer behavior, and in the current study we also focused on these dimensions to investigate their relationships with other consumer responses.

In their research on actual self-congruity, Sirgy et al. (1991) showed that consumers prefer to buy products with symbolic and value-expressive meanings that are similar to their self-concept, and that consumers form a positive attitude toward the brand when the brand personality is similar to their self-concept. According to Sirgy (1982), actual self-congruity influences product preference and purchase intention. Similarly, a retail store has a retail patron image created from various store attributes, such as atmospheric cues, product quality, price, and promotion, and a closer match between this image and a consumer’s self-concept creates positive attitudes toward the retail store, consequently influencing consumers’ behavioral intentions (Sirgy et al., 2000). In an online context, Cho and Kim (2012) found that consumers who perceived greater, vs. lower, congruity between their own and a website’s personality were more likely to evaluate the website as being more pleasing and professional, judge the information shown to be more relevant, report website navigation as being easier, and perceive online transactions as being more secure.

In the context of online mass customization, actual and ideal congruity may enhance emotional product attachment, that is, an individual’s emotional feelings connected to a product (Kleine & Baker, 2004) or the emotional bond between a consumer and a product (Bowlby, 1979). According to the theory of attachment (Ainsworth, 1979), an individual is motivated to look for proximity to a specific product (i.e., actual self-congruity) to induce emotional feelings (Bowlby, 1979). Govers and Schoormans (2005) further revealed that congruence between self-concept and a product influenced consumers’ preference for that product. Accordingly, we developed the following hypothesis:
Hypotheses 1a: Actual self-congruity will positively influence emotional product attachment.

Ideal congruity is another factor influencing how consumers respond to a product. According to Munson (1973), ideal congruity is a significant factor for product preference when a product is highly visible. However, when a product is not visible to the public, self-congruity is a more significant factor. Other researchers have suggested that actual self-congruity and ideal congruity are equally significant in influencing brand preferences (Landon, 1974) and purchase motivation (Sirgy, 1985). In advertising research, congruity between a celebrity image and a consumer’s ideal self-concept has been found to positively influence favorable attitudes toward the advertisement and purchase intention (Choi & Rifon, 2012).

Self-enhancement theory (Sedikides & Strube, 1997) has been invoked to explain the effect of ideal congruity on emotional attachment. Because an individual is inherently motivated to increase his or her feelings of personal value, people attempt to approach their ideal self-concept. Thus, consumers may have a stronger emotional attachment to a customized product that is congruent, compared to one that is incongruent, with their ideal self-concept, leading to the following hypothesis:
Hypotheses 1b: Ideal congruity will positively influence emotional product attachment.

Functional Congruity

Most researchers of self-congruity have focused on the symbolic values of a product and consumers’ self-concept; however, consumers also use a product for its functional value (Sirgy, 1982, 1985). For example, consumers seek out the functional attributes of a product, such as its physical characteristics and performance features, to help them achieve specific tasks in a satisfactory manner (Fournier, 1991). According to the product attribute model, consumers choose a product based on its functional attributes, and these attributes determine brand preferences (Lancaster, 1979). Sirgy and Su (2000) stated that when consumers’ expected attributes of a product prior to purchase match their perceived attributes after they use the product, functional congruity occurs. The greater the functional congruity, the greater the likelihood of favorable consumer responses, such as attitude change and persuasion (Johar & Sirgy, 1991). Grisaffe and Nguyen (2011) agreed, reporting that superior quality attributes of a product are one of the drivers of emotional attachment. Thus, we proposed the following hypothesis:
Hypotheses 2a: Functional congruity will positively influence emotional product attachment.

Perceived quality refers to a “consumer’s judgment about a product’s overall excellence or superiority” (Zeithaml, 1988, p. 3). In contrast to concrete or objective actual product quality, perceived quality is subjective, relativistic, and abstract (Olson & Reynolds, 1983; Zeithaml, 1988). According to the means–end chain model (Gutman, 1982), product information in a consumer’s memory consists of several levels, with concrete attributes stored in the lowest level, and abstract attributes in the next level up (Olson & Reynolds, 1983; Zeithaml, 1988). According to Zeithaml (1988), consumers use the specific and concrete product attributes in the lowest level to perceive quality in the next level up. In the current study, we believed that the match between consumers’ expected functional attributes and the actual attributes of a customized product may enhance their perceived quality. Therefore, the following hypothesis was developed:
Hypotheses 2b: Functional congruity will positively influence perceived quality.

