Stylish Alliances: Co-branding sportswear and luxury fashion brands as an effective marketing strategy for improving customer equity
Emmy de Visser - 10875611 Marketing Thesis: Final Draft
MSc. in Business Administration - Marketing Track Amsterdam Business School / University of Amsterdam
Supervisor: Drs. Ing. A.C.J. Meulemans Second Reader: Drs. F. Slisser
“A fashion that does not reach the streets is not a fashion.” -Coco Chanel
Acknowledgments
I love fashion. I developed my fashion sense ever since I moved from the Netherlands to the United States for my last year of high school, where I was also privileged to pursue a bachelor and a master degree. I adjusted my style to the one in this new country by visiting big malls that displayed clothes reflecting the latest trends in the fast-moving fashion industry.
As I was expanding my knowledge about fashion in order to pursue a potential marketing career in this industry, I decided to educate myself to get a quick overview of the inner workings of this business. Through a ten day summer school course in fashion management at the Antwerp Management School in Belgium, in 2014, I became aware that there is lack of scientific
literature in fashion management, despite the global size of the fashion industry. My objective was to study this topic in more depth and bring insights to my new career in the field of fashion marketing, which revolves around a highly dynamic industry that can greatly benefit from this type of research.
I would like to thank my family, specifically my brother for his academic expertise, and friends for supporting me throughout my graduate school journey. Lastly, I would like to thank my supervisor Toon, who helped me through my thesis process with his kind patience and advice.
Abstract
Due to the high-paced and global competitive marketing landscape, the sportswear and luxury fashion industry often engage in short-term opportunistic co-branding collaborations to create buzz and add value to their brands. While co-branding has been studied extensively for other product categories, it is not clear whether co-branding between sportswear and luxury fashion industries is an effective marketing strategy. This study was designed to assess whether co-branding is an effective marketing strategy for these two different industries using the customer equity model. One-hundred and sixty Dutch women participated in an online survey to assess the key drivers of customer equity for a single sportswear brand (Adidas), a single luxury fashion brand (Chanel), and two fictitious co-brands (Adidas & Gucci and Nike & Chanel). Results showed that for value equity, the two co-brands were assessed equally or higher on price and quality compared to the single fashion brands. Co-branding did not result in a higher assessment of brand equity and retention equity, most likely due to the fact that the co-brands were fictitious and were not positioned as a brand or had retention programs in place. A principal component analysis further confirmed that rather than the conventional three components of customer equity, survey items loaded on only two components that explained most of the variance. In the early stages of a co-branding collaboration, the customer equity model can therefore be an effective way to assess such a relationship, provided the focus is on value equity when the brand has not been established yet. Overall, this research provides strong evidence that co-branding between sportswear and luxury fashion brands is a promising marketing strategy.
Statement of Originality
This document is written by Emmy de Visser who declares to take full responsibility for the content of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the
Table of Contents Acknowledgments 2 Abstract 3 Statement of Originality 4 1. Introduction 7 2. Literature Review 11
2.1 Cobranding: A global trend, but understudied 11
2.1.1 Co-branding Origins 11
2.1.2 Purpose and Definition 11
2.1.3 Benefits and Risks 13
2.1.4 Co-branding research is lacking for fashion 15 2.2 Customer Equity: A quantitative method to assess co-branding 16
2.2.1 The Customer Equity Framework 16
2.2.2 Value Equity 18
2.2.3 Brand Equity 19
2.2.4 Retention Equity 21
2.3 Research Question and Hypothesis 22
3. Method 23 3.1 Participants 23 3.2 Materials 24 3.3 Study Design 25 3.4 Measures 25 3.5 Procedure 26 3.6 Analysis 27 4. Results 29 4.1 Sample statistics 29 4.1.1 Income 29 4.1.2 Education 30 4.1.3 Age 30 4.1.4 Purchase Behavior 31
4.2 Reliability Analysis and Computing scale means 33
4.3 Value Equity Analysis 33
4.4 Brand Equity Analysis 34
4.5 Retention Equity Analysis 36
4.6 Overall Customer Equity Analysis 37
4.7 Relative Importance Customer Equity 38
4.8 Principal Component Analyses 40
4.8.1 Principal Component Analysis All Items 40
4.8.2 Principal Component Analysis Nine Factors 41 4.8.3 Principal Component Analysis Importance Factors 43
5. Discussion 45
5.1 Summary of results 45
5.2 Theoretical implications 46
5.3 Practical implications 49
5.4. Limitations and Future Research 52
6. Conclusion 54 6.1 Summary 54 6.2 Research Contributions 56 6.3 Future Directions 56 References 59 Appendices 64
Appendix A Pre-test Fashion Brands 64
Appendix B Pre-test Outcomes 66
Appendix C Fashion Brands Survey 67
Appendix D PanelClix Screenout Page 78
Appendix E Customer Equity Drivers Importance Calculations 79 Appendix F Principal Component Analysis Importance Factor Ratings 80
1. Introduction
The popularity of fashionable “activewear” (Schuessler, 2015), also called “athleisure” (Schiffer, 2015) is growing fast as people are simultaneously seeking clothes for style, comfort and convenience (Thomas, 2010: Lee & Burns, 2014; Singh & Pattanayak, 2014). Both the sportswear industry and the luxury fashion industry are positioning themselves to take advantage of this trend. The sportswear industry creates high-end sports fashion that consumers not only enjoy wearing for sport activities, but for everyday use as well (Ko, Taylor, Sung, Lee, Wagner, Navarro, & Wang, 2012). Consistent with this consumer-oriented approach, luxury fashion brands seek a new and broader customer base by trying to make fashion more attractive and affordable for everyone (Rollet, Hoffmann, Cost-Manière, & Panchout, 2013).
With global consumers becoming more sophisticated by following the latest trends online, according to Ko et al. (2012), co-branding can be used as a strategic tool to further promote luxury fashion brands to mass market segments by enhancing their reputation (Rollet et al., 2013), adding unique value and sensory appeal (Kim, Ko, Lee, Mattila, & Kim, 2014) and effectively adapt to emerging trends in fast fashion (Lee, Ko, Tikkanen, Phan, Aiello, Donvito, & Raithel, 2014). Even though luxury fashion brands may not follow the same fast fashion cycle pace, something that is fashionable will eventually loose popularity over time (Barnes, 2013). Given the new trend of activewear, sporty clothing for everyday use, sportswear brands should consider collaborations with luxury fashion brands. Luxury brands can add a stylish credit to the sportswear brand and expand the use of sportswear items to a diverse set of activities beyond athletics. A potential negative side of the co-branding strategy may be that it creates opposing brand images (Wu & Chalip, 2014) and it is therefore not clear whether these alliances are successful or not (Wu & Chalip, 2014).
Co-branding is important because more companies are engaging in this kind of practice to keep their brands fresh and relevant. Creating a co-brand is a key marketing decision that can have both major beneficial and disadvantageous consequences for either brand. Co-branding is highly beneficial when the collaboration is successful because both brands add value to their name. For instance, H&M collaborated with Karl Lagerfeld and produced a fashion collection that was highly successful by adding class to a normally ordinary product (Rollet et al., 2013). But co-branding is not without risks. For instance, the initial collaboration between H&M and Madonna was not successful because the collection produced from this collaboration may have resembled the type of clothes that H&M normally offers (Rollet et al., 2013). Co-branding marketing in fashion is therefore complex and challenging primarily due to its impulsive fast-paced nature and the multiple factors that influence fashion (Barnes, 2013). Investigating which factors are most predictive to determine the success of a co-brand is therefore an important and promising area of research.
