Linking usage and shopping: How value experiences can distinguish consumers

Journal of Retailing and Consumer Services 30 (2016) 165–174

Contents lists available at ScienceDirect

Journal of Retailing and Consumer Services journal homepage: www.elsevier.com/locate/jretconser

Linking usage and shopping: How value experiences can distinguish consumers Gicquel Inès a, Castéran Herbert b,n a IUT de Colmar (University of « Haute-Alsace »), Research fellow at the Beta UMR 7522, Professional contact: 34 rue du Grillenbreit BP 50568, 68008 Colmar cedex, France b EM Strasbourg Business School (Strasbourg University), Professional contact: 61, avenue de la Forêt-Noire, 67085 Strasbourg Cedex, France

art ic l e i nf o

a b s t r a c t

Article history: Received 31 March 2015 Received in revised form 30 November 2015 Accepted 9 January 2016

This study uses the context of a ready-to-wear market to analyze the value of two consumer experiences, usage and in-person shopping. A logit model applied to 374 questionnaires highlights the relationships between the value dimensions of each experiment. This research demonstrates the link made by consumers between these two moments of consumption. Consistent with shopper typologies established by literature, the study reveals three classes of consumers. One class is shown to highly value sign and selfexpression of usage and the utility dimension of the shopping experience, which questions the overall purchase experience. The study proposes some measurement instruments and suggests further research to address this specificity. & 2016 Elsevier Ltd. All rights reserved.

Keywords: Shopping Usage Typology Value Experience

1. Introduction The maximization of customer value is often seen as the ultimate goal for firms, along with shareholder value (Bolton et al., 2007; Woodruff, 1997). To analyze value, focus recently moved from the producer and the production of goods to the usage of resources by the customer during usage processes (Gummerus, 2013). This can be illustrated, for example, by the development of many fashion-related social media applications (e.g Gilt, Gap Style Mixer1) which allow consumers to interact with retail brands, stores, and related elements. Consumers are showing a willingness to connect their various interactions to increase their global value. However, although retailers are recognizing that little things—ease of interaction with the firm, consistency of the message across all communication channels, provision of multiple buying channels (Grewal et al., 2009)—make big differences, they are failing to account for the link that exists in consumers’ minds between shopping and usage experiences. During usage, consumers select, drop, reject, and choose to wear items. While shopping, they mentally manipulate their associations with those items. Are the two experiences independent? Does a consumer consider each experience without any representation or any memory about items already owned? Studies of shopper experiences have not yet n

Corresponding author. E-mail addresses: [email protected] (G. Inès), [email protected] (C. Herbert ). 1 http://www.gilt.com, https://itunes.apple.com/us/app/gap-stylemixer/id326347260 http://dx.doi.org/10.1016/j.jretconser.2016.01.014 0969-6989/& 2016 Elsevier Ltd. All rights reserved.

considered the effects of previous usage experiences. Shopper-oriented marketing refers to “the planning and execution of all marketing activities that influence a shopper along, and beyond, the entire path-to-purchase, from the point at which the motivation to shop first emerges through to purchase, consumption, repurchase, and recommendation” (Shankar et al., 2011, p. 29). In this sense, because shoppers become consumers after they make purchases, shopping and usage must be considered simultaneously to acknowledge and achieve advantages along the entire purchase path. This research seeks to establish a link between usage and shopping throughout the cycle. Researchers (Baron and Harris, 2008; Lusch and Vargo, 2012; Vargo and Lusch, 2004) have identified consumers as integrators of operant resources (physical, social, cultural) as they immerse themselves in experiences in the course of defining experiences and creating value and highlighted the importance of interaction. A consumer experience exists primarily to provide consumer value, which can be conceptualized in various ways (Boztepe, 2007). Value is widely used as a key indicator of behavior, and is the subject of intense research interest (Gallarza et al., 2011). The role of usage in the value generation process is still under examination (Iyengar et al., 2011; Datta et al., 2015). As a hidden source of value, it is drawing interest as a key factor in updating existing typologies of shoppers (Babin et al., 1994; Bellenger and Korgaonkar, 1980; Darden and Reynolds, 1971; Stone, 1954; Tauber, 1972; Westbrook and Black, 1985), and is regarded as the starting point of the shopping trip (Buttle, 1992). However, most research focuses on

166

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

the cognitive approach of the consumer (Puccinelli et al., 2009) and does not investigate the value attained through the connection between shopping and usage experience. This study investigates the value that consumers attain in the shopping and usage stages of their consumption. To bridge the gap between the values of usage and shopping, we assess and measure shopping and usage experiences values separately. By defining consumer values in this way, we seek to understand and track various types of consumer-shoppers. Our research focuses on the nature and mechanisms of the interaction between the shopping and usage experiences, from a consumer perspective. We use market data from the French ready-to-wear retail market. This market offers a suitable research context because the product types enforce the links between shopping and usage. Furthermore, the market relies strongly on interactions (Murray, 2002; Thompson and Haytko, 1997). Using dimensional measures of shopping and usage experience values, our study constructs two consumer typologies (shopping and usage) and establishes a link between dimension values of each experience by using a logit model to explain consumer classification. We adopt an inductive approach to reexamine issues related to perceived value typology (Ormerod, 2010; Tellis and Gaeth, 1990). We identify three classes of consumers. In addition to the anticipated opposite classes of “enthusiasts” and “apathetics,” we find a third class, the “pragmatics”, that highly values the usage experience and the utility dimension of the shopping experience. For this class, the shopping experience is associated with staying connected to fashion, rather than an interest in shopping itself. This is a new vision of usage value that questions the overall purchase experience.