Relationships Among Consumer Response Types

Behavioral intention refers to “what the person intends to do” in a specific area of behaviors (O’Keefe, 2002, p. 101). Consumers’ behavioral intentions are broadly divided into favorable and unfavorable, and Zeithaml, Berry, and Parasuraman (1996) suggested that the former type includes a willingness to repurchase from the store, recommend the store to other people, spread positive word-of-mouth, spend more money, and even to pay extra money for products.

Few scholars have examined the relationships between emotional attachment and other consumer behaviors. However, Thomson, MacInnis, and Park (2005) distinguished between emotional attachment and having a positive attitude toward an object, arguing that the former is a stronger indicator of consumer behavior. Compared to a positive attitude, attachment pertains to an individual’s strong and important feelings toward a product, thus making the product more significant to the individual. Emotional attachment also leads consumers to engage in protective behaviors in order to continue to use the product (Ball & Tasaki, 1992). According to Park, MacInnis, and Priester (2006), consumers’ behaviors differ based on the strength of their emotional attachment. Consumers with a low level of attachment form a positive attitude that can influence purchase behavior more than brand attachment does, whereas a moderate level of attachment results in brand supporting behaviors, such as repeat purchases. The highest level of attachment further increases loyalty and other supporting behaviors, including repeat purchases, brand community participation, and investing in the brand. Therefore, it is reasonable to assume that the stronger the emotional brand attachment is, the greater will be the behavioral intentions:
Hypothesis 3: Emotional product attachment will positively influence behavioral intentions.

Most prior researchers have provided empirical support for the relationship between perceived quality and behavioral intentions (Cronin, Brady, & Hult, 2000; Jang & Namkung, 2009). For example, Jang and Namkung (2009) demonstrated that favorable service quality and product quality increase behavioral intentions in a service setting. Further, in an online retailing context, Sun, Ni, and Wang (2016) found that perceived product quality has a positive impact on behavioral intentions. Accordingly, we proposed the following hypothesis:
Hypothesis 4: Perceived quality will positively influence behavioral intentions.

Self-Monitoring as an Individual Difference

We proposed that the personality trait of self-monitoring would moderate the relationship between congruity and emotional product attachment, and perceived quality. Self-monitoring is defined as a tendency to control and modify one’s self-presentation in a given context (Snyder, 1974). Depending on their individual style, people may focus on the physical appearance or social presentation of products, or expressive behaviors (Browne & Kaldenberg, 1997) to different degrees, making them either high or low self-monitors. High self-monitoring people are more concerned with the presentation of self-image than are low self- monitoring people, and, thus, seek to improve their self-image (Graeff, 1996). According to Snyder and DeBono (1985), the effects of advertising strategies on consumer responses vary as a function of self-monitoring, with high self-monitoring people reacting more favorably to image-oriented and experiential aspects in advertising than do low self-monitoring people. On the other hand, low self-monitoring people have a more favorable attitude toward quality-oriented and utilitarian aspects in advertising than do high self-monitoring people. Similarly, self-monitoring is likely to have significant implications for consumers customizing a product. In line with this reasoning, we proposed the following hypotheses:
Hypothesis 5a: The effect of actual self-congruity on emotional product attachment will be greater for high self-monitoring people than it is for low self- monitoring people.
Hypothesis 5b: The effect of ideal congruity on emotional product attachment will be greater for high self-monitoring people than it is for low self-monitoring people.
Hypothesis 6a: The effect of functional congruity on emotional product attachment will be greater for low self-monitoring people than it is for high self-monitoring people.
Hypothesis 6b: The effect of functional congruity on perceived quality will be greater for low self-monitoring people than it is for high self-monitoring people.

Method

Participants and Procedure

Female online apparel shoppers in South Korea were selected as the sample for this study because they devote a high percentage of their discretionary spending to apparel purchases (AIP Corporation, 2013; FedEx, 2015), and the survey was administered by an online survey company. Potential participants received an email that explained the purpose of the study and confidentiality of information. If they agreed to take part in the survey, they were guided to click a survey link and to experience an actual mass customization program to enhance external validity. Participants customized a winter coat by choosing its overall style, a button style, preferred colors of fabrics and linings, and the style of collars and sleeves as though they intended to make an actual purchase. On the basis of their experiences with the customization program, participants were then asked to answer the online survey.