Co-branding has been extensively studied in the context of other industries such as consumer electronics, advertising and food (Helmig, Huber, & Leeflang, 2008). Notably lacking from this research area is the fashion industry. In addition, when co-branding is studied, the customer equity of the brand is not typically evaluated. Applying the customer equity model to the fashion industry may provide unique insights into fashion marketing because this industry is largely driven by how customers feel about their product. This thesis presents a significant step towards addressing these two gaps.
This thesis will examine the effectiveness of various co-branding strategies of sportswear and luxury fashion brands using the customer equity model previously applied to many other industries (Rust, Zeithaml, & Lemon, 2000, p. 170). Evaluating the customer equity of a
combined sportswear and luxury fashion brand is an important step towards evaluating the true value of a co-brand in the fashion industry. Customer equity consists of three drivers including value equity, brand equity and retention equity (Rust et al., 2000, p. 9). This thesis will examine which of these drivers are most sensitive and predictive to assess customer equity of co-brands through the following research question: To what extent do co-branding relationships between sportswear brands and luxury fashion brands enhance customer equity?
Sub questions that can help support answering the above mentioned research questions are: - What is co-branding?
- What is customer equity?
- What is the impact of co-branding on value equity? - What is the impact of co-branding on brand equity? - What is the impact of co-branding on retention equity? - What is the impact of co-branding on customer equity?
A standardized online survey will be used to examine attitudes towards possible new co-branding strategies. Attitudes will be derived from the sample survey for the airline market by Rust et al. (2000, p. 267), which they recommend to use as a guideline when developing the customer equity survey tool to a particular industry of interest. Separate groups will be exposed to different co-brand combinations and will be asked about items that assess value, brand, and retention equity. Attitudes towards single brands will also be examined. The survey will be distributed through a professional online marketing research company PanelClix, who will seek out a stratified panel sample consisting of Dutch women from metropolitan areas in the
The contribution of this work will be to assess whether co-branding is a beneficial marketing strategy and whether major brands should consider this type of strategy. In addition, the thesis will examine which parts of the customer equity model are most relevant to the study of co-brands, so future marketing researchers can focus on assessing the dimensions of the customer equity that are most relevant. Ultimately, the results of this study can be used to pre-assess whether certain co-branding partnerships are more beneficial than others potentially preventing suboptimal collaborations and maximizing the chances that a co-brand strategy will be effective and profitable.
The thesis will begin with a thorough literature review of co-branding as it applies to the sportswear and luxury fashion industries. Then, the method of the study will be described that details the creation of the pre-assessment, the full survey as well as the sample used to complete the study. Results will then be explained followed by a meaningful discussion. The thesis will end with a conclusion and actionable recommendations will be made for other researchers, marketing executives and the fashion industry at large.
2. Literature Review 2.1 Co-branding: A global trend, but understudied
2.1.1 Co-branding Origins
Historically, co-branding has been a business strategy for the last 60 years (Rollet et al., 2013). Co-branding has been extensively studied in the industries of fast moving consumer goods, grocery products and the consumer electronics market (Oeppen & Jamal, 2014). This marketing strategy has been more often studied across rather than within industries, mainly with a focus on functional rather than a pleasurable appeal, such as luxury items (Oeppen & Jamal, 2014). The main two co-branding topics that have been studied have focused on how customers make sense of the host brands in relation to their associations of the co-brands and the other way around. Secondly, the effectiveness of co-branding has been studied in relation to other brand strategies of innovative products (Leuthesser, Kohli, & Suri, 2003).
Co-branding has been a popular branding phenomenon in the luxury and fashion industry for only the past three decades (Uggla & Asberg, 2010; Rollet et al., 2013). Even though co-branding is a popular co-branding strategy and different co-co-branding classifications exist in practice, these concepts unfortunately lack academic rigor with opposing outcomes (Wu & Chalip, 2014).
2.1.2 Purpose and Definition
One of the reasons why academic rigor may be lacking in the study of co-branding in marketing, is because of its complex nature as it goes under the guise of many labels such as brand extension (Helmig et al., 2008) brand collaboration (Uggla & Asberg, 2010) or
co-marketing alliance (Ahn, Kim & Forney, 2010), brand alliance (Lanseng & Olson, 2012) to name a few.
Another reason may be, because a collective academic agreement on the specific characterization of co-branding has not been established (Leuthesser et al., 2003). The reason why a consistent description of co-branding may still be absent is because it has not been claimed by a specific marketing field or a research area that easily fits well with other scientific areas, such as consumer behavior or strategic brand management (Uggla & Asberg, 2010).
Besides the controversy regarding what co-branding is all about, the accepted definition for the purpose of this thesis is as follows: “associating a single product with two or more brands” (Rollet et al., 2013, p. 58). Even though co-branding is not a uniformly applied strategy, two main types of co-branding have been academically studied. Scholars often make a
distinction between “ingredient co-branding” (Leuthesser et al. 2003, p. 36) in which one brand becomes a component of the other, such as the DSM Dyneema® fiber that was used in a fashion collection by Tony Cohen (Koning, 2012) and “symmetrical co-branding” (Uggla, 2004, p.106) in which both brands share an equal contribution to the brand, for instance the Dutch coffee pad machine Senseo® by Philips is a co-brand because of the technology incorporated by electronics company Philips and the coffee expertise added by the coffee and tea company Douwe Egberts.
The origins of co-branding between two brands lies with the fit of the product category (Lanseng & Olson, 2012, p.1108). The most common form of co-branding form in the fashion industry happens to occur between luxury brands and fast fashion brands (Oeppen & Jamal, 2014). Although sportswear brands and luxury fashion brands seem to share the same fashion category, Wu & Chalip (2014) make a distinction between two separate apparel classifications. Therefore, the type of co-branding that will be discussed in this research can be identified as symmetrical co-branding (Uggla, 2004) in which both the sportswear and luxury fashion brands have an equal share in their collaboration.
2.1.3. Benefits and Risks
As the fashion industry is growing rapidly with an annual spending of $350 billion (Craik, 2013, p.7) academic expertise is vital to help the fashion industry remain its competitive edge, for which co-branding could greatly contribute as an innovative marketing strategy (Oeppen & Jamal, 2014). The purpose of co-branding is to form a strategic mutually beneficial alliance to create a new brand. Co-branding can be beneficial as it can attract new consumers (Rollet et al., 2013), add value to both brands than either can do alone (Rollet et al., 2013; Wu & Chalip, 2014) can help build status and differentiation compared to other brands, reduce
expenditures for a company by sharing research development and marketing communications costs and can serve as a promotional sales tool (Rollet et al., 2013).
On the contrary, if not executed well, co-branding can become a precarious marketing approach according to Uggla & Asberg (2010). First the original brand’s integrity can be damaged due to loss of control over the brand’s personality and its related images. Second, the brand can experience dilution if it is too involved in collaborating with other companies, through which overexposure can occur. A brand’s exposure may grow, but its vulnerability increases as well. Lastly, the brand could lose sight of the original intended clientele of the brand, which could potentially be reduced or lost.
