A Study on Korean Customers’ Intentions to Repurchase for the Sustainable Growth of the Athleisure Market

Abstract

The athleisure market has experienced significant growth in recent years, establishing itself as a mainstream trend in the fashion industry. Given the escalating demand for athleisure wear, businesses must secure sustainable growth by comprehending customer intentions to repurchase. This study conducted a survey to collect customer data in order to study customers’ intentions to repurchase athleisure wear. Additionally, survey questions were developed through a literature review and incorporated into the survey. To determine the suitable sample size for the analysis while considering statistical significance, the study took into account the current total population of South Korea, a confidence level of 95%, and a margin of error of 5%. This calculation determined that a sample size of 400 in this study was well-suited to the data analysis. In a study investigating customer intentions to repurchase athleisure wear, several influential factors were identified. Firstly, the purpose of product use (motivation for wearing) and functionality emerged as critical determinants affecting customer intentions to repurchase. Customers who perceived a clear purpose of use and functional excellence were more inclined to repurchase, underscoring the paramount importance of designing athleisure products with a strong focus on functionality. Nevertheless, it was observed that male and female customers exhibited distinctive levels of satisfaction with the product. Male customers placed greater emphasis on the product’s essential attributes, whereas female customers highlighted the importance of how athleisure wear fits into their everyday lives and its aesthetics. This divergence indicates that male and female customers possess varying preferences when it comes to product attributes. Consequently, it is imperative to devise tailored marketing strategies that align with the distinct priorities and interests of male and female consumers during the sale of athleisure wear products. In summary, this study underscores the significance of comprehending customer behavior and intentions to repurchase within the athleisure market. By prioritizing the articulation of the product’s purpose and enhancing its functionality, businesses operating in the athleisure sector can secure enduring growth and success.

1. Introduction

Modern individuals prioritize their personal lives over work, leading to a gradual shift in lifestyles towards the pursuit of a healthy life through exercise as a form of self-management. These evolving preferences have created an opportunity to design products that offer comfort during physical activities. The growing number of people incorporating sports into their daily routines and the rising demand for comfort in everyday life have intensified the desire for exercise-related products.

Moreover, economic growth has not only enhanced the availability of materials but has also improved the overall quality of living, fostering a lifestyle that encourages diverse sports and leisure activities. Concurrently, the global apparel industry faced unprecedented challenges due to the outbreak of the COVID-19 pandemic, with most segments experiencing a decline in sales due to economic containment measures, social distancing protocols, and waning consumer sentiment.

However, as consumers have increasingly prioritized their health, fitness activities have gained momentum. Within this shifting societal landscape, athleisure has piqued significant interest. Consumers, whether engaged in exercise or not, have adopted sportswear-style clothing as a means of expressing their individuality, reflecting a change in consumer psychology [1].

“Athleisure” is a portmanteau of “athletic” and “leisure”, denoting casual attire suitable for both exercise and everyday wear. The concept of athleisure has gained significant traction in the fashion world, particularly with the introduction of form-fitting yoga pants [2,3]. Subsequently, athleisure has solidified its position as a prevailing fashion trend in the 21st century [4]. This evolution suggests that athleisure wear, which originated primarily in North America and Europe, seamlessly combines the functionality of sportswear with the fashion-forward elements of traditional apparel.

The athleisure market has experienced substantial growth in recent years, driven by consumers’ growing interest in garments that offer comfort, style, and versatility for both athletic activities and casual wear. Therefore, to ensure the continued growth and competitiveness of companies within this market, it is imperative to grasp customer intentions regarding repurchasing. However, previous studies have shown that there is a lack of differentiated research on customer behavior and the factors that can affect intentions to repurchase for the sustainable growth of the athleisure wear market.

Modern consumers exhibit a penchant for affordable yet fashionable attire [5]. Consequently, the sales of fast fashion brands have been on the rise, particularly among the younger demographic. Nevertheless, by the onset of 2019, fast fashion brands like H&M had accumulated substantial inventories worth trillions of KRW. Faced with the risk of transitioning from maturity to decline, these brands required innovative strategies to embrace new changes and sustain their market presence.