Of 1,136 emails that were sent out, 360 responses were returned (response rate = 31.7%), and after excluding incomplete and inappropriate responses, 303 were included in the data analyses. The mean age was 39 years, with relatively even distributions among those aged 20–29 years (22.8%), 30–39 years (28.7%), 40–49 years (25.7%), and 50–59 years (22.8%).

Measures

The instruments were adapted from existing studies, with all items measured on a 7-point Likert-type scale ranging from 1 = strongly disagree to 7 = strongly agree. Actual and ideal congruity were measured with four items from Malär, Krohjmer, Hoyer, and Nyffenegger’s (2011) self-congruity scale: “The personality of the customized product is…consistent with how I see myself,” “…a mirror image of me,” “…consistent with how I would like to be,” and “…a mirror image of the person I would like to be.” Emotional product attachment was measured with three items (Malär et al., 2011; Thomson et al., 2005): “My feeling toward the brand can be characterized by…affection,” “…love,” and “… connection.” Product quality was measured with four items (Buil, de Chernatony, & Martínez, 2013): “This customization program offers…very good quality products,” “…products of consistent quality,” “…very reliable products,” and “…products with excellent features.” Behavioral intentions were measured with four items assessing willingness to revisit the website, willingness to recommend the website, willingness to purchase, and loyalty intention (Kwon & Lennon, 2009). Self-monitoring was measured with six items (Bian & Forsythe, 2012; Lennox & Wolfe, 1984): “Once I know what the situation calls for, it’s easy for me to regulate my actions accordingly,” “When I feel the image I am portraying isn’t working, I can readily change it to something that does,” “I have the ability to control the way I come across to people, depending on the impression I wish to give them,” “In social situations, I have the ability to alter my behavior if I feel the need to do so,” “I can usually tell when I’ve said something inappropriate by reading it in the listener’s eyes,” and “I am often able to read people’s true emotions correctly through their eyes.”

To measure functional congruity, we adopted four functional attributes of apparel from Eckman, Damhorst, and Kadolph (1990), who used these attributes to assess apparel quality. The four functional attributes were fit, utility (particular wardrobe needs), comfort, and versatility (various end uses). Participants were asked to evaluate whether or not their expectations before customizing the product matched their evaluation after customizing the product in terms of the four functional attributes.

Data Analysis

Descriptive analyses were performed to examine sample characteristics. Preliminary analyses comprised assessing the reliability of measures and model specification, by employing confirmatory factor analyses (CFA), matric invariance tests, and a median-split analysis. Structural equation modeling and a multiple group comparison analysis were conducted to test the hypotheses. SPSS version 22.0 and AMOS version 22.0 were used to analyze the data.

Results

Grouping Check

To test the moderating effects of self-monitoring, we used a median split to divide the participants into high and low self-monitoring groups (Mdn = 4.50). The Cronbach’s alpha for self-monitoring was .84 and there was a significant difference in mean scores between the high (n = 166, M = 5.20, SD = 0.51) and low (n = 137, M = 4.01, SD = 0.49) self-monitoring groups (t = 20.58, p < .001).

Confirmatory Factor Analyses and Metric Invariance Tests

The CFA chi-square statistic was significant, χ²(134) = 207.00, p < .001, owing to the large sample size (N = 303), and other fit indices suggested an acceptable model fit to the data: root mean square error of approximation (RMSEA) = .04, normed fit index (NFI) = .97, Tucker–Lewis index (TLI) = .99, comparative fit index (CFI) = .99). All the t values for the factor loadings were significant, supporting the convergent validity.

We focused on the moderating effects of self-monitoring on the paths from actual and ideal congruity to emotional product attachment and from functional congruity to emotional product attachment and to perceived quality. Before estimating the moderating effects of self-monitoring, the equality of factor loadings between the high and low self-monitoring groups was tested. The chi-square differences between the full metric invariance model and the nonrestricted model were nonsignificant for the comparisons between the high and low self-monitoring groups, χ²d(19) = 29.70, p > .05, implying that the full metric invariance model could be accepted. The reliabilities of all the measurements, as well as the measurements for each group, were greater than .80, indicating an adequate level of internal consistency for the scales.