2.1.4 Co-branding research is lacking for fashion
Despite the consistent application and popularity of co-branding in apparel marketing (Wu & Chalip, 2014), existing research has been sparse and the few studies that exist have found contradictory outcomes about influences of co-branding within the fashion industry (Rollet et al., 2013). For instance, Wu and Chalip (2014) showed mixed results for this type of co-branding strategy by finding an overall neutral outcome for men’s assessment of a shirt that was
co-branded with a fashion designer brand and a sportswear brand, but a negative outcome when women assessed the shirt on aesthetics, quality and cost. In contrast, Kim et al. (2014) concluded that even though co-branding can be beneficial for both luxury brands and fast fashion brands in different ways, managers should still be careful when applying co-branding due to its substantial risk of brand dilution, which can greatly reduce its value. One of the reasons the research
conducted to date reached opposite conclusions is because the nature of this field of inquiry is still exploratory and lacks rigorous investigation with controlled studies (Rollet et al., 2013; Kim et al., 2014; Oeppen & Jamal, 2014). Another reason is that collaborations between brands in the fashion industry are unpredictable in nature (Kim et al., 2014; Oeppen & Jamal, 2014) making it difficult for researchers to examine the precise impact of this strategy in a controlled manner. In addition, most of the co-branding literature mainly originated in the fast moving consumer goods and electronics market as a long-term research program (Oeppen & Jamal, 2014) and has only been peripherally studied in the fashion industry where such investigations are often used for short-term opportunistic collaborations instead (Rollet et al., 2013). Finally, there is limited research on brand extensions in the fashion luxury goods sector, despite the rapid growth and profitability of the sector and its trend-setting nature for the marketing field (Ko & Megehee, 2012; Miller & Mills, 2012). Moreover, the unique integrated co-branding relationship between sportswear and luxury fashion brands deserves further investigation because both brands are not competitors of each other, which is rare in the fashion industry (Oeppen & Jamal, 2014).All researchers who have examined co-branding within a fashion context recommend future research in this area with a specific demand to deploy quantitative measurements (Kim et al., 2014; Rollet et al., 2013; Oeppen & Jamal, 2014).
As the luxury market is developing and growing in emerging markets and luxury fashion brands do not have a solid customer base anymore due to an enduring global economic crisis, adding value for a consumer is essential to remain innovative and rapid adaptation of the luxury market is a matter of survival (Kim & Ko, 2012). As the luxury fashion industry is exploring how to add value in different ways, it is important to anticipate the future behavior of the
consumer (Kim & Ko, 2012). Although fashion designer Stella McCartney has collaborated with Adidas for the past decade, this long-term collaboration remains an exception (Matthews, 2004; Schuessler, 2015). Because of often short-term collaborations between sportswear industry and luxury fashion designers, according to Rollet et al. (2013), and the limited research on brand extensions and the challenge to continue to keep customers interested, it is important to examine whether these often short-term collaborations also influence the performance of a company in the long-term. This performance could be measured by the marketing management model of
customer equity because of the focus on the customer in a long-term relationship, which could lead to an increase in profits (Kim et al., 2014; Lemon, Rust & Zeithaml, 2001). The study of customer equity recognizes the need to focus on the customer and the lifetime value of him or her, meaning both the current and future profits of the customer for the firm. This model can be applied to the fashion industry because the opinions and values of consumers are central in this market.
2.2 Customer Equity: A quantitative method to assess co-branding
According to Rust et al. (2000, p. 54) customer equity can be defined as a customer’s evaluation of a firm when considering future purchases. The Customer Equity framework consists of three specific drivers: value equity, brand equity and relationship equity. By
value for the firm. Although customer equity has been applied in only a few studies about the luxury fashion industry (Kim & Ko, 2012; Kim, Ko, Xu, & Han, 2012) and to fast fashion (Lee et al., 2014; Sun, Kim, & Kim., 2014), only one has been applied to the sport shoe industry (Zhang, Ko, & Kim, 2010) and only one study has measured customer equity in a luxury and fast fashion brands collaboration (Kim et al., 2014). Although brand equity has been researched before on its own in the sportswear industry by Su and Tong (2015), it has not been combined with value equity or relationship equity before in a co-branding relationship with a luxury fashion brand.
Both the sportswear industry as well as the luxury fashion industry are highly branded industries and are growing globally and could therefore benefit from understanding the customer equity of a co-branding relationship(Tong & Hawley, 2009; Kim & Ko, 2012; Miller & Mills, 2012). Both industries are unfortunately still under-researched and have few studies about customer equity. However, the authors of fashion collaborations highly encourage continuation of this line of research to create consistency in this field. Often collaboration for a luxury fashion brand are short-term to “create an initial buzz and to reinforce the rarity and the short-lived effect of the product” (Rollet et al., 2013, p. 59), but the consumer develops the same type of
attachment to the product as it would do if it were a luxury item only (Rollet et al., 2013). 2.2.1 The Customer Equity Framework
The Customer Equity Framework makes a company put its focus on the customer, so that it can be succesfully competitive in the long run (Rust et al., 2000, p.113) through the relative position
of a firm towards Customer Equity and its key 3 drivers: value, brand and retention equity.
Figure 1. Conceptual Model based on the customer equity model by Rust et al. (2000, p. 64). Besides the customer-focused benefit of this model, it visualizes through what drivers, actions
should be initiated to continue to connect the firm with its customer. Each of these drivers with its sub driver will be explained in the next sections (see Figure 1).
2.2.2 Value Equity
This driver lies at the heart of the customer’s connection with a firm, which starts before a product or service is bought by meeting their needs and expectations (Rust et al., 2000, p. 69). It encompasses the rational and cognitive assessment of the brand (Rust et al., 2000, p.68). The indicators of the objective value are quality, price, and convenience (Rust et al., 2000, p.74). Value equity thus assumes a rationale evaluation of these indicators. Quality consists of four components: the physical product, service delivery, service product and service environment according to Rust et al. (2000, p. 75). Quality assessment in the context of fashion clothing concerns the physical product and focuses on assessing the quality of the fabric of a clothing item, the style or its maintainability over time. Customers are also price conscious when it comes to purchasing fashion clothing items. While processing price related considerations about the product, questions that arise are whether the quality of the co-branded fashion item is worth the cost and whether it is reasonably priced compared to alternative sportswear, luxury fashion or co-branded products. Lastly, convenience is a sub driver of quality equity, which is defined by three elements according to the authors: location, ease of use and availability (Rust et al, 2000, p.78). Applied to fashion, convenience related questions are whether the fashion clothing is easy to find in local stores or online, whether it is easy to put on and maintain and whether there are enough items in stock in the appropriate sizes.
For the fashion context, value equity can be especially important when it comes to novel products and services (Rust et al., 2000, p. 73). Consumers will have no experience with buying the new product, which are often paired with a price increase, so they have to judge the product
or service by evaluating how much they pay and how much they gain to take the risk of buying a product (Rust et al., 2000, p. 73). This could be applied to a co-branded fashion item since these are by definition entirely novel and original products. Customers will not be sure how to evaluate such a new product, so they will assess quality, price and convenience as best as they can instead of focusing on a specific sub driver only (Rust et al., 2000, p. 73). Through a cool design made by two co-branded fashion brands, the value could increase for the product and customers would be willing to pay a higher price. Although value equity may be seen as a simplistic evaluation, its significance does not only depend on how customers draw their conclusions about a specific product. The specific industry and the development stage of the product’s firm are factors that can also influence value equity (Lemon et al., 2001).
