I LEGGINGS ARE the NEW DENIM: an INVESTIGATION OF
LEGGINGS ARE THE NEW DENIM: AN INVESTIGATION OF
CONSUMER ACTIVEWEAR EXPERIENCE
A Dissertation
Submitted to
the Temple University Graduate Board
In Partial Fulfillment
of the Requirement of the Degree
DOCTOR OF PHILOSOPHY
By
Xiaochen Zhou
August 2018
Examining Committee Members:
Daniel C. Funk, Ph.D., Advisory Chair, School of Sport, Tourism, and Hospitality
Management
Thilo Kunkel, Ph.D., School of Sport, Tourism, and Hospitality Management
Lu Lu, Ph.D., School of Sport, Tourism, and Hospitality Management
Clare Hanlon, Ph.D., External Member, Victoria University, Australia i
ABSTRACT
Building upon the Sport Experience Design (SX) framework of Funk (2017), this dissertation investigates consumer experience with activewear in different usage contexts.
The intersection of user and context in the SX framework is examined by integrating the means-end chain theory of Gutman (1982) and the situation research of Belk (1975). This theoretical integration creates a conceptual approach to understand how consumers construct and evaluate the sport experience in different contexts. Three research questions were asked about what types of perceptions consumers develop with activewear, how the perceptions form the means-end chain structure, and how the structure varies across fitness and non-fitness contexts. Findings of Study 1 revealed five important attributes
(i.e., fashion design, color and pattern, fit, functional design, and fabric), four consequences (i.e., physical appearance, physical comfort, social relationship, and task facilitation), and three end-state values (i.e., fun and enjoyment, self-respect, and sense of accomplishment) that connect and form the means-end chain structure. Informed by findings of Study 1, Study 2 found the direction of means-end chain structure and its specific paths vary across fitness and non-fitness contexts. Findings contribute to the SX framework by using the means-end chain theory as a theoretical approach to examine consumers’ experience with a sport product while considering the context in which the product is used. Practical implications are provided on how brands can link product attributes with consumers’ self-concepts to enhance the consumer experience.
ii ACKNOWLEDGMENTS
This dissertation would not have been possible without the support and guidance of many individuals. First and foremost, I would like to thank my advisor and mentor,
Dr. Daniel C. Funk. His knowledge and wisdom have not only shaped my research interest in sport consumer experience but also my understandings of academic study.
Without Dr. Funk’s guidance and support, I would not have grown so much during my
Ph.D. journey.
I would also like to thank my committee members, Dr. Lu Lu and Dr. Thilo
Kunkel, as well as my external reader, Dr. Clare Hanlon. Their comments and advice have made this dissertation stronger and inspired me with new ideas. I would also like to thank Allison Hossack for her helps on developing this dissertation.
I would like to thank all my colleagues and the faculty at the School of Sport,
Tourism, and Hospitality Management and the FOX School of Business at Temple
University. The intellectual conversations with them help me become a better researcher and pave the way for my future career as a professor.
Last but not least, I would like to thank my parents, Caiying Yan and Xuling
Zhou, and my husband, Hao Huang, for their love and support.
iii TABLE OF CONTENTS Page
ABSTRACT ...... ii
ACKNOWLEDGMENTS ...... iii
LIST OF TABLES ...... ix
LIST OF FIGURES ...... x
CHAPTER
1. INTRODUCTION ...... 1
Statement of the Problem ...... 2
Purpose of the Study ...... 3
Significance of the Study ...... 4
Delimitation of the Study ...... 5
Definition of Terms...... 7
2. REVIEW OF LITERATURE ...... 8
Sport Experience Design Framework ...... 8
Means-end Chain Theory ...... 12
Inclusiveness and Abstraction...... 13
Means-end Chain Content...... 14
Attributes...... 14
Consequences ...... 16
iv End-state Values ...... 18
Means-end Chain Structure...... 20
The Inclusive and Non-inclusive Views ...... 22
The Upward and Downward Directions ...... 24
Fitting the Means-end Chain Theory Into the SX Framework ...... 26
Product-Usage Context ...... 28
Physical Surrounding ...... 29
Temporal Perspective...... 29
Antecedent State ...... 30
Social Surrounding...... 30
Task Definition ...... 31
Summary and the Conceptual Approach ...... 32
Research Questions ...... 35
3. METHOD ...... 38
Research Subjects ...... 39
Study 1 ...... 40
Participants and Interview Procedure ...... 41
Data Analysis ...... 46
Study 2 ...... 48
Participants and Procedure ...... 49
v Measures ...... 54
Data Analysis ...... 57
4. RESULTS ...... 61
Study 1 Findings ...... 61
Identified Elements, The Implication Matrix, And The HVM ...... 61
Identified Means-End Chain Elements ...... 61
The Implication Matrix ...... 65
The Hierarchical Value Map ...... 65
Attributes...... 68
Functional Design ...... 68
Fabric ...... 69
Color and Pattern ...... 69
Fit ...... 70
Fashion Design...... 71
Consequences ...... 72
Physical Appearance ...... 72
Physical Comfort ...... 74
Social Relationship ...... 74
Task Facilitation...... 75
End-State Values ...... 76
vi Fun And Enjoyment ...... 76
Self-respect ...... 76
Sense of Accomplishment...... 77
Representative Means-End Chains ...... 78
Discussion of Study 1 Findings ...... 81
The First Research Question ...... 81
The Second Research Question ...... 83
Study 2 Results ...... 85
Measurement Model ...... 85
Within-Group Comparison Between Upward And Downward Models ... 95
Multiple-Group Analysis Between Fitness And Non-Fitness Contexts ... 97
Discussion of Study 2 Findings ...... 102
The Second Research Question ...... 103
The Third Research Question ...... 104
5. DISCUSSION ...... 107
Theoretical Contributions ...... 107
Contributions To The SX Framework ...... 107
Contributions To The Means-End Chain Theory ...... 109
Overall Contributions To Sport Experience Research ...... 110
Practical Implications...... 112
vii Limitations and Future Research ...... 114
Conclusion ...... 116
REFERENCES ...... 118
APPENDICES
A. MOVEMENTS OF ITEMS IN THE EFA PROCEDURE ...... 136
B. MEAN COMPARISONS BETWEEN FITNESS AND NON-FITNESS GROUPS 138
viii LIST OF TABLES
Table Page
Table 1.1. Definitions of Terms ...... 7
Table 3.1. Demographic Information of Interview Participants ...... 45
Table 3.2. Demographic Information and Activewear Usage Behavior of Survey Respondents ...... 52
Table 3.3. Initial Items for Attributes, Consequences, and End-State Values ...... 55
Table 4.1. Overview of Attributes, Consequences, and End-State Values ...... 62
Table 4.2. Implication Matrix (Direct Paths) ...... 66
Table 4.3. Implication Matrix (Indirect Paths) ...... 67
Table 4.4. Salient Means-End Chains and Quotes ...... 79
Table 4.5. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model A ...... 86
Table 4.6. Exploratory Factor Analysis ...... 88
Table 4.7. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model B ...... 90
Table 4.8. Factor Loadings of Model C ...... 94
Table 4.9. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model C ...... 95
Table 4.10. Comparison between Up- and Downward Models for The Fitness Group ... 96
Table 4.11. Comparison between Up- and Downward Models for The Non-Fitness Group ...... 97
Table 4.12. Invariance Test of The Upward Model between Fitness and Non-Fitness Groups ...... 99
Table 4.13. Invariance Test of The Downward Model between Fitness and Non-Fitness Groups ...... 101
ix LIST OF FIGURES
Figure Page
Figure 2.1. Sport Experience Design (SX) Framework (Funk, 2017)...... 9
Figure 2.2. A Conceptual Model of the Means-chain chain Theory (Gutman, 1982)...... 12
Figure 2.3. A Model of Experience Construction and Evaluation...... 34
Figure 4.1. Hierarchical Value Map ...... 68
Figure 4.2. Model C ...... 92
Figure 4.3. The Structural Model in The Upward Direction...... 96
Figure 4.4. Standardized Path Coefficients across Fitness And Non-Fitness Groups of The Upward Model...... 100
Figure 4.5. Standardized Path Coefficients across Fitness And Non-Fitness Groups of
The Downward Model...... 102
x
CHAPTER 1
1. INTRODUCTION
Athleisure—the trend of wearing activewear in non-fitness contexts—has become fashionable in recent years (NPD Group, 2014). As a result of its increasing popularity, the activewear industry had an annual increase in sales of 7% in 2016 globally (Bobila,
2017). That growth was almost two times faster than the growth in other clothing categories, making activewear an alluring area for expansion by apparel brands and retail companies.
While the activewear market shows optimism, activewear brands are facing problems of brand positioning. Should brands position themselves and their products toward the sport performance domain or toward fashion and relaxation? One possible indication of where the market is heading lies with Adidas. Adidas, a brand that has been ranked far under Nike for years in the U.S. market, has recently begun to catch up with
Nike, boosted by a 31% increase in sale in the second quarter in 2016 (Kell, 2016).
Adidas's North American head Mark King attributed the increase in sales to fashion- driven product design and marketing strategies that position the brand’s products as everyday casual apparel instead of athletic clothing (Woolf, 2017). Accordingly, Nike, with its strong focus on sport performance, is planning to reposition itself to be more efficient in adapting to the athleisure trend (Kell, 2017). However, this shift also heralds a threat for Nike’s sustainable growth as the brand’s image is built around sport performance (Ratner, 2017).
The problem of brand positioning is not unique to Nike. For example, Under
Armour is undergoing restructuring as the company struggles with decreasing consumer 1
interest in performance-focused products (Gregg, 2017). Many other brands also need to rethink their brand positioning as a more and more brands enter the activewear market.
Statement of the Problem
At its core, brand positioning is concerned with consumer perception (Sujan &
Bettman, 1989). Sport management literature has provided limited insight into consumer perceptions of activewear brands. Existing literature on sport apparel consumption has focused on sport team-licensed merchandise, which is largely used for symbolic purposes
(Kwon, Trail, & Lee, 2008). However, as activewear is engineered for fitness purposes, consumer perceptions of activewear also have an important functional component (Zhou et al., in press). Consumers may not care about the fabric of a team jersey as long as the jersey bears a team logo, but they may place a major emphasis on the fabric of a running shirt because the fabric could have a direct impact on how consumers feel when running.
In addition to the functional aspect, the contemporary activewear experience has a significant fashion component that relates to consumers’ lifestyle, emotional state, and personality (O'Sullivan, Hanlon, Spaaij, & Westerbeek, 2017). Consumers develop diverse perceptions regarding activewear, and this diversity cannot be fully captured by existing literature on sport team-license merchandise.
Another important limitation in existing literature is the neglect of consumer perception from the “using” perspective. Previous studies have emphasized “buying” sport products by examining outcomes such as purchase intention (Kwon, Trail, & James,
2007), purchase frequency (Kwon & Armstrong, 2006), and product choice (Lee &
Ferreira, 2011), all of which happen at the point of purchase. However, the athleisure phenomenon is characterized by consumers “using” sport products in various contexts.
2 While “buying” is a necessary step for "using", it is limited in its ability to inform consumers' experience “using” the product. Existing research has shown that consumers’ actual product usage behavior is not fully explained through self-reported behavior intentions; furthermore, consumers’ product perceptions fluctuate during product usage
(Richins & Bloch, 1991; Sutton, 1998). According to Funk (2017), understanding the
“using” experience requires in-depth, focused information about consumers’ thoughts and feelings during product usage as well as consumers’ responses to the specific design attributes of the product. By focusing on “buying,” existing research provides a narrow scope to understand consumer experience. Examining the “using” experience could instead provide insightful information about the sport product experience, revealing
“what consumers ‘do’ and ‘feel’ and not just what they ‘say’ on the survey” (Funk, 2017, p. 155).
Purpose of the Study
The overall purpose of this dissertation is to understand consumer perceptions of wearing activewear in different contexts. To understand the perceptions, the current research examines the intersection of the user and the context in the Sport Experience
Design (SX) framework of Funk (2017). Specifically, the means-end chain theory of
Gutman (1982) and the situation research of Belk (1975) are integrated to understand how consumers construct and evaluate product usage. Three research questions are asked about the content and structure of consumer perceptions of activewear usage, and variations of the perceptions in different contexts. Through answering these questions, this research provides an approach to studying the intersection of the user and the context in the SX framework as well as empirical insights into the marketing of activewear.
3 Significance of the Study
The current research contributes to the sport experience design literature.
Specifically, the means-end chain theory and situation research are integrated to examine the intersection of the user and the context in the SX framework. Activewear provides an ideal context to study the intersection of user and context in the SX framework because the athleisure phenomenon involves activewear consumers (i.e., the user) wearing activewear in and outside of the gym (i.e., the context). Additionally, activewear represents an intriguing product category to understand multiple facets of sport consumer perception, as it has “filled a gap in the marketplace, where clothing that was functional wasn’t particularly stylish” (Forbes, 2016).
This research also contributes to Gutman (1982)’s means-end chain theory, which serves as the theoretical foundation for understanding the intersection of user and context.
While means-end chains can be interpreted from the inclusive and non-inclusive view and the upward and downward directions (Snelders & Schoormans, 2004; Overby,
Woodruff, & Gardial, 2005), existing research has neglected to compare and contrast these different approaches. The current research addresses this neglect by adapting situation research of Belk (1975) to examine the influence of context on means-end chain structure. Knowledge of the context component in the SX framework is therefore reinforced.
Last but not the least, the current research makes practical contributions to activewear brands and brand positioning. This research identifies the important attributes, benefits, and end-state values in consumers’ activewear experience and how they connect in consumers’ minds. Based on these findings, brands will have a better knowledge of
4 what consumers value in activewear. The identified connections are valuable for brands to align themselves with consumers' personal values (Reynolds & Gutman, 1988).
Moreover, the findings illustrate differences in consumer perception of activewear in fitness and non-fitness contexts. Activewear brands can position themselves toward the sport performance orientation by marketing activewear in the fitness context, or toward the fashion orientation by marketing activewear in the non-fitness context. Based on the findings, activewear brands can decide how to connect the products to the consumers according to the brand positioning orientations they want to take. Overall, this research will inform activewear brands about possible design and marketing strategies they could use to develop consumer perceptions in different contexts, and therefore be more precise in targeted brand positioning.
Delimitation of the Study
There are several limitations regarding the overall design of the current research.
First, with its interest in activewear, the current research is limited in its ability to generalize to the consumer experience with other products. As discussed earlier, consumer experience with sport team-licensed apparel may be significantly different from the experience with activewear (Kwon et al., 2008; Zhou et al., in press). The current research chooses to focus on activewear consumption because of its growing relevance to consumer life and the various contexts in which it is used, which is beneficial to inform sport consumer experience research.
The current research uses the means-end chain theory, which has its limitations.
The means-end chain theory outlines three types of consumer perceptions and presents a rationale for how these perceptions are connected (Gutman, 1982). However, the
5 attributes-consequences-values chain does not intend to describe the steps that consumers take to develop perceptions regarding a product. Therefore, while means-end chain theory reflects how consumers organize their product perceptions, it should not be understood as a theory of cognitive processes, as it does not describe a process of change or development. Future research should integrate the current research with process theories, such as the elaboration likelihood model (Petty & Cacioppo, 1986), to further understand how sport consumers develop product experiences.
6 Definition of Terms
Table 1.1. Definitions of Terms
Terms Definitions References Attributes The descriptive characteristics of a product Gutman (1982); that represent the concrete meanings of the Keller (1993) experience. Consequences The relatively abstract meanings consumers Gutman (1982); interpret from their behaviors of using the Keller (1993) product. End-state values The preferred end-state of being that has the Gutman (1982); most abstract meanings that consumers Thompson and Chen could employ when constructing their (1998) experience. Means-end chain The pathways that connect attributes with Gutman (1982); structure end-state values through consequences. Overby et al. (2005) Product-usage context A set of circumstances in which a product is Belk (1975) used and do not follow the traits of the consumer and the product.
7 CHAPTER 2
2. REVIEW OF LITERATURE
The following chapter outlines the relevant theoretical and empirical works that contribute to understanding consumer perceptions of the sport experience. This chapter is organized into four main sections. The first section reviews the Sport Experience Design
(SX) framework (Funk, 2017). This framework outlines the sport user, the sport context, and the sport organization as three sectors that are involved in designing the sport experience. The framework highlights the need for sport organizations such as activewear brands to understand the intersection of sport user and the context.
Accordingly, the second section reviews literature related to sport consumers and introduces the means-end chain theory, which is the primary theory the current research uses to understand consumer perceptions at the intersection of user and context.
The third section reviews the literature on context, which is the set of circumstances in which the user uses a product. Specifically, works in environmental psychology represented by Belk (1975) is reviewed to further explain the role of context in consumer perceptions.
Integrating the previous sections, the fourth section proposes an approach to understand the intersection of the user and the context. Three research questions are developed based on the proposed approach.
Sport Experience Design Framework
Consumer experience can be understood as the overall journey and outcomes formed by consumers’ encounters with a product (Lewis & Chambers, 2000). The focus of consumer experience is not on the product that is offered or consumed, but on a
8 consumer’s interactions with the product. For sport consumers, the consumer experience is formed on the basis of a multitude of behaviors, feelings, and thoughts that occur to the consumers before, during, and after they use sport products (Funk, 2017).
The SX framework provides an approach to design sport experience with a focus on the consumer (Funk, 2017). According to the SX framework, designing the sport experience involves three elements: sport organization, sport user, and sport context (see
Figure 2.1).
Figure 2.1. Sport Experience Design (SX) Framework (Funk, 2017).
The sport organization is the entity that produces and delivers sport products. In the activewear experience, the sport organization is represented by activewear brands such as Nike and Adidas that design, manufacture, and sell activewear to consumers.
Every activewear brand has its own organizational structure, policies, and strategies that influence the operation of the brand and the products it offers.
The sport user is the consumer who uses the products offered by a sport organization (Funk, 2017). In activewear consumption, the sport user refers to consumers who wear activewear in various types of activities. According to the consumer experience
9 literature, users are not passive actors that accept ready-to-use experiences that are handed over by business organizations. Instead, users actively participate in creating the experience (Walls, Okumus, Wang, & Kwun, 2011). Furthermore, consumers’ characteristics, such as personal values, goals, and involvement with a product, influence consumers’ cognitive activity, product preference and satisfaction, and the meanings they associate with the product (e.g., Celsi & Olson, 1988; Ligas, 2000; Shim & Eastlick,
1998). A consumer’s physical exercises involvement (Casper, Gray, & Stellino, 2007), fashion taste (Chae, Black, & Heitmeyer, 2006), and involvement with activewear itself
(Bloch, Black, &, Lichtenstein, 1989) could influence the experience with activewear.
The sport context is the environment that mediates interactions between the sport user and the sport organization (Funk, 2017). In the activewear experience, the sport context can be the physical and social environment in which a consumer wears activewear or the activity that is carried out when a piece of activewear is used. Previous sport management literature has mostly studied the sport context as the physical features and interpersonal interactions that are designed by sport organizations when sport consumers enter a sport facility or participate in an event (e.g., Du, Jordan, & Funk,
2015; Yoshida, James, & Cronin, 2013). Yet, the broader consumer experience literature suggests context should also capture other factors, such as time and consumers’ mood, over which sport organizations have limited control (Belk, 1975). Moreover, Funk (2017) points out that the sport context also includes contextual factors before and after the sport consumption behavior to “include experiences not directly controlled by the sport organization” (p. 153). This requires organizations to understand the contextual factors
10 that may influence how consumers use and feel about products, even though the organization may not be able to control those factors.
As indicated in the SX framework and its related literature, sport organizations including activewear brands need to consider the intersection of the user and the context, both of which they do not have the full control. After a pair of Nike yoga pants is purchased from the store, Nike has limited control over how, when, and where the consumer wears the pants. When a consumer wears the pants to run on the treadmill in a gym, his or her experience with the pants is likely to be different from when the pants are worn for outdoor running or grocery shopping. Therefore, in addition to designing and manufacturing high-quality products, brands need to understand how consumers use and perceive the product in different usage-contexts. This understanding is especially relevant for the success of activewear brands in the athleisure trend.