Hypotheses Testing

Hypotheses 1 to 4 were tested using single-group structural equation modeling. Although the chi-square statistic was significant, χ²(140) = 225.18, p < .001, this tends to be sensitive to a large sample size, as was the case here (N = 303). The overall fit indices of the model indicate a satisfactory fit to the data (RMSEA = .05, NFI = .97, TLI = .98, CFI = .98). The path coefficients reveal the significant positive impacts of ideal congruity on emotional product attachment, functional congruity on emotional product attachment and perceived quality, and emotional product attachment and perceived quality on behavioral intentions (see Figure 1). However, actual self-congruity did not significantly influence emotional product attachment. Thus, Hypotheses 1b, 2, 3, and 4 were supported, but Hypothesis 1a was not supported.

Hypotheses 5 and 6 relate to the proposed moderating effects of self-monitoring on the paths from actual and ideal congruity to emotional product attachment and from functional congruity to emotional product attachment and perceived quality (see Figure 2). Individual path coefficients were compared across the high and low self-monitoring groups, and between-group chi-square difference tests were conducted. The path from ideal congruity to emotional product attachment was of higher significance for the high, vs. low, self-monitoring group, but only the path for the high self-monitoring group was statistically significant. The paths from functional congruity to emotional product attachment and to perceived quality were of higher significance for the low self-monitoring group than for the high self-monitoring group. Therefore, Hypotheses 5 and 6 were partially supported.

Discussion

On the basis of self-congruity theory, we proposed that actual and ideal congruity, and functional congruity would be antecedents of emotional attachment and perceived quality, which enhance behavioral intentions. The results provide empirical evidence that ideal congruity plays a key role in increasing emotional product attachment, and that functional congruity increases both emotional product attachment and perceived quality. Compared to those who do not perceive ideal congruity, consumers who perceive that the customized clothing matches their ideal self-concept experience greater emotional attachment to the clothing they design. When consumers perceive that expected attributes of the clothing match those of the customized product, they feel greater emotional attachment and perceive better quality than do consumers who do not perceive functional congruity. Our findings are consistent with those obtained in previous research regarding ideal and functional congruity (Choi & Rifon, 2012; Graeff, 1996; Munson, 1973; Sirgy, Grzeskowiak, & Su, 2005).

Contrary to the findings of some prior researchers (e.g., Govers & Schoormans, 2005), our results indicate that actual self-congruity is not a significant predictor of emotional product attachment. This lack of support could be explained by the fact that ideal self-concept is more important when consuming highly visible products, whereas actual self-concept is more important for private product consumption (Hughes, 1976; Munson, 1973).

Belk’s (1984) argument that consumers attempt to display their identity through possessing visible products supports this explanation. Because apparel is categorized as a highly and socially visible product (Stern, 1992), when consumers customize their winter coat, their ideal self-concept is related to the identity that they wish to express. Thus, ideal congruity plays a key role in affecting emotional product attachment to apparel.

Another explanation might be the context of the current study, in which participants were asked to create their own winter coat in a customization program. Unlike previous researchers, who examined congruity between a product that had already been manufactured and self-concept (Quester, Karunaratna, & Goh, 2000; Sirgy et al., 1991), we examined how mass customization requires a consumer’s active involvement in the manufacturing process. This direct “hands on” contribution might have encouraged the participants to express their ideal, rather than actual, self-concept. Therefore, it is reasonable to assume that the match between the participant’s ideal self-concept and the customized coat may enhance emotional product attachment.

Our results regarding the relationships among consumer responses align with findings in prior research (Ball & Tasaki, 1992; Cronin et al., 2000; Park et al., 2006), thus providing further empirical support. Consumers who feel emotional attachment to a customized item of clothing and those who perceive it to be of high quality have stronger behavioral intentions than consumers who do not.

With respect to the moderating role of self-monitoring, our findings show partial support for those obtained in previous studies (Browne & Kaldenberg, 1997; Snyder & DeBono, 1985). For consumers in the high self-monitoring group, only ideal congruity plays a key role in influencing emotional product attachment. According to Snyder (1974), self-monitoring reflects an individual’s tendency to tailor his or her behavior in a given situation. Thus, consumers attempt to manage their outfits according to their self-concept for a certain social context, and customizing a coat may be related more to consumers’ ideal selves than to their actual selves.