2.2.3 Brand Equity
As opposed to the rational and observable assessment of value equity, brand equity focuses on the emotional and subjective assessment of a product or service. A brand can increase valuation by drawing fresh clientele, but the brand can also help customers remember the brand and it can serve as an emotional link between the customer and the brand (Rust et al., 2000, p. 81-83). Brand equity consists of three sub drivers: customer brand awareness, customer brand attitude and customer brand ethics. All these drivers determine how the brand is perceived, so that it can include past, current, and future customers, but also customers who have never bought the brand before (Rust et al., 2000, p. 87).
Customer brand awareness means that the customer is well aware of the brand, which can be best increased through a brand communication tool to current and potential customers (Rust et al., p. 87). Specific sub drivers of this driver are: communications mix, media, and message (Rust et al., 2000, p. 88). In the context of fashion, brand awareness can be assessed in terms of
the types of media tools that are used to advertise fashion (i.e. magazines, commercials, fashion shows and billboards) and how a fashion item is framed and positioned towards the customer.
Customer brand attitude involves the firm’s impact on how the customer identifies with the brand emotionally and through its brand’s associations, which involve communications message, special events, brand extensions, brand partners, product placement and celebrity endorsements (Rust et al. 2000, p. 89) which all need to bring out a consistent message to make an effective emotional and cognitive impact on its customers. Under brand equity also brand partnering is mentioned, relating to co-branding, with the advice of the authors to be meticulous about who to partner with to make sure both brands will be perceived with positive associations by its customers, which could lead to an increase in brand equity (Rust et al., 2000, p. 90-91). In the context of fashion, factors that influence brand attitude could be selecting celebrities that best embody the fashion brand, which public and highly visible events can promote (Oscars, Fashion Week, and Athletic competitions) and how to create a resonating narrative around a particular fashion look.
Lastly, customer brand ethics is defined as comparing the brand values of the firm with the customers’ own values through community events, private policy, environmental record, hiring practices, and guarantees (Rust et al., 2000, p. 91). In the fashion context, questions about brand ethics would be whether the fashion clothing item is produced in an ethical way, without child labor, whether protected animals have been used in the production of the fashion item, and whether the fashion item is produced in a sustainable way.
Brand equity is especially important in a fashion context, because its fashion products are often prominently displayed in public with a strong identity message confronting customers with the question of how the brand matches their own identity (Rust et al., 2000, p. 86). The extent to
which brand equity plays a role in the customer equity model will be influenced through different customer driven connections of the product (Lemon et al., 2001).
2.2.4 Retention Equity
Value and brand equity will not be adequate for a company’s long-term success only. Therefore, a third equity driver called retention equity is part of the customer equity model as well, which involves the adhesiveness factor between a brand and its customers with five sub-drivers: loyalty programs, special recognition and treatment programs, affinity programs, community programs and knowledge building programs (Rust et al, 2000, p. 99-100). Loyalty programs mean that customers are rewarded through frequent buying behavior (Rust et al., 2000, p. 99). In the context of fashion, loyalty programs typically materialize in the form of discount coupons and other substantial store rewards. Special recognition and treatment programs involve non-monetary rewards (Rust et al., 2000, p. 102). A good example of such a program in the fashion industry is a special VIP store experience with a personal stylist. An affinity or an emotional connection program is also a nonmonetary way of a firm to build a relationship with a customer, created by figuring out which customers share similar interests (Rust et al., 2000, p. 103). For instance, promoting a sporty or luxurious lifestyle in general can establish an emotional tie between the customer and the firm. Similar to affinity programs are community programs, which mean that a firm can create a community for customers to connect with each other based on the identity of the firm, which helps the customers get more involved and are therefore less likely to choose another product or service (Rust et al., 2000, p. 105). Examples of such communities are rock climbing groups who need durable but also fashionable clothing to scale mountains on the weekend. Lastly, there are knowledge building programs who keep track of customer’s data (Rust et al., p. 107). In the context of fashion, data such as purchasing habits,
style preferences, and social and sports activities could all help in building up knowledge about customers that can enhance the brand customer relationship. Not every retention tactic works for every customer, so it is crucial to be aware of the needs and expectations of different types of customer before actionable retention drivers are applied (Rust et al., 2000, p.110). In a fashion context, retention equity can be important when fashion companies are trying to learn about the customer’s preferences by investing in the relationship through collecting information, but also personalizing the shopping experience for instance.
2.3 Research Question and Hypothesis
In the current study, the customer equity marketing management model will be applied to co-branding as the impact of the three sub-drivers will be evaluated on the overall assessment of customer equity, leading to the following research question: To what extent do co-branding relationships between sportswear brands and luxury fashion brands enhance customer equity? The main hypothesis of this work is that co-branding has a positive effect on customer equity and its three drivers, because co-branding can add value to a brand, strengthen the brand’s image through positive associations and distinguish a brand from others as a long-term competitive advantage. The specific hypothesis of this work is that co-brands composed of sportswear and luxury fashion brands will be rated higher on value equity, brand equity, and retention equity compared to single sportswear and single luxury fashion brands.
3. Method
Most research about customer equity in a fashion context has been measured through a survey method in the form of an online questionnaire (Zhang et al., 2010; Kim & Ko, 2012; Kim et al., 2012; Kim et al., 2014; Sun et al., 2014). To make this study relevant, existing methods and scales were used to contribute and add to the current customer equity research in a fashion marketing context. Therefore, the survey method has been chosen for data collection, which will provide quantitative data for the overall customer equity and its three drivers: value equity, brand equity and relationship equity (Lemon et al., 2001).
3.1 Participants
A professional online panel of 161 Dutch women (age: M = 27.95, SD = 4.91) living in metropolitan areas in the Netherlands was recruited by the Dutch online marketing research company PanelClix. This urban oriented sample size is sufficient to assess customer equity reliably (Rust et al., 2000, p. 121). An all-female sample was selected between the age of 20-35 years old, because women are generally more aware of fashion brands and trends than men and are likely more motivated to answer a survey about novel types of branding (Wu & Chalip, 2014). For this research a form of stratified random sampling with systematic sampling was applied, or as PanelClix calls it “interlocked stratification” by using segments with quota’s. This probability sampling technique was used to pre-select participants based on gender (all-female), education (low, middle, and highly educated), age (20-24, 25-29 and 30-35) and region (large Dutch metropolitan regions according to the Nielsen 1 region: Amsterdam, Rotterdam, the Hague and surrounding counties). Participants who completed the survey were rewarded with 75 “clix” (~ €1), which are the points a participant can earn that can be exchanged for cash.