2. Theoretical background According to Kwortnik and Ross (2007), experience is composed by “fusing tangible (sensory) and intangible (symbolic) attributes co-produced by consumer and marketer to create an event that is pleasurable, meaningful and memorable.” Experience is characterized by a set of interactions between a customer and a product, a company, or part of its organization (Gentile et al., 2007). The entire experience includes search, purchase, consumption, and after-sale phases (Verhoef et al., 2009). Holt (1995) and Holbrook (1999) conceptualize perceived consumer value as a result of an interaction with a product during the course of such an experience. Literature highlights both the theoretical and managerial potential of perceived value (Arnould, 2014; Karababa and Kjeldgaard, 2014; Rivière and Mencarelli, 2012) but also recognizes the difficulty of developing an integrated theory of value. Research shows retailers who use a “store as the brand” strategy should continue to invest in creating a specific, unique shopping experience for their target customers. From a consumer's viewpoint, obtaining value is a fundamental goal of all successful exchange transaction (Holbrook, 1999). Consumer value can help predict the future behavior of consumers (Prentice, 1987). Consumer perceived value is better suited than satisfaction or loyalty for measuring customer preference for the point-of-sale over time because it mitigates the impact of occasional shortcomings in quality of service (Antéblian et al., 2013; Berry and Carbone, 2007; Carpenter, 2008; Chaudhuri and Ligas, 2009). In order to measure value, Evrard and Aurier (1996) recommend combining a functional theory of attitudes (Herek, 1986, 1987) with the theory of value (Holbrook, 1999; Holt, 1995; Lai, 1995; Richins, 1994; Sheth et al., 1991). They complete the initial works of Herek (1986, 1987) and Katz (1960) on attitude (Lutz, 1991).This larger

framework adds the consumer–object relation (Evrard and Aurier, 1996) to overall experience evaluation (Aurier et al., 2004) in a factorial design in which components of value are defined from the intersection of the fundamental dimensions of experience. Six components describe the consumer–object relation (Aurier et al., 2004): (1) utilitarian value (benefits the consumer receives from using the products together), (2) value of knowledge (expertize gained through the interaction with the object and other consumers), (3) stimulation value (when the experience offers interest during the shopping process), (4) self-expression value (opportunity for the consumer to express something personal), (5) social value (obtained through interactions with other people), and (6) spirituality value (self-reflection in a changing world). The nature of the value dimensions is important because the structure of the experience and links between experiences across the shopping cycle can have emergent effects. Consumers who differ in certain traits may develop different relationships during their consumer–object experiences. Our research goal is to assess the link between shopping and usage experiences. To test for the existence and nature of this link, it is necessary to identify shopper and user typologies. Stone (1954) identified four main types: economic shopper, personalization seeker, ethical shopper, and apathetic shopper. Darden and Reynolds (1971) provide external validation for Stone's (1954) typology and suggest a shopping orientation perspective, featuring utilitarian and recreational modes. Babin et al. (1994), in their discrete evaluation scale for shopping experiences, include hedonic (Arnold and Reynolds, 2003) and utilitarian motivations and identify six groups of shoppers: entertainers, optimizers, apathetic shoppers, smart shoppers, smart shoppers interested in hedonic aspects, and shoppers with unknown motivations. Three categories of shoppers remain constant across the various classifications: apathetic, social, and economic. Usage and shopping are closely related processes in the consumption cycle. As noted by Buttle (1992), people try to account for shopping behavior logically: shopping trips result from external causes and for practical reasons, linked to usage. Therefore, we explore the mechanisms of experience interactions throughout the shopper typologies. Reexamination of the typologies is necessary to determine which remain stable and which need readjustment, to account for usage values and the evolution of the market.

3. Data and methodology By using a snowballing technique from a random initial group of 250 French respondents, we collected 374 online questionnaires during May 2010. This approach supported communication with each member of a large population. The study sample is predominantly female (77%), from urban or suburban locations (90%). Single-person households represent one-third of the sample; higher socio-professional categories represent more than the half (56%). Although this sample is not perfectly representative of the population, it allows focus on our main target (cf. Appendix A). Although Davis and Hodges (2012) suggest a holistic perspective, built on previous works (Babin et al., 1994; Diep and Sweeney, 2008; Kim, 2002; Mathwick et al., 2001), findings on shopping value are inconsistent and unreliable. Therefore, we have adapted an integrated approach to determining a measurement scale for consumption value, by applying two scales that have been validated for shopping and usage experience in the French retail ready-to-wear market (cf. Appendix B). Fornell and Larcker's (1981) criteria are used and met for the validation, the factor loadings are greater than 0.5 and R² is greater than 0.1 (cf. Appendices C and D). We adopt the readily available indicators of Aurier et al., 2004 and Evrard and Aurier (1996) that reflect Herek's

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

4 3.1 3

4.7 4.7

4.7

5 3.5

3.2 3.3

167

3.4

3.7

2.6

Shopping

2

Use 1 0 Spirituality Knowledge & Social Link

Sign

Value

Utilitarian & Systemic

Fig. 1. Means of use and shopping dimension.