However, Funk (2017) does not identify a specific approach that the intersection of the user and the context could be examined. On the user side, while user characteristics are “important considerations that influence assessment of the sport user experience”
(Funk, 2017, p. 153), the SX framework does not provide a clear direction on how to examine consumers’ assessment of the experience. On the context side, while literature has highlighted “the importance of describing context-specific interactions that influence the sport user experience” (Funk, 2017, p. 153), the SX framework does not provide a guideline to examine the contextual elements. Overall, the SX framework offers big- picture ideas and principles for sport experience research but does not provide specific assumptions and relationships to examine regarding the intersection of user and context.
To fill in these assumptions and relationships, this research supplements the SX
11 framework with the means-end chain theory, which is used to explore how consumers construct and evaluate their experience with using a sport product (e.g., activewear) in a specific context.
Means-end Chain Theory
The means-end chain theory considers consumers’ perceptions of a product as a network of chains that connect product attributes to consumers’ personal values (Gutman,
1982). As depicted in Figure 2.2, the means-end chain theory posits that consumers’ product perceptions are organized on three levels: attributes, consequences, and end-state values. The three levels are connected by double-headed arrows that illustrate two approaches to construct means-end chains. The upward chain connects attributes to consequences and then end-state values. The downward chain connects end-state values to consequences and then attributes. The upward chain reflects an inclusive and attribute- driven approach to study consumer perceptions, while the downward chain reflects a non- inclusive and value-driven approach (Overby et al., 2005). This difference is elaborated further in the following sections.
Figure 2.2. A Conceptual Model of the Means-chain chain Theory (Gutman, 1982).
The following sections review the literature on means-end chain theory. The sections are organized into four parts. The first part is a review of the concepts of inclusiveness and abstraction, as they are the basis of means-end chain theory. In the
12 second part, means-end chain content, including attributes, consequences, and end-state values, are introduced as three types of means-end chain content that are on different levels of abstraction. The third section reviews the means-end chain structure, which refers to the double-headed arrows that connect the three components (see Figure 2.2).
Two issues on the means-end structure are discussed: the inclusive vs. non-inclusive view of abstraction, and the upward vs. downward direction of means-end chain structure. The fourth part summarizes the means-end chain theory and suggests the necessity to consider the context, which is reviewed next.
Inclusiveness and Abstraction
The core of means-end chain theory attempts to determine how consumers organize their perceptions of a product into categories (Gutman, 1982). There is an infinite amount of perceptions that a consumer can develop toward a product. This huge volume of information has to be arranged into a more manageable form when the consumer needs to evaluate the product (Rosch, 1978).
Gutman (1982) suggests that in order to reduce cognitive workloads when discriminating between products, consumers subconsciously engage in a categorization activity that aggregates perceptions into categories with different levels of inclusiveness.
Inclusiveness refers to “the degree of similarity among object in a category” (Gutman,
1982, p. 63). Perceptions that focus on the specific details of a product are less inclusive.
When consumers are to describe yoga pants, a concrete description “black color” has low inclusiveness because it excludes anything that is not in black. In contrast, the description
“attractive design” has high inclusiveness as it may include “black color”, “flattering fit”, and many more details. A category with high inclusiveness is likely to have a high level
13 of abstraction, which is the inverse of how directly the information within a category denotes a particular objects (Bettman & Sujanm 1987). A category with low inclusiveness is less abstract, whereas a category with high inclusiveness is more abstract.
Means-end Chain Content
According to Gutman (1982), consumers’ perceptions of a product can be arranged along three major levels of abstraction. The three levels are attributes, consequences, and end-state values with attributes on the lowest level of abstraction and end-state values on the highest (see Figure 2.2). A detailed review of attributes, consequences, and end-state values is provided below.
Attributes
While Gutman (1982) does not formally define attributes, attributes are usually operationalized as descriptive features of a product. Some of these attributes are very concrete (Walker & Olson, 1991). Concrete attributes are attributes that can be represented as a distinct material form and tend be unidimensional, meaning that a concrete attribute describes one specific feature of a product (Snelders & Schoormans,
2004)). For example, the texture of organic foods (Zanoli & Naspetti, 2002), the size of lens and shutter speed of cameras (Graeff, 1997), and the fabric of women’s clothing
(Hines & O’Neal, 1995) concretely describe specific features of the products. Concrete attributes also tend to be the intrinsic functions that allow a product to perform (Keller,
1993; Rao & Monroe, 1988). Overall, concrete attributes are the least abstract units of information in consumer perceptions of a product (Zeithaml, 1988).
In addition to concrete attributes, consumers also develop more generic perceptions of product attributes. These generic perceptions are called abstract attributes
14 (Walker & Olson, 1991). Instead of explicitly describing product features, abstract attributes consist of product information that needs to be inferred (Bettman & Sujan,
1987). For example, workmanship is an abstract attribute of clothing because it needs to be inferred from concrete attributes such as seams and hems (Abraham-Murali & Littrell,
1995).
Consumers perceive a range of concrete and abstract attributes in clothing usage and these perceptions are used to construct consumers’ experience with the apparel.
Using focus group data collected from female activewear consumers, Zhou et al. (in press) identify six attributes associated with activewear. While the study does not make the distinction between concrete and abstract attributes, four of the attributes, namely functional design, color, size and fit, and price are relatively concrete. The other two attributes, presentation of femininity and model imagery, are relatively abstract as they are developed based on evaluations of concrete attributes.
Abraham-Murali and Littrell (1995) generate a list of concrete apparel attributes and group the attributes into four abstract categories. The first category is physical appearance, which includes attributes such as color that influence how the apparel looks.
The second category is physical performance, which includes attributes such as durability that influence usage. The third category is expressive, which includes attributes such as style that evoke feelings. The fourth category is extrinsic, which includes attributes such as brand name that are not part of the product itself. The study also reveal that attributes in the physical performance category tend to be more concrete and unidimensional, whereas attributes in the other three categories are more abstract and multi-dimensional.
As aesthetic elements in activewear are becoming increasingly popular, consumers may
15 develop many perceptions of the fashion and expressive features of activewear and these perceptions are likely to be abstract. However, as shown in Figure 2.2, consequences are on a higher level of abstraction than attributes.
Consequences
Consequences are “any result (physiological or psychological) accruing directly or indirectly to the consumer (sooner or later) from his/her behavior” (Gutman, 1982, p.
61). Scholars use “consequence” and “benefit” interchangeably, denoting considerable overlap between the two concepts (Gutman, 1982; Keller, 1993). Similar to consequences, benefits represent the outcomes of using the product and as such have more abstract meanings than attributes (Keller, 1993). Consequences can be physiological, psychological, or sociological (Gutman, 1982). Physiological consequences are outcomes that relate to human’s physiological needs such as satisfying hunger. Psychological consequences relate to one’s concepts about himself or herself such as self-esteem. Sociological consequences emphasize on one’s relationships with others such as enhanced status.
Research into apparel consumption provides a similar typology of consequence as that which is offered in Gutman (1982). Specifically, Lamb and Kallal (1992) identify the three types of benefits in apparel usage as functional, expressive, and aesthetic. The functional benefits belong to Gutman’s (1982) physiological dimension; they include outcomes such as comfort and thermal balance (e.g., Uttam, 2013). Functional benefits usually correspond to attributes such as fit, pretention, and comfort. Expressive benefits represent the psychological and sociological domains. When using activewear, consumers usually expect activewear to convey an image of competence, sincerity, and
16 ruggedness (Tong & Su, 2014). Expressive benefits are achieved through symbolic elements and marketing messages associated with the apparel (Zhou et al., in press).
Finally, aesthetic benefits are about how the apparel influences consumers’ pursuit of beauty and usually correspond to the apparel’s art elements, such as color and style, which create relationships between the body and the garment.
While functional and expressive benefits have a clear fit in Gutman’s (1982) typology, the position of aesthetic benefits is not quite clear. Zhou et al. (in press) find that female activewear consumers pursue a physically fit body image as an aesthetic benefit of wearing activewear. While beauty corresponds to physiological forms, it also has a psychosocial component. This belief can be traced back to Kant and Pluhar’s
(1987) philosophy, where it is argued that the judgment of beauty is about a sense of harmony that is universal to anyone. Critical to understanding aesthetic concerns is the knowledge that consumers choose and evaluate apparels within a social context, which defines the standard of beauty that may change over time (Lamb & Kallal, 1992). Labat and DeLong (1990, p. 44) likewise state that “each society develops an image of the ideal body”, suggesting that beauty is a sociological construct. In Zhou et al. (in press), the fit body that female consumers pursue reflects an ideal image for women in western cultures. Hence, aesthetic benefits may overlap the physiological and psychosocial dimensions of consequences.
It is meaningful at this point to discern how aesthetic benefit is situated in
Gutman’s (1982) typology as it relates to the concept of abstraction, which is the basis of means-end chain theory. While Gutman (1982) originally categorizes consequences as physiological, psychological, and social, Walker and Olson (1992) extend this
17 categorization by considering the level of abstraction involved in these categories. On the one hand, physiological consequences are less abstract as they relate closer to how the product functions. Psychological and social consequences, on the other hand, are more abstract as they relate closer to the consumers’ self-concepts. This physiological and psychosocial distinction has been supported by Heinze, Thomann, and Fischer’s (2017) study on mobile commerce consumption that identifies five physiological consequences that lead to four psychological consequences, suggesting that psychological consequences are outcomes of experiencing physiological consequences. However, researchers remain ambivalent as to understanding the abstraction level of aesthetic benefits. Following the trend of combining beauty and functionality into activewear, the role of aesthetic benefits in the means-end chain network awaits investigation.
End-state Values
As shown in Figure 2.2, end-state values are on the top level of the hierarchy of abstraction. End-state values, also referred to simply as values, are the “preferred end- states of being…. a type of consequence for which a person has no further (higher) reason for preference” (Gutman, 1982, p. 64). Values are enduring and stable over time and across contexts (Rokeach, 1973). Values are central to human lives because they closely connect to individuals’ cognitive activity, influence attitude, and predict behaviors
(Homer & Kahle, 1988). Emotional well-being (Jägel, Keeling, Repple, & Gruber, 2012), self-fulfillment and self-confidence (Amatulli & Guido, 2011), and contentment
(Wagner, 2007) are identified as important values in clothing consumption. These values are more abstract than consequences and reflect the important beliefs consumers hold with respect to themselves or what kind of person they strive to become (Rokeach, 1968).
18 When a woman says, “this activewear makes me feel accomplished,” it connects more closely with her self-concept than if she says, “this activewear makes me look slim,” which exists on the consequence level.
Values have internal and external dimensions and this distinction reflects the internal and external locus of control (Homer & Kahle, 1988; Rotter, 1966). Self-respect, sense of accomplishment, and fun and enjoyment represent internal values because they are based on outcomes that are relatively controllable by an individual. Values such as sense of belonging, being well-respected, and security are more dependent on factors to which an individual has less control, and therefore fall into the external dimension. The internal dimension of values is further divided into individual and interpersonal aspects
(Homer & Kahle, 1988). Individual values, including self-respect and sense of accomplishment, are free from the judgment or opinion of others. Interpersonal values, represented by fun and enjoyment, combine the aspects of individual and external values as they relate to social interactions but are internally driven (Rose, Shoham, & Kahle,
1994).
While values are held relatively stable, their importance varies across individuals and contexts. A consumer is usually oriented toward one of the value dimensions than another. Those who have strong interval values tend to be frequent shoppers of a product, believe they can always control outcomes, and are more critical in evaluating core product features (Homer & Kahle, 1988). Consumers who are driven by external values purchase a product less frequently, place more importance on sociological benefits of the product, and are more likely use the product in inappropriate ways (Chryssohoidis &
Krystallis, 2005; Limon, Kahle, & Orth, 2009). Comparing values across contexts,
19 Walker and Olson (1991) find that self and social-oriented shopping tasks differentially activate the internal and external value dimensions, thereby influence consumers’ product preference. While an activewear consumer may perceive values such as fun, accomplishment, or sense of belonging in his or her overall experience with activewear, one of the value dimensions may be more salient when the consumer wears activewear at work than in a physical exercise context.
Existing research has neglected to address the salient end-state value in sport experience. Chi and Kilduff (2011) use the PERVAL framework of Sweeney and Soutar
(2001) to study the consumer-perceived value of activewear. However, the PERVAL confuses end-state values with attributes, which are two distinct components of the means-end chain (Lee, Trail, Kwon, Anderson, 2011). Based on the brand association theory, Zhou et al. (in press) investigate consumers’ perceived attributes and benefits in activewear consumption but fail to identify perceptions on the level of values. More importantly, sport marketing research has largely neglected to link consumers’ personally important values with the actual product (e.g., Bauer, Stokbuerger-Sauer, & Exler, 2008).
An important limitation has therefore resulted regarding how brands can create sport products that fit into consumer’s life. The next section reviews literature on means-end chain structure, which addresses this limitation.
Means-end Chain Structure
On the basis of the three levels of means-end chain content, the means-end chain theory posits that consumers link content of attributes, consequence, and end-state values to form means-end chains. Understanding how the chains are
20 formed is a central concern of the means-end chain theory, as Gutman (1982) points out:
Knowing that consumers want to look well-dressed doesn't tell us much unless we know why they want to look that way (sexual attractiveness, accomplishment, neatness, etc., which are value-level considerations) and what attributes in clothing they associate with being well dressed. (p. 60)
Knowing that consumers would like to feel accomplished in activewear does not help activewear brands much unless we know what attributes in activewear can create a sense of accomplishment. Mapping the means-end chain structure that connects attributes with end-state values is necessary for designing sport experience. To map this structure requires an understanding of two issues.
First, the relationship among attributes, consequences, and values needs to be clarified. Specifically, the literature suggests that higher order means-end chain elements, such as consequences and values, can be viewed as inclusive or non-inclusive of lower order elements, such as attributes (Snelders & Schoormans, 2004). To distinguish the inclusive and non-inclusive views is important for understanding how consumer perceptions are organized.
Second, the connections to and from attributes, consequences, and values need to be discerned. Specifically, both an upward direction that links attributes to consequences and then to values, and a downward direction from values to consequences and attributes have been applied in empirical studies without justifications (Overby et al., 2005). To compare the two directions in Figure 2.2 is important for understanding what type of perceptions drives consumer experience. In the following sections, the inclusive and non- inclusive views are discussed first, followed by the upward and downward directions.
21 The Inclusive and Non-inclusive Views
The means-end chain theory describes how consumers organize their perceptions of a product into different levels of abstraction (Gutman, 1982). Research suggests that there are two approaches to the relationships between abstract perceptions and concrete perceptions. The first approach, the inclusive view, was adopted in the early stage of means-end chain research (Gutman, 1982; Walker & Olson, 1991). The inclusive view posits that an abstract perception is inclusive of, and inferred from, several concrete perceptions. Specifically, abstract perceptions are developed by aggregating concrete perceptions such that consumers can evaluate a product effectively without having to process the concrete information. If consumers hold the perceptions that an activewear has “nice color” and “flattering fit”, an abstract attribute “attractive design” is formed accordingly. In a sense, there is a causal relationship from concrete perceptions to abstract perceptions.
On the contrary, the second approach, called as the non-inclusive view, does not assume any relationship between abstract and concrete perceptions. Instead, the non- inclusive view thinks consumers can form general beliefs about a product without relying on any concrete information (Snelders & Schoormans, 2004). For example, the judgment of product quality is influenced by consumers’ perceptions of some intangible and conceptual factors that even consumers themselves could not identify where these perceptions come from (Silverman & Grover, 1995). This view relates to Fishbein and
Ajzen’s (1975) concept of descriptive belief, which is a belief that is established based on direct observation without making any inference. The notion of non-inclusive concept can also be traced back to Kant and Pluhar’s (1987) philosophical work on aesthetic.
22 According to Kant and Pluhar (1987), the judgment of beauty is not tied to any absolute quality of the object itself. Instead, when people say an object is beautiful, it is free from logical reasoning and people feel beauty immediately upon observing it. As Snelders and
Schoormans (2004, p. 808) say, “a consumer may call a product elegant, without being able to point to the exact things that make the car elegant.”
Although the means-end chain theory was initially developed with the inclusive approach in mind, the non-inclusive approach has found support in later research. Using laddering interviews, Snelders and Schoormans (2004) find a large portion of abstract attributes that are not inclusive of any concrete attributes. When explaining their findings, the authors use the context availability theory, which makes a distinction between abstract and concrete information based on the contextual information required for information processing. Specifically, it is argued that abstract information can be used in wider domains than concrete information, and therefore requires more context-specific information to reduce the uncertainty involved in processing information
(Schwanenflugel & Shoben, 1983). Snelders and Schoormans (2004) use the example of
“safety” and “airbag” to illustrate this view. While the two concepts are related, “safety” is more abstract than “airbag” because the former is applicable to multiple product domains while the latter is only applicable to automobiles. In this case, “safety” would be hard to interpret if its context is not specified. However, when adequate contextual support is available, consumers are able to process abstract information as quickly as concrete information (Schwanenflugel, Akin, & Luh, 1992). Therefore, abstract information does not need to subsume concrete information when the context is well- defined. Moreover, multiple means-end chain studies have identified direct paths from
23 attributes to end-state values without going through consequences, suggesting that consumer perceptions may not proceed through all levels of abstraction (e.g., Amatulli &
Guido, 2009; Russell, Flight, Leppard, Van Pabst, Syrette, & Cox, 2004; Zanoli &
Naspetti, 2002). When activewear is worn in a defined context, consumers may form an abstract perception of “attractive design” without being able to identify any concrete attribute that makes the activewear attractive.
The Upward and Downward Directions
The difference between inclusive and non-inclusive views connects to a discussion on the upward and downward directions of means-end chains. The two directions are visualized in Figure 2.2. In the upward direction, a consumer wears a pair of yoga leggings and develops the perception that the legging has a good fit (i.e., attribute). As a result, the consumer’s body shape looks nicer (i.e., consequence), leading the consumer to feel more confident (i.e., end-state value). In this direction, the consumer’s perceptions are driven by attributes of the activewear. In the downward direction, a consumer who wants to be more confident would appreciate the nice fit of yoga leggings because the legging makes the consumer look nicer. In this direction, the consumer’s perceptions are driven by personally important end-state values. Differences between the two directions and their correspondence with the inclusive and non-inclusive views are further elaborated below.
Same with the inclusive view of abstraction, the upward direction is also adopted in the original means-end chain theory of Gutman (1982). The upward direction starts on the attribute level, where consumers develop perceptions regarding their experience of using attributes. These experiences lead to consequences. The meaning of the
24 consequences are then evaluated by consumers and are attached with end-state values. As end-state values are held relatively constant and reflect consumers’ self-concepts
(Rokeach, 1968), the upward direction describes a flow that connects the product to the consumer. Consistent with the inclusive view, the upward direction is built on the basis of concrete perceptions of product attributes and the concrete perceptions are further organized in abstract perceptions that are easier to be stored and retrieved (Brunsø,
Scholderer, & Grunert, 2004). In a sense, both the upward direction and the inclusive view consider abstract perceptions as outcomes derived from concrete perceptions.
In contrast, the downward direction considers abstract perceptions as goals and these goals decide how product attributes are used and perceived (Overby et al., 2005).
Starting on the end-state value, the downward direction describes a flow that connects the consumer to the product (Overby et al., 2005). Consistent with the non-inclusive view, abstract perceptions in the downward flow can exist on their own. A consumer may hold some relatively stable and abstract perceptions and these perceptions influence how the consumer would evaluate the consequences that occurred and the attributes that are used.
Hence, the downward direction can be interpreted as a goal-directed process, one that is driven by end-state values held by consumers (Brunsø et al., 2004).