On the other hand, functional congruity was more significant in influencing emotional product attachment and perceived quality for consumers in the low, vs. high, self-monitoring group. Because consumers with low self-monitoring regard the quality-oriented aspects of a product to be important (Snyder & DeBono, 1985), the utilitarian attributes of clothing (i.e., functional congruity) are a stronger predictor of emotional attachment and perceived quality.

Our findings provide useful theoretical insights that extend the existing literature by providing empirical support for the effects of ideal congruity and functional congruity on consumer responses in an online mass customization context and reveal a new perspective for those seeking to enhance the effectiveness of mass customization. Additionally, we examined two complementary theories, self-congruity and functional congruity, that describe consumer behaviors (Sirgy et al., 2005). The finding of a moderating role of self-monitoring provides additional empirical evidence supporting self-monitoring theory (Snyder, 1974). Our study also has practical implications for online retailers offering mass customization programs. Consumers tend to choose an apparel product for symbolic reasons (self-congruity) as well as for its functional benefits (functional congruity). As our findings show, retailers need to understand the ideal self-image of their target customers and what functional attributes are important for them. For example, retailers may opt to create advertising messages that emphasize the functional benefits of their clothing in more ideal, as opposed to actual, social contexts that appeal to the consumer’s ideal self-image. Furthermore, if online retailers understand their target market’s lifestyles, this may facilitate emphasizing the functional attributes of clothing.

Although we have contributed to, and extended, the existing literature, there are several limitations to our study. Our sample was limited to female consumers in South Korea. Although members of this group are considered representative consumers of apparel online (AIP Corporation, 2013; FedEx, 2015), they may not represent all shoppers of online mass customization. Thus, future researchers need to consider testing more diverse groups for increased generalizability.

Another potential limitation is the nonsignificant result for actual self-congruity, which may have occurred because we used a socially visible clothing item as the product, so future researchers could consider using a wider range of products to examine the effects of actual and ideal congruity. In addition, empirical research is needed to show whether or not consumers’ direct contribution to the manufacturing process is related to their ideal self-concept.

Ainsworth, M. S. (1979). Infant–mother attachment. American Psychologist, 34, 932–937. http://doi.org/d5532g

AIP Corporation. (2013, April 17). Online shopping behavior in Asia [Online newsletter]. Retrieved from http://bit.ly/1TtWysy

Ball, A. D., & Tasaki, L. H. (1992). The role and measurement of attachment in consumer behavior. Journal of Consumer Psychology, 1, 155–172. http://doi.org/c7g9gv

Belk, R. W. (1984). Three scales to measure constructs related to materialism: Reliability, validity, and relationships to measures of happiness. In T. Kinnear (Ed.), Advances in consumer research (Vol. 11, pp. 291–297). Provo, UT: Association for Consumer Research.

Bian, Q., & Forsythe, S. (2012). Purchase intention for luxury brands: A cross cultural comparison. Journal of Business Research, 65, 1443–1451. http://doi.org/fzgnhk

Bowlby, J. (1979). The making and breaking of affectional bonds. London, UK: Tavistock.

Browne, B. A., & Kaldenberg, D. O. (1997). Conceptualizing self-monitoring: Links to materialism and product involvement. Journal of Consumer Marketing, 14, 31–44. http://doi.org/fsj9kj

Buil, I., de Chernatony, L., & Martínez, E. (2013). Examining the role of advertising and sales promotions in brand equity creation. Journal of Business Research, 66, 115–122. http://doi.org/c9kbt9

Cho, E., & Kim, Y.-K. (2012). The effects of website designs, self-congruity, and flow on behavioral intention. International Journal of Design, 6, 31–39.

Choi, S. M., & Rifon, N. J. (2012). It is a match: The impact of congruence between celebrity image and consumer ideal self on endorsement effectiveness. Psychology & Marketing, 29, 639–650. http://doi.org/4vt

Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76, 193–218. http://doi.org/b5q

Eckman, M., Damhorst, M. L., & Kadolph, S. J. (1990). Toward a model of the in-store purchase decision process: Consumer use of criteria for evaluating women’s apparel. Clothing and Textiles Research Journal, 8, 13–22. http://doi.org/b23k8m

FedEx. (2015, February 9). Consumer behavior study reveals South Korean online shopping habits. Retrieved from http://bit.ly/23XWp90

Fiore, A. M., Lee, S.-E., & Kunz, G. (2004). Individual differences, motivations, and willingness to use a mass customization option for fashion products. European Journal of Marketing, 38, 835–849. http://doi.org/bgqsfx

Fournier, S. (1991). A meaning-based framework for the study of consumer-object relations. In R. H. Holman & M. R. Solomon (Eds.), Advances in consumer research (Vol. 18, pp. 736–742). Provo, UT: Association for Consumer Research.