These shifts in the fashion market have resulted in exponential growth within the athleisure apparel market, even as other segments of the apparel industry have experienced stagnant growth [6].

The sporting goods industry has experienced substantial growth in recent years and is poised to maintain this trajectory, thanks to the increasing health consciousness of consumers and their growing interest in outdoor lifestyles and athleisure apparel. Sportswear brands and retailers have enjoyed remarkable success in recent times, with a remarkable compound annual growth rate (CAGR) of approximately 13.9% from 2019 to 2020, fueled by the athleisure trend.

Investors have also enjoyed strong performance as the total return to shareholders surged by 20.3% from 2019 to 2021. In contrast, traditional apparel companies experienced a mere 4.5% increase during the same period. This evidence underscores the resilience of sportswear brands in the face of economic downturns, outperforming their traditional apparel counterparts. The global athleisure market size is anticipated to reach USD 330.97 billion by 2022 and grow at a compound annual growth rate (CAGR) of 9.1% from 2023 to 2030 [7]. Notably, athleisure items command a substantial price premium, with leggings frequently selling for over USD 80 and select luxury brands offering leggings priced at USD 400 [8].

Market leaders have consistently forecasted the continued growth of the athleisure apparel market (Kell, 2016). Market analysts have cited research findings indicating that the “athleisure wear market” will expand in tandem with the cultural trend of consumers aspiring to appear “healthy” [9,10].

However, since the onset of COVID-19, health and comfort have gained heightened significance, driven by shifts in the work environment like remote work. As a result, leggings, sweatpants, and loungewear have swiftly emerged as substitutes for traditional professional attire. In terms of clothing usage, sportswear, footwear, and products once exclusively reserved for athletes have garnered widespread popularity, expanding their reach to encompass activities such as yoga, Pilates, and indoor sportswear, making them suitable for everyday wear.

As a result, the athleisure wear market has experienced substantial growth in recent years and is poised to maintain its upward trajectory, driven by the increasing health consciousness of consumers and a burgeoning interest in outdoor lifestyles and athleisure apparel. The growth of athleisure wear aligns with evolving individual lifestyles, characterized by greater leisure time and improved living standards. Additionally, advancements in science and technology, coupled with innovations in textile technology and the textile industry, are further fueling the expansion of high-performance athleisure wear. Despite this remarkable growth, limited research has been conducted on the casual consumption of athleisure wear.

In summary, conducting a study on customer intention to repurchase is crucial for fostering sustainable growth within the athleisure market. Such research can yield invaluable insights for companies striving to maintain a competitive edge in this industry. By gaining a deeper understanding of the factors that influence customer loyalty and repurchasing behavior, companies can make informed, data-driven decisions to enhance their products, services, and marketing strategies.

In this research, the aim was to formulate a sustainable growth strategy for athleisure wear by investigating customers’ intentions to repurchase such apparel. To achieve this objective, this study addressed the following research questions: (1) What constitutes a sustainable growth strategy for athleisure apparel? (2) What are the key factors influencing consumers’ decisions to repurchase athleisure apparel? (3) Does the brand value associated with the distribution channel impact the repurchase of athleisure apparel?

In this research, this paper examined a sample of 400 consumers aged between 20 and 70 years old to investigate the factors influencing satisfaction and repurchase behavior among individuals who have bought athleisure wear. Furthermore, we explored the moderating impact of the distribution channel on the purchase of athleisure apparel.

Athleisure wear, traditionally linked with sports or exercise, has seen a surge in popularity as everyday clothing. In light of these evolving customer preferences, it becomes imperative to manufacture athleisure wear using comfortable, highly elastic materials and incorporate designs suitable for daily wear. Additionally, recognizing the growing consumer inclination towards stylish designs and colors alongside functional features is crucial. Nevertheless, it is essential to acknowledge discernible gender-based preferences in the selection of athleisure wear, underscoring the need for tailored approaches for male and female customers.