7 6 5 4 3

Apathetic people Pragmatists

2

Enthusiasts

1

7 6 5 4 3

Apathetic people

2

Pragmatists

1

Enthusiasts

0

USpirit3 USystem20 UValue3 UValue1 USocLnk4 USocLnk2 USocLnk3 UKnowl4 UKnowl6 UKnowl1 UCumSat3 UCumSat1 USystem4 USystem21 USystem11 USystem7 USign5 USign3 USpirit4 USign4 USpirit2

(1986, 1987) theory of functional attitudes. Confirmatory analysis results in identification of dimensions for each experience. We compare the means for each value dimension obtained from consumers regarding their shopping and usage experiences, as shown in Fig. 1. Our results show usage tends to exhibit higher values than shopping. Consumers appear to emphasize personal reflection and coherence in the clothing retail environment. Each dimension is characterized by multiple items (AENG scale). Utility, sign, social link and knowledge, self-expression, experiential arousal, and spirituality (thoughts about life that a consumer may evoke during a consumption situation) are identified as the components of global perceived value. These components differ slightly from one situation to another. For example, experiential arousal does not exist during usage, and social link is adapted to the context of consumption (Figs. 2 and 3). We conduct two separate hierarchical classifications for shopping and usage experiences. Underlying consumer attitudes can be analyzed with classifications that provide a synthesized view of the information. An analysis of variance (ANOVA) supports the accuracy of this classification by showing significant differences between classes. The comparison between class belonging allows measurement of the consistency of usage and shopping experiences. We explain the consumer classification for each experience according to the dimension values of the other experience. The dependent variable is consumer classification (a categorical

Fig. 3. Item means by class for the Usage Experience.

variable) and the independent variables are scales. Three main approaches are possible in this case: discriminant analysis, multinomial probit model, and multinomial logit model. Discriminant analysis assumes independent variables are normally distributed, whereas the logit model makes no assumption about the distribution of independent variables (Baltas and Doyle, 2001). In contrast to the probit formulation, logit coefficients have direct interpretations in terms of odds ratio (Baltas and Doyle, 2001); we prefer the logit model, which identifies the probabilities of the outcomes of a categorical dependent variable, given a set of independent variables. We use two logit models to explain each consumer classification (for usage and shopping) according to the values of the other experience and to support analyses of the interactions between experiences. The explanatory variables X are the value dimensions from the other experience. All the value dimensions of shopping are tested to explain usage classification, just as the value dimensions of usage are tested to explain usage classification. The probability of belonging to class c among C classes is given by:

P (C ) =

e X ′ βc C

∑k = 1 e X ′ βk

The βc represents the coefficient vector of the explanatory variables X for the class c while βκ represents the coefficient vector for each class k among the c classes.

0

Fig. 2. Item means by class for the shopping experience.

168

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

4. Data analysis and results

Table 2 Significant differences across classes (p-value o .05).

4.1. Typologies according to experience values

Apathetics

Using hierarchical clustering on the basis of consumers’ perceived value for each dimension, we determine that, for each dimension, the optimal number of classes is three: apathetics, pragmatists, and enthusiasts. Both typologies are consistent (see Table 1). The strong links across classifications indicate 79% of consumers belong to the same groups for both their shopping and usage experiences. Usage experience thus seems to prompt shopping behaviors, and vice versa. Apathetics and pragmatists seem more similar than pragmatists and enthusiasts. As we would expect, we find no overlap between enthusiasts and apathetics. In terms of AENG scales, we observe the following differences: The χ2 tests were significant (p ¼.015). The ANOVA were significant at 1% (with the exception of two satisfaction items). According to classes, item differences are very significant. Apathetics and enthusiasts are opposite in valuing both experiences, while pragmatists try to take some advantage and pleasure from consumption situations. (we chose to eliminate the “social” denomination presented by literature, because it appears the most valued dimensions of experiences are not only social). Enthusiasts express high values for each dimension and live experiences more intensely. Pragmatists match apathetics with regard to social links and knowledge dimensions across usage and shopping experiences; they also match on the spirituality dimension for shopping and the sign dimension for usage. However, they are closer to enthusiasts on the utilitarian dimension for both consumption experiences. Shopping is a way for pragmatists to discover or try new products. In terms of usage, pragmatists consider clothing part of the overall environment. Apathetics express low consumption values overall. Table 2 summarizes the significant differences across the classes (χ2, p o.05) in terms of behavior and socio-demographic characteristics. As expected, apathetics exhibit low shopping and buying frequency. In socio-demographic terms, the apathetics include more men on average. Apathetics belong to a high socioeconomic category and place little value on the experience. In contrast, enthusiasts are mostly women without children. 4.2. The link between experiences We start with a multinomial logit model analysis of the usage experience by shopping items (Appendix E), before we conduct the analysis of the shopping experience by usage items. Each item of the explanatory dimension is introduced as an independent variable. We retain only significant variables. By construction, a multinomial logit model uses coefficient normalization for identification. It means that the coefficients of one class are fixed to 0; in our case, all the coefficients of enthusiasts equal 0. The coefficients of the logit regressions have to be interpreted as relative coefficients Table 1 Cross-table of both classifications from experiences. Shopping experience Usage experience

Apathetics Pragmatists Enthusiasts Total

Total

Apathetics

Pragmatists Enthusiasts

19.8% (74) 8.8% (33) 0% (0) 28.6%

3.5% (13) 31.9% (119) 6.2% (23) 41.6%

X-squared ¼355.51, df¼ 4, p-value o .01.