Existing research has neglected to examine the bi-directional conceptualization of means-end chains and their structural differences. Indeed, the means-end chain theory and its associated methodology, the laddering method, have not taken a clear stand on which of the two directions should be endorsed when analyzing and interpreting means- end chains (Grunert & Grunert, 1995). While most of the existing studies have conceptually adopted the downward direction to uncover end-state values as consumer
25 motives, the way their data were collected are not different from studies that are conceptualized in the upward direction (e.g., Amatulli & Guido, 2011; Zanoli & Naspetti,
2002). In addition, studies following the downward direction present and interpret their findings in an upward way (e.g., Bagozzi & Dabholkar, 1994). Assuming a downward direction of means-end chains, Brunsø et al. (2004) compare different models reflecting the attribute-consequences-value relationship. They find that the model in which consequences fully mediate the influence of end-state values on attributes yielded the best fit. While Brunsø et al. (2004) transform the means-end chain structure from a heuristic concept to a falsifiable model, the study has not compared the downward and upward chains. Moreover, across several studies that follow the upward direction, the chain is not conceptualized and operationalized as a structure that is different from the downward chain. The upward and downward directions of means-end chains (see Figure 2.2) awaits further investigation
Fitting the Means-end Chain Theory Into the SX Framework
The SX framework does not provide a specific approach to use when examining the intersection of user and context (Funk, 2017). The means-end chain theory can be applied to study this intersection from the approach of consumer perceptions. Consumers form various perceptions of the usage experience when they use a product in a context.
The means-end chain theory informs the SX framework about the types of perceptions that consumers develop (i.e., means-end chain content) and structural relationships of these perceptions (i.e., means-end chain structure).
Based on the means-end chain model, the intersection of user and context can be interpreted from the consumer’s perspective. When a consumer thinks about the
26 experience wearing a pair of yoga pants, the consumer has concrete perceptions regarding fabric and color (i.e., attributes) of the pants, more abstract perceptions of how he or she performs and looks (i.e., consequences) in the pants, and very abstract perceptions of how the consumer feels about him- for herself (i.e., end-state values) when wearing the pants.
Depending on the approach the consumer takes, these perceptions are connected in the upward and downward directions shown in Figure 2.2.
While the means-end chain theory informs the SX framework, it is not without its limitations. With a focus on consumer perceptions, the means-end chain theory describes the user component in the SX framework (see Figure 2.1). Context, another important component of this intersection, is not the central concern of the means-end chain theory.
The role of context in means-end chains has been explored in some empirical studies.
Findings suggest that situational factors, such as different shopping tasks (Walker &
Olson, 1991) and affective states (Huber, Beckmann, & Herrmann, 2004), influence the content and structure of means-end chains. However, with limited conceptual guidance from Gutman (1982), these empirical studies are unsystematic and capture a narrow range of situational factors. Other situational factors, such as time pressure during shopping (Park, Iyer, & Smith, 1989), public versus private usage situations (Aqueveque,
2006), and the atmosphere of the consumption situation (Turley & Milliman, 2000), may also influence -means-end chains. With few studies taking product-usage context into consideration, little is known about variations of means-end chains across different contexts. To introduce a systematic way to study the context component in the SX framework, the next section reviews research on the role of context in consumer behavior.
27 Product-Usage Context
An important element to consider when investigating consumer experience with a sport product is the context in which the product is used. When a consumer wears a pair of yoga pants to yoga class, the most important feature influencing the experience may be fabric, which connects to having a good practice (i.e., the consequence) and a sense of accomplishment (i.e., the end-state value). Switching to a scenario where the consumer wears the yoga pants for shopping, fabric may connect with a relaxed mood (i.e., the consequence) and fun and enjoyment (i.e., the end-state value). This example demonstrates how the product-usage context determines the way a product is used and the perceptions that are formed.
According to Belk’s (1975) situation research, behavior is influenced by external stimuli, which include all marketing and environmental factors that are external to a consumer. External stimuli are divided into two categories: the product, and the context in which the product is used. While long-lasting characteristics of the product have systematic effects on consumer behavior, context manifests its own influence because many consumer behaviors “may be enacted only under specific conditions” (Belk, 1975, p. 157).
Since the product-usage context is an omnibus construct, a taxonomy is necessary when exploring consumers’ activewear experience in different situations (Rauthmann,
Sherman, & Funder, 2015). Summarizing several existing taxonomies, Belk (1975) concludes that a product-usage context could be defined by five groups of situational variables: physical surrounding, temporal perspective, antecedent state, social surrounding, and task definition.
28 Physical Surrounding
Physical surrounding is composed of observable features such as location, weather, and material surroundings. Research has investigated the influence of store layout on store preference (Thang & Tan, 2003), the influence of in-store lighting on the number of wines consumers examine (Areni & Kim, 1994), and the influence of restaurant table-type and location on meal duration and spending (Kimes & Robson,
2004). These physical elements are studied as in-store atmospheric factors that facilitate product purchase, with very limited attention on how physical surrounding influences the experience of using the product (Turley & Milliman, 2000; Tombs & McColl-Kennedy,
2003). When a consumer wears activewear in different situations, such as running by a river vs. on a treadmill, the physical surroundings change, leading the consumer to have different perceptions.
Temporal Perspective
The temporal perspective describes product-usage context in terms of time, focusing on either a time period or time point. With a focus on buying, existing research on time-period has mainly focused on time pressure while shopping (e.g., Park, Iyer, &
Smith, 1989). The effect of usage at a point of time is not well-examined, as doing so requires multiple collections of real-time product usage data. A small body of research interested in the concept of time-of-day service marketing has found that consumers’ emotions and behaviors fluctuate during a service experience, suggesting that companies should cater to consumers based on the clock time (e.g., Maguire & Geiger, 2015;
Vassiliadis, Priporas, & Andronikidis, 2013). Research also reveals that the time-of-day influences product preference because people’s cognitive ability changes throughout the
29 day (e.g., Gehrt & Shim, 2003). Considering that activewear is used in consumers’ daily routine, the temporal perspective may influence the activewear experience. For example, a consumer who works out and uses activewear in the morning may develop a more complex means-end chain structure than a consumer who works out in the evening because people tend to be more alert and cognitively active in the morning (Dacko,
2012).
Antecedent State
The antecedent state includes those transient states such as mood or monetary condition that a consumer brings into the consumption situation. These states, while describing characteristics of the consumer, are considered as situational variables because they are temporary (Belk, 1975). For example, a consumer’s mood state usually results from external triggers and serves as an input into consumers’ chronic traits to influence cognitive processes and affective reactions (Gardner, 1985). From the means-end chain approach, moods influence a consumer’s cognitive style so that consumers in positive moods have shorter means-end chains than consumers in negative or neutral moods
(Huber et al., 2004). For consumers who wear activewear as a way to escape from negative moods, their means-end chains may be more complicated than others as these consumers deliberately process positively charged information to repair their moods
(Isen, Daubman, & Nowicki, 1987 Zhou et al, in press),
Social Surrounding
Social surrounding includes the presence, characteristics, and roles of other people who are involved in the situation and the interactions among these people.
Research on social surrounding has its roots in social psychology theories such as the
30 theory of reasoned action (Fishbein, 1979), social identity theories (Ashforth & Mael,
1989), and symbolic interactionism (Solomon, 1983). Empirical studies have investigated the influence of dining companion on frequency of eating convenience food (Verlegh &
Candel, 1999), the influence of peer evaluation on tourism decision (Josiassen & Assaf,
2013), and the influence of peers’ presence on purchasing sport team-licensed merchandise (Chen, Lin, & Chang, 2013). Overall, this body of research suggests that the presence of important others lead consumers to use products for social concerns, such as to conform to the social norm, celebrate a culture, or to manage one’s social images. A consumer may care more about how the activewear complements his or her social image when working out in the public than working out alone at home.
Task Definition
Task definition describes a situation in terms of the primary task that needs to be accomplished when using a product. Empirical studies have investigated the influence of different shopping tasks on store choice (Van Kenhove, De Wulf, & Van Waterschoot,
1999), shopping motivation on female’s purchase intention (Tong, Lai, & Tong, 2012), and leisure tasks on subjective leisure experience (Unger, 1984). According to Unger
(1984), sport (i.e., fitness activities) represents a distinct task definition that is different from the easy/social category, which includes shopping, going to movies, dining, and many other non-sport activities. Unger (1984) also finds that sport activities interact with other situational variables, including antecedent state and social surroundings, to influence consumers’ leisure experience. As such, whether activewear is worn to fitness activities or a social event may have similar impacts on the activewear experience.
31 Task definition can alter the content and structure of the means-end chain because a consumer adopts different mindsets in response to different task definitions (Shepard,
1964). When a task is given, consumers tend to focus on product attributes and consequences that are associated with the task (Van Kenhove et al., 1999). Task definition also affects consumers’ desired consequences and end-state values. Walker and
Olson (1991) use an experimental design to elicit subjects’ means-end chain structure in different shopping tasks. It is found that self and other-oriented shopping tasks activate different aspects of consumers’ desired end-state values, leading consumers to select different product attributes that correspond to the values. This finding could be extended to better understand task definition when applied to activewear use. When a consumer wears activewear in a bar, he or she will develop perceptions around social image and beauty in accordance with the values dictated by the task. Switching to another task definition in which activewear is worn to a fitness class, the task is likely to influence the consumer’s concerns about whether the activewear provides comfort and physical support.
To sum up, the means-end chain literature has heretofore neglected the role of product-usage context as an important factor that affects consumers’ means-end chains.
Situation research like that conducted by Belk (1975) suggests that a situation is defined by physical surrounding, time, mood state of the consumer, social surrounding, and task definition. These characteristics of a situation, together with the characteristics of the consumer, decide how consumers develop perceptions of their activewear experience.
Summary and the Conceptual Approach
32 The SX framework has identified the intersection of the user and the context without specifying how the intersection could be examined (Funk, 2017). The current research uses means-end chain theory and the situation research to inform this intersection. Gutman’s (1982) means-end chain theory continues to serve as the primary approach to study the interaction from consumers’ perceptive, while the situation research put forth by Belk (1975) addresses the underlying context component of the interaction.
In this way, means-end chain theory illustrates consumer experience as a chain that connects attributes, consequences, and end-state values (Gutman, 1982). Two important issues to consider when mapping means-end chains are the inclusive and non- inclusive views to understand abstraction and the upward and downward directions of the overall means-end chain structure. While Gutman (1982) develops the means-end chain theory in an upward direction using the inclusive view, the downward direction and non- inclusive view have also found support in later research (e.g., Snelders & Schoormans,
2004).
An additional factor to consider in examining the sport experience is the context in which a sport product is used (Funk, 2017). As sport products such as activewear are used in various contexts in consumers’ daily lives, the experiences should be influenced by the nature of the product-usage context. Environmental psychology research, exemplified by Belk (1975), provides a typology of contextual variables that is applied to studying the sport experience. Depending upon the physical surrounding, temporal perspective, antecedent state, social surrounding, and task definition of the situation, consumers develop perceptions in diverse ways. Integrating the situation research with
33 the SX framework and means-end chain theory provides an intriguing opportunity to understand consumers’ sport experiences across various contexts in a systematic manner.
Building upon the preceding literature, the current research proposes a model of experience construction and evaluation to inform the intersection of user and context in
Funk’s (2017) SX framework. As shown in Figure 2.3, the model integrates the means- end chain theory (Gutman, 1982) and the situation research literature represented by Belk
(1975) into the SX framework.
Figure 2.3. A Model of Experience Construction and Evaluation.
Overall, the proposed model depicts how sport consumers construct and evaluate their experience with a sport product. The model can be applied to study the experience of wearing activewear at the intersection of activewear consumer and the various contexts in which activewear is worn. For example, when a consumer (i.e., a user) wears a pair of yoga pants from Nike (i.e., an organization) while shopping (i.e., a context), the consumer may develop a perception that the pants have high-quality fabric (i.e., an attribute). The nice fabric gives the consumer a nice look (i.e., a consequence), and therefore higher self-esteem (i.e., an end-state value). Moreover, the consumer may also
34 have perceptions that are not based on attributes of the yoga pants but are developed from the consumer’s own personally important values such as a sense of self-respect (i.e., the downward direction). In addition, the perceptions may be different if the consumer wears the yoga pants to a yoga class (i.e., another context), where high-quality fabric contributes to a nice practice and therefore a sense of accomplishment. A lack of systematic research on product-usage context is a significant knowledge gap in existing sport experience design literature as well as the means-end chain theory. The proposed model provides solutions to address this gap.
Research Questions
The current research focuses on the intersection of the user and the context in
Figure 2.3. The means-end chain specifies that when sport consumers think about their experience with a sport product, they develop perceptions regarding attributes, consequences, and end-state values that are linked with chains and networks. Existing studies do not offer clear identification of important attributes, consequences, and end- state values in the sport experience (e.g., Zhou et al., in press). Identifying these elements is the first step to understanding the specific perceptions that consumers use to evaluate the activewear experience. Therefore, the current research asks the first research question:
RQ1: What are the important attributes, consequences, and end-state values that
consumers perceive from their experience with activewear?
Once the attributes, consequences, and values are identified, the next questions is about how they relate to each other and how they connect to form mean-end chains. To map this structure requires an understanding of the inclusive vs. non-inclusive views
35 (Snelders & Schoormans, 2004) and the upward vs. downward directions (Overby et al.,
2005). As the existing means-end chain literature has neglected to address both issues, the second research question asks:
RQ2: What are the structural relationships among attributes, consequences, and
end-state values?
Answering questions above will provide insights into the key aspects of consumer perceptions of activewear. However, it neglects the role of context, which is an important element that influences experience evaluation. Situation research suggests that the context can influence consumers’ mindset (e.g., Shepard, 1964). It is possible that whether an activewear consumer follows the upward or downward chain is influenced by the context in which the activewear is worn. A comparison between the fitness and non- fitness contexts will be intriguing, as they are characterized by different situational variables (e.g., different physical surroundings, social surroundings, and task definitions).
Gutman (1997) suggests that taking the context into account improves the understanding of the bi-directional means-end chain structure. Hence, the third research question is asked:
RQ3: How does structural relationships of means-end chains vary in fitness and
non-fitness contexts?
Overall, the three research questions seek to examine consumers’ experience with activewear while considering the product-usage context. The first and second research questions explore the content and structure of activewear consumers’ means-end chains.
The third research question discovers variations in means-end chains structures across fitness and non-fitness contexts. Answering the research questions will provide
36 theoretical contributions to the SX framework at the intersection of the user and the context and practical contributions to activewear brand positioning.
37 CHAPTER 3
3. METHOD
The current research used a mixed-method design to address the research questions. The rationale for using mixed-method design is that neither quantitative nor qualitative methods alone can sufficiently address the posed questions (Creswell, 2003).
Rudd and Johnson (2010) call for more mixed-method research in sport management because it facilitates in-depth analysis, which is not the strength of traditionally used quantitative methods in sport management studies.
For the current research, a mixed-method research design is optimal for three reasons. First, activewear consumption is a research context about which existing sport management literature has little knowledge. In this case, a qualitative study has the potential to uncover new information about activewear consumption and provide a basic understanding of consumers’ perceptions (Shaw & Hoeber, 2016). Second, the means- end chain theory has developed its own research method, the laddering method, which is a qualitative method that usually involves one-on-one in-depth interviews with consumers (Reynolds & Gutman, 1988). The laddering technique has been extensively used in research on the means-end chain theory and has been proven useful in uncovering the consumer experience in industry research (e.g., Saaka, Sidon, & Blake, 2004). A qualitative study using laddering interviews can benefit the current research with an in- depth investigation on the meaning of activewear experience from consumers' own perspectives (Funk, 2017). Last but not least, a quantitative study is necessary because quantitative method has strengths in generalizing results to a greater population
(Creswell, 2003).
38 The current research followed an exploratory sequential design, which is usually used to develop measurements of the variables that need to be examined in a quantitative study (Roest, Spaaij, & Bottenburg, 2015). For the current research, an initial qualitative study is necessary to discover the important means-end chain content and the overall means-end chain network. This information will inform the quantitative study about what variables and relationships to test and how to measure them to address the third research question.
Research Subjects
Female activewear consumers were chosen as the subjects of this research.
Female consumers have significant relevance to the athleisure phenomena and the recent growth in activewear sales. Mark Parker, the CEO of Nike, once proclaimed that
“leggings are the new denim,” as women replace jeans with yoga pants and integrate other types of activewear into their wardrobes. In the U.S. alone, women purchase makes up $15.1 billion of activewear sales every year (Malcolm, 2015). The female influence has forced apparel companies to design comfortable and versatile clothing for women, and companies that have traditionally focused on the men’s market are now developing new lines of women’s garments. Fashion brands such as Forever 21, H&M, and
Victoria’s Secret have all launched female activewear in order to acquire a share of the market. As a result, female consumers represent the key consumer group contributing to the increasing popularity of activewear (O’Sullivan et al., 2017).
From a theoretical perspective, using a one-gender sample can eliminate the gender difference that is not a purpose of the current research. The difference between male and female in terms of their cognitive styles, value orientations in consumption, and
39 their behaviors have been well documented in the literature (e.g., Meyers-Levy &
Sternthal, 1991). Gender differences are salient in clothing consumption because the way one dresses has close associations with his or her gender-related self-concepts (Crane,
2012). Therefore, using an all-female sample can eliminate possible gender differences in the content and structure of means-end chains. In addition, female consumers are likely to represent a more informative consumer group than males. Females tend to connect various kinds of information by looking for interrelationships, similarities, and differences (Putrevu, 2001). Compared to males, females are more likely to process peripheral product information and associate a greater number of attributes, consequences, and end-state values with products (Kempf, Laczniak, & Smith, 2006).
Hence, using a female-only sample can generate more information about means-end chains than using a male-only sample.
Study 1
The purposes of Study 1 are twofold. The first purpose is to discover the important attributes, consequences, and end-state values that female consumers perceive from wearing activewear. These findings will address the first research question.
The second purpose is to address the second research question by identifying the upward means-end chain relationships that connect attributes, consequences, and end- state values from the inclusive view. Although the downward direction and non-inclusive view have been revealed in a few studies (e.g., Snelders & Schoormans, 2004), an upward and inclusive approach was adopted in Study 1 for two reasons. First, an upward and inclusive approach follows how the original means-end chain theory is originally developed in Gutman (1982). Second, while previous studies have interpreted the means-
40 end chain theory from the downward direction, they offer limited direction on how to collect and analyze laddering interview data in the downward direction (e.g., Amatulli &
Guido, 2011; Zanoli & Naspetti, 2002). Therefore, Study 1 took an approach that is consistent with Gutman (1982) to ensure correct implementation of the laddering method and interpretation of findings. This approach addresses part of the second research question and informs structural relationships to test in Study 2, which will further answer the research questions.
Study 1 used soft laddering interviews to collect data from 24 female activewear consumers. Interviews are often used when a researcher seeks detailed information about subjects’ experiences or to explore a new research topic in depth (Flick, 2002). For means-end chain studies specifically, soft laddering is an interview technique that probes research participants to think about the underlying consequences and end-state values that connect to attributes of a product (e.g., Amatulli & Guido, 2011). Compared to the hard laddering method that relies primary on questionnaires for data collection, soft laddering collects information that is more in-depth and uncovers a more representative structure of means-end chains as it does not force participants to follow a predetermined structure
(Russell, Busson, Bryan, Van Lawick Van Pabst, & Cox, 2004).
Participants and Interview Procedure
Participants were recruited through a purposeful sampling approach. The goal of purposeful sampling is to select participants who can provide rich information regarding a research topic (Patton, 2002). In light of this purpose, participants of Study 1 needed to have sufficient experience wearing activewear in either or both of fitness and non-fitness context. In order to recruit these participants, a sampling criterion based on the level of
41 fitness activity participation was used. Participants needed to involve in at least 150 minutes a week of moderate-intensity aerobic physical activity, or 75 minutes a week of vigorous-intensity aerobic physical activity, or moderate to high-intensity level muscle- strengthening activities for two or more days a week, or any equivalent combination of the above, for at least six months (Marcus, Selby, Niaura, & Rossi, 1992; Physical
Activity Guideline Advisory Committee, 2018). The assumption was that participants who met these requirements have sufficient experience wearing activewear at least in the fitness context and were likely to have experience wearing activewear in the non-fitness context as well.
An additional sampling criterion based on activewear usage was used to recruit participants who did not meet the fitness activity criteria but had sufficient experience wearing activewear in non-fitness contexts. Based on an unpublished industry report from
Australia, female consumers wear activewear to non-fitness contexts, such as running errands, catching up with friends, and shopping, at an average frequency of two times a week (Hanlon, Spaaij, Westerbeek, & Robertson, 2017). Based on this information, participants who did not meet the physical activity criterion needed to wear activewear for at least two times a week in non-fitness contexts to be eligible to participate in the study.