2. Theoretical Background

2.1. The Stimulus–Organism–Response (SOR) Model

The SOR (stimulus–organism–response) theory originates from the field of psychology and pertains to the process by which an object’s interaction with the external environment initiates the psychological processing of said object [11]. Put differently, it is a psychological theory that suggests that individuals engage in particular actions in response to stimuli and posits that knowledge, attitudes, and values acquired through life experiences influence behavior. Figure 1 is the conceptual framework of SOR theory.

Abbasi et al., (2023) researched how consumers are influenced by various factors within the physical external environment [13].

Furthermore, it was suggested that a customer’s response in the SOR model encompasses not only factors stemming from external stimuli but also the customer’s own perceptions and psychological influences. Additionally, Mhrabian and Russell (1974) [11] examined customer behavior with a focus on emotional responses, while Nieves-Pavón (2023) [14] extended the SOR theory and applied it to the service sector. Therefore, summarizing these prior studies, it can be inferred that a customer’s response to external stimuli encompasses both physical and emotional aspects, which subsequently impact the customer’s behavior. In this study, grounded in the SOR theory, we developed a research model to analyze the influencing factors of psychological and external environmental elements on consumer satisfaction and repurchase intentions concerning athleisure wear.

2.2. Relationship between Product Selection Attributes and Purchase Satisfaction

An attribute pertains to the intrinsic nature of an object, representing the characteristics a product possesses, and it plays a crucial role in fulfilling consumer needs while communicating the product’s advantages [15].

Hence, consumers make purchasing decisions based on a product’s attributes and, at times, they may also consider optional attributes.

Selective attributes are the criteria employed by consumers to compare and evaluate choices when seeking to fulfill their needs during the product purchase process. This aspect is intimately and directly linked to consumer preferences and their ultimate purchase decisions [16,17].

Moreover, in line with a study conducted by Chacko and Fenich (2000), it was emphasized that companies should meticulously understand the impact of various attributes that consumers respond to and develop marketing strategies accordingly [18]. Given the abundance of products in the market, consumers typically seek justifications for their consumption behavior among these competing offerings.

Furthermore, consumers often seek to justify their choices and analyze the various attributes offered by a product to attain satisfaction. They tend to prioritize certain attributes as more significant. Consequently, selective attributes not only serve as crucial indicators when consumers make purchase decisions regarding products but also play a role in influencing satisfaction after use.

Furthermore, selection attributes also significantly contribute to determining satisfaction or dissatisfaction as they influence the variance between a consumer’s expectations of the purchased product and its perceived performance following the purchase.

Hence, delving into the correlation between these attributes and the intention to repurchase represents a highly meaningful avenue of scholarly investigation. Numerous scholars have undertaken the synthesis of factors influencing repurchase intentions, dedicating efforts to scrutinizing the intricate connections within this context [19,20,21,22].

3. Research Hypotheses and Research Model

3.1. Purpose of Use of the Product (Motivation for Wearing)

Motivation refers to the process by which a person acts to fulfill a need when it arises [23]. According to Kerby’s (1975) study, motivation is not formed independently but is instead established based on desire [24]. Therefore, motivation has been suggested as an important influencing factor in consumers’ purchasing decision-making, serving as both a reason and a driving force behind their behavior.

Furthermore, Bansal and Eiselt (2004) emphasized the significance of motivation as a key variable in comprehending leisure behavior related to travel and sports [25]. Kucukemiroglu (1999) conducted a study that explored a behavioral model, taking into account the concept of lifestyle, encompassing individual characteristics, societal factors, habits, and values [26]. Bourdieu (1984) also investigated the profound connection between an individual’s constitution and their consumption behavior, highlighting how this shapes one’s lifestyle and preferences [27].

Individuals who prioritize a wellness-based lifestyle are more inclined to incorporate athleisure wear into their daily attire compared to those who do not share this lifestyle preference.