3.2 Materials
A preliminary online survey based on a convenience sample (N = 17, females = 12) narrowed down a set of comparable sportswear, luxury fashion and sportswear and luxury fashion co-brands (see Appendix A). Both sportswear brand and luxury fashion brands were selected through a combination of ranking lists from Interbrand.com, Brandz
(millwardbrown.com), Forbes.com and The Richest.com. The participants were required to rate their preferred top 10 sportswear brands and luxury fashion brands. Lastly, they were informed about what a co-brand was and were then asked, after a brief instruction, to write down their top four co-brand preferences based on the previously listed 20 brands. This was done to ensure participants would be familiar with both brands to understand the online survey measures and make deliberate choices when filling out the survey. Fictitious co-brands were used instead of existing co-brands, to avoid a prejudice towards the co-brand that could possibly weaken the results (Ahn et al., 2010). The top four sportswear brands were: 1) Nike, 2) Adidas, 3) Asics and 4) Puma. The top four luxury fashion brands were: 1) Chanel 2) Dior, 3) Louis Vuitton, and 4) Gucci. The top four most popular constructed co-brands were: 1) Adidas & Gucci, 2) Nike & Chanel and 3) a shared third place by Nike & Gucci and Adidas & Louis Vuitton. The individual brands of the two most popular co-brands were checked for their popularity (see Figure B1 for average rankings of sportswear brands and Figure B2 for average rankings of luxury fashion brands in Appendix B). Each brand collection was then constructed with this reduced set and contained either a combination of a sportswear brand (Adidas), a luxury fashion brand (Chanel) or a co-branded sportswear and luxury fashion brand (Adidas & Gucci and Nike & Chanel).
3.3 Study Design
Four surveys were constructed to assess the four selected brands (Adidas, Chanel, Adidas & Gucci, and Nike & Chanel). Each of the four surveys contained two brands for a total of eight brand presentations (each brand was presented two times). Brands were randomly distributed across the surveys to ensure that participants would examine two different brands (see Table 1). The first survey consisted of a single sportswear fashion brand called Adidas, and a single luxury fashion brand called Chanel. The second survey consisted of a single sportswear brand Adidas and a sportswear and luxury fashion co-brand Adidas & Gucci. The third survey consisted of the single luxury fashion brand Chanel and a sportswear and luxury fashion co-brand Nike &
Chanel. The fourth survey consisted of two co-branded sportswear fashion and luxury fashion brands: Adidas & Gucci and Nike & Chanel.
Table 1. Four surveys with their brand distributions. 3.4 Measures
The online survey is based on the customer survey sample for airlines developed by Rust et al. (2000, p. 267) and has been adjusted to a fashion marketing context (see Appendix C for the survey 4 example with two co-brands). An online questionnaire is a relatively inexpensive way to gather quantitative data in a short amount of time and is convenient to use when
comparing data. Generally, it is also a respected and accessible method to use (Saunders, Lewis & Thornhill, 2012, p. 177). The survey results can produce data about potential relationships that
Survey Brand 1 Brand 2
1 Adidas Chanel
2 Adidas Adidas & Gucci
3 Chanel Nike & Chanel
can be generalized beyond the sample of the study (Saunders et al., 2012, p. 178). The survey items consist of ranking questions relating to how familiar the respondents are with the brands and 5-point Likert scale questions evaluating the separate customer equity drivers: value equity, brand equity and relationship equity and their sub-drivers as well as their relative positions towards each other. Key sub-drivers and the total customer equity of each separate brand and co-brand will be evaluated. For the purpose of this study, a practical decision was made to include the measurement of only three sub drivers of the retention equity driver, namely loyalty
programs, special recognition and treatment programs and community building programs instead of the five sub-drivers. The two other drivers called affinity programs and knowledge building programs will not be included in this study as these do not seem relevant to the fashion brands. Measuring only three drivers can still give an accurate indication about the retention equity in relation to value equity and brand equity.
3.5 Procedure
The online survey was composed through the computer-based survey platform Qualtrics. In order for PanelClix members to receive their clix (credits) and the correct PanelClix screenout screen, in case the member was a male or the survey was completed, information in the survey flow had to be adjusted through embedded data. In this way the Qualtrics survey link was connected to the PanelClix system. The results could be immediately observed and used by both the computer-based Qualtrics and PanelClix simultaneously. After the information was added, PanelClix performed several test runs. After successful completion, PanelClix sent out the survey by embedding the Qualtrics link in an email, which introduced the survey’s topic as “fashion brands” and was first sent out to 20 participants only, to examine whether the Qualtrics link was received correctly. After the test run, the survey was sent out by PanelClix to which 194
participants responded and of which 161 completed the survey. The questionnaire was written in English, which was the same language used in the sample survey by Rust et al. (2000, p. 267). The first item asked for gender in order to make sure the participant was female. If participants were male, they were redirected to a screen out page. Following approximately the same order of the sample survey questions, items 3-8 asked respondents about size and frequency of purchase of fashion clothing item brands, item 9 asked about the probability of their next clothing item purchase type (a sportswear brand, a luxury fashion brand or a sportswear and luxury fashion co-brand). Value equity driver questions depicted items 10-13. Brand equity and Retentions drivers depicted items 14. In item 15, respondents were asked to rate the importance of all the drivers mentioned in the survey. Lastly, items 16-19 depicted demographic information.
Data were collected between November 25th and November 26th and between November 30 and December 3rd in 2015. Confidentiality was ensured by Qualtrics who automatically provided a response ID number combined with an IP address number. After the survey was completed, respondents were thanked for their participation and were led to the PanelClix completion re-direct screen, where they evaluated the survey (Appendix D).
3.6 Analysis
Data were gathered through Qualtrics and analyzed with IBM SPSS Statistics version 22. For analyses purposes, responses for each repeated brand was averaged and the dataset was analyzed with a one-way ANOVA with Brand as a between-subjects variable with four levels (Adidas, Chanel, Adidas & Gucci, and Nike & Chanel). All post-hoc comparisons were conducted with the Tukey procedure to correct for Type I errors.
Three principal component analyses (PCA) were used to further analyze the shared variance between items, also called factors. The first PCA analyzed the factors of all survey
items based on a component matrix. The second PCA analyzed the factors of all nine drivers, each representing a different equity driver based on a component matrix. Lastly, the third PCA analyzed the factors of the importance ratings given by the participants in item 15, which was based on both a component matrix and a rotated component matrix.
4. Results 4.1 Sample statistics
4.1.1. Income
Some general characteristics of the respondents will be discussed in order to verify if the sample was indeed a motivated sample. In total 161 respondents filled out the survey. As a stratified sample was used, income distribution seems a little skewed to the right. Although 20.5% of the respondents did not prefer to disclose their income despite their guaranteed
Figure 2a-b. Sample education distribution (2a, left) and sample annual income distribution (2b, right).
anonymity, 79.5% of the sample disclosed it of which the major income group with 26.1% was < €10.000 followed by the €10.000- €19.000 income group with 21.7%. The smallest income group was represented through the > €50.000 income group with 3.7%. It is
unfortunately not clear whether these groups truly represent the majority of the sample, however it does give a sufficient indication of the different variations of incomes in the sample (see Figure 2a-b).
4.1.2. Education
The education level of the sample seems normally distributed. Although the majority of the sample has an MBO degree with 36%, both lower educated (< MBO = 47.1%) and highly educated (> HBO = 52.7%) respondents are almost equally distributed, with both PhD as well as no high school degree as the lowest groups with 1.2%. This is reasonable since the PhD degree takes the most amount of time to invest in education and due to the compulsory education system in the Netherlands, it is rare to find respondents that do not finish their high school degree. The normal distribution with its equally distributed variations seems to confirm the intentional stratified sample strategy that was pursued by PanelClix.