0% (0) 2.4% (9) 27.3% (102) 29.7%

23.3% 43.1% 33.5%

Pragmatists

Enthusiasts

Gender (Classes and gender: χ² value ¼34.95, df ¼ 2, p-value o .01) Women 51% (55) 81% (115) 91% (113) Familial status (Classes and familial status: χ²¼ 18.9, df ¼ 6, p-value o .01) Couple without 30% (32) 19% (27) 39% (48) children Single without 38% (41) 35% (50) 38% (47) children Couple with child 24% (26) 40% (57) 17% (21) (ren) Single with child(ren) 8% (9) 7% (10) 5% (6) Shopping frequency (Classes and snowball frequency: χ² value ¼ 83.85, df ¼6, p-value o .01) Less than once per 82% (88) 39% (55) 18% (22) month 1–2 times per month 14% (15) 30% (43) 28% (35) 2–3 times per month 4% (4) 18% (26) 27% (33) More than 3 times 0% (0) 13% (18) 28% (35) per month Clothes buying frequency (Classes and frequency: χ² value ¼129.41, df ¼ 6, p-value o .01) Less than once per 82% (88) 59% (84) 51% (63) month 1–2 times per month 18% (19) 33% (47) 29% (36) 2–3 times per month 0% (0) 5% (7) 11% (14) More than 3 times 0% (0) 3% (4) 9% (11) per month

with respect to enthusiast class. The logit model (Appendix E, Table E.1) explains the consumer classification of usage value by items from shopping value scale. The likelihood-ratio test statistic equals 502.8, with 42 degrees of freedom; the associated p-value is 0%, which implies the overall significance of the model. The results show good model fit: McFadden's R² equals.67. Empirically, 85% of the respondents are assigned in the same way, according to the logit model. The usage classification relies on the “social link and knowledge” and “spirituality” dimensions. Social link and knowledge seem more efficient in terms of moving apathetics to the enthusiast group, compared with the effect of shifting pragmatics to the enthusiast group. The underlying affiliation logics are comparable for the two classes: the signs of the coefficients are the same, and the loading rankings are quite similar. However if we carefully observe the coefficients for the “spirituality” dimension (items “going shopping gives the opportunity to put myself in question” and “after shopping, I often take time for thinking about myself”) they are smaller for pragmatists or even non-significant. Then, a low role of the “spirituality dimension” in shopping induces an apathetic usage. More precisely, introspection during shopping represents a source of differentiation in terms of usage between apathetics and enthusiasts. Shopping utility and arousal are not useful for distinguishing consumers during their usage experience; it is likely that the two experiences are temporally and geographically disconnected. In contrast, social links, knowledge, and the search for meaning are interdependent and predictive of usage. The logit model (Appendix E, Table E.2) explains the consumer classification of shopping value by items from usage value scale. The likelihood-ratio test statistic equals 490.4, with 30 degrees of freedom; the associated p-value is again 0%. McFadden's R2 equals .71, with 87% of observations assigned the same way. This good fit suggests consumer typologies are stable and effectively obtained from consumers’ value assessments. Furthermore, assigning consumers to usage classes according to their shopping evaluations reveals some pertinent differences across classes. The typology validates the existence of consumers’ experiential profiles,

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

extracted from the perceived values of shopping and using. Here again, apathetics and pragmatists can be distinguished through specific dimension activations. But the results are different to the results of usage classification. The utilitarian and systemic dimension has a non-trivial role. A low result of two usage items, “I like finding new ways of coordinating clothes”, and “I would be ready to buy new things to optimize the clothes I already own” implies a higher probability of an “apathetic” behavior. On the opposite side, a higher concern to “What I expect from my clothes is that many other things can be associated with” characterizes the apathetics whereas enthusiasts (by construction) and pragmatists show a non-significantly different from 0 coefficient for this item. The practical aspect, a passe-partout expectation for clothes usage induces an apathetic attitude during shopping. 4.3. Discussion of results This new typology of consumer-shoppers updates existing contributions. We confirm the permanence of enthusiast and apathetic groups and identify a new pragmatic group. By taking usage value into account, we reach a new understanding of the group formally known as “social” (e.g. Babin et al. (1994)). For members of this group, the activity of shopping is not in itself attractive, but is a way of staying connected to fashion. Pragmatists have a high utility value and a low social value for shopping, and a strong sign value for usage. This result shows the importance of simultaneously considering usage and shopping. The dimensions of perceived value retain their differences between classes and can be regarded as managerial value levels for each type of consumer, taking into account the details of the score reflecting the global estimation of value. The overall results suggest consumers grant ideological meaning to fashion and retail in general. There is a clear contrast between enthusiasts and apathetics with regard to the global value they obtain from shopping and usage. This difference is particularly acute for the spirituality dimension: enthusiasts treat commercial settings as a sort of resource for thinking about their position in the world and the image they want to communicate, whereas apathetics do not find the context relevant to any spiritual reflection. Overall, the spiritual dimension of consumption, associated with transforming the self to find meaning and stability in a commercial context, has a major influence on enthusiasts. Depending on the value dimension, pragmatists express a much subtler message. The findings related to utility and spirituality appear relevant, particularly for identifying the group of pragmatic consumers. Utility and its maximization are a greater concern for pragmatists than for enthusiasts. If we consider the details of the logit model coefficients, apathetics represent a group separated from the other two not by an intensity of dimension activation but by a question of nature of expectations, representations and, finally, behaviors. Our results show mobile, web, and in-store applications should enhance usage value to better address the pragmatic group through at least two ways: (1) a usage of future product consistent with already-purchased products and (2) a usage of future product linked with typical usage contexts. The more contexts provided, the more valuable the product. Because we find links that differ, moving from usage to shopping versus shopping to usage, we can frame the interactions between these two experiences. Fig. 4 presents the links identified by our analysis. The one-sided arrow indicates an impact of one dimension of the experience on an other one from the other experience, while a two-sided arrow indicates a reciprocal influence. The dimensions involved are not surprising, given their meanings for the consumer. Social link and knowledge, and spirituality (the way consumers evaluate life positioning) are hardly considered during both

169

Systemic value Usage experience

Social link and knowledege

Shopping experience

Sign value

Fig. 4. Shopping and usage experience interaction. A one-sided arrow indicates a significant influence of the dimension of one experience on the other one while a two-sided arrow indicates a significant reciprocal influence.

experiences because they are strongly connected to the preparation of social life and conformity to roles (Goffman, 1959). For the same reasons, the way the consumer evaluates sign value during shopping is more or less important during further usage; sign value predicts experience type of value. Conversely, consumers try to get the most from what they have, taking advantage of the system of utility provided by the products as a whole. Consumers try to improve their benefit/loss ratio, that is, their return on investment. This is an important dimension for distinguishing shoppers from their usage value.