These consumer behaviors are associated with the motivation behind purchasing athleisure clothing [28].

Based on the analysis of previous studies, it can be inferred that the importance attributed to physical activity in daily life may significantly influence the consumption of athleisure wear. In essence, a health-conscious lifestyle can be indicative of a particular consumption preference. Therefore, in this study, we formulate the following research hypothesis, building upon previous research:

H1: 

The motivation to use athleisure wear has a positive effect on customer satisfaction.

3.2. Functionality

According to a study conducted by Rhee (2014) [29], when it comes to activewear, consumers prioritize functional factors such as active functionality, waterproofing, and warmth over design. Furthermore, Lee and Kim (2000) [30] suggested that the functionality of sports and leisure products plays a crucial role in the purchasing decision-making process.

Athleisure wear is designed to be worn during sports or leisure activities, making its product function comparable to that of sportswear or outdoor wear [31].

Furthermore, with athleisure wear, the emphasis lies in combining both functionality and fashion [32], making it suitable for everyday wear [33].

As a result, this study deduced that functionality would be a significant factor in the criteria for product selection and satisfaction when it comes to athleisure wear, as supported by the analysis of previous studies. Consequently, based on prior research, the following research hypothesis is established in this study:

H2: 

The functionality of athleisure wear has a positive effect on satisfaction with athleisure wear.

3.3. Dailiness

According to Sung (2012), 65% of consumers opt for products that are suitable for both sporting activities and everyday wear when buying sportswear. This underscores the significance of factoring in the aspect of daily wear during the product development phase [34].

Consequently, companies are now closely examining the preferences of consumers purchasing athleisure wear with the aim of enhancing customer satisfaction and cultivating a robust brand image. They are also crafting products with the dual considerations of design and functionality, taking into account athleisure wear’s suitability for daily wear [35].

Furthermore, the aspect of everyday wear has been studied as a pivotal factor influencing customer satisfaction among athleisure wear buyers [36]. Therefore, this study establishes the following research hypothesis based on prior research:

H3: 

The daily wear of athleisure wear has a positive impact on satisfaction levels with athleisure wear.

3.4. Aesthetics

The appeal of clothing is often juxtaposed with its ability to fulfill particular purposes. There are situations where functional requirements take precedence over aesthetic considerations, while, in other instances, aesthetics outweigh functional concerns [37]. Quinn and Chase (1990) have argued that the objective of specially tailored garments for individuals in unique circumstances is to seamlessly blend function and aesthetics [38]. Consequently, in this study, we establish the following research hypothesis based on prior research:

H4: 

The aesthetics of athleisure wear have a positive impact on satisfaction levels with athleisure wear.

3.5. Scarcity

This paper defines the expectation of scarcity as consumers’ belief that a specific product is likely to be in short supply.

Previous research has explored various types of consumer expectations and their impacts on judgment and decision-making. For instance, the satisfaction literature has concentrated on performance expectations and their influence on satisfaction through an expectancy–disconfirmation process [39,40]. Therefore, in this study, this paper establishes the following research hypothesis based on prior research:

H5: 

The scarcity of athleisure wear has a positive impact on satisfaction levels with athleisure wear.

3.6. Distribution Channel Brand Value

Kim and Hwang (2013) conducted a study examining the influence of online shopping, a familiar concept for consumers, on purchasing behavior. Their findings revealed that the convenience of online shopping, facilitated by reliable distribution channels, significantly impacts consumers’ purchase intentions [41].

Similarly, Han et al. (2013) demonstrated that consumer satisfaction with distribution channels positively correlates with their purchasing intentions [42]. Therefore, in this study, this paper formulates the following research hypothesis, drawing from prior research:

H6: 

In the relationship between customer satisfaction and intentions to repurchase, the brand value of the distribution channel positively moderates this relationship.