Franke, N., Keinz, P., & Steger, C. (2009). Testing the value of customization: When do customers really prefer products tailored to their preferences? Journal of Marketing, 73, 103–121. http://doi.org/fmvj2h

Govers, P. C. M., & Schoormans, J. P. L. (2005). Product personality and its influence on consumer preference. Journal of Consumer Marketing, 22, 189–197. http://doi.org/dsd6xn

Graeff, T. R. (1996). Image congruence effects on product evaluations: The role of self-monitoring and public/private consumption. Psychology & Marketing, 13, 481–499. http://doi.org/d86b3p

Grisaffe, D. B., & Nguyen, H. P. (2011). Antecedents of emotional attachment to brands. Journal of Business Research, 64, 1052–1059. http://doi.org/c83kt4

Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of Marketing, 46, 60–72. http://doi.org/dspn3j

Hedge, V. G., Kekre, S., Radiv, S., & Tadikamalla, P. R. (2005). Customization: Impact on product and process performance. Production and Operations Management, 14, 388–399. http://doi.org/bsbb52

Hosany, S., & Martin, D. (2012). Self-image congruence in consumer behavior. Journal of Business Research, 65, 685–691. http://doi.org/fmps9n

Hughes, R. E. (1976). Self-concept and brand preference: A partial replication. The Journal of Business, 49, 530–540.

Jang, S., & Namkung, Y. (2009). Perceived quality, emotions, and behavioral intentions: Application of an extended Mehrabian-Russell model to restaurants. Journal of Business Research, 62, 451–460. http://doi.org/cc492w

Johar, J. S., & Sirgy, M. J. (1991). Value-expressive versus utilitarian advertising appeals: When and why to use which appeal. Journal of Advertising, 20, 22–33. http://doi.org/4pk

Kleine, S. S., & Baker, S. M. (2004). An integrative review of material possession attachment. Academy of Marketing Science Review, 1, 1–35.

Kwon, W.-S., & Lennon, S. (2009). What induces online loyalty? Online versus offline brand images. Journal of Business Research, 62, 557–564. http://doi.org/bqt2bg

Lancaster, K. J. (1979). Consumer demand: A new approach. New York, NY: Columbia Press.

Landon, E. L., Jr. (1974). Self-concept, ideal self-concept, and consumer purchase intentions. Journal of Consumer Research, 1, 44–51.

Lennox, R. D., & Wolfe, R. N. (1984). Revision of the Self-Monitoring Scale. Journal of Personality and Social Psychology, 46, 1349–1364. http://doi.org/cgzkhz

Malär, L., Krohjmer, H., Hoyer, W. D., & Nyffenegger, B. (2011). Emotional brand attachment and brand personality: The relative importance of the actual and the ideal self. Journal of Marketing, 75, 35–52. http://doi.org/btwjj8

Merle, A., Chandon, J.-L., Roux, E., & Alizon, F. (2010). Perceived value of the mass-customized product and mass customization experience for individual consumers. Production and Operation Management, 19, 503–514. http://doi.org/dpbdck

Munson, J. M. (1973). A typological investigation of self-concept congruity and brand preferences: Toward a predictive model (Unpublished doctoral dissertation). University of Illinois at Urbana- Champaign, Champaign, IL, USA.

O’Keefe, D. J. (2002). Persuasion: Theory & research. Thousand Oaks, CA: Sage.

Olson, J. C., & Reynolds, T. J. (1983). Understanding consumers’ cognitive structure: Implications for advertising strategy. In L. Percy & A. Woodside (Eds.), Advertising and consumer psychology (pp. 77–90). Lexington, MA: Lexington Books.

Park, C. W., MacInnis, D. J., & Priester, J. R. (2006). Beyond attitudes: Attachment and consumer behavior. Seoul National Journal, 12, 3–36.

Pine, B. J., & Gilmore, J. H. (1998). Welcome to the experience economy. Harvard Business Review, 76, 97–105.

Pine, J., II., & Gilmore, J. H. (1999). The experience economy: Work is theater and every business a stage. Boston, MA: Harvard Business School Press.