4.1.3 Age
Only one respondent from the 161 respondents did not report their age. Respondents had a minimum age of 18 and a maximum age of 40 (M = 27.95, SD = 4.91). The preferred requested sample between 20-25 years old represented 97% of the sample. Overall, the age groups seem approximately equally distributed, with only one outlier at the 35 year age group.
4.1.4 Purchase Behavior
The majority of the respondents are familiar with both purchasing a sportswear clothing item (78.9%) and also a luxury fashion clothing item (62.1%) in the past year, which makes the majority of the respondents a motivated and well-informed sample to answer the survey
questions accurately (see Figure 4a and 4d). Most women in this sample purchased both sportswear (85.1%) and luxury fashion clothing items at least once a year (70.8 %). When looking at the frequency of purchase of which the majority purchases both sportswear clothing items (36.6%) and luxury fashion clothing items (28.6%) 3-4 times a year, it indicates that a variety of fashion clothing items are bought annually (see Figure 4b and 4e). More specifically, when looking at how much on average respondents spent on sportswear clothing items, more than half of the respondents (53%) spends between €25 - €49. Due to the different budget scales, luxury fashion clothing items may not be comparable with sportswear clothing items, however luxury fashion clothing items tend to be more expensive than sportswear clothing items. One can still see that the majority of the respondents spends €300 or less on luxury fashion clothing items (see Figure 4c and 4f). When respondents were asked about the probability of the brand type when shopping for fashion clothing items in the future, means were very close to each other with sportswear having the highest probability (M = 38.92, SD = 26.96), co-brands being in the middle (M = 37.15, SD = 24.65) and luxury fashion brands having the lowest probability score (M = 36.19, SD = 26.55). For both sportswear and luxury fashion brands N = 161, however co-brands had N = 123, because the co-co-brands were excluded from the questionnaire in which only single brands were presented (see survey 1 in Table 1).
Figure 4a-f. Sportswear purchase behavior of the past year (4a, top left). Sportswear purchase frequency (4b, middle left). Sportswear cost (4c, bottom left). Luxury purchase behavior of the
past year (4d, top right). Luxury purchase frequency (4e, middle right). Sportswear cost (4f, bottom right).
4.2 Reliability and Computing scale means
Reliability was assessed for the drivers that consisted of multiple items only (price a = 0.57, convenience a = 0.58, brand attitude a = 0.87, brand awareness a = 0.62). Scale means were then computed for the three items of price (M = 2.99 SD = 0.72), the two items of
convenience (M = 2.93, SD = 0.80), the five items of brand attitude (M = 2.84, SD = 0.83) and the two items of brand awareness (M = 2.87, SD = 0.88). High reliability (α >.70) was found for all three separate sub-drivers: price, convenience, brand attitude and brand awareness (Field, 2013, p. 709).
4.3 Value Equity Analysis
There was a significant main effect for Brand on Quality, F(3, 318) = 4.43, p < 0.05, ƞ2=0.04. Tukey post hoc comparisons revealed that the co-brand Adidas & Gucci was rated significantly higher on Quality compared to Chanel, p = 0.02. The co-brand Nike & Chanel was also rated significantly higher on Quality compared to Chanel, p = 0.01 (see Figure 11, note that the origins of the graph start at 1.5, instead of zero to highlight the differences in more detail).
There was a significant main effect for Brand on Price, F(3, 318) = 7.58, p < 0.05, ƞ2 = 0.07. As expected, the luxury fashion brand Chanel was rated significantly higher on price compared to Adidas, p = 0.002. The co-brand Adidas & Gucci was rated significantly higher on price compared to Adidas, p = 0.001. The co-brand Nike & Chanel was also rated significantly higher on Price compared to Adidas, p = 0.001. Both co-brands Adidas & Gucci and Nike & Chanel were rated as high as Chanel on Price with no significant differences between them, p = 0.992 and p = 0.988, respectively (see Figure 11).
p < 0.05, ƞ2 = 0.13. As expected, the luxury fashion brand Chanel was rated significantly lower on Convenience compared to Adidas, p = 0.001. The co-brand Adidas & Gucci was rated significantly lower on Convenience compared to Adidas, p = 0.001. The co-brand Nike & Chanel was also rated significantly lower on Convenience compared to Adidas, p = 0.001. Both the co-brands Adidas & Gucci and Nike & Chanel were rated as high as Chanel on Convenience with no significant differences between them, p = 0.559 and p = 0.369, respectively (see Figure 11).
Figure 11. Quality, Price, and Convenience drivers of Value Equity 4.4 Brand Equity Analysis
There was a significant main effect for Brand on Brand Awareness, F(3, 318) = 5.26, p < 0.05, ƞ2 = 0.05. Tukey post hoc comparisons revealed that single sportwear brand Adidas was rated significantly higher on Brand Awareness compared to the luxury fashion brand Chanel, p = 0.039, but Adidas was also rated significantly higher compared to both co-brands Adidas & Gucci p = 0.008 and Nike & Chanel p = 0.002 (see Figure 12, note that the origins of the graph
start at 2.5, instead of zero to highlight the differences in more detail). Both Chanel and the two co-brands were rated as equally low on Brand Awareness with no significant differences between them: Adidas & Gucci p = 0.967 and Nike & Chanel p = 0.827.
There was a significant main effect for Brand on Brand Attitude, F(3, 318) = 3.26, p < 0.05, ƞ2= 0,30. Also, for this driver Tukey post-hoc comparisons revealed that sportswear brand Adidas p = 0.015 was rated significantly higher than Nike & Chanel p = 0.015. However, no other significant effects were found between Adidas and the co-brands Adidas & Gucci p = 0.103 and Nike & Chanel with the luxury fashion brand Chanel, p = 0.304. No significant differences were found between the two co-brands p = 0.877 or the two co-brands compared to the luxury fashion brand Chanel between Adidas & Gucci p = .961 and between Chanel and Nike & Chanel p = 0.619, respectively (see Figure 12).
No significant main effect was found for Brand on Brand Ethics F(3, 318) = 1.466, p>0.05, ƞ2 = 0.014 (see Figure 12).
4.5 Retention Equity Analysis
There was a significant main effect for Brand on Loyalty Programs, F(3, 318) = 4.57, p < 0.05, ƞ2 = 0.041. Tukey post hoc comparisons revealed that the sportswear brand Adidas was rated significantly higher on Loyalty Programs compared to Chanel, p = 0.029. Also Adidas was rated significantly higher than the co-brand Nike & Chanel p = 0.003. However, no significant effect was found between Adidas and the other co-brand Adidas & Gucci p = 0.286, nor was there a significant effect between the co-brands p = 0.306. Also, no significant effect was found between Adidas & Gucci and Chanel p = 0.709 (see Figure 13, note that the origins of the graph start at 2, instead of zero to highlight the differences in more detail).
There was no significant main effect for Brand on Recognition Programs, F(3, 318) = 1,369, p > 0.05, ƞ2 = 0.013. Also, no significant effect was found for Brand on Community Building Programs, F(3,318) =1,892, p > 0.05, ƞ2 = 0.018 (see Figure 13).
Figure 13. Loyalty Programs, Recognition Programs and Community Building Programs as drivers of Retention Equity.