3.7. Satisfaction and Intention to Repurchase

Early studies on consumer behavior explored the connection between repurchase behavior and satisfaction, but this association is not straightforward. Vakulenko (2022) observed positive correlations between consumer satisfaction and consumer retention [43]. Wen et al., (2011) discovered that satisfaction positively influenced intentions to repurchase online [44]. Olson (2002), however, revealed that despite the common assumption that satisfaction is linked to repurchase intentions, few empirical studies have established a clear connection between satisfaction and actual repurchase behavior [45]. Kamakura (2001) pointed out the challenge of establishing a direct link between satisfaction assessment and repurchase behavior for many organizations [46]. Furthermore, the satisfaction–repurchase relationship can be influenced by various consumer characteristics. Even when satisfaction ratings are equal, repurchase behavior can significantly differ due to variations in consumer age, education, marital status, gender, and residential area [46].

Additionally, it was observed that satisfaction with sports clothing had a significant impact on consumers’ repurchase intentions [47].

Therefore, in this study, this paper formulates the following research hypothesis based on prior research:

H7: 

Satisfaction has a positive effect on consumers’ intentions to repurchase.

3.8. Research Model

Previous research analyses served as the foundation for the research model and its components (Figure 2). To investigate the experiences of consumers who use the same brand of athleisure wear, the research model was constructed based on research factors.

However, in this study, a gender-based approach was employed to examine the research model of athleisure wear, taking into consideration the unique characteristics of male and female consumers. Such an approach is commonly utilized to gain insights into the distinct design and fit requirements of each gender, which, in turn, informs better product development and marketing strategies tailored to their specific needs and preferences.

4. Research Method

4.1. Sample Size for Structural Equation Models Formula

In this study, the structural equation modeling (SEM) analysis method was employed to analyze the sample size for structural equation models. This study determined the necessary sample size for the analysis while considering the statistical significance level of the specified SEM. The calculation of the sample size followed the method outlined by Cohen (2013) and Westland (2010) [48,49]. Equations (1)–(3) were utilized to compute a priori sample sizes for structural equation models.

Error function:

$$\mathrm{e}rf\left(\chi \right)=\frac{2}{\sqrt{\pi }}{{\displaystyle \int }}_0^x{\mathrm{e}}^{-t^2}\mathrm{d}t$$

(1)

Lower bound sample size for a structural equation model:

n = max (n1, n2)

where

$$\begin{gathered} n1 =[50{(\frac{j}{k})}^2-450\left(\frac{j}{k}\right)+1100] \\ n2=\left[\frac{1}{2H}\left(\left.A\left(\frac{\pi }{6}\right.-B+D\right)+H+ \\ \sqrt{{\left(A\left(\frac{\pi }{6}-B+D\right)+H\right)}^2+4AH\left(\frac{\pi }{6}+\sqrt{A}+2B-C-2D\right)}\right) \right] \end{gathered}$$

(2)

• A = 1 − $\rho$2;
• B = $\rho$arcsin$(\frac{\rho }{2})$;
• C = $\rho$arcsin$\left(\rho \right)$;
• D =$\frac{A}{\sqrt{3-A}}$;
• H =${\left(\frac{\delta }{Z_{1-\alpha /2}-Z_{1-\beta }}\right)}^2$

where j is the number of observed variables, k is the number of latent variables, ρ is the estimated Gini correlation for a bivariate normal random vector, δ is the anticipated effect size, α is the Sidak-corrected Type I error rate, β is the Type II error rate, and z is a standard normal score.

Normal distribution cumulative distribution function:

$$\mathrm{F}\left(x; \mu , {\sigma }^2\right)=\frac{1}{2}\left[1+\mathrm{erf}(\frac{x-\mu }{\sigma \sqrt{2}})\right]$$

(3)

where µ is the mean, σ is the standard deviation, and erf is the error function. The study model used had 8 latent variables and 28 observation variables. Therefore, at least 138 samples were required, considering a 95% significance level.