Quester, P. G., Karunaratna, A., & Goh, L. K. (2000). Self-congruity and product evaluation: A cross-cultural study. Journal of Consumer Marketing, 17, 525–535. http://doi.org/fdc6ns

Randall, T., Terwiesch, C., & Ulrich, K. T. (2005). Principles for user design of customized products. California Management Review, 47, 68–85. http://doi.org/bhfj

Roumeliotis, J. D. (2013, March 7). Mass customization & personalization: The pinnacle of differ- entiation and brand loyalty. Retrieved from http://bit.ly/1qDwnWh

Sedikides, C., & Strube, M. J. (1997). Self-evaluation: To thine own self be good, to thine own self be sure, to thine own self be true, and to thine own self be better. Advances in Experimental Social Psychology, 29, 209–269. http://doi.org/cjg6qs

Simonson, I. (2005). Determinants of customers’ responses to customized offers: Conceptual framework and research propositions. Journal of Marketing, 69, 32–45. http://doi.org/d8stkw

Sirgy, M. J. (1982). Self-concept in consumer behavior: A critical review. Journal of Consumer Research, 9, 287–300. http://doi.org/fcd6d5

Sirgy, M. J. (1985). Using self-congruity and ideal congruity to predict purchase motivation. Journal of Business Research, 13, 195–206. http://doi.org/d27439

Sirgy, M. J. (1986). Self-congruity: Toward a theory of personality and cybernetics. Westport, CT: Praeger.

Sirgy, M. J., Grewal, D., & Mangleburg, T. (2000). Retail environment, self-congruity, and retail patronage: An integrative model and a research agenda. Journal of Business Research, 49, 127–138. http://doi.org/bppqv9

Sirgy, M. J., Grzeskowiak, S., & Su, C. (2005). Explaining housing preference and choice: The role of self-congruity and functional congruity. Journal of Housing and the Built Environment, 20, 329–347. http://doi.org/dmc9zw

Sirgy, M. J., Johar, J. S., Samli, A. C., & Claiborne, C. B. (1991). Self-congruity versus functional congruity: Predictors of consumer behavior. Journal of the Academy of Marketing Science, 19, 363–375. http://doi.org/fgsn5t

Sirgy, M. J., & Su, C. (2000). Destination image, self-congruity, and travel behavior: Toward an integrative model. Journal of Travel Research, 38, 340–352. http://doi.org/ccnp8s

Snyder, M. (1974). Self-monitoring of expressive behavior. Journal of Personality and Social Psychology, 30, 526–537. http://doi.org/bxc5nq

Snyder, M., & DeBono, K. G. (1985). Appeals to image and claims about quality: Understanding the psychology of advertising. Journal of Personality and Social Psychology, 49, 586–597. http://doi.org/fk3sph

Stern, B. B. (1992). Historical and personal nostalgia in advertising text: The fin de siècle effect. Journal of Advertising, 21, 11–22. http://doi.org/bfrs

Sun, H., Ni, W., & Wang, Z. (2016). A consumption system model integrating quality, satisfaction and behavioral intentions in online shopping. Information Technology and Management, 17, 165–177. http://doi.org/bfrv

Technavio. (2015, July 21). Increase in mass customization accelerating growth prospects in the CAD market in Italy. Retrieved from http://bit.ly/1RiD85Q

Thomson, M., MacInnis, D. J., & Park, C. W. (2005). The ties that bind: Measuring the strength of consumers’ emotional attachments to brands. Journal of Consumer Psychology, 15, 77–91. http://doi.org/b77jmm

Yue, J., Xia, Y., Tran, T., & Chen, B. (2009). Using frontier portfolios to improve make-to-order operations. Production and Operations Management, 18, 226–239. http://doi.org/cbzjr3

Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52, 2–22. http://doi.org/b9j

Zeithaml, V. A., Berry, L. K., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60, 31–46. http://doi.org/b9k

Zhang, J., & Bloemer, J. M. M. (2008). The impact of value congruence on consumer-service brand relationships. Journal of Service Research, 11, 161–178. http://doi.org/cgct7d

Jungmin Yoo, College of Humanities and Social Sciences, Department of Business Administration, Duksung Women’s University, 33 Samyang-ro 144-gil, Ssangmun-dong, Dobong-gu, Seoul 132-714, Republic of Korea. Email: [email protected]