The researcher used a combination of the snowballing technique and advertisements to recruit eligible participants. The snowballing technique is a recruitment procedure in which interview participants are asked to identify potential participants of the study (Bailey, 1994). The advantage of the snowballing technique is its low cost and the rapport it creates between the researcher and the participants because of the
42 acquaintance system (Van Meter, 1990). The snowballing initiated from an acquaintance of the researcher and resulted in a total of five participants recruited to the study.
Since participants recruited through the snowballing technique may over- represent a certain group of consumers, a majority of participants were recruited through advertisements that were designed to access a more diverse sample (Van Meter, 1990).
Specifically, posters and flyers were distributed in two fitness facilities in a large northeast metropolitan area. Two online advertisements were posted on Craigslist and
Amazon Mechanical Turk (MTurk). The online advertisements required participants to answer a brief survey on their activewear usage behavior and exercise behavior. The researcher reviewed survey answers and based on the criteria, selected participants who wore activewear for fitness or non-fitness activities on a regular basis. Based on the sample size recommended by Olson and Reynolds (1983), 24 participants were recruited and participated in one-on-one soft laddering interviews. See Table 3.1 for information about the participants.
Before each interview, the researcher asked the participant to wear or bring her favorite activewear to the interview. The activewear served as a stimulus material that stimulated participants’ thoughts regarding their activewear experience (Wibeck,
Dahlgren, & Öberg, 2007). After a short introduction on the purpose of the interview, the researcher asked the participant to describe what she likes about her favorite activewear.
From there, the researcher asked a series of questions that guide the participant to think about her activewear experience. Interview questions were designed to determine the following: (1) What are the important attributes of activewear? (2) What consequences
43 does each attribute generate? (3) What end-state values does each consequence generate?
Below is an example of the laddering procedure in an interview with participant Donna:
Donna: Let’s say I’m wearing a black pair of yoga pants and a coordinated gray razor back. And then I would wear a pink sports bra, so it sort of stands out. Researcher: Why do you want to wear something that stands out? Why not just go with a gray bra? Donna: I think it looks nice. Because I can’t really accentuate much with my bottom. I do it with my top. I think it’s because I want to stand out. Researcher: Why do you want to stand out? Donna: I do it more to boast my own self-confidence. There are days when I’m extremely stressed out, but when I pick these really colorful things and wear them, and then I feel better about myself
In this case, Donna’s experience with activewear evolved around the attribute of color, the consequence of standing out, and the end-state value of self-confidence. The conversation illustrates how the researcher probed participants to talk about the attributes, consequences, and end-state values associated with their experience with activewear.
Means-end chains were discovered accordingly.
A combination of face-to-face interviews and phone interviews were conducted as research has shown no significant difference between transcripts produced by the two techniques (Sturges & Hanrahan, 2004). Among the 24 interviews, seven were conducted over the phone while the rest were held in places where the participants feel familiar and comfortable such as gyms that they owned memberships or cafés in their neighborhoods.
Each interview lasted for about 40 minutes and each participant was compensated with a
$25 Amazon gift card for her participation. All interviews were audio-recorded and transcribed.
44 Table 3.1. Demographic Information of Interview Participants
Pseudonym Age Race Occupation Exercise time/week Mary 26 White and Asian High school teacher No physical exercise Patricia 21 White Part-time research No physical exercise assistant Jennifer 31 White Librarian 1h Elizabeth 54 White Hairdresser 1h 20min Linda 50 Black School bus driver 1h 30min Barbara 26 White Medicine marketer 1h 30min Susan 31 White Non-profit 2h organization Jessica 55 Black Nanny 2h Margaret 28 Asian Graduate student 2h 30min Sarah 28 Black Event manager 3 hours Karen 29 Asian Graduate student 3h Nancy 28 White and Asian Project manager in 3h technology Betty 29 White YMCA front desk 3h 30min assistant Lisa 30 White Children's librarian 3h 30min Dorothy 28 White Project manager in 4h marketing Sandra 53 White Sales and marketing 4h Ashley 29 White Project manager in 4h 30min human resource Kim 24 White Graduate student 5h Donna 25 Asian Graduate student 5h Carol 31 White Project manager in 6h marketing Michelle 24 White Mental therapist 6h Emily 30 White Research associate 7h Amanda 35 White Event manager, part- 7h 30min time CrossFit trainer Helen 26 White Associate brand 10h manager
45 Data Analysis
Analysis of laddering interview data followed the three steps laid out in Reynolds and Gutman (1988). The first step was a content analysis in which the interview data were coded into attributes, consequences, and end-state values. The researcher read interview transcripts sentence by sentence to identify contents that represent the attributes of activewear, and consequences and end-state values of wearing activewear. After that, the researcher compared and contrasted the codes to group the codes into master codes based on their similarities. The purpose of this step was to make sure the coding was sufficiently abstract so that they can summarize important relationships that would be otherwise diluted (Gutman, 1991). Each type of attributes, consequences, and end-state values was then assigned a unique number. All procedures above were conducted in
Dedoose (2018), a web application for managing and analyzing qualitative data.
A concern regarding the coding process in laddering interview is that it may represent the researcher’s cognitive structure instead of that of the participants (Grunert
& Grunert, 1995). When laddering interview data is not interpreted from participants’ perspective, the credibility of findings is challenged (Creswell & Miller, 2000).
According to Lincoln and Guba (1985), member checking should be used when credibility needs to be established through the lens of research participants. Hence, the researcher conducted member check with participants. Following suggestions of Creswell and Miller (2000), the researcher sent the codebook and two randomly selected coded transcripts to the corresponding participants. The two participants reviewed the materials and made comments on their own transcripts. The researcher then discussed the changes with the two participants individually. While the participants made some minor changes
46 to their transcripts, the discussion revealed no change in how the codebook applied to the data. For example, during the discussion one participant realized that she should have used code “Color and Pattern”, instead of “Fabric”, to code context that described the color and decorative design of activewear fabric. To avoid such miss-interpretation, the researcher added clarifications and examples to the codebook. However, such changes did not affect the application of the codebook to the data.
The second step was constructing two implication matrices that contain the number of times that each attribute directly and indirectly connects to a consequence, one consequence to another, and each consequence with an end-state value. The implication matrix is the most important part of means-end chain research because it transforms qualitative findings from content analysis to a quantitative representation of means-end chain relationships, which is essential for the means-end chain theory (Makatouni, 2002).
To construct the implication matrices, the researcher read through quotes of each master code and recorded the number of times that each master code directly and indirectly leads to other master codes. For example, when a participant implied that activewear with bright colors (i.e., color and pattern) makes her look nicer (i.e., physical appearance) and therefore boost her self-confidence (i.e., self-respect), direct paths from
“color and pattern” to “physical appearance” and from “physical appearance” to “self- respect” were recorded, while an indirect path from “color and pattern” to “self-respect” was recorded.
The third step was to generate a hierarchical value map (HVM), which visually depicts the means-end chain network and is the main output from a laddering analysis.
The implication matrix of direct paths was used to map the HVM (Reynolds & Gutman,
47 1988). The HVM can be constructed from an ambitious view or a modest view (Grunert
& Grunert, 1995). The ambitious view applies the non-redundancy assumption when mapping the HVM. The non-redundancy assumption suggests that if an attribute directly links with a consequence, which directly links to an end-state value, then any direct link between the attribute and the end-state value is redundant (Grunert & Grunert, 1995). In contrast, the modest view would include the redundant link because it is a part of laddering interview findings and its omission would result in misinterpretation of consumers’ actual experience (Grunert & Grunert, 1995). Considering the consumer- centric approach of this study, a modest view was used to map the HVM.
In addition, a cutoff value of three was used to avoid crossing lines in the HVM and improve interpretability of HVM (Reynolds & Gutman, 1988). A cutoff value of three means that a direct linkage needs to be mentioned by at least three participants to be mapped in the HVM. The cutoff value is determined by mapping the HVM using different cutoff values and evaluate the different solutions based on interpretability. The selected cut-off value should produce an HVM that capture at least two-third of the direction paths in the implication matrix (Reynolds & Gutman, 1988). A cutoff value of three generated an HVM that is the easiest to interpret while retaining sufficient details of the implication matrix.
Study 2
The purpose of Study 2 was to further address the second research question with quantitative data and answer the third research question. Survey data were collected on consumers’ most recent experience with activewear in fitness and non-fitness contexts.
48 The survey included measurements of attributes, consequences, and end-state values that were generated based on the important means-end chain content found in Study 1.
To answer the second research question, model selection analysis was conducted to decide whether it is the upward or downward means-end chains that better describes consumers’ perception structure. While the upward model reflected the HVM discovered in Study 1, the downward model had all the paths reversed. Two model selection analyses were conducted, with one in the fitness context and another in the non-fitness context. To answer the third research question, two multiple-group analyses, one in the upward direction and one in the downward direction, were conducted across the fitness and non- fitness contexts.
Participants and Procedure
Participants 20 years of age or older completed an online survey that was created with Qualtrics and distributed on an online survey panel service Amazon Mechanical
Turk (Mturk). Online survey panels such as MTurk have been used in consumer behavior research because they provide convenient access to a pool of diverse participants
(Goodman & Paolacci, 2017). The main criticism against recruiting participants on
MTurk is its threat to validity, as there is the concern that MTurk participants are careless about the research and produce low-quality data (Cheung, Burns, Sinclair, & Sliter,
2017). However, researchers have identified evidence that data collected via MTurk can generate results that are consistent with those from traditional samples, suggesting that
MTurk sample can provide high-quality data if used properly (Casler, Bickel, & Hackett,
2013).
49 Concerns about the quality of MTurk participants can be addressed through applying screening techniques. The current study used three techniques to screen participants. First, following Goodman and Paolacci’s (2017) guideline on minimizing the risk of self-selection, the survey was posted on MTurk with a generic title “Clothing consumer survey” without revealing too many details regarding its purpose about activewear. At the beginning of the survey, participants were presented with the question
“What types of clothing have you worn in the last seven days?” and were asked to choose one or more options from “Business casual”, “Casual wear”, and “Activewear”. Only participants whose answers included “Activewear” were allowed to proceed with the survey. Respondents who did not choose “Activewear” were told they were not qualified for the research and their participation will have to be ended. Using this technique, 255 people who started the survey were screened out. Second, a forced-choice attention check question “Check ‘Disagree’ for this question” was inserted in the middle of the survey
(Smyth, Dillman, Christian, & Stern, 2006). This technique resulted in the deletion of 16 participants from the dataset. Third, the survey included two open-ended questions that required participants to write about their most recent experience with wearing activewear.
Three participants whose answers were copy-pasted from other resources were deleted from the dataset. The final dataset included a total of 976 respondents, each of which was compensated with 80 cents for participation.
The survey had three parts. The purpose of Part I was to assign participants to the fitness or the non-fitness context. Participants who were randomly assigned to the fitness context were presented with the question “Think about the most recent time in the last seven days that you wore activewear for physical exercise (such as working out or
50 playing sport). Which of the following activities did you most recently participate in?” and a list of physical exercises (e.g., treadmill, elliptical, and cycling). Participants who were randomly assigned to the non-fitness context were presented with the question “In the last 7 days, other than for physical exercise (activities other than working out or playing sport), for what other activity did you wear activewear? Select the most recent activity” and a list of non-fitness activities (e.g., movie, shopping, and dining out).
According to the leisure activity typology, these activities are largely social in nature and present a category that is distinctive from sport and physical exercise (Unger, 1984). Both questions included the option for respondents to switch to the other context if she had not worn activewear in her assigned context. This assignment resulted in a total of 468 participants in the fitness context and 508 in the non-fitness context.
The purpose of Part II was to measure respondents’ perceptions of the activewear experience within the specific usage context in terms of attributes, consequences, and end-state values. Respondents answered all questions based on their experience with activewear in the activity they selected in Part I. Measures of attributes, consequences, and end-state values are presented in the next section.
The purpose of Part III was to collect data that describe respondents in terms of their demographic characteristics and activewear-related behavior. See Table 3.2 for a summary of demographic information and activewear usage behavior of survey respondents. Overall, a typical respondent was a middle-class white female in her thirties, had a 4-year college degree and a full-time job. She had spent $94.27 on purchasing one to three items of activewear in the last three months and wore activewear on about four days in a typical week.
51 Table 3.2. Demographic Information and Activewear Usage Behavior of Survey Respondents
Characteristics Frequency Percentage Age 20-30 308 31.6% 31-40 359 36.8% 41-50 168 17.2% 51-60 107 11.0% 61 and above 34 3.5% Race White 784 80.3% Black or African American 69 7.1% Hispanic 44 4.5% American Indian or Alaska Native 3 0.3% Asian 57 5.8% Native Hawaiian or Pacific Islander 2 0.2% Other 17 1.7% Annual Household Income $40,000 or less 309 31.7% $40,001 - $80,000 391 40.1% $80,001 - $100,000 128 13.1% Over $100,000 149 15.3% Highest Degree Completed Less than high school 5 0.5% High school graduate 78 8.0% Some college 213 21.8% 2-year degree 132 13.5% 4-year degree 396 40.6% Master's degree 125 12.8% Doctorate 27 2.8% Employment Status Employed full time 552 56.6% Employed part-time 203 20.8% Unemployed looking for work 50 5.1% Unemployed not looking for work 82 8.4% Retired 18 1.8% Student 56 5.7% Disabled 15 1.5%
52 Table 3.2. (continued)
Characteristics Frequency Percentage Number of Activewear Purchased in the Last 3 Months 0 160 16.4% 1 - 3 490 50.2% 4 - 6 257 26.3% 7 - 9 25 2.6% 10 items and above 44 4.5% Other Activewear Related Behaviors Mean SD Amount of money spent on activewear the last 3 months $ 94.27 $ 89.98 Number of days wearing activewear in a typical week 4.40 1.66
53 Measures
Based on findings in Study 1, five attributes, four consequences, and three end- state values were measured. Items were adapted from previous literature when existing scales were available. If not, new items were generated using interview quotes in Study 1.
A panel of experts was used to determine content validity of items. Content validity refers to “the degree to which elements of an assessment instrument are relevant to and representative of the target construct for a particular assessment purpose” (Haynes,
Richard, & Kubany, 1995, p. 238). Following suggestions of DeVellis (1991), four doctoral candidates from sport management and three sport management faculty members were asked to evaluate whether the items are clearly and concisely stated. The sport management students and faculties were considered as experts because of their knowledge in sport consumer behavior research and personal experience with wearing activewear. In the current study, the purpose of testing content validity is to judge if the adapted and created items make sense to activewear consumers. All items were measured on 7-point Likert scales ranged from (1) Strongly disagree to (7) Strongly agree. A 7- point Likert scale was chosen over a 5-point one because scale points increases sensitivity and reduces skewness (Leung, 2011). To put respondents into the activewear usage context, each item included a piped-in text of the activity respondents selected in
Part one of the survey. See Table 3.3 for a list of constructs and their items.
54 Table 3.3. Initial Items for Attributes, Consequences, and End-State Values Item Label Attributes Fashion Design The activewear was stylish. FD1 The activewear was fashionable. FD2 The activewear was flattering. FD3 Color and Pattern The colors and/or patterns of the activewear were sophisticated. CP1 The activewear had nice colors and/or patterns CP2 The activewear had desirable colors and patterns. CP3 Fit The activewear was shaped nicely. FT1 The activewear had an attractive cut. FT2 The activewear was in the right shape and size. FT3 Functional Design The activewear provided many functionalities. FCD1 The activewear had useful features. FCD2 The activewear offered some unique functions. FCD3 Fabric The activewear was made of high-quality fabric. FB1 The activewear was made of durable fabric FB2 The activewear was made of breathable fabric. FB3 Consequences Physical Appearance The activewear helped me to look the best I could while I was doing PA1 [piped-in activity]. I looked nice in the activewear while I was doing [piped-in activity]. PA2 I looked presentable in the activewear while I was doing [piped-in PA3 activity]. Physical Comfort I felt physically comfortable in the activewear while I was doing [piped- PC1 in activity]. The activewear was comfortable to wear while I was doing [piped-in PC2 activity]. The activewear put my body at ease while I was doing [piped-in activity]. PC3 Social Relationship The activewear helped me to feel accepted by others while I was doing SCR1 [piped-in activity].
55 Table 3.3. (continued)
Item Label The activewear improved the way I was perceived by others while I was SCR2 doing [piped-in activity]. The activewear helped me to make a good impression on others while I SCR3 was doing [piped-in activity]. Task Facilitation The activewear allowed me to be efficient at what I was doing while I TF1 was doing [piped-in activity]. The activewear provided me a lot of practical usefulness while I was TF2 doing [piped-in activity]. The activewear didn't get in the way of what I was doing while I was TF3 doing [piped-in activity]. End-state Values Self-respect I felt I had a number of good qualities while I was doing [piped-in SR1 activity] wearing the activewear I felt satisfied with myself while I was doing [piped-in activity] wearing SR2 the activewear. I felt I had positive attitudes toward myself while I was doing [piped-in SR3 activity] wearing the activewear. Sense of Accomplishment I felt I was meeting my goals while I was doing [piped-in activity] SA1 wearing the activewear. I felt I have achieved something while I was doing [piped-in activity] SA2 wearing the activewear, I felt I was making progress toward my goal while I was doing [piped-in SA3 activity] wearing the activewear. Fun and Enjoyment I felt I was in a good mood while I was doing [piped-in activity] wearing FE1 the activewear. I had fun doing [piped-in activity] in the activewear. FE2 Wearing the activewear while doing [piped-in activity], I had a sense of FE3 pleasure.
56 Data Analysis
The first step of data analysis was to assess the measurement model. An exploratory factor analysis (EFA) and a series of confirmatory factor analyses (CFA) were performed to establish reliability and validity of measurements and fit of the entire measurement model.
An initial CFA was performed in Amos 25 to access the reliability and validity of the constructs in Table 3.1. Reliability concerns with the consistency of a scale
(Churchill, 1979). The reliability of each scale was assessed using Cronbach’s alpha, which reflects the extent to which items within a scale are indeed measuring the same construct (Hair, Black, Babin, Anderson, & Tatham, 2005). A score over .50 indicates that the scale has an acceptable level of reliability (Hair et al., 2005).
Validity refers to the extent to which a scale that is intended to measure a construct is indeed measuring that particular construct (Churchill, 1979). Validity can be established through testing convergent validity and discriminant validity. Convergent validity means items within a scale are representative of the construct, whereas discriminant validity means the scale can be distinguished from another scale that measures a different construct. Convergent validity was assessed using factor loadings and the average variance extracted (AVE) with a cutoff value of .50 (Hair et al., 2005;
Jöreskog & Sörbom, 1996). Discriminant validity was assessed by comparing a construct’s AVE with maximum shared variance (MSV) and square root of AVE with inter-construct correlations (Fornell & Larcker, 1981). Specifically, a construct’s AVE should be greater than MSV and the square root of AVE should be greater than all of its inter-construct correlations.
57 To assess the overall fit of the model, comparative fit index (CFI) greater than .95, root mean square error of approximation (RMSEA) less than .07, standardized root mean square residual (SRMR) less than .08, Goodness-of-fit index (GFI) greater than .90, and adjusted goodness-of-fit index (AGFI) greater than .85 were used as the cutoff criteria to determine an acceptable model fit (Kline, 1998; Schermelleh-Engel,
Moosbrugger, & Müller, 2003).
As the initial CFA suggested reliability and validity issues in several constructs, an EFA using the maximum likelihood method was conducted in SPSS Statistics 25 to reconstitute the factor structure. EFA is useful in uncovering the structure of measurement model and serves as an alternative to using modification indices provided from a CFA in model refinement (Gerbing & Hamilton, 1996). Since the CFA is a cross- validation of the factor structure discovered by the EFA, the full dataset was split into two subsets, one of which is used to perform the EFA. The “Select Cases” function in
SPSS was used to randomly select approximately half of full sample. This procedure resulted in two subsets with sample sizes of 470 and 506. The EFA was performed on the subset with 470 cases. The oblique rotation was used because the constructs are conceptually correlated (Fabrigar, Wegener, MacCallum, & Strahan, 1999). Multiple criteria, including the eigenvalue criterion (Kaiser, 1970), the scree test (Zwick &
Velicer, 1982), and interpretability of factor structure were used to determine the number of factors to retain. Items were eliminated when their factor loadings failed to reach the cut-off value of .35 and cross-load on different factors (Field, 2005; Park, Mahony, &
Greenwell, 2010). Following the EFA, two additional CFAs were performed to validate the refined measurement model.