4.2. Data Collection

To analyze the research model, this study gathered data on intentions to repurchase from customers residing in South Korea. Questionnaires were distributed to 400 individuals and their responses were collected and analyzed to assess the hypotheses. The investigation included 400 customers (n = 400) who had repurchased athleisure wear within the past 6 months. Respondents to the survey were recruited through communities specializing in athleisure wear and data were collected through an online survey. Survey data were collected online for 20 days from 10 August to 29 August 2023. Coffee coupons were provided to respondents who participated in the survey. This study aimed to test the research hypotheses and address the research questions using a questionnaire as its research instrument. The items for each construct were sourced from existing literature. All items were assessed using a 5-point Likert scale, with 1 indicating “strongly disagree” and 5 indicating “strongly agree”. To determine the suitable sample size for the analysis while considering statistical significance, this study took into account the current total population of South Korea, a confidence level of 95%, and a margin of error of 5%. This calculation determined that a sample size of 100 individuals would be appropriate. Therefore, the sample size of 400 (n = 400) utilized in this study was well-suited to the data analysis.

4.3. Measurement

This study examined customer behavior by utilizing validated measurement items extracted from previous research analyses. The findings have been summarized in

Table 1. Measurement items.

Construct	Measurement Items	Related Studies
Purpose of Use of the Product (Motivation for Wearing)	I enjoy learning new ways to exercise. I exercise to feel refreshed after exercise. I exercise constantly because exercise is a habit.	[50,51]
Functionality	I check whether the athleisure wear I’m purchasing has quick sweat absorption and fast drying. I check whether the athleisure wear I’m purchasing is easy to manage or wash. I check if the athleisure clothing I purchase is durable. I check if the quality of the athleisure wear I am purchasing is good.	[52,53,54]
Dailies	When it comes to choosing athleisure wear, it is important that it can be used for daily wear. When it comes to choosing athleisure wear, it is important that it can be used for daily wear.	[35,54]
Aesthetics	When choosing athleisure clothing, design is important. Color is important when it comes to choosing athleisure wear. In choosing athleisure wear, it is important to express your beauty and sophistication. When it comes to choosing athleisure wear, fit is important.	[37,38,53]
Product Scarcity	I want to immediately buy clothing products that are about to be out of stock. When I see a deadline message, I feel compelled to buy. I want to purchase clothing products in limited quantities. I want to purchase athleisure wear when product types are limited.	[50]
Customer Satisfaction	I am satisfied with the athleisure wear I purchased. I am satisfied with the quality of the athleisure wear I purchased. The athleisure wear I bought lives up to my expectations. The more I wear the athleisure wear I purchased, the more I feel that I have made a good purchase. I will recommend the athleisure wear I bought to others.	[47,54,55,56]
Brand Value of Distribution Channel	The online shopping mall I am using is a well-known company. The online shopping mall I use is an authoritative company. The online shopping mall I am using is a company that customers use frequently.	[57]
Intention to Repurchase	I am willing to pay a premium price to repurchase the brand of athleisure clothing I am currently wearing. I plan to continue to purchase athleisure wear from the same brand in the future. I would recommend the brand of athleisure wear I am using to others.	[52,56,57,58]

.

5. Research Results

5.1. General Characteristics of the Survey Respondents

In this study, the valid sample consisted of 400 respondents, evenly distributed between males (51.2%) and females (48.8%). Specifically, there were 207 males (45%) and 253 females (55%). Concerning age distribution, 25.3% were aged between 20 and 29, 33.5% were aged between 30 and 39, 25.8% were aged between 40 and 49, and 15.5% were aged 50 or older.

Table 2. Analysis of survey respondents.

		All	Gender
			Male	Female
Age	20–29	101 (25.3%)	44 (21.5%)	57 (29.2%)
	30–39	134 (35.5%)	57 (27.8%)	77 (39.5%)
	40–49	103 (25.8%)	60 (29.3%)	43 (22.1%)
	Over 50	62 (15.5%)	44 (21.5%)	18 (9.2%)
Total		400 (100.0%)	205 (100.0%)	195 (100.0%)

presents the survey participants’ characteristics, elucidating the findings.