4.6 Overall Customer Equity Analysis
Value equity was computed by averaging the Quality, Price and Convenience
dimensions. Overall, there was a significant main effect for Brand on Value, F(3, 318) = 4.415, p < 0.05, ƞ2 = 0.04. Tukey post hoc comparisons revealed that Adidas was rated significantly higher on overall value equity compared to Chanel, p = 0.02. Both co-brands were also rated significantly higher on value equity compared to the luxury fashion brand Chanel (Adidas & Gucci, p = 0.030, Nike & Chanel, p = 0.008). The co-brand Nike & Chanel was also rated significantly higher on quality compared to Chanel, p = 0.01. No significant difference was found between the two co-brands Adidas & Gucci and Nike & Chanel, p = 0.963, and no
significant difference could be found between Adidas and the two co-brands (Adidas & Gucci, p = 0.997 and Nike & Chanel p = 0.993) (see Figure 14, note that the origins of the graph start at 2, instead of zero to highlight the differences in more detail).
Brand equity was computed by averaging the Brand Awareness, Brand Attitude and Brand Ethics dimensions. There was a significant main effect for Brand on overall Brand Equity, F(3, 318) = 3.823, p < 0.05, ƞ2 = 0.04. Post-hoc comparisons revealed that Adidas was rated significantly higher on brand equity than Nike & Chanel p = 0.007. No other significant differences between brands were found. Adidas only differed significantly from one co-brand, but not from the other co-brand Adidas & Gucci, p = 0.078 nor with the luxury fashion brand Chanel, p = 0.324. Also the co-brands did not differ from each other, p = 0.801 (see Figure 14).
Retention equity was computed by averaging the Loyalty Programs, Recognition
Programs and Community Building Programs dimensions. There was no significant main effect for Brand on Retention Equity, F(3, 318) = 2,116, p >0.05, ƞ2 = 0.020 (see Figure 14).
Figure 14. Value Equity, Brand Equity and Retention Equity as drivers of Customer Equity. 4.7 Relative Importance Customer Equity
Customer Equity (CE) was calculated with two different methods. The first method for calculating customer equity was by simply averaging value equity, brand equity, and retention equity, which will be called CEAverage. A second method for calculating customer equity is based on assessing the relative importance of each of the sub drivers of CE as suggested by Rust, Lemon & Zeithaml (2001). This relative importance was assessed using a set of questionnaire items that asked participants to rate each of the CE subdrivers on a scale from 1 to 5 (see Methods section). To calculate CEWeighted, the relative importance of value equity, brand equity and retention equity was converted as a percentage for each of the customer equity drivers and then multiplied by the average values of VE, BE, and RE (see Appendix E).
Figure 15. Customer Equity Weighted and Customer Equity Average
Overall, there was a significant main effect for Brand on CEAverage, F(3, 318) = 3.186, p < 0.05, ƞ2 = 0.029. Post hoc comparisons revealed that Adidas was rated significantly higher on customer equity compared to Nike & Chanel, p = 0.012. No other significant differences were found between the Brands on CEAverage (see Figure 15, note that the origins of the graph start at 2.5, instead of zero to highlight the differences in more detail). There was also a significant main effect for Brand on CEWeighted, F(3, 318) = 2.854, p < 0.05, ƞ2 = 0.026. Post comparisons revealed that, as with CEAverage, Adidas was rated significantly higher on customer equity compared to Nike & Chanel, p = 0.019. No other significant differences were found between the Brands on CEWeighted (see Figure 15). There were thus not any meaningful differences for the two different methods of calculating CE and the grand mean for CEAverage (M = 2.720, SE = 0.029) was virtually identical to CEWeighted (M = 2.761, SE = 0.027).
4.8. Principal Component Analyses
4.8.1 Principal Component Analysis All Items
A principal component analysis (PCA) was conducted on the sub drivers of customer equity and included all equity survey questions. The PCA is a recommended procedure to assess if all questions were separated into the three theoretical equity components (Rust et al., 2004) and to determine if any factors out of all the equity drivers would be more important than other factors (Rust et al., 2004). The customer equity model, applied to for example the aviation industry, may be represented differently across other industries such as sportswear and luxury fashion. Although the equity measures have been carefully analyzed, some drivers may be considered more important than others in this sample and with the topic of co-branding. Therefore, a principal component analysis was conducted on all questions first. The factor analysis was based on 161 respondents based on 17 items total. The Kaiser-Meyer-Olkin (KMO) measure verified the sampling adequacy for the analysis (KMO = .919). Bartlett’s test of
sphericity χ2 (136) = 3009, p < 0.001 indicated that correlations between items were sufficiently large for a PCA (Field, 2013, p. 684-685). Three components were extracted with eigenvalues over Kaiser’s criterion of 1, which explained 61.13 % of the variance (see Figure 16).
Component 1 was represented by Brand Equity items and Retention equity items combined with all loadings above 0.5 of which the highest loading were loyalty programs: 0.823. Component 2 was represented by mainly the highest loadings above 0.5 on all three Price items. Component 3 was mainly represented by quality with the highest and only relevant loading above 0.5 on quality. These factor loadings seem logical as the strongest differences between brands were found in quality and price. However, it seems a bit peculiar that quality and price are not loaded on 1 component, but two components since they are both part of value equity. However, quality
consists of only 1 item, while price consists of 3 separate questions, and even though it loaded on component 2 to some extent (0.310), it may be a sub driver that loads more strongly on a
separate component. Also, quality produced different effects between the brands compared to price.
Figure 16. Principal Component Analysis of All Customer Equity Dimensions. 4.8.2 Principal Component Analysis Nine Factors
To obtain a more accurate result, a principal component analysis was also conducted in which 17 items were reduced to 9 factors, each representing a different equity driver.
Confirming the results of the separate drivers, the analysis loaded the equity sub-drivers on 2 components, the first one being characterized by quality and price (and notably not
convenience), both drivers of value equity. Interestingly, the second component was represented Component Matrixa Component 1 2 3 Quality -,211 ,310 ,754 Price1 -,456 ,652 ,165 Price2 -,342 ,696 ,110 Price3 -,147 ,585 -,526 Convenience1 ,614 -,039 ,351 Convenience2 ,695 ,183 -,108 BrandAwareness2 ,607 ,088 ,187 BrandAwareness1 ,769 -,030 ,001 BrandAttitude1 ,783 ,087 ,061 BrandAttitude2 ,603 ,241 -,262 BrandAttitude3 ,812 ,095 -,166 BrandAttitude4 ,819 ,001 ,073 BrandAttitude5 ,822 ,164 ,013 BrandEthics ,703 ,125 -,200 LoyaltyPrograms ,823 ,007 ,154 CommunityBuildingPrograms ,782 ,012 ,143 RecognitionProgrrams ,812 ,029 ,019
Extraction Method: Principal Component Analysis. a. 3 components extracted.
by both brand equity and retention equity items, which showed that participants did not assess these two drivers as separate dimensions. The factor analysis was based on 161 respondents and 9 factors. The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = .888. Bartlett’s test of sphericity χ2 (36) = 1651, p < 0.001 indicated that correlations between items were sufficiently large for a PCA (Field, 2013, p. 684-685). Two components had eigenvalues over Kaiser’s criterion of 1, which explained 66,04 % of the variance, about 5% more than the previous PCA analysis.