58 The second step of analysis contained two model selections that decide the means-end chain direction (i.e., upward or downward) that better describes the data within fitness or non-fitness context. Considering that chi-square fit indices is inflated when sample size is large (Hair et al., 2005), the RMSEA and its confidence interval, the
Akaike’s information criterion (AIC), and Akaike weights were also included (Burnham
& Anderson, 2004; Kim, Chelladurai, & Trail, 2007) for model selection. While a smaller
RMSEA value indicates a better model fit, a value under .08 is considered reasonable and overlapped confidence intervals indicate the two models are not distinct (Byrne, 2000).
AIC is used for model selection because it measures model fit while considering model parsimony, which is a strength over other fit indices that are based on log likelihood
(Burnham & Anderson, 2004). A lower AIC indicates better fit. Akaike weights that are calculated based on AICs provide the likelihood that a model should be favored over alternatives (Burnham & Anderson, 2004).
The final step was to test the structural model informed by the HVM in Study 1 across the fitness and non-fitness groups to answer the third research question. A preliminary inspection of differences between the fitness and non-fitness group can be reflected by a comparison of means for all items between the two groups. The mean comparison was conducted using a multivariate analysis of variance analysis
(MANOVA). However, a more thorough analysis of differences in the means-end chain structure requires direct comparisons of the model structure between the two groups (e.g.,
Boyle & Magnusson, 2007). Hence, multiple-group analysis in Amos 25 was used. The first step of multiple-group analysis was to test measurement invariance between fitness and non-fitness groups. Measurement invariance ensures a measurement operates in the
59 same manner across different groups and serves as the basis for group comparison on the structural level (Reise, Widaman, & Pugh, 1993). A chi-square difference test of the model with no constraint and the model with constraints on all factor loadings was conducted and a non-significant result would indicate measurement invariance. In this step, the model does not have to achieve full invariance to allow further analysis (Byrne,
Shavelson, & Muthén, 1989). Partial measurement invariance, which relaxes constraints on some of the items, is sufficient for establishing a common measurement model as long as two-thirds of the items are invariant across groups (Reise et al., 1993). After a common measurement model was established, the next step was to compare this model and the model with all structural weights and factor loadings constrained. A significant chi-square difference test suggests group differences on the model level (Jöreskog &
Sörbom, 1996). Lastly, chi-square difference tests on the path-level were conducted by constraining each of the paths one at a time. Path coefficients in the two groups were also inspected and compared.
60 CHAPTER 4
4. RESULTS
Study 1 Findings
This section is organized into five major parts. The first part presents the findings that have been generated throughout the data analysis steps as they address the first and second research questions. This includes an overview of the identified means-end chain elements (i.e., attributes, consequences, and end-state values), the implication matrix, and the HVM. The second, third, and fourth parts answer the first research question by presenting findings regarding the important attributes, consequences, and end-state values respectively. Since a good number of means-end chains in the HVM have already been demonstrated in the first three parts, it would be redundant to go through all the chains again when answering the second research question. Therefore, the fifth part presents a list of quotes that are representative of some of the most salient chains. A more detailed discussion of the means-end chain structure can be found in the discussion section.
Identified Elements, The Implication Matrix, And The HVM
Identified Means-End Chain Elements
The initial coding procedure resulted in the identification of 23 attributes, 34 consequences, and 10 end-state values. These codes were further condensed to 16 master codes that represent five attributes (i.e., functional designs, fabric, color and pattern, fit, and fashion design), seven consequences (i.e., physical appearance, physical comfort, convenience, task facilitation, personable brand, psychological comfort, and social relationship), and four end-state values (i.e., sense of accomplishment, security, self- respect, and fun and enjoyment). See Table 4.1 for a summary of the codes.
61 Table 4.1. Overview of Attributes, Consequences, and End-State Values
No. Category Citationsa Respondentsb Definition Attributes 01 Functional 16 7% 9 38% Features that are designed to design offer some specific utility. An example is wide sports bra straps that offer support. 02 Fabric 11 5% 10 42% The stretchiness, durability, permeability, and tactile features of activewear fabric. An example is a soft fabric that stays dry during exercise. 03 Color and 62 28% 19 79% The color and decorative pattern design of activewear fabric. An example is a sport tank with white base color and navy stripes.
04 Fit 82 37% 24 100% The three-dimensional shape of activewear in its different parts. An example is the length and tightness of yoga pants. 05 Fashion design 54 24% 15 63% Visually pleasant and unique features that communicate aesthetics and beauty. An example is crossed bra straps. Total 225
Consequences 06 Physical 110 37% 24 100% How the consumer looks. appearance For example, the consumer looks slimmer in activewear. 07 Physical comfort 38 13% 18 75% The consumer's physical ease and relaxation. For example, the consumer feels easy to move in an activewear.
62 Table 4.1. (continued) No. Category Citationsa Respondentsb Definition 08 Convenience 28 9% 19 79% Whether the consumer can wear the activewear with other types of clothing in a variety of situations. For example, a pair of black yoga leggings is easy to pair with a casual shirt. 09 Task facilitation 58 19% 20 83% The effectiveness of doing the defined task within the situation. For example, a consumer feels that running is made easier when wearing the activewear. 10 Personal brand 19 6% 11 46% The consumer's clothing style and personality. For example, a consumer likes an activewear because it shows a simplistic clothing style.
11 Psychological 10 3% 6 25% Feels at ease instead of comfort being anxious or self- conscious. For example, a consumer may feel anxious wearing activewear that is too tight. 12 Social 37 12% 18 75% The consumer's interaction relationship with other people and how the consumer is perceived by others. For example, a consumer is perceived as a physically active person when wearing activewear for shopping. Total 300
End-state Values 13 Sense of 15 14% 10 42% The value of being focused accomplishment and achieving a goal through effort. For example, a consumer feels her body shape has been improved.
63 Table 4.1. (continued) No. Category Citationsa Respondentsb Definition 14 Security 14 13% 11 46% The value of being free from social judgment and pressure. For example, a consumer feels free judgment from others when she wears activewear in neutral colors. 15 Self-respect 49 47% 20 83% The value of feeling good and confident about oneself. For example, a consumers feels confident when she looks nice in activewear. 16 Fun and 26 25% 13 54% The value of feeling happy enjoyment and amused. For example, a consumer feels amused by nice fashion design in activewear. Total 104 Notes. a The numbers represent the number of quotes for the category and its percentage in the according level (i.e., attributes, consequences, end-state values). b The numbers represent the number of participants who mentioned the category and the corresponding percentage.
64 The Implication Matrix
The second step of analysis generated two implication matrices shown in Table
4.2 and Error! Reference source not found.. Numbers in Table 4.2 represent the number of times that the corresponding row element directly leads to the corresponding column element. Numbers in Error! Reference source not found. represent the number f times that the corresponding row element indirectly leads to the corresponding column element.
The Hierarchical Value Map
The final step of analysis generated the HVM based on the implication matrix of the direct paths. As shown in the HVM (see Figure 4.1), the means-end chain network had three major levels: attributes, consequences, and end-state values. Moreover, consequences existed on two levels, denoting consequences that occurred directly and indirectly to the participants. The size of arrows in the HVM is proportional to the number of direct links between the connected elements. The HVM mapped a total of 130 direct linkages, which account for 79% of all direct linkages identified in the implication matrix, indicating that the HVM has sufficiently summarized the laddering interview findings (Reynolds & Gutman, 1988).
65 Table 4.2. Implication Matrix (Direct Paths)
Consequences End-state Values Attribute
/Consequence 6 7 8 9 10 11 12 13 14 15 16 PA PC CV TF PB PSC SCR SA SC SR FE ∑ 1 FCD 1 5 6 2 FB 6 1 7
3 CP 14 2 2 18 4 FT 15 12 2 29 5 FD 16 1 2 5 24 6 PA 1 5 2 2 7 2 2 16 3 40 7 PC 1 11 1 13 8 CV 1 1 9 TF 1 3 7 11 10 PB 1 2 3 11 PSC 1 1 2 2 6 12 SCR 2 5 7 ∑ 47 24 3 24 6 2 9 6 4 28 12 Note. FCD = functional design; FB = fabric; CP = color and pattern; FT = fit; FD = fashion design; PA = physical appearance; PC = physical comfort; CV = convenience; TF = task facilitation; PB = personal brand; PC = psychological comfort; SCR = social relationship; SA = sense of accomplishment, SC = security, SR = self-respect, FE = fun and enjoyment. 1-5 = attributes; 6-12 = consequences; 13-16 = values.
66 Table 4.3. Implication Matrix (Indirect Paths)
Consequences End-state Values Attribute
/Consequence 6 7 8 9 10 11 12 13 14 15 16 PA PC CV TF PB PSC SCR SA SC SR FE ∑ 1 FCD 3 1 1 3 1 1 2 1 13 2 FB 3 2 1 1 7
3 CP 9 1 4 2 8 3 5 4 36 4 FT 3 12 2 4 4 6 2 6 4 43 5 FD 2 2 4 5 3 2 2 2 1 23 6 PA 1 1 2 2 1 7 7 PC 1 2 1 3 1 8 8 CV 2 2 1 1 3 2 11 9 TF 1 1 10 PB 0 11 PSC 1 1 1 3 0 12 SCR ∑ 2 22 22 16 8 21 15 10 22 14 Note. FCD = functional design; FB = fabric; CP = color and pattern; FT = fit; FD = fashion design; PA = physical appearance; PC = physical comfort; CV = convenience; TF = task facilitation; PB = personal brand; PC = psychological comfort; SCR = social relationship; SA = sense of accomplishment, SC = security, SR = self-respect, FE = fun and enjoyment. 1-5 = attributes; 6-12 = consequences; 13-16 = values.
67
Figure 4.1. Hierarchical Value Map
Attributes
Functional Design
The attribute of functional design involved designs that provide some specific functions, such as kneepads that provide protection, bra straps that offer support, and reflective materials that increase safety. Participants liked functional designs because they provide physical support and comfort during exercises. For example, Margaret explained the reasons why she preferred an Adidas sports bra: “Because it is comfortable and gives me more support. I read articles about choosing activewear and it suggested to wear wider shoulder straps. The Adidas one had wide straps and you can adjust the length.”
Some functional add-ons, such as pockets and zippers, provided usefulness and convenience during exercise and other activities. Susan said she always buy activewear with pockets because “when I go to the gym, I don't like to use the locker. I typically would just bring my car key and I need a pocket for that.”
68 While functional designs were mentioned in most interviews, they were not regarded as a crucial attribute that influenced how participants evaluated activewear.
Many participants thought that functional designs were something handy but not the must-have. As Lisa explained:
I always want to have a pocket so there are some functions [that I can use], but I am not going to like a certain piece [of activewear] just because of the pocket. I definitely gravitate to what it looks like first before I read the tag that tells me all the benefits of the pants.
Fabric
Fabric also influenced participants’ experience with activewear. Participants evaluated the stretchiness, durability, permeability, and tactile features of activewear fabric and these features were especially important in physical exercises. Most participants preferred fabric specially designed for physical exercises rather than ordinary fabric like cotton because, as Helen explained:
Cotton workout clothes just do not seem to have the same longevity as athletic fabrics do. They [cotton-made activewear] peel more easily and the colors fade. If you sweat in it [cotton-made activewear] a lot, you cannot actually get the sweat smell out of it versus the athletic gear is designed to not lock in odor at any point.
High-quality fabric was also easier to take care off and provided convenience.
Emily talked about a type of fabric she likes: “It is one of those sweat-wicking ones. For me, as someone who travels, it’s nice to have a fabric that doesn’t really feel like it absorbs sweat as much, and I can wash it easily.”
Color and Pattern
A majority of the participants perceived color and pattern as an important attribute of activewear. Participants usually favor activewear that was in their favorite colors.
When brighter colors were favored, it was usually explained as: “brighter colors are more
69 fun”. When darker and neutral colors were preferred, participants said those colors matched their clothing aesthetic.
While there was no consensus on what type of color and pattern was the nicest, most participants preferred solid dark colors for activewear bottoms (e.g., leggings, pants, and shorts). The “slimming effect” of dark color was an important reason for this preference. For example, Lisa said, “I think black is just a little more slimming, especially in your legs.” Another reason that dark colors were preferred was that dark colors were easy to match with other colors. When asked if she likes yoga pants with bright colors or patterns, Nancy said:
I still prefer black. It is easier to match with different tops and I can also wear that on a regular basis. Whether it is under a dress or I can stroll on with a sweater and boots and a long cardigan, I can still look good. I have many black leggings because they are versatile and I have them in different lengths.
Fit
Fit was mentioned in all interviews and had the highest number of quotes on the attribute level, showing its importance for participants’ activewear experience.
Participants preferred a tighter fit because it looked nicer and made participants feel better about themselves. Lisa said:
You feel like you look good [when wearing tight pants]. And it is always better to go in a workout already thinking that you look good than being like, “Oh, I'm so bloated and fat.” I think putting on a pair of tight capris makes you feel good about yourself.
Participants also pointed out that the fit of activewear top and bottom needed to be balanced to create an attractive apperance. A general style that participants liked was a tight-fitting bottom with a fitted but slightly looser top, as Patricia said, “It just feels more balanced if I wear tight bottoms and a looser top.”
70 In addition to a nicer look, participants said that activewear that fitted tighter can facilitate physical exercise, as it was less likely to get in the way of movement. Emily said: “I don’t like the loose tops, because they fly into your face when you are upside down in yoga.” A tight-fit activewear could also allow participants observe themselves during exercises, while a loose and baggy activewear would mask the body. Susan explained:
If I am wearing a tighter fit top and I am doing yoga. I could look in the mirror and see that my body actually is in the position it is supposed to be in. If I have a really baggy shirt on, I can't necessarily see if the upper part of my body is doing what it is supposed to do.
Fashion Design
While participants were able to easily articulate the five attributes presented above, it required extra efforts for them to explain perceptions of fashion designs in activewear. Fashion design did not focus on a specific attribute of activewear. Instead, it included all the elements that were visually pleasant, unique, and communicate a message of beauty. Designs mentioned by participants ranged from crossed-straps in the back of tops, to high-waist leggings, and ruffles on the edge of tops. Barbara explained what she likes about her favorite activewear top:
The top has the racerback design. It was an hourglass type shape. Men can’t wear that. I think it (the design) is just about presenting yourself well. It feels nice to feel feminine but powerful in the gym. Whether a design is visually pleasant or not depends on the person who wears it.
Interviews revealed that participants would consider a design beautiful only when the design flattered the body. While a fashion design may look nice by itself, participants would not appreciate the design if they don’t look good in it. Karen brought to the
71 interview her favorite yoga top that had a cutout in the back. When asked if she would wear a pair of yoga leggings with a similar design, Karen said no, explaining:
I do not exactly feel comfortable with the leggings because I have slightly larger hips. I like to have the cutout just for the top. I have muscles on my back so it looks nice on me. I cannot really accentuate much with my bottom so I just do it with my top.
While participants appreciated fashion designs, they did not favor designs that were “too fancy and complicated”. An example was mesh embellishment, which looked nice but as Mary said, “I don't really need a thing that has mesh for any reason.”
Participants also indicated that they adapted fashion designs based on their personal clothing style instead of the popular trend, as Carol commented:
Even though it [a fashion design] might look cool in the store or it might be something that is trendy, I have a better sense of my own style now. I am not going to just buy it like, “Oh, maybe this could work”.
Consequences
Physical Appearance
Having an attractive physical appearance was a salient consequence that emerged from the interviews. Looking good in activewear was important for all participants, as
Sandra said, “You want to look presentable, you want to look nice, you want to look attractive, I think everyone wants that.” Participants interpreted the meaning of nice physical appearance from three aspects.
First, many participants thought that an important part of attractive physical appearance was to look slimmer. For them, fitted activewear produced a slimming effect, and a slimmer body always looked better. This was obvious when Lisa said:
Even if no one else is home and I am working out, I still want to look nice. I like to have the slimming effect, and if I were to walk by a mirror, I would see myself looking good. I never want to put on a pair of frumpy sweatpants and workout. I would rather wear something that makes my body look good.
72 Connecting to the first point, participants also expected activewear to hide specific body parts, which were usually the “large” parts. When asked why she did not have any leggings in bright colors, Ashley said: “I’ve got large hips proportionally, so I try not to emphasize it too much. I would not want to draw too much attention to that part
[hips].”
The final aspect of an attractive physical appearance was to look presentable in exercise and other activities. While working out was not a time when participants would dress up, they still wanted to look as presentable as they could. Carol elaborated on why she puts effort into matching workout outfit:
If I am going in public, I want to look presentable and put together, and the gym is just another [public] place. If I am putting myself out there, I want to be the best presentable version of myself. Yes, I do put effort into making sure everything [activewear] matches and looks good.
For participants who wore activewear in other activities, activewear made them feel more dressed up, especially in a situation that they cared less such as at home or shopping for groceries. As Barbara explained: “I don’t want to wear sweatpants to the grocery store because that’s a little too sloppy so I’ll wear my activewear pants. They are tight and look a little bit nicer.”
It is necessary to point out that not all participants preferred to wear activewear in daily activities. Especially in public settings, a more dressed-up outfit, even just a pair of jeans, was “more presentable and more appropriate”. As Lisa said:
[Compared with wearing a activewear,] I don't feel like I look as good as I could in other clothes in a public setting. I feel like my activewear, even though it looks stylish and fun, I don't think that it fits the task that I'm doing and it just always makes me feel weird.
73 Physical Comfort
Being physically comfortable was a basic and important benefit of wearing activewear. During physical exercises, participants expected activewear to be comfortable and supportive for the body such that they can perform the exercise.
Amanda, a part-time fitness instructor, said:
It [An activewear] is more than something that covers my body. If I am lifting weights, I need to wear pants to protect my knees. If I do more intense exercises, I will wear taller socks and high-waist pants because I don't want to keep pulling my pants up when I work out. If my pants are not fitting, it is very frustrating.
Activewear also provided physical comfort in other activities. Some participants enjoyed wearing activewear whenever they could because it allowed them to move freely and feel relaxed throughout the day. Helen explained:
When I wake up in the morning and know I am able to wear activewear for the course of my day, I know I am not going to be in physical discomfort. Whether that’s just a day of administrative work on my laptop or running errands, it has a positive impact on my outlook for the day.
Social Relationship
During the interviews, several participants mentioned how activewear influenced their social images and interactions with other people. The prevailing thought was that activewear should give the wearer an image that is unique but not too standing-out.
Especially during exercises, participants did not want to attract other people’s attention.
Dorothy showed the researcher a pair of running leggings with subtle patterns and said:
I thought it [the pattern] was cool. It is a bit different from the solid plain black ones. It was something that was different enough but not too different. [I don’t like an obvious pattern because] I don’t want to be perceived as a crazy person. You are still around people [when you exercise] and you want to present yourself well. And something that I'm most conscious of is how I dress.
74 The social aspect was also an important concern for participants who wore activewear in non-fitness settings. Mary, who primarily wore activewear to her work at a middle school, said she prefered solid black yoga pants because:
It is a little more professional seeming [than other colors]. Especially around students, you do not want to look like a creepy person. It is important for teaching because as close as you want to be with your students, you do have to have a little bit of distance. If I wore colorful sweatpants, that would lessen the distance.
Task Facilitation
In interviews, many participants talked about how activewear could influence the activity they were doing and the goal they wanted to achieve in the activity. During physical exercises, participants expected activewear to not get in the way of the exercise.
Multiple participants complained that they would be distracted from the exercise if the activewear was uncomfortable to wear. Emily, a certified yoga instructor, said:
In yoga, you are in a lot of different positions and it is supposed to be calming and relaxing and you're supposed to focus on your breathing. When things [activewear] are uncomfortable and I have to pull things down, it kind of takes me out of what I am supposed to be doing.
Activewear also influenced the fulfillment of non-fitness tasks. Compared with wearing other types of clothing, participants felt activewear was less demanding and more motivational to wear in mundane tasks. Jennifer elaborated on the reasons she liked to wear activewear in her day-to-day activities:
I just feel activewear is more comfortable and easier to pull together. You do not have to worry about what kind of shirt you are going to wear with your jeans. I am moving around a lot. If I put on activewear, I feel like I am ready for the day, not just like I am lazing around the house.