5.2. Descriptive Statistics

In this study,

Table 3. Descriptive statistics.

	N	Minimum	Maximum	Mean	Std. Deviation	Variance
q11	400	1	5	3.00	1.004	1.008
q12	400	1	5	3.69	0.914	0.836
q17	400	1	5	3.26	1.033	1.066
q18	400	1	5	3.78	0.816	0.665
q19	400	1	5	3.52	0.867	0.751
q20	400	1	5	3.96	0.794	0.630
q23	400	1	5	4.01	0.764	0.584
q24	400	2	5	4.04	0.634	0.402
q25	400	2	5	4.11	0.694	0.482
q26	400	1	5	4.03	0.711	0.506
q27	400	1	5	3.90	0.761	0.579
q29	400	1	5	3.59	0.851	0.724
q30	400	1	5	4.12	0.724	0.524
q40	400	1	5	2.81	1.128	1.272
q41	400	1	5	2.80	1.072	1.149
q42	400	1	5	2.92	1.053	1.108
q43	400	1	5	2.98	1.040	1.082
q44	400	2	5	3.80	0.598	0.357
q45	400	2	5	3.80	0.607	0.368
q46	400	1	5	3.72	0.660	0.435
q49	400	2	5	3.71	0.635	0.403
q50	400	1	5	3.60	0.722	0.521
q51	400	1	5	2.98	0.969	0.940
q52	400	1	5	3.60	0.735	0.541
q53	400	1	5	3.54	0.735	0.540
q66	400	1	5	3.92	0.776	0.602
q67	400	1	5	3.63	0.819	0.670
q68	400	2	5	3.93	0.752	0.566
Valid N (listwise)	400

displays the descriptive statistics of the survey results. Table 3 provides an overview of the characteristics of the survey participants, consisting of both male (51.2%) and female (48.8%) respondents.

Table 4. Descriptive statistics of latent variables (male and female).

Latent Variable	Mean				Std. Deviation Statistic
	Statistic		Std. Error
	Male	Female	Male	Female	Male	Female
Purpose of Use of the Product (Motivation for Wearing)	3.3951	3.2359	0.05208	0.05948	0.74571	0.83052
Functionality	3.9707	4.0910	0.03997	0.04087	0.57234	0.57075
Dailiness	3.7000	3.6051	0.04811	0.05931	0.68885	0.82828
Aesthetics	3.8415	3.9821	0.03953	0.04195	0.56598	0.58575
Scarcity	2.8390	2.9154	0.06486	0.06898	0.92868	0.96319
Customer Satisfaction	3.6849	3.7713	0.03424	0.03553	0.49031	0.49617
Customer Satisfaction and Brand Value of Distribution Channel (Moderator)	14.8515	15.9216	0.24203	0.23416	3.46530	3.26982
Intention to Repurchase	3.3496	3.4017	0.04695	0.04348	0.67216	0.60723

presents the arithmetic averages of the latent variables within the study model. It shows the descriptive statistics of the latent variables for the overall customer group who responded to the survey.

5.3. Reliability and Validation of Factor Analysis

Table 5. Squared multiple correlations.

	Estimate
Latent Variable	Male	Female
Customer Satisfaction	0.59	0.495
Intention to Repurchase	0.656	0.8
q53	0.552	0.684
q52	0.477	0.494
q51	0.295	0.472
q50	0.451	0.533
q49	0.413	0.624
q46	0.472	0.449
q45	0.484	0.48
q44	0.373	0.443

displays eight latent variables representing the properties of observed variables alongside forty observed variables. These observed variables have been grouped based on the shared characteristics of the underlying factors.

5.4. Squared Multiple Correlations

Descriptive statistics from the survey were examined to calculate the means and standard deviations of the responses, utilizing AMOS 24.0. Furthermore, this paper explored the relationships between variables and observed variables through squared multiple correlations analysis (SMC). SMC typically quantifies the proportion of variance in a variable that is accounted for by its predictors [59