5. Conclusion Our conclusions remain consistent with those of typology literature. We add to the literature, however, by showing how typologies are established and providing more details about how usage influences shopping. Our research offers both academic and managerial insights. From an academic perspective, usage experience value paid little interest for the moment from academics even if usage conceptualization regains important attention recently (Pfisterer and Roth, 2015); and this study offers to bridge the gap between the two experiences. Indeed, usage can be taken into account to better understand the path-to-purchase. We see that apathetic and enthusiast groups have an equivalent evaluation of usage and shopping experiences (negative for the former, very positive for the latter), but in the pragmatic group, the shopping experience is dedicated to usage. The underlying idea (still to be confirmed) is that shopping experience is subordinated to usage experience. The usage value measure of the pragmatic group questions the overall purchase experience. We also establish the link between shopping and usage experiences. We find they are distinct, yet consumers gain some specific and linked values from both of them. Value from usage builds relationship to the point-of-sale. Understanding value from usage and its interaction with shopping value helps integrate consumers who are increasingly committed to their relationship with retailers. In our research context, the interactions between experiences reveal the shopping cycle is oriented by the search for meaning. On this strategic level, perceived value helps define and reexamine the segmentation process (Slater, 1997), as well as provide effective measurement tools for managers (Woodruff, 1997). Our proposed typology of consumer-shoppers is also coherent with existing typologies (Babin et al., 1994; Bellenger and Korgaonkar, 1980; Darden and Reynolds, 1971; Stone, 1954; Tauber, 1972; Westbrook and Black, 1985). By offering a corresponding typology of users, we specify the logic in terms of value dimensions that are distinct for each class of consumer but consistent through the two experiences. The profiles of apathetic, enthusiastic, and pragmatic consumers remain consistent across both experiences. These results have potentially significant implications for retailing, because retailers can adapt their commercial propositions to appeal to

170

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

these three profiles. However, within the same classes, experiences are interconnected, such that specific dimension values of each experience can predict the values for the other related experience. If retailers are interested in building and co-creating value with consumers, they should seek to enhance the dimensions that have greater impacts on consumer usage. This could be an interesting way of enriching experiences and delivering more consistent valuable aspects of each experience in relation to the other (as demonstrated by recent mobile applications). Sales training should incorporate aspects such as the ability to describe products in environments adapted to customers. The physical context allows salespeople to go beyond simple product descriptions (“it suits you well,” “it is a high textile quality”) to initiate real exchanges about product usages. Such information could also be integrated into written product descriptions, in addition to objective product characteristics (materials, washing instructions). This approach is a way of adding value to physical retail settings, by allowing close interactions between a seller and a customer. It represents a major asset for physical channels. The virtual network serves the physical network (especially for the garment category of products) and promotes the concept of ‘web to store,’ in which fans make an appointment to share shopping time among friends, attend an event, or discuss and display product usage. The development of new applications that integrate historical purchase data, existing products, and typical usage contexts needs to be encouraged. It represents a new way of understanding customer behaviors and offering a quasi-personalized approach. Value creation depends on the ability to rely on consumers, products, and usage context, especially for the pragmatic group. On the specific interest of examining usage and shopping together, we can say that these two experiences are fairly linked and that value profiles can be stressed. These profiles are new for at least one category and enriched in every case of usage experience insertion.

Since the interrelationship between value creation and value perceptions remained understudied, this research brings to light that some dimensions are connected in different experiences of consumption and the retail firm can analyze which activities are vital for the creation of a competitive edge (Gummerus, 2013). Perceived value takes into account the consumer's long-term relationship with the product and with stores in general. It exerts a positive and direct effect on positive word of mouth and loyalty behavior (Gallarza et al., 2011; Johnson et al., 2006). 5.1. Limitations and further research To gain greater external validity, this study should be replicated in other activity sectors with larger samples and in virtual networks to take advantage of all touchpoints with the consumer, including mobile devices and social networks (Blázquez, 2014), even if physical retail is dominant ( it still concentrates around 92% of transactions in developed countries). More specifically, comparison between from real and virtual samples could add to our approach to enrich the omni-channel and cross-channel issues as well. Additional research could consider the potential influence of involvement on social links and knowledge. We find the search for meaning in the commercial world is a key distinction of consumers; this spiritual dimension may also depend on the way people represent themselves in interactions with others. For people with fragile self-representations (e.g., younger versus older people), retail markets offer the appealing ability to deliver useful meanings in the course of social interactions. Further, sizes of consumer classifications should be precisely measured to anticipate the efficiency of new actions (e.g. applications). This efficiency could be also assessed by taking into account timing of last purchase, loyalty, and purchase frequency, to estimate customer lifetime value.