75 End-State Values
Fun And Enjoyment
According to participants, a well-designed activewear could bring them a sense of pleasure. Many participants thought that nice colors, unique patterns, and fashionable designs made it fun to wear activewear. Susan explained how activewear with bright colors makes her feel:
I think it is really a matter of fun. The first thing in the morning I do when I get out of bed is I am going to put on my workout clothes. When it is something bright, it is just more fun. Maybe I don't want to work out, but I've got my really bright shirt and sneakers. It is just more enticing to put on than dark clothes.
Wearing “fun” activewear also added enjoyment to the act of physical exercise.
Especially for participants who do not exercise a lot, “fun” activewear could change a droll workout to a pleasant experience. Lisa, a mother of two kids, could not spare much time on exercise, and said she had never bought any “boring workout clothes”:
I want them [activewewar] to be fun. It makes the workout process more fun when you are wearing fun pants as opposed to putting on a boring uniform to have to go get on the treadmill. It [fun activewear] lightens things up and makes it less of a chore to workout.
Self-respect
When participants talked about how they feel when wearing their favorite activewear, a reoccurring phrase was “I feel good about myself”. A well-designed activewear could make participants aware of good qualities in themselves. Patricia said:
Part of why I like really bright colorful leggings is because they make me feel like “oh yeah, you can do it!” It just makes me feel more motivated to have a really good workout and feel good about my body’s abilities. That makes me feel strong and not like “ok. I am just going to get through this workout.”
For many participants, part of the sense of feeling good about themselves was derived from how they look in activewear. Many participants acknowledged that to be fit
76 and looking good were important reasons they exercise. A well-designed activewear that complements the body made participants feel confident about their bodies and be more dedicated to the workout. Betty explained:
I am obviously working out for a reason and wanting to stay healthy and look good. If I go into it [exercise] already looking good, I am going to feel even better. I am going to have a more successful workout than if I were to throw on a giant T-shirt and giant sweatpants.
Sense of Accomplishment
A well-designed activewear could also make participants feel that they have achieved something. Some participants indicated that they gained a sense of accomplishment when they noticed their bodies were transforming, and activewear should accentuate and show the changes they have achieved. As a result, many participants preferred activewear that accentuated the body parts that they were happy with. Donna explained why she prefered tank tops to other types of activewear tops:
My shoulders are a part of my body that I like and when I wear a tank top, I can see my shoulders. I can see if I am starting to get some muscle definition on my shoulders. It just helps me feel more accomplished when I can look in the mirror and see a part of my body getting stronger.
A well-designed activewear also allowed participants to focus on the exercise and therefore feel accomplished. Susan elaborated:
When I exercise, I can focus on myself and not think about all the other things. I try to make sure that I am getting the most out of it [exercise]. When I can focus on the exercise and not have to adjust my clothes, I can get the most value out of the time that I am putting into it [exercise]. That makes me feel accomplished.
Activewear also brought about a sense of accomplishment in non-fitness activities, especially in a private setting where participants could have worn more relaxed clothing such as pajamas. Jennifer elaborated on how wearing activewear at home makes her feel more accomplished:
77 Before I had kids, I did my hair and makeup every day. Now that I have kids, it [doing hair and makeup] is not always possible. By wearing activewear, I feel like I am making an effort on myself and I am still like my old self. It makes me feel presentable, not just a mom.
Representative Means-End Chains
Table 4.4 provides quotes that represent the most salient linkages in the HVM.
Means-end chains in HVM were generated by aggregating information provided by all participants. As Reynolds and Gutman pointed out, “there doesn’t necessarily have to be an individual with an A-B-C-D ladder for an A-B-C-D chain to emerge from the analysis” (1988, p. 20). Therefore, two of the means-end chains, chains No. 1 and No. 4, were represented by quotes from two participants.
78 Table 4.4. Salient Means-End Chains and Quotes
Label Means-end Chain Quote (Pseudonym) I love having a functional pocket. I have a few pairs of leggings that have a decent sized zipper pocket and that’s perfect when I am running outside. Then I can put my house key Functional design -> in it so I do not have to worry about having Physical comfort -> No. 1 things in my hands while running. (Dorothy) Task facilitation ->
Self-respect I want to feel so comfortable that I don’t even have to think about it. I can appreciate what my body does for me and what I am doing at the moment. (Betty) I generally wear stretchy yoga pants. I teach and I am running around all day with the kids Fabric -> so I do have to be very mobile. If I am Physical comfort -> wearing something uncomfortable, I would No. 2 Task facilitation -> want to get out of it as soon as possible. For Sense of accomplishment me to focus on my job and not have to be worried about what I am wearing, I like to wear activewear. (Mary)
I guess it makes you feel better doing the exercise when you wear the colorful Color and pattern -> activewear, as opposed to the duller solid Physical appearance -> ones. Dark colors make me feel like "I have a No. 3 Task facilitation -> chore to do, and this is my chore clothes." If it Sense of accomplishment is a bright color, it makes me feel I am doing something great for my body, helping my body to be leaner and healthier. (Jessica)
I just think it [neutral color and pattern] projects an image of who I am. I don't want people to think I have a crazy personality. And even when I'm going to the gym and Color and pattern -> know I'm going to sweat, I want to look nice Physical appearance -> No. 4 and put together. I think wearing neutral Social relationship -> colors conveys that message. (Sarah) Self-respect
It [looking nice] helps me be more confident. If I look nice, I feel better about myself and it gives me a boost. (Jennifer)
79 Table 4.4. (continued)
Label Means-end chain Quote (Pseudonym) I prefer activewear that is fit. When I do a Fit -> headstand in yoga, I do not want my shirt Physical comfort -> falling over my face. My goal for doing yoga No. 5 Task facilitation -> are stress reduction and mindfulness. I would Sense of accomplishment not feel peaceful and relaxed if I have to adjust my cloth all the time. (Emily) When I'm working out, it's nice to have Fit -> something that accentuates and shows off the No. 6 Physical appearance -> body shape. It makes me feel good about Self-respect myself. That's why I like the more fitted pieces. (Carol) I like the tightness of leggings. When everything is like tight and compact, I am more focused on the workout because I Fit -> already feel confident in the way that I’m Physical appearance -> No. 8 looking. So I can perform better because it’s Task facilitation -> like "ok, I’m looking good in it." Like the shirt Sense of accomplishment that I bought, I feel like it shows makes my arms look muscular. Then I would feel I’m doing the exercise right. (Barbara) The open-back design is pretty. And when I wear it, it makes my back looks good. I want Fashion design -> my activewear to have one sparkling point No. 9 Physical appearance -> that makes it unique. I like myself to look Self-respect pretty and then I feel better about myself. (Karen) Every activewear brand makes full-length black pants, so to have those extra cute details Fashion design -> No. 10 on there [full-length black pants] gives it a Fun and enjoyment little bit of aesthetic interest and uniqueness to it. (Helen) I don’t want to make my outfit look extremely baggy. Extremely baggy clothes make a Fit -> person look fat or just not well dressed. I think Physical appearance -> No. 11 I look better in a more fitted activewear and I Social relationship -> get compliments from people. That motivates Self-respect me to work out more. It gives me a boost in self-confidence. (Donna) Note. The arrows represent the paths identified in the HVM in Figure 4.1.
80 Discussion of Study 1 Findings
The First Research Question
The first research question seeks to identify the important attributes, consequences, and end-state values that consumers perceive from their experience using activewear. Using the laddering method, Study 1 identifies functional design, fabric, color and pattern, fit, and fashion design as the important attributes of activewear. This list of attributes overlaps with those in previous studies on activewear (Zhou et al., in press). Specifically, functional design, color and pattern, and fit are consistent with the concrete attributes identified in Zhou et al. (in press). Mover, consistent with Zhou et al.
(in press), fit emerges as an important concrete attribute as it was the most-mentioned attributes and connected to multiple consequences. A tight fit, especially for bottoms, is preferred because it makes consumers look better and perform better in physical exercises.
While some attributes concretely describe specific features of the product, other attributes are more abstract and generic (Bettman & Sujan, 1987). Findings reveal that fashion design is relative abstract compared to the other four concrete attributes. Unlike fabric, color and pattern, and fit, fashion design includes a range of visually beautiful elements instead of focusing on a specific feature. Unlike functional design, with which participants could clearly identify the utility, the evaluation of fashion design is highly dependent on the person who wears it. The non-inclusive view of abstraction suggests abstract attributes do not need to subsume concrete attributes and could be developed from direct observations (Snelders & Schoormans, 2004). The interview participants
81 indicated that they evaluate fashion design based on how they look in it, suggesting that fashion design is an abstract and non-inclusive attribute in activewear usage.
Physical appearance, physical comfort, social relationship, and task facilitation emerge as the important consequences of wearing activewear. According to the means- end chain theory and apparel design research, consequences can be physiological/functional, psychosocial, and aesthetic (Gutman, 1982; Lamb & Kallal,
1992). Social relationship falls into the psychosocial category with its focus on consumers’ relationships with others. Physical comfort and task facilitation belong to the physiological/functional category as they relate to consumers’ physical experience and the utilitarian value that is gained. In the HVM (see Figure 4.1), physical comfort has 23 paths going into it and 11 paths going out. In addition, the 11 paths going out from physical comfort all go into task facilitation. These numbers suggest that consumers’ perception of physical comfort is strongly associated with their perceptions of how efficient they are at the defined task.
Physical appearance, also referred to as beauty and aesthetics, has not been well explored in the means-end chain literature. Findings from Study 1 show that physical appearance has both physiological and psychosocial components. Consistent with Zhou et al.’s (in press) finding on physical fitness, the physiological component identified in the current research involves looking slim and hiding unsatisfactory body parts. The psychosocial component is about being presentable, which relates closer to physiological benefits as they are about how consumers’ self-concepts and how they are perceived by others. In the literature on aesthetics, beauty is considered as a judgment shaped by social and cultural influences (Kant & Pluhar, 1987; Labat and DeLong, 1990). The current
82 finding supports this view and finds aesthetic as a consequence that overlaps the physiological and psychosocial categories in Gutman (1982).
Self-respect, sense of accomplishment, and fun and enjoyment are identified as the important end-state values in activewear usage. The value typology research categorizes values into internal and external dimensions while the internal dimension consists of individual and interpersonal aspects (Homer & Kahle, 1988). The three values identified in the current findings all belong to the internal dimension, with self-respect and sense of accomplishment representing the individual aspect and fun and enjoyment representing the interpersonal aspects. This finding suggests a prominent role of internal values in the activewear experience. Security, as an external value identified in the implication matrix (see Table 4.2), is deemed unimportant and not included in the HVM.
Consumers who place a major importance on internal values tend to actively control their experience with the product as well as other events in life (Homer & Kahle, 1988). The dominant role of internal values among activewear consumers suggests this group of consumer values independence and a focus on the self in activewear consumption.
The Second Research Question
The second research question asks about structural relationships amongst the important attributes, consequences, and end-state values. The structural relationships have been revealed by the identified HVM. Generated through the laddering method, the
HVM has further extended findings in Zhou et al. (in press) by adding end-state values into consumers’ perception structure. The inclusion of end-state values is essential, as to create psychological connections between the product and the consumer is an important task of marketing (Walker & Olson, 1991).
83 The HVM (see Figure 4.1) can be viewed in two major branches. The first branch consists of paths from functional design, fabric, and fit to physical comfort, which connects to task definition and further influences sense of accomplishment and self- respect. The other branch consists of paths from color and pattern, fit, and fashion design to physical appearance and the three end-state values. These two branches support Lamb and Kallal’s (1992) framework for apparel design, in which art elements (e.g., color) connect to aesthetic benefits while utilitarian elements (e.g., protection) connect to functional benefits.
Fashion design, as an abstract attribute, has a direct impact on the fun and enjoyment that consumers derive from the activewear experience. Consistent with some of the previous studies (e.g., Amatulli & Guido, 2009; Zanoli & Naspetti, 2002), this direct path suggests that perceptions of an attribute can lead to end-state values without going through consequences. The non-inclusive view is therefore supported, as consumer perceptions do not have to be built by layers of abstraction (Snelders & Schoormans,
2004).
Direct paths have also been identified from physical appearance to end-state values (i.e., self-respect and fun and enjoyment). While physical appearance seems to exist on a level that is lower than social relationship, a closer look at the two consequences suggests physical appearance is not subsumed under social relationship.
Specifically, only seven participants made the connection from physical appearance to self-respect while 16 directly connected physical appearance to self-respect. In interviews, some participants explicitly stated that to look nice is more about how they feel about themselves rather than how other people think. This finding further illustrates
84 consumers’ focus on the self and challenge the hierarchical structure of perceptions proposed by Gutman (1982). The direct path also illustrates the advantage of adopting the modest view to map HVM as it includes redundant links to avoid misinterpretation
(Grunert & Grunert, 1995).
Study 2 Results
Measurement Model
The first step of data analysis in Study 2 was to assess the reliability and validity of measurements and fit of the measurement model. A CFA with 12 constructs showed that while construct reliabilities were acceptable (ranged from .73 to .94), several constructs had validity issues. As shown in Table 4.5, there were three constructs (i.e.,
FD, FCD, and PC) with the square root of AVE values smaller than the construct’s correlation with other constructs. These three constructs, along with constructs CP, FT,
FB, PA, TF, had AVE scores that were smaller than the corresponding MSV, indicating issues in discriminant validity (Fornell & Larcker, 1981). In addition, there was a lack of convergent validity for constructs FCD and TF as their AVE scores did not reach the .5 threshold, indicating that the amount of variance accounted by the measures is smaller than that accounted by measurement errors (Hair et al., 2005). These results suggested that the measurement model (Model A) needed to be revisited.
85
Table 4.5. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model A
Label Construct (Label) FD CP FT FCD FB PA PC SC R TF SR SA FE Fashion Design (FD) 1 Color and Pattern (CP) .83 1 Fit (FT) .91 .73 1 Functional Design (FCD) .57 .55 .59 1 Fabric (FB) .69 .66 .78 .75 1 Physical Appearance (PA) .83 .62 .75 .45 .59 1 Physical Comfort (PC) .28 .28 .48 .29 .51 .38 1 Social Relationship (SCR) .41 .30 .33 .28 .26 .46 .04 1 Task Facilitation (TF) .27 .27 .44 .43 .48 .40 .83 .10 1 Self-respect (SR) .46 .35 .51 .44 .45 .61 .51 .29 .59 1 Sense of Accomplishment (SA) .32 .24 .40 .40 .40 .47 .37 .25 .58 .79 1 Fun and Enjoyment (FE) .40 .31 .41 .38 .42 .55 .46 .32 .48 .75 .57 1 Square root of AVE .85 .81 .79 .70 .72 .80 .75 .91 .70 .86 .85 .87 AVE .73 .65 .62 .49 .52 .65 .57 .83 .49 .74 .72 .76 MSV .83 .69 .83 .57 .61 .69 .68 .21 .68 .63 .63 .56 Note. All correlations were statistically significant at the α = .001 level (two-tailed). AVE = average shared variance; MSV = maximum shared variance. The analysis is based on the entire sample of 976 cases.
86 Given that the number of factors suggested by Study 1 was not supported, factor structure of the measurement was re-assessed using EFA with 470 cases that were randomly selected from the full dataset. The EFA procedure yielded six factors with 28 items. The six factors were labeled as aesthetic design (AD), functional design (FCD), social relationship (SCR), ease (EZ), fun and enjoyment (FE), and individual values (IV).
Among these six factors, three (i.e., functional design, social relationship, and fun and enjoyment) maintained their original items. Aesthetic design, ease, and individual value were composed of items from different factors in Table 4.5. Aesthetic design included three items from fashion design, three from color and pattern, two from fit, and two from physical appearance. This factor was labeled as aesthetic design because the items reflect the beauty aspect of activewear. Ease included three items from physical comfort and one from task facilitation. This factor was labeled as ease because the items focus on consumer’s physical ease when wearing activewear. Individual values included two items from self-respect and three from sense of accomplishment. According to Homer and
Kahle (1988), self-respect and sense of accomplishment represent the individual dimension of values and hence the label of this factor. See Table 4.6 for details on the six factors and the retained items. See Appendix A for items that remained in the original constructs and items that have been moved to a different construct.
87 Table 4.6. Exploratory Factor Analysis
Variance Item M SD β α Eigenvalue Explained Aesthetic Design .93 10.34 34.85% (FD1) The activewear was stylish. 5.41 1.38 .87 (FD2) The activewear was 5.33 1.41 .93 fashionable. (FD3) The activewear was flattering. 5.62 1.25 .81 (CP1) The colors and/or patterns of 4.76 1.58 .61 the activewear were sophisticated. (CP2) The activewear had nice 5.54 1.34 .63 colors and/or patterns (CP3) The activewear had desirable 5.68 1.18 .73 colors and patterns. (FT1) The activewear was shaped 5.87 1.07 .57 nicely. (FT2) The activewear had an 5.63 1.30 .77 attractive cut. (PA2) I looked nice in the 5.40 1.32 .70 activewear while I was doing [piped- in activity]. (PA3) I looked presentable in the 5.75 1.08 .56 activewear while I was doing [piped- in activity]. Functional Design .72 1.24 2.95% (FCD1) The activewear provided 5.88 1.05 .49 many functionalities. (FCD2) The activewear had useful 5.36 1.37 .66 features. (FCD3) The activewear offered 4.55 1.56 .60 some unique functions. Social Relationship .93 3.42 10.12% (SCR1) The activewear helped me to 4.04 1.56 .87 feel accepted by others while I was doing [piped-in activity]. (SCR2) The activewear improved 3.86 1.48 .92 the way I was perceived by others while I was doing [piped-in activity]. (SCR3) The activewear helped me to 3.90 1.51 .93 make a good impression on others while I was doing [piped-in activity].
88 Table 4.6. (continued)
Variance Item M SD β α Eigenvalue Explained Ease .85 1.27 5.17% (PC1) I felt physically comfortable 6.46 0.76 .81 in the activewear while I was doing [piped-in activity]. (PC2) The activewear was 6.46 0.75 .85 comfortable to wear while I was doing [piped-in activity]. (PC3) The activewear put my body 6.12 0.88 .57 at ease while I was doing [piped-in activity]. (TF3) The activewear didn't get in 6.38 0.74 .75 the way of what I was doing while I was doing [piped-in activity]. Fun and Enjoyment .92 1.58 3.73% (FE1) I felt I was in a good mood 5.85 1.07 .77 while I was doing [piped-in activity] wearing the activewear. (FE2) I had fun doing [piped-in 5.50 1.31 .91 activity] in the activewear. (FE3) Wearing the activewear while 5.53 1.24 .85 doing [piped-in activity], I had a sense of pleasure. Individual Values .90 2.63 9.55% (SR1) I felt I had a number of good 5.54 1.13 .49 qualities while I was doing [piped- in activity] wearing the activewear (SR2) I felt satisfied with myself 5.82 1.01 .50 while I was doing [piped-in activity] wearing the activewear. (SA1) I felt I was meeting my goals 5.69 1.16 .88 while I was doing [piped-in activity] wearing the activewear. (SA2) I felt I have achieved 5.45 1.29 .93 something while I was doing [piped-in activity] wearing the activewear, (SA3) I felt I was making progress 5.56 1.24 .74 toward my goal while I was doing [piped-in activity] wearing the activewear. Note. M = mean; SD = standard deviation; β = factor loading; α = Cronbach’s alpha. The analysis was based on a sample of 470 cases randomly selected from the dataset.
89 The six-factor measurement model (Model B) was then assessed using CFA with the other subset of the data (N = 506). As shown in Table 4.7, the six constructs had good discriminant and convergent validities. However, the fit indices, χ2(df) = 1567.54(335),
χ2/df = 4.68, p = .000; RMSEA= .085, SRMR= .065, CFI= .871, GFI= .801, AGFI= .767, indicated that the model (Model 2) had an unacceptable fit (Kline, 1998; Schermelleh-
Engel et al., 2003). Therefore, modification procedures were conducted to improve the model (Byrne, 2001).