Figure 17. Principal Component Analysis of Nine Customer Equity Drivers. By having the questions clustered under sub drivers of equity, it is evident that the third component from the previous principal component analysis has been eliminated. Instead, this analysis shows that CE is comprised of two components. Component 1 had high loadings above 0.5 for both brand equity and retention drivers. Component 2 consisted of high loadings above or around 0.5 on quality and price only. A reason that convenience may be loaded on component 1, even though it is still a value equity driver, may be because of the fictitious nature of the two
co-1 2 Quality -,198 ,881 Price -,431 ,486 Convenience ,765 ,048 BrandAttitude ,899 ,023 BrandAwareness ,791 ,065 BrandEthics ,707 ,000 LoyaltyPrograms ,857 ,129 CommunityBuildingPrograms ,832 ,139 RecognitionProgrrams ,846 ,057 a. 2 components extracted. Component Matrixa Component
brands in the survey. Respondents may have had difficulty with estimating the accessibility and service of the fashion clothing item brands compared to price and quality.
4.8.3 Principal Component Analysis Importance Factors
Lastly, a principal component analysis was conducted to determine if the components were consistent based on what respondents found important when they were directly asked to rate the overall importance of the factors when choosing to purchase fashion clothing item brands. The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = .774. Bartlett’s test of sphericity χ2 (55) = 663,94, p <0.001 indicated that correlations between items were sufficiently large for a PCA (Field, 2013, p. 684-685). Three components had
eigenvalues over Kaiser’s criterion of 1, which explained 57,13 % of the variance. The analysis shows that factors loaded less extremely than the previous two analyses. The “attractive” factor is the only problematic factor since it cross-loads almost equally on both components. However, this may be due to the content of the item. Attractiveness in the fashion industry may be seen as both an indicator of quality as well as brand perceptions. Although attractiveness is an important factor when evaluating fashion brand items, it is not part of the original survey that Rust et al. (2004) developed. The rotated matrix, however, shows that attractiveness becomes part of the value component (see Appendix F). Again, this confirms the consistency of the findings in both the one-way ANOVA and the PCA’s. Component 1 shows that “image” with the highest loading was found most important, followed by “personality” match with the brand, “loyalty”, and “status”. Even though quality and price differed significantly, these are also factors that should be taken into account when examining customer equity in a fashion context.
Figure 18. Principal Component Analysis of Importance Factors 1 2 I_VE_Quality ,474 ,685 I_VE_Price ,361 ,765 I_VE_Access ,535 ,199 I_VE_Service ,527 ,402 I_BE_Media ,549 -,460 I_BE_Personality ,720 ,035 I_BE_Image ,758 -,183 I_BE_Attractive ,544 ,575 I_BE_Status ,606 -,532 I_RE_Loyalty ,647 -,378 I_RE_Community ,464 -,644 Component Matrixa Component
Extraction Method: Principal Component Analysis.
5. Discussion 5.1 Summary of results
The goal of this research was to assess the customer equity of co-branding between sportswear brands and luxury fashion brands as an effective marketing strategy. A survey was used to assess each of the drivers of customer equity including value equity, brand equity, and retention equity. Results of a one-way ANOVA showed that, compared to single brands, branding enhanced value equity, but not branding and retention equity. More specifically, co-branding resulted in a higher evaluation of price compared to single sportswear brands and was rated higher on quality compared to a luxury fashion brand. In contrast, the single sportswear brand was rated higher on brand and retention equity compared to the co-brands. Therefore, the hypothesis that co-branding enhances customer equity is partially supported.
In addition, a principal component analysis further confirmed that instead of the three theoretical drivers of customer equity, the individual survey items loaded on only two distinct components. The first component consisted of value equity related drivers (quality, price) and the second component loaded mainly with items from brand and retention equity related drivers.
Both the PCA factoring on every item of the survey, but also the PCA of the importance ranking of the sub dimensions, revealed that rather than the complete customer equity convention
consisting of the three dimensions of equity in this sample, the two components value equity and brand/retention equity really drove the results, and those components were a smaller version of value equity and brand and retention equity combined. This means that for co-branding customer equity is really determined by these components. Even when looking at the overall customer equity, Adidas turns out to be significantly higher for overall customer equity than both co-brands and the single luxury fashion brand. Both the customer equity average and the customer
equity weighted hardly showed any different results, so both the one-way ANOVA and the principal component analysis give a much more in-depth story of the results.
Combined, these two main findings show that hypothetical co-brands are seen as beneficial in terms of value equity, but are more difficult to assess in terms of brand equity and retention equity.
5.2 Theoretical implications
Co-branding is an efficient marketing strategy based purely on the value component of customer equity. Therefore, value equity is the most important and best indicator for co-branded fashion, especially when such hypothetical brands have not been established. This seems logical as Rust et al. (2000, p. 73) argue that value equity is especially important for innovative
products, which are often priced higher. Another reason for the higher ratings on value equity for co-brands is that the participants were most likely able to make an educated guess about the price and quality of the new co-brand product. In fact, the results for value equity are consistent with a positive spill-over effect by associating the sportswear and luxury fashion partner brands
together (Washburn, Till, & Priluck, 2004). In sum, people can more easily assess the value for an existing brand than for an imagined co-brand, and brand equity and retention equity did not exist for the fictitious brands used in this study.
It is logical that brand equity and retention equity are not good assessments for co-brands that have not been established yet. This was confirmed by the high ratings of the Adidas brand due to its great branding, however even though Chanel is also an established real-life brand, brand equity and retention may have been perceived differently due the more exclusive nature of the luxury brand. This is comprehensible because these were based on fiction and there was no real brand strategy and retention program. Assessing the more subjective brand equity is harder
for an imagined brand, especially when such a brand has not been marketed or does not exist. Retention equity may face similar issues because retention programs were not established for the co-brand. Brand equity is about subjective feelings, which are hard to imagine. Images of actual fashion products or real-life communication and marketing strategies may produce bigger effects. A reason why convenience, a sub-driver of value equity, may have been excluded from the positive value equity evaluation of co-brands, is because the accessibility and service of these fictitious clothing items co-brands, may have been hard to imagine for respondents compared to price and quality. Hence, convenience was only rated significantly higher for Adidas, since the sample may have had more experience with buying a well-known sportswear brand, which may have been easier to imagine than a luxury fashion brand. In addition, the respondents did not actually buy the fictitious co-brands in an available store, which again would make it harder to imagine this sub driver. Although Rust et al. (2000, p. 95) emphasize the importance of retention equity, they also argue that the long-term orientation may not always suit a retail environment (p.171). This may be a good reason to reduce confidence in the retention equity results. Only value equity and brand equity may matter in this fashion context. Even though co-branding is often described as a long-term-commitment and even suggested to be a sustainable marketing strategy that can differentiate a fashion product also in the long-term (Rollet et al., 2013), this still may not match reality today. Especially, since the co-branding of sportswear and luxury fashion brands is still a novel phenomenon and this type of collaboration is in its early stages.
The findings from this research show it is clear that the customer equity model does not always apply to every industry and should be extended with a more extensive guided approach. A guide should specify the differences for the customer equity model for brands in different industries, because it may too elaborate for brands in a volatile market or just simply not match