Appendix A. Sample Characteristics

Gender Female Residence Suburban Rural Urban Family situation Couple without child Single without child Couple with child(ren) Single with child(ren) Socioeconomic status Farmers Self-employed High socioeconomic status Middle status Low status Retired Jobless Age Average Standard deviation 1st quartile Median 3rd quartile Maximum Minimum

77% 12% 14% 74% 29% 38% 27% 6% 1% 3% 47% 5% 21% 2% 21% 33 12 23 30 40 70 15

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

When did you go for the last time to XX? Not more than one week later More than one week later More than two weeks later More than one month later More than three months later More than six months later Latest shopping trip Not more than one week later More than one week later More than two weeks later More than one month later More than three months later More than six months later How many times a month do you go shopping? Once to twice a month Two to three times per month More than three times per month Less than once a month How many times a month do you buy something to XX on average? Once to twice a month Two to three times per month More than three times per month Less than once a month How many times a month do you buy clothes on average? Once to twice a month Two to three times per month More than three times per month Less than once a month Amount spent during one shopping trip Average Standard deviation Last expenditure Average Standard deviation

171

41% 14% 18% 17% 7% 3% 41% 17% 14% 18% 3% 7% 28% 16% 13% 43% 28% 16% 13% 43% 27% 6% 4% 63% 119 € 126 € 135 € 229 €

Appendix B. Usage and Shopping Scales

AENG usage scale 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

Choosing a look gives me the opportunity to talk about it with my friends later. When people talk about looks, I love it. I like seeing many looks and then talking about it with my friends. I often listen to or look at shows talking about looks. I often read articles talking about looks on the Web or in magazines. I try to catch up with fashion trends. Overall, I am satisfied with my look. Looking at my expectations in terms of look, I am often disappointed. What I expect from my clothes is that many other things can be associated with them. I like seeing, after having bought new things, that they coordinate easily each other. I like finding new ways of coordinating clothes. I would be ready to buy new things to optimize the clothes I already own. My personality is very important for my clothes’ choices. Choosing a look offers me the opportunity to express my personality. I judge people looking at the way they are dressed. Wearing some clothes gives me the impression to be a little bit more than what I am. After having decided on a look, I often take time for thinking about myself. Choosing a look gives me the opportunity to put myself in questions. I like thinking that clothes I own represent a certain amount of global value.

ULiensoc2 ULiensoc3 ULiensoc4 UConnai4 UConnai6 UConnai1 USatcum3 USatcum1 USystem4 USystem21 USystem11 USystem7 USigne4 USigne5 USigne3 USpirit4 USpirit2 USpirit3 USystem20

172

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

Overall deciding for a look is worth the sacrifices I make. Overall, I think that choosing a look deserves spending energy on it. AENG shopping scale

UValeur3 UValeur1

20. 21.

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26.

I like shopping and then talking about it with my friends. Shopping gives me the opportunity to talk about it with my friends later. When people talk about shopping, I love it. I often read articles talking about fashion brands on the Web or in magazines. I try to catch up with shopping trends. I often listen to or look at shows talking about looks. After shopping, I often take time for thinking about myself. Going shopping gives me the opportunity to put myself in questions. After having elaborated on different styles seen during shopping, I often take time for thinking about myself. Shopping gives me the opportunity to have some thoughts about my life. Looking at my expectations, I am often disappointed by stores where I shop. I am more often disappointed than happy with the stores where I shop. Overall, I am satisfied with the stores where I shop. I can get an idea about somebody from the stores where he/she shops. I judge people from the stores where they shop. Going shopping gives me the opportunity to try on clothes. Going shopping helps me elaborate about looks I could wear. Going shopping is the way to keep in touch with new products. Going shopping helps me imagine all the different styles I could wear. Overall, going shopping is worth the sacrifices I make Overall, going shopping is worth the time and money I spend on it. Overall, going shopping is worth the energy I spend on it. When I look at clothes in stores, I feel good about myself. When I look at clothes in stores, I am totally absorbed. Going shopping is a way to escape from everyday life. Going shopping makes me euphoric.

Appendix C. Confirmatory analysis for Usage AENG scale See Table C.1 and Table C.2

Table C.1 Fornell-Larcker Discriminating Validity Check for Usage Value Experience. Self Expression

Self Expression Social Link and Knowledge Global Perceived Value Spirituality Utility

Social Link and Knowledge

Global Perceived Value

0.73 0,43

0.8

0.56

0.67

0.83

0.50 0.48

0.46 0.52

0.46 0.53

Spirituality

Utility

0.82 0.37

0.81

MLiensoc4 MLiensoc2 MLiensoc3 MConnai6 MConnai1 MConnai4 MSpirit2 MSpirit3 MSpirit5 MSpirit1 MSatcum1 MSatcum2 MSarcum3 MSigne1 MSigne3 MUtil3 MUtil1 MUtil2 MSystem15 MValeur3 MValeur4 MValeur1 MStimul3 MStimul4 MStimul2 MStimul8

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

173

Table C.2 Reliability and Convergent Validity Issues of Value Experience.

Standard Self Expression Social Link and Knowledge Global Perceived Value Spirituality Utility

AVE

Reliability

Cronbach Alpha

Rhô of Convergent Validity

Jöreskog Rhô

40.5 0.53 0.64 0.69 0.67 0.65

4 0.7 0.77 0.91 0.87 0.86 0.85

4 0.7 0.55 0.89 0.78 0.75 0.73

40.5 0.53 0.64 0.69 0.78 0.65

4 0.7 0.77 0.91 0.87 0.88 0.85

Appendix D. Confirmatory analysis for Shopping AENG scale See Table D.1 and Table D.2

Table D.1 Fornell-Larcker Discriminating Validity Check for Shopping Value.

Self Expression Social Link and Knowledge Environment stimulation Global Perceived Value Spirituality Utility

Self Expression

Social Link and Knowledge

Environment Stimulation

Global Perceived Value

Spirituality

Utility

0.93 0.39 0.38 0.40 0.46 0.32

0.85 0.73 0.69 0.56 0.61

0.84 0.73 0.59 0.65

0.92 0.55 0.61

0.87 0.44

0.81

Table D.2 Reliability and Convergent Validity Issues of Value Experience.