Table 4.7. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model B Label Construct (Label) AD FCD SCR EZ FE IV Aesthetic Design (AD) 1 Functional Design (FCD) .55 1 Social Relationship (SCR) .42 .28 1 Ease (EZ) .31 .22 -.01 1 Fun and Enjoyment (FE) .41 .32 .33 .45 1 Individual Values (IV) .44 .41 .27 .43 .64 1
Square root of AVE .76 .72 .92 .72 .86 .78 AVE .58 .51 .84 .51 .74 .61 MSV .30 .30 .17 .20 .41 .41 Note. All correlations were statistically significant at the α = .001 level (two-tailed). AVE = average shared variance; MSV = maximum shared variance. The analysis was based on a sample of 506 cases randomly selected from the dataset.
An inspection of the modification indices revealed the largest modification index pertained to correlated measurement errors between CP2 and CP3, FT2 and FD3, and
PA2 and PA3, all of which were within latent factor AD. In addition, correlated measurement errors among multiple items of latent factor FE and IV had modification indices above 20, suggesting a considerable improvement in model fit if the relationships are specified (Byrne, 2000).
90 While adding the suggested correlations could improve the measurement model, this procedure should be conducted with caution because the model may be rendered meaningless if the correlated error terms are not backed up by theoretical justifications
(Schermelleh-Engel & Moosbrugger, 2003). Correlated measurement errors between observed variables is a sign that the covariance between the two variables is not adequately accounted for by the latent variable (Gerbing & Anderson, 1984). Hence, there might exist an underlying, second-order factor structure that was more meaningful for data analysis and theory development. A second-order model considers the correlated measurement errors as the product of a latent variable that has not been specified in the first-order model (Keith, 2005). As such, because discovering the structure of consumer perception was the essential purpose of Study 2, a second-order model was created.
A closer look at the items with correlated error suggested theoretical justifications for a second-order model. First, the three pairs of items within latent factor AD could be considered as three first-order factors nested under AD. CP2 and CP3 both emphasized on the likability of the color and pattern of activewear (Likable Color, LC); FT2 and FD3 were both related to the overall attractiveness of activewear (Nice Design, ND); PA2 and
PA3 were both about consumer’s physical appearance in the activewear (Physical
Appearance, PA). Wording of the rest of the items, namely FD1, FD2, CP1, and FT1, tended to focus on the fashion aspect (Fashion, FS). In addition, latent factors FE and IV could be considered as two first-order factors that are nested under an overarching second-order construct. According to the literature on values (Gutman, 1982; Homer &
Kahle, 1988), fun and enjoyment represent the interpersonal dimension of internal values while self-respect and sense of accomplishment belong to the individual dimension
91 (Homer & Kahle, 1988). In multiple studies that use the value dimensions to explain consumer attitude and behavior, covariance amongst the dimensions is specified in the structural equation model (e.g., Chryssohoidis & Krystallis, 2005; Homer & Kahle,
1988). Based on these theoretical justifications, a second-order factor Internal values
(INV) was created with FE and IV as its first-order factors.
Accordingly, a second-order measurement model (Model C) was developed with four first-order factors (LC, ND, PA, and FS) nested under second-order factor AD, and two first-order factors (FE and IV) nested under second-order factor INV. See Figure 4.2 for a diagram of Model C.
Figure 4.2. Model C. The final measurement model.
Factor loading scores supported the measurement structure of Model C. As shown in Table 4.8, all items loaded significantly on their respective factors with scores ranged from .65 for FCD3 to .94 for SCR1. Moreover, factor loadings of the six first-order
92 factors (LC, ND, PA, FS, FE and IV) on the two second-order factors (AD and INV) were also significant, ranging from .77 for LC to AD to .93 for ND to AD. The model also showed an acceptable fit with χ2(df) = 1024.18 (334), χ2/df = 3.07, p< .001; RMSEA
= .064, SRMR = .068, CFI = .928, GFI = .865, and AGFI = .836 (Kline, 1998;
Schermelleh-Engel et al., 2003). Although GFI and AGFI did not reach the preferred cutoff value of .90 and .85, they were likely to be biased by sample size and should not be interpreted alone (Schermelleh-Engel et al., 2003).
The measurements also had good convergent and discriminant validities. As shown in Table 4.9, the AVE for the five second-order constructs ranged from .72 to .91, indicating that the measures had satisfactory convergent validity. The square root of every AVE score was larger than corresponding correlations and every AVE score was larger than the MSV. These results suggested that the six constructs were distinct from each other (Fornell & Larcker, 1981). Based on the results discussed above, Model C was accepted as the final measurement model and was used for further analyses on the structural level.
93 Table 4.8. Factor Loadings of Model C Factor Item FS LC ND PA FCD EZ SCR FE IV AD INV FD1 .89 FD2 .89 CP1 .67 FT1 .69 CP3 .89 CP2 .87 FD3 .92 FT2 .88 PA3 .77 PA2 .93 FCD1 .73 FCD2 .79 FCD3 .65 PC1 .72 PC2 .82 PC3 .67 TF3 .72 SCR1 .94 SCR2 .92 SCR3 .88 FE1 .87 FE2 .88 FE3 .90 SR1 .84 SR2 .84 SA3 .78 SA1 .84 SA2 .80 FS .93 ND .92 LC .77 PA .83 FE .88 IV .85 Note. All factor loadings were statistically significant at the α = .001 level (two-tailed). The analysis was based on a sample of 506 cases randomly selected from the dataset. FS = fashion; LC = likable color; ND = nice design; PA = physical appearance; FCD = functional design; EZ = ease; SCR = social relationship; FE = fun and enjoyment; IV = individual value; AD = aesthetic design; INV = internal value.
94 Table 4.9. Constructs Correlations, the Square Root of AVE, AVE, and MSV Of Model C Label Construct (Label) AD FCD SR EZ INV Aesthetic Design (AD) 1 Functional Design (FCD) .60 1 Social Relationship (SCR) .41 .24 1 Ease (EZ) .40 .34 - .01 1 Internal Values (INV) .60 .51 .28 .58 1 Square root of AVE .87 .72 .91 .74 .86 AVE .75 .52 .84 .54 .85 MSV .37 .36 .16 .33 .37 Note. All correlations were statistically significant at the α = .001 level (two-tailed). AVE = average shared variance; MSV = maximum shared variance. The analysis was based on a sample of 506 cases randomly selected from the dataset.
Within-Group Comparison Between Upward And Downward Models
The second step of analysis contained two model selections. The goal of model selection was to decide whether it is the upward or downward direction (see Figure 2.2) that better describes the means-end chain structure. Figure 4.3 shows the upward model that was created based on the measurement model and the HVM in Study 1. Several paths in the HVM were merged because the corresponding HVM elements were merged into the same construct in the measurement model. An example of merged link is path f, which combined the direct link from Task facilitation to Self-respect and Sense of
Accomplishment in the HVM (see Figure 4.1). Path f was created because the measurement of Self-respect and Sense of Accomplishment was merged into Internal
Values. Another example is path a. While this link did not exist in the HVM, it was created because the measurement of Aesthetic Design included Physical Appearance, which led to Social Relationship in the HVM. In the downward model, directions of all paths in Figure 4.3 were reversed.
95
Figure 4.3. The Structural Model in The Upward Direction.
The model selection results in the fitness group are reported in Table 4.10. Both the upward and downward models had acceptable fit with RMSEAs close to .07. A comparison of fit indices between the upward and downward model showed that the two models fitted the data equally weak, as confidence intervals of the two model’s RMSEA overlapped each other. However, AICs and AIC weights suggested there is 100% certainty that it was the downward model that fitted better with data of the fitness group
(N = 468).
Table 4.10. Comparison between Up- and Downward Models for The Fitness Group
Direction Statistics Upward Downward χ2 1129.19 1086.64 df 338 338 χ2/df 3.341 3.22 RMSEA (confidence interval) .071 (.066 - .075) .069 (.064 - .073) AIC 1265.185 1222.636 AIC weights 0% 100% Note. The analysis was based on a sample of 468 cases that were assigned to the fitness context.
96 Model selection results in the non-fitness group are reported in Table 4.11. Both the upward and downward models had acceptable fit with RMSEAs just under .08.
Confidences intervals of RMSEAs of the two groups overlapped, indicating no significant difference between how well the two models fitted the data. However, AICs and AIC weights suggested there is 85% certainty that the upward model fitted better with data of the non-fitness group (N = 508).
Table 4.11. Comparison between Up- and Downward Models for The Non-Fitness Group
Direction Statistics Upward Downward χ2 1389.51 1393.09 df 338 338 χ2/df 4.11 4.12 RMSEA (confidence interval) .078 (.074 - .083) .078 (.074 - .083) AIC 1525.507 1529.087 AIC weights 85% 15% Note. The analysis was based on a sample of 508 cases that were assigned to the non- fitness context.
Multiple-Group Analysis Between Fitness And Non-Fitness Contexts
To answer the third research question, the final part of the results compared the means-end chain structure across fitness and non-fitness groups in the upward and downward directions respectively. Differences between the fitness and non-fitness group was first tested with an MANOVA on all items included in the model (See Figure 4.2 and
Table 4.8). See Appendix B for descriptive statistics and a mean comparison of each item between the fitness and non-fitness groups. However, the main results that answered the third research question were generated by multiple-group analyses that compared differences in the two groups’ means-end chains on the model and path levels (e.g.,
Boyle & Magnusson, 2007). To do so, a measurement invariance was tested by 97 comparing the structural model with no constraint and with constraints on all factor loadings. The unconstrained model had an acceptable fit (RMSEA = .053, CFI = .904,
GFI = .840, AGFI = .807) with a chi-square of χ2(df) = 2518.68(676). The constrained model had a chi-square of χ2(df) = 2595.70(695), which was not significantly different from the unconstrained model (∆χ2 [19] = 77.02, p < .001) and indicated that the measurement model was variant between the fitness and non-fitness groups.
When full measurement invariance is not achieved, partial measurement invariance is sufficient for multiple-group analysis (Byrne et al., 1989). The unstandardized regression weights of items were inspected to identify items that have significantly different factor loadings across the fitness and non-fitness groups
(McDonald, Karg, & Vocino, 2013). This procedure resulted in the relaxation of constraints on the three items designed to measure sense of accomplishment. Partial invariance was accordingly achieved with an insignificant test for difference: ∆χ2 (16) =
20.18, p = .212.
The upward means-end chain model with a comparison between the fitness and non-fitness groups was tested first. As shown in Table 4.12, the chi-square difference test was significant on the .05 significance level with ∆χ2 (10) = 21.36, p = .019, suggesting variance between the fitness and non-fitness groups on the model level, meaning that means-end chain structures of the upward means-end chain structures of fitness and non- fitness groups had significant differences.
98 Table 4.12. Invariance Test of The Upward Model between Fitness and Non-Fitness Groups Model Goodness of Fit Test of Invariance M1: Unconstrained χ2 (676) = 2518.70, p < .001 M2: Equal factor χ2 (692) = 2538.86, p < .001 M2-M1: loadings ∆χ2 (16) = 20.18, p = .212 M3: Equal factor χ2 (702) = 2560.22, p < .001 M3-M2: loadings and paths ∆χ2 (10) = 21.36, p = .019 M4: Equal factor χ2 (697) = 2548.12, p < .001 M4-M2: loadings and path a ∆χ2 (5) = 9.27, p > .05 M5: Equal factor χ2 (697) = 2549.77, p < .001 M5-M2: loadings and path b ∆χ2 (5) = 10.91, p > .05 M6: Equal factor χ2 (697) = 2548.74, p < .001 M6-M2: loadings and path c ∆χ2 (5) = 9.88, p > .05
M7: Equal factor χ2 (697) = 2553.31, p < .001 M7-M2: loadings and path d ∆χ2 (5) = 14.45, p = .013 M8: Equal factor χ2 (697) = 2553.62, p < .001 M8-M2: loadings and path e ∆χ2 (5) = 14.76, p = .011 M9: Equal factor χ2 (697) = 2548.71, p < .001 M9-M2: loadings and path f ∆χ2 (5) = 9.852, p > .05
99 Chi-square difference test on each of the paths showed that the difference in the path from social relationship to internal values was significant: ∆χ2 (5) = 14.45, p = .013.
The difference in path from aesthetic design to internal values was also significant: ∆χ2
(5) = 14.76, p = .011. Path coefficients, as shown in Figure 4.4, revealed that all six paths were significant on the .001 level for both fitness and non-fitness groups.
Figure 4.4. Standardized Path Coefficients across Fitness And Non-Fitness Groups of The Upward Model.
Another comparison was tested between the fitness and non-fitness groups using the downward means-end chain model. As shown in Table 4.13, the chi-square difference test comparing the partially constrained measurement model and the model with all structural weights and partial measurement weights constrained was insignificant with χ2
(10) = 16.21, p= .094, suggesting invariance between the fitness and non-fitness group on the model level.
100 Table 4.13. Invariance Test of The Downward Model between Fitness and Non-Fitness Groups Model Goodness of Fit Test of Invariance M1: Unconstrained χ2 (676) = 2479.71, p < .001 M2: Equal factor χ2 (692) = 2498.66, p < .001 M2-M1: loadings ∆χ2 (16) = 18.94, p= .271 M3: Equal factor χ2 (702) = 2514.87, p < .001 M3-M2: loadings and paths ∆χ2 (10) = 16.21, p= .094 M4: Equal factor χ2 (697) = 2506.33, p < .001 M4-M2: loadings and path a ∆χ2 (5) = 7.67, p > .05 M5: Equal factor χ2 (697) = 2506.33, p < .001 M5-M2: loadings and path b ∆χ2 (5) = 7.67, p > .05 M6: Equal factor χ2 (697) = 2509.68, p < .001 M6-M2: loadings and path c ∆χ2 (5) = 11.02, p > .05 M7: Equal factor χ2 (697) = 2507.86, p < .001 M7-M2: loadings and path d ∆χ2 (5) = 9.20, p > .05 M8: Equal factor χ2 (697) = 2505.95, p < .001 M8-M2: loadings and path e ∆χ2 (5) = 7.29, p > .05 M9: Equal factor χ2 (697) = 2505.74, p < .001 M9-M2: loadings and path f ∆χ2 (5) = 7.08, p > .05
101 Chi-square difference tests on each path showed that none of the paths had a significant difference between the two groups. Path coefficients, as shown in Figure 4.5, were all significant on the .001 level for both fitness and non-fitness groups.
Figure 4.5. Standardized Path Coefficients across Fitness And Non-Fitness Groups of The Downward Model.
Discussion of Study 2 Findings
On the basis of means-end chain elements identified in Study 1, Study 2 focused on structural relationships amongst these elements to answer the second and third research questions. Previous research is ambiguous on the inclusive and non-inclusive views to understand relationships amongst attributes, consequences, and end-state values
(Snelders & Schoormans, 2004) as well as the upward and downward directions of the overall means-end chain structure (Overby et al., 2005). Results of Study 2 provide insights on these two issues while considering the influence of fitness and non-fitness contexts.
102 The Second Research Question
The issue of inclusiveness is a part of the second research question and Study 2’s results about aesthetics (i.e., physical appearance) offer insight on this issue. While Study
1 finds physical appearance as a consequence that overlaps the physiological and psychosocial categories, Study 2 finds physical appearance as a sub-dimension of the abstraction attribute “aesthetic design”. Treating physical appearance as a consequence would put it on a higher level of abstraction that is harder to process compared to concrete information (Snelders & Schoormans, 2004). However, in the presence of context-specific information, consumers are able to process abstract information as easily as concrete information (Schwanenflugel et al., 1992). As contextual information (i.e., fitness or non-fitness activities) was always made available to survey respondents in
Study 2, it is likely that the respondents were able to form perceptions of physical appearance without relying on attributes (i.e., fashion design, color and pattern, and fit).
Moreover, Study 1 participants stated that they evaluate fashion design based on whether they would look good in the activewear, meaning that while a nice design contributes to physical appearance, the perception of physical appearance also influences perceptions of aesthetic elements in activewear. Hence, results from Study 2 suggest that in activewear consumption, aesthetics (i.e., physical appearance) is a non-inclusive and abstract attribute that consumers directly develop from observing themselves wearing activewear.
Study 2 offers further insights on how attributes identified in Study 1 relate to each other and the perception structure they form. According to Study 2, when consumers reflect on activewear usage in a given context, they form perceptions in the aesthetic aspect, which is a multidimensional abstract attribute that includes fashion, color and
103 pattern, physical appearance, and fit. In contrast, consumers’ perception in the functional aspect is unidimensional and concretely describes functional designs in activewear. This finding is consistent with the previous research, which finds that attributes in the functional category tend to be more concrete and unidimensional, whereas attributes in the aesthetic categories are more abstract and multi-dimensional (Abraham-Murila &
Littrell, 1995). Hence, the current research concludes that aesthetic design and functional design are two groups of attributes that consumers perceive from their activewear experience while the aesthetic dimension consists of multiple aspects of designs.
Another issue embedded in the second research question is the upward and downward means-end chain. Results in Study 2 suggest the direction is dependent upon the context. Within-group comparisons between the upward and downward model reveal that the downward structure is more likely to be a better approximation of consumers’ perceptions of their activewear experience in the fitness context, while the upward structure works better in the non-fitness context (Burnham & Anderson, 2004). These results directly connect to a discussion on the third research question.
The Third Research Question
The third research question asks how structural relationships of means-end chains vary in fitness and non-fitness contexts. The situation research suggests that product- usage context defines the values to achieve and influences consumers’ mindset during product usage (Belk, 1975). The current finding shows that the context (i.e., fitness and non-fitness activities) can alter the means-end chain structure by changing its direction.
Consumer perceptions are more value-driven when using activewear in the fitness context than the non-fitness context. According to the non-inclusive view and context
104 availability theory, contextual information can help people process abstract perceptions
(Schwanenflugel et al., 1992). It is possible that the fitness context, as it aligns better with the default purpose of activewear, provides stronger contextual support. When contextual support is strong, consumers are more certain of the abstract values they have, and accordingly more value-driven (Snelders & Schoormans, 2004). In contrast, the non- fitness context may not be effective in reducing uncertainty, and therefore makes it harder for consumers to form abstract perceptions and more likely to rely on product attributes to make sense of their experience. This distinction highlights the importance of contextual variables and further supports the leisure activity typology, in which sport and fitness activities represent a task definition that is distinguished from easy and social activities (Unger, 1984).
The different means-end chain directions in fitness and non-fitness contexts could also be explained by the topology of values. Existing research has found that people with high internal values are more active in searching for products that satisfy their needs, and vice versa, consumers who are highly involved with a product are more likely to be driven by internal values (Chryssohoidis & Krystallis, 2005; Limon et al., 2009). In the current research, interview participants who were more physically active and survey respondents in the fitness context may represent highly-involved activewear consumers.
According to the literature, this group of consumers is driven by internal values rather than external stimuli (Homer & Kahle, 1988). Multiple interview participants also indicated that although activewear did have an influence on their experience during physical exercise, the exercise itself was still the core activity and activewear acted as a facilitator of the experience. Hence, when these consumers think of their experience with
105 activewear, they tend to start from the self (i.e., end-state values) and use self-concepts to evaluate product attributes. In contrast, activewear consumers who are not physically active need to rely on the specific attributes of activewear to derive benefits and develop internal values.
The specific means-end paths also vary across fitness and non-fitness contexts.
According to multiple-group analysis of the upward model (see Table 4.12 and Figure
4.4. Standardized Path Coefficients across Fitness And Non-Fitness Groups of The
Upward Model.), end-state values in the non-fitness context are more susceptible to aesthetic design and social relationship compared to values in the fitness context. The situation research has found that the context affects consumers’ desired end-state values, leading consumers to focus on product attributes and consequences that are associated with the context (Van Kenhove et al., 1999; Walker & Olson, 1991). As non-fitness activities included in Study 2’s survey were mainly social in nature, the context may have led respondents to gravitate to the social and aesthetic aspects of wearing activewear.
106 CHAPTER 5
5. DISCUSSION
This chapter represents a discussion of the overall research based on the literature review and the conceptual model. The chapter is organized as the following. First, findings are used to reflect on the conceptual model and its theoretical contributions.
Practical implications are discussed next, followed by limitations and future directions.
The last section concludes the dissertation.
Theoretical Contributions
The current research is built upon the SX framework of Funk (2017). It examines the intersection of the user and the context in the SX framework by integrating the means-end chain theory (Gutman, 1982) and the situation research (Belk, 1975). Findings provide theoretical contributions to the SX framework, the means-end chain theory, and the role of context in consumer research.
Contributions To The SX Framework
First, the current research applies the means-end chain theory to study a part of the SX framework. While the SX framework has identified sport user, sport context, and sport organization as three components in sport experience (Funk, 2017), the framework does not specify how the intersection of the user and the context can be examined. The means-end chain theory considers consumers’ perceptions of a product as a network of chains that connect product attributes with consumers’ personal values (Gutman, 1982).
By adapting the theory and its laddering method, the current research identifies five attributes, four consequences, and three end-state values in the context of activewear experience. In addition, relationships amongst the attributes, consequences, and values
107 were tested and compared. Overall, findings reflect how consumers use perceptions on different levels of abstraction to make sense of their experience with a product. While existing research is concerned that means-end chains reflect the researcher’s perceptions instead of that of consumers (Grunert & Grunert, 1995), the current research, particularly structural models in Study 2, confirms that the theory can adequately capture consumers’ perception structure. Future research can continue applying the means-end chain theory to examine the SX framework because the theory introduces falsifiable relationships to the SX framework.
The current research also represents an initial empirical investigation on part of the SX framework. Existing research in sport marketing has neglected to understand consumer experience in terms of how consumers use a product and develop perceptions of the “using” experience. While the SX framework was proposed to address this gap, the framework has not been applied in empirical studies. The current research illustrates how the user (i.e., activewear consumer) uses and perceives sport product (i.e., activewear) in different contexts (i.e., fitness and non-fitness contexts). In the SX framework (Funk,
2017), the context is “the experienced environment through which a sport customer navigates an experience and encounters touchpoints before, during and after” (p. 152).
How the experienced environment is designed influences the sport user experience (e.g.,
Du et al., 2015; Yoshida et al., 2013). Findings of the current research support this view by showing that the product-usage context influences the means-end chain structure.
Specifically, results reveal that consumers’ evaluation of the sport experience is value- driven in sport-contexts but attribute-driven in non-sport contexts. This finding provides support that the context is a part of the sport experience (Funk, 2017).
108 Contributions To The Means-End Chain Theory
The current research also contributes to Gutman’s (1982) means-end chain theory.
While the means-end chain theory has been widely adopted in marketing research, two crucial questions were left unattended. The first question involves the concept of abstract and asks whether perceptions are formed from the inclusive view or non-inclusive view
(Snelders & Schoormans, 2004). Findings of the current research offer support for the non-inclusive view by showing that there are some abstract perceptions, such as physical appearance, that does not subsume concrete perceptions. This finding provides insights on how relationships amongst attributes, consequences, and end-state values should be conceptualized. Specifically, abstract perceptions such as consequences are not limited to those resulting from using and consciously evaluating attributes. Instead, consequences could be developed from direct observation and intuition of the overall product experience (Schwanenflugel et al., 1992).
The second question inquires whether means-end chains follow an upward attribute-driven direction or a downward value-driven direction. The current research reveals that the direction varies across consumers who wear activewear in fitness or non- fitness contexts. This distinction could be explained from the non-inclusive view
(Schwanenflugel et al., 1992), which emphasizes on the amount of contextual support offered in each context, or from the value typology approach, which emphasizes on the value-orientation of different consumer groups (Homer & Kahle, 1988). Hence, future research that applies the means-end chain theory should justify the directions they take by considering characteristics of the consumer and the context in which the product is used.
109 Overall Contributions To Sport Experience Research
The discussion above leads to contributions that the current research makes to the overall sport experience research. The first contribution relates to the role of context.
While both the SX framework and the means-end chain theory acknowledge the importance of context, they provide vague directions on how context should be studied.
The current research introduces the situation research of Belk (1975) to understand the role of context in how consumers construct and evaluate product usage. This theoretical integration clarifies the scope of context and provides directions on the types of situational variables that influence sport consumers. Specifically, sport consumer researchers should consider the physical surrounding, temporal perspective, antecedent state, social surrounding, and task definition in which a sport product is used (Belk,
1975). Moreover, the important role of context revealed in the current research reinforces
Funk’s (2017) advice to have a thorough understanding of the context and how consumers think and behave in the context when studying the sport experience.
Specifically, results of the current research suggest that the sport consumer experience is more value-driven in sport-related contexts and more attribute-driven in non-sport contexts. This finding adds new knowledge to the sport experience literature at the intersection of the user and the context.
Findings also illustrate the importance of considering characteristics of users of sport products. Instead of passively accepting a designed experience, sport users actively create the experience when they use sport products (Walls et al., 2011). While the current research does not intend to make comparisons across different consumer groups, the importance of user characteristics is addressed by a focus on female consumers. The
110 predominant roles of fit and physical appearance revealed in Study 1 may be a result of the female-only focus as female consumers tend to concern about the aesthetic aspect of clothing (Zhou et al., 2017). In addition, the current research recruited consumers with different activewear usage behaviors. Particularly in Study 1, consumers who wear activewear primarily for fitness or non-fitness contexts were interviewed. Findings show nuances in how the two groups of consumers perceive their activewear experience. For example, while those who were highly active perceived task facilitation as being focused on the exercise, those who were not physically active perceived the concept as feeling motivated in mundane tasks. These nuances are reflected in Study 2, which shows differences across the fitness and non-fitness groups on model and path levels. Hence, sport consumer researchers should take consumers’ demographic and psychographic characteristics into account when studying the sport experience (Funk, 2017).
Overall, the current research provides insights on examining the intersection of the user and the context (see Figure 2.3). According to the model and findings, when a consumer wears a pair of yoga pants while shopping, her experience is driven by attributes of the pants. She may develop a perception that the pants have nice colors, which ultimately increases her self-respect. However, if she wears the pants to a yoga class, her experience is driven by how she feels about herself, not the yoga pants. When she feels a sense of self-respect during the yoga practice, the perception will spill-over to how she evaluates the pants’ color such that the color looks prettier to her. A lack of understanding of how the user and the context interact is a significant knowledge gap in existing sport consumer research (Funk, 2017). The current research addresses this gap
111 by integrating the means-end chain theory and situation research to understand consumers’ construction and evaluation of sport product usage in different contexts.
Practical Implications
The current research also provides practical implications for sport brands.
Specifically for activewear brands, aesthetic details and functional features need to be designed in ways that provide physical ease, facilitate social relationships, and contribute to consumers’ self-concepts. Aesthetics, including fashion design, color and pattern, and fit, is especially important because it influences social relationship and ease, and directly affects consumers’ end-state values. Hence, brands should design unique aesthetic features to form distinct and favorable consumer perceptions. Specifically, brands should be more creative with activewear tops as female consumers can pair the top with a black piece on the bottom to create a balanced outfit. Fashion elements should be integrated into the tops to deliver a sense of fun and enjoyment. The fashion elements should not be too fancy and complicated as it may risk consumers’ aesthetic taste and interfere with physical movement. Although a pair of black tight pants appears boring, it is still a style preferred by female consumers. Black and tightness in the bottom give consumers a better look and contribute to their self-respect.
In addition to product design, the current research offers useful implications relate to marketing. The central concern of marketing deals with creating consumer perceptions
(Sujan & Bettman, 1989). To create strong and favorable perceptions, brands need to know how concrete aspects of the product that they can control fit into consumers’ life
(Reynolds & Gutman, 1988). Findings regarding the direction of means-end chain provide implications for creating targeted marketing messages. For activewear brands
112 that want to position themselves as athleisure brands that can be worn in the daily life, their marketing messages should depict specific product attributes because consumers’ perceptions are driven by attributes in the non-fitness context. In addition, the marketing message should also clearly illustrates how attributes contribute to consumers’ end-values because consumers who wear activewear in non-fitness context may not evaluate product attributes carefully. For example, the online advertisement of an athleisure brand could show details of the product and tell a story of how the product makes consumers feel.
For activewear brands that want to position themselves as high-performance sport brands, their marketing messages should emphasize the values that consumers can derive when they wear the products in sport and physical exercises. As consumers who wear activewear for sport and fitness are internally driven, the advertisement should deliver abstract concepts such as self-respect and a sense of accomplishment. An online advertisement should use inspirational words and images that communicate internal feelings of the athletes. In contrast, this commercial would not work for athleisure brands because consumers may be uncertain of the message and develop weak perceptions
(Schwanenflugel et al., 1992). The implication also applies to brands in other domains.
Marketers of retail brands need to create marketing messages based on an understanding of where consumers use the product and how they perceive the product in the context.
Finally, the current research confirms that the laddering method is useful for understanding consumers. The laddering method, as a method associated with the means- end chain theory, uncovers the underlying values that guide consumer behavior and product attributes that satisfy these values (Reynolds & Gutman, 1988). Laddering method probes consumers think of connections that would be otherwise hidden from the
113 consumers and the researcher (Grunert & Grunert, 1995). In the current research, several perceptions, such as physical appearance and its relationship with concrete attributes and self-respect, would be neglected if laddering interviews were not conducted. Brands should continue using the laddering method to inform product design and marketing.
Limitations and Future Research
While the current research provides contributions to research and practice, it has several limitations that provide opportunities for future research. First, these findings might have been influenced by the samples used in the studies. A convenient sample of activewear consumers was recruited in Study 2, and while several screening techniques were used to select qualified respondents, people who opted into the research may be systematically different from those who did not (Goodman & Paolacci, 2017). Moreover, the current research focuses on female consumers, and as such female-only samples were used in both studies to eliminate gender differences in consumers’ cognitive style and value orientation (Gruber, Szmigin, & Voss, 2009). The means-end chains identified in the current study may not apply to activewear consumers of other genders. Future research should compare means-end chain content and structure across consumers of different genders. The findings will inform the role of sport user in the SX framework and provide practical implications on how brands should target different consumer groups.
Additionally, while the current research focuses on “using”, the two studies were conducted retrospectively. The researcher used several techniques, such as the stimulus material in interviews and the recall tasks in surveys, to help research subjects reflect on their activewear experience. However, the results generated may not be a perfect
114 representation of the actual experience. Research has shown that current events influence how prior experiences are perceived such that recalls are usually inaccurate reflections of the actual experience (Aaker, Drolet, & Griffin, 2008). From the temporal perspective, consumer perceptions fluctuate before, during, and after the core consumption period
(e.g., Vassiliadis et al., 2013). Future research should gather data on the real-time consumer experience. For example, researchers can design studies on smartphone ethnography platforms, such as Over the ShoulderTM, that allow participants to record their thoughts while they are using the product.
While the current research examines the upward and downward means-end chain, the laddering method used in Study 1 followed the upward direction. The researcher made this decision, as there is a lack of direction in the literature as to how one conducts and analyzes laddering interviews in the downward direction. More empirical studies and theoretical pieces, like that of Grunert and Grunert (1995), are needed to develop a coherent methodology for laddering data collection and analysis in both directions.
The concept of physical appearance deserves further investigation as contradicting results were found in the two studies. While Study 1 identifies physical appearance as an aesthetic consequence, Study 2 put physical appearance on the attribute level. The current research has used the context availability theory to explain this inconsistent finding. However, there needs to be a more thorough explanation to decide whether physical appearance is an attribute or a consequence, or in what context would consumers consider the concept as an attribute or a consequence. Future research can conduct in-depth interviews focusing on physical appearance and the concepts of aesthetic and beauty in activewear consumption. Those findings will provide theoretical
115 implications for the inclusive and non-inclusive view of abstraction, and practical implications for how brands can communicate the concept of beauty to consumers.
The current research compares the activewear experience in fitness and non- fitness contexts. While fitness and non-fitness activities represent different task definitions, the two contexts may also be distinguished in terms of physical surrounding, temporal perspective, antecedent state, and social surrounding (Belk, 1975). Therefore, findings of the current research are interpreted based on the confounding effect of several situational variables. The specific effect of each situational variables on the activewear experience needs to be examined. According to Study 1 participants, the social surrounding had an influence on how they felt about wearing activewear. Future research can use experimental designs to control other variables while manipulating the type of social surrounding in which activewear is worn.
Finally, this research focuses on the intersection of the user and the context. As such, this focus is only a part of the conceptual model (see Figure 2.3), of which the other parts deserve to be examined in future research. Consumers develop different perceptions toward products provided by different sport organizations (Lock, Filo, Kunkel, &
Skinner, 2015). Future studies should consider how the sport experience is influenced by sport organization’s characteristics such as brand personality (Carlson & Donavan, 2013).
An investigation in the context of activewear will be especially fruitful as the activewear industry is highly competitive.
Conclusion
The athleisure trend is more than just a phenomenon. It reveals how products, when used in various contexts, can cultivate different experiences for consumers. This
116 dissertation contributes to the conversation on sports consumer experience with a focus on the intersection of the user and the context in Funk’s (2017) SX framework. A conceptual approach to examine the intersection was proposed by integrating the means- end chain theory (Gutman, 1982) and situation research (Belk, 1975) into the SX framework. This approach illustrates how consumer experience is constructed and evaluated from the consumer perspective. The two empirical studies within this dissertation showed that consumer perceptions of the product experience are formed on levels of abstraction and connect in different patterns and directions depending on the context in which the product is used. This dissertation demonstrates the need to investigate the consumer experience while considering characteristics of the context.
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135 APPENDIX A
MOVEMENTS OF ITEMS IN THE EFA PROCEDURE
Construct and Item Item Movement Aesthetic Design (FD1) The activewear was stylish. Moved from "Fashion Design" (FD2) The activewear was fashionable. Moved from "Fashion Design" (FD3) The activewear was flattering. Moved from "Fashion Design" (CP1) The colors and/or patterns of the activewear were Moved from "Color sophisticated. and Pattern" Moved from "Color (CP2) The activewear had nice colors and/or patterns and Pattern"
(CP3) The activewear had desirable colors and patterns. Moved from "Color and Pattern" (FT1) The activewear was shaped nicely. Moved from "Fit" (FT2) The activewear had an attractive cut. Moved from "Fit" (PA2) I looked nice in the activewear while I was doing Moved from [piped-in activity]. "Physical Appearance" (PA3) I looked presentable in the activewear while I was Moved from doing [piped-in activity]. "Physical Appearance" Functional Design (FCD1) The activewear provided many functionalities. Remained in the original construct (FCD2) The activewear had useful features. Remained in the original construct (FCD3) The activewear offered some unique functions. Remained in the original construct Social Relationship (SCR1) The activewear helped me to feel accepted by Remained in the others while I was doing [piped-in activity]. original construct (SCR2) The activewear improved the way I was perceived Remained in the by others while I was doing [piped-in activity]. original construct (SCR3) The activewear helped me to make a good Remained in the impression on others while I was doing [piped-in activity]. original construct
136 Appendix A (continued)
Construct and Item Item Movement Ease (PC1) I felt physically comfortable in the activewear while I Moved from was doing [piped-in activity]. "Physical Comfort" (PC2) The activewear was comfortable to wear while I was Moved from doing [piped-in activity]. "Physical Comfort" (PC3) The activewear put my body at ease while I was Moved from doing [piped-in activity]. "Physical Comfort" (TF3) The activewear didn't get in the way of what I was Moved from "Task doing while I was doing [piped-in activity]. Facilitation"
Internal Values (FE1) I felt I was in a good mood while I was doing [piped- Moved from "Fun & in activity] wearing the activewear. Enjoyment" (FE2) I had fun doing [piped-in activity] in the activewear. Moved from "Fun & Enjoyment" (FE3) Wearing the activewear while doing [piped-in Moved from "Fun & activity], I had a sense of pleasure. Enjoyment" (SR1) I felt I had a number of good qualities while I was Moved from "Self- doing [piped-in activity] wearing the activewear respect" (SR2) I felt satisfied with myself while I was doing [piped- Moved from "Self- in activity] wearing the activewear. respect" (SA1) I felt I was meeting my goals while I was doing Moved from "Sense [piped-in activity] wearing the activewear. of Accomplishment" (SA2) I felt I have achieved something while I was doing Moved from "Sense [piped-in activity] wearing the activewear, of Accomplishment" (SA3) I felt I was making progress toward my goal while I Moved from "Sense was doing [piped-in activity] wearing the activewear. of Accomplishment"
137 APPENDIX B
MEAN COMPARISONS BETWEEN FITNESS AND NON-FITNESS GROUPS
M (SD) Fitness Non-fitness Item N = 468 N = 508 F Sig. Aesthetic Design (FD1) The activewear was stylish. 5.47 (1.28) 5.39 (1.41) 0.86 0.353 (FD2) The activewear was 5.39 (1.28) 5.29 (1.43) 1.30 0.254 fashionable. (FD3) The activewear was flattering. 5.67 (1.14) 5.59 (1.32) 1.08 0.298 (CP1) The colors and/or patterns of the 4.81 (1.54) 4.73 (1.61) 0.56 0.455 activewear were sophisticated. (CP2) The activewear had nice colors 5.56 (1.31) 5.56 (1.35) 0.00 0.993 and/or patterns (CP3) The activewear had desirable 5.72 (1.19) 5.64 (1.24) 1.17 0.280 colors and patterns. (FT1) The activewear was shaped 5.89 (1.01) 5.87 (1.10) 0.08 0.777 nicely. (FT2) The activewear had an attractive 5.71 (1.19) 5.66 (1.25) 0.38 0.538 cut. (PA2) I looked nice in the activewear 5.46 (1.19) 5.44 (1.30) 0.08 0.777 while I was doing [piped-in activity]. (PA3) I looked presentable in the 5.86 (0.97) 5.68 (1.17) 7.24 0.007 activewear while I was doing [piped-in activity]. Functional Design (FCD1) The activewear provided 5.74 (1.13) 5.95 (0.96) 9.55 0.002 many functionalities. (FCD2) The activewear had useful 5.41 (1.31) 5.35 (1.34) 0.37 0.544 features. (FCD3) The activewear offered some 4.59 (1.59) 4.61 (1.56) 0.03 0.872 unique functions. Social Relationship (SCR1) The activewear helped me to 4.31 (1.51) 3.92 (1.53) 15.41 0.000 feel accepted by others while I was doing [piped-in activity]. (SCR2) The activewear improved the 4.17 (1.44) 3.80 (1.50) 15.69 0.000 way I was perceived by others while I was doing [piped-in activity]. (SCR3) The activewear helped me to 4.19 (1.48) 3.83 (1.51) 14.78 0.000 make a good impression on others while I was doing [piped-in activity].
138 APPENDIX B (continued) M (SD) Fitness Non-fitness Item N = 468 N = 508 F Sig. Ease (PC1) I felt physically comfortable in the 6.36 (0.78) 6.52 (0.75) 11.40 0.001 activewear while I was doing [piped-in activity]. (PC2) The activewear was comfortable to 6.41 (0.69) 6.52 (0.72) 5.68 0.017 wear while I was doing [piped-in activity]. (PC3) The activewear put my body at ease 6.02 (0.92) 6.19 (0.90) 8.66 0.003 while I was doing [piped-in activity]. (TF3) The activewear didn't get in the way 6.39 (0.76) 6.40 (0.78) 0.02 0.896 of what I was doing while I was doing [piped-in activity]. Internal Values (FE1) I felt I was in a good mood while I 5.99 (0.91) 5.80 (1.11) 8.67 0.003 was doing [piped-in activity] wearing the activewear. (FE2) I had fun doing [piped-in activity] 5.79 (1.05) 5.37 (1.39) 28.62 0.000 in the activewear. (FE3) Wearing the activewear while doing 5.78 (1.04) 5.37 (1.29) 29.47 0.000 [piped-in activity], I had a sense of pleasure. (SR1) I felt I had a number of good 5.63 (1.06) 5.51 (1.13) 2.82 0.093 qualities while I was doing [piped-in activity] wearing the activewear (SR2) I felt satisfied with myself while I 5.88 (0.94) 5.83 (1.01) 0.62 0.431 was doing [piped-in activity] wearing the activewear. (SA1) I felt I was meeting my goals while 5.87 (0.95) 5.58 (1.25) 16.06 0.000 I was doing [piped-in activity] wearing the activewear. (SA2) I felt I have achieved something 5.76 (1.05) 5.30 (1.37) 33.44 0.000 while I was doing [piped-in activity] wearing the activewear, (SA3) I felt I was making progress toward 5.95 (0.91) 5.36 (1.31) 64.91 0.000 my goal while I was doing [piped-in activity] wearing the activewear.
139