Standard Self Expression Social Link and Knowledge Environment Stimulation Global Perceived Value Spirituality Utility

AVE

Reliability

4 0.5 0.86 0.72 0.70 0.84 0.75 0.65

4 0.7 0.92 0.94 0.91 0.94 0.92 0.88

Cronbach Alpha 4 0.7 0.83 0.92 0.86 0.91 0.89 0.82

Rhô of Convergent Validity

Jöreskog Rhô

4 0.5 0.86 0.72 0.705 0.84 0.75 0.61

4 0.7 0.92 0.94 0.905 0.94 0.92 0.82

Appendix E. Logit models See Table E.1 and Table E.2

Table E.1 Logit model: usage by shopping items. Apathetics

Constant I try to keep in touch with shopping trends I like shopping and then talking about it with my friends I can make an idea about somebody from the stores where he/she shops. Going shopping gives me the opportunity to put myself in questions After shopping, I often take time for thinking about myself

Pragmatists

b

SE

Sig.

b

SE

Sig.

24.08  2.62

4.09 .50

.00 .00

18.03  1.94

3.87 .45

.00 .00

 1.41

.41

.00

 .52

.26

.05

 .86

.32

.01

 .68

.27

.01

 1.38

.49

.00

 .18

.28

.52

 1.45

.52

.01

 1.19

.38

.00

174

G. Inès, C. Herbert / Journal of Retailing and Consumer Services 30 (2016) 165–174

Table E.2 Logit model: shopping by usage items Apathetics

Constant I often listen to or look at shows talking about looks I often read articles talking about looks on the Web or in magazines Choosing a look gives me the opportunity to talk about it with my friends later After having decided on a look, I often take time for thinking about myself I like finding new ways of coordinating clothes What I expect from my clothes is that many other things can be associated with them I would be ready to buy new things to optimize the clothes I already own Overall deciding on a look is worth the sacrifices I make

Pragmatists

b

SE

Sig.

b

SE

Sig.

41.98  1.44  1.60  2.05  2.13  2.16 1.02  1.27  2.25

8.31 .45 .45 .47 .57 .65 .43 .39 .55

.00 .00 .00 .00 .00 .00 .02 .00 .00

32.03  1.02  .98  1.28  1.60  1.32 .57  .77  1.59

8.09 .33 .32 .39 .50 .61 .39 .34 .49

.00 .00 .00 .00 .00 .03 .14 .02 .00

References Antéblian, B., Filser, M., Roederer, C., 2013. Consumption experience in retail environments: a literature review. Rech. Et. Appl. En. Mark. (Engl. Ed.) 28 (3), 82–109. Arnold, M.J., Reynolds, K.E., 2003. Hedonic shopping motivations. J. Retail. 79, 77–95. Arnould, E., 2014. Rudiments of value praxeology. Mark. Theory 14 (1), 129–133. Aurier, P., Evrard, Y., N’Goala, G., 2004. Comprendre et mesurer la valeur du point de vue du consommateur. Rech. Et. Appl. En. Mark. 19 (32), 1–20. Babin, B.J., Darden, W.R., Griffin, M., 1994. Work and/or fun: measuring hedonic and utilitarian shopping value. J. Consum. Res. 20 (4), 644–656. Baltas, G., Doyle, P., 2001. Random utility models in marketing research: a survey. J. Bus. Res. 51, 115–125. Baron, S., Harris, K., 2008. Consumers as resource integrators. J. Mark. Manag. 24 (1– 2), 113–130. Bellenger, D.N., Korgaonkar, P.K., 1980. Profiling the recreational shopper. J. Retail. 56 (3), 77–92. Berry, L.L., Carbone, L.P., 2007. Build loyalty through experience management. Qual. Prog. 40 (9), 26–32. Blázquez, M., 2014. Fashion shopping in multichannel retail: the role of technology in enhancing the customer experience. Int. J. Electron. Commer. 18 (4), 97–116. Bolton, R.N., Grewal, D., Levy, M., 2007. Six strategies for competing through service: an agenda for future research. J. Retail. 83 (1), 1–4. Boztepe, S., 2007. User value: competing theories and models. Int. J. Des. 1 (2), 55–63. Buttle, F., 1992. Shopping motives constructionist perspective. Serv. Ind. J. 12 (3), 349–367. Carpenter, J.M., 2008. Consumer shopping value, satisfaction and loyalty in discount retailing. J. Retail. Consum. Serv. 15 (5), 358–363. Chaudhuri, A., Ligas, M., 2009. Consequences of value in retail markets. J. Retail. 85 (3), 406–419. Datta, H., Foubert, B., Van Heerde, H.J., 2015. The challenge of retaining customers acquired with free trials. J. Mark. Res. 52 (2), p217–p234. Darden, W.R., Reynolds, F.D., 1971. Shopping orientations and product usage rate. J. Mark. Res. 8 (4), 505–508. Davis, L., Hodges, N., 2012. Consumer shopping value: an investigation of shopping trip value, in-store shopping value and retail format. J. Retail. Consum. Serv. 19 (2), 229–239. Diep, V.C.S., Sweeney, J.C., 2008. Shopping trip value: do stores and products matter? J. Retail. Consum. Serv. 15, 399–409. Evrard, Y., Aurier, P., 1996. Identification and validation of the components of the person-object relationship. J. Bus. Res. 37, 127–134. Fornell, C.L., Larcker, D.F., 1981. Structural equation models with unobservable variables and measurement error: algebra and statistics. J. Mark. Res. 18 (3), 382–388. Gallarza, M.G., Saura, I.G., Holbrook, M.B., 2011. The value of value: further excursions on the meaning and role of customer value. J. Consum. Behav. 10 (4), 179–191. Gentile, C., Spiller, N., Noci, G., 2007. How to sustain the customer experience: an overview of experience components that co-create value with the customer. Eur. Manag. J. 25 (5), 395–410. Goffman, E., 1959. The Presentation of Self in Everyday Life. Anchor Books, New York. Grewal, D., Levy, M., Kumar, V., 2009. Customer experience management in retailing: an organizing framework. J. Retail. 85 (1), 1–14. Gummerus, J., 2013. Value creation processes and value outcomes in marketing theory: strangers or siblings? Mark. Theory 13 (1), 19–46. Herek, G.M., 1986. The instrumentality of attitudes: toward a neofunctional theory. J. Soc. Issues 42 (2), 99–114. Herek, G.M., 1987. Can functions be measured? A new perspective on the functional approach to attitudes. Soc. Psychol. Q. 50 (4), 285. Holbrook, M.B., 1999. Consumer Value: A Framework for Analysis and Research. Sage Publications, Newbury Park, CA, pp. 21–71.

Holt, D., 1995. How consumers consume: a typology of consumption practices. J. Consum. Res. 22 (1), 1–16. Iyengar, R., Van den Bulte, C., Valente, T.W., 2011. Opinion leadership and social contagion in new product diffusion. Mark. Sci. 30 (2), 195–212. Johnson, M.D., Herrmann, A., Huber, F., 2006. The evolution of loyalty intentions. J. Mark. 70 (2), 122–132. Karababa, E., Kjeldgaard, D., 2014. Value in marketing: toward sociocultural perspectives. Mark. Theory 14 (1), 119–127. Katz, D., 1960. The functional approach to the study of attitudes. Public Opin. Quaterly 24 (2), 163–204. Kim, Y.K., 2002. Consumer value: an application to mall and Internet shopping. Int. J. Retail. Distrib. Manag. 30 (12), 595–602. Kwortnik, R.J.J.R., Ross Jr, W.T., 2007. The role of positive emotions in experiential decisions. Int. J. Res. Mark. 24, 324–335. Lai, A.W., 1995. Consumer values, product benefits and customer value: a consumption behavior approach. Adv. Consum. Res. 22 (1), 381–388. Lusch, R.F., Vargo, S.L., 2012. Marketing value. Mark. News 46 (6), 324–335. Lutz, R.J., 1991. The role of attitude theory on marketing. In: Harold, H., Kassarjan, H. H., Robertson, J.J. (Eds.), Perspectives in Consumer Behavior, fourth ed PrenticeHall, pp. 317–339. Mathwick, C., Malhotra, N.K., Rigdon, E., 2001. Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment. J. Retail. 77 (1), 39–56. Murray, J.B., 2002. The politics of consumption: a re-inquiry on Thompson and Haytko's (1997) ‘Speaking of fashion. J. Consum. Res. 29 (3), 427–440. Ormerod, R.J., 2010. Rational inference: deductive, inductive and probabilistic thinking. J. Oper. Res. Soc. 61, 1207–1223. Pfisterer, L., Roth, S., 2015. Customer usage processes A conceptualization and differentiation. Mark. Theory 15 (3), 401–422. Prentice, D., 1987. Psychological correspondence of possessions, attitudes and values. J. Pers. Soc. Psychol. 53 (6), 993–1003. Puccinelli, N.M., Goodstein, R.C., Grewal, D., Price, R., Raghubir, R., Stewart, D., 2009. Customer experience management in retailing: understanding the buying process. J. Retail. 85 (1), 15–30. Richins, M.L., 1994. Valuing things: the public and private meanings of possessions. J. Consum. Res. 21 (3), 504–521. Rivière, A., Mencarelli, R., 2012. Towards a theoretical clarification of perceived value in marketing. Rech. Et. Appl. En. Mark. (Engl. Ed.) 27 (3), 97–122. Shankar, V., Inman, J.J., Mantrala, M., Keilay, E., Rizley, R., 2011. Innovations in shopper marketing: current insights and future research issues. J. Retail. 87 (1), 29–42. Sheth, J.N., Newman, B.I., Gross, Barbara L., 1991. Consumption Values and Market Choices: Theory and Applications. South-Western Publishing, Cincinatti, OH.. Slater, S.F., 1997. Developing a customer value-based theory of the firm. J. Acad. Mark. Sci. 25 (2), 162–167. Stone, G.P., 1954. City shoppers and urban identification. Observation on the social psychology of city life. Am. J. Sociol. 60, 36–45. Tauber, E.M., 1972. Why do people shop? J. Mark. 72 (36), 46–59. Tellis, G.J., Gaeth, G.J., 1990. Best value, price-seeking and price aversion: the impact of information and learning on consumer choices. J. Mark. 54, 34–45. Thompson, C.J., Haytko, D.L., 1997. Speaking of fashion: consumers’ uses of fashion discourses and the appropriation of countervailing cultural meanings. J. Consum. Res. 24 (1), 15–42. Vargo, S., Lusch, R., 2004. Evolving to a new dominant logic for marketing? J. Mark. 68 (1), 1–17. Verhoef, P.C., Lemon, K.N., Parasuraman, A., Roggeveen, A., Tsiros, M., Schlesinger, L. A., 2009. Customer experience creation: determinants, dynamics and management strategies. J. Retail. 85 (1), 31–41. Westbrook, R.A., Black, W.C., 1985. A motivation-based shopper typology. J. Retail. 61 (1), 79–103. Woodruff, R.B., 1997. Customer value: the next source for competitive advantage. J. Acad. Mark. Sci. 25 (2), 139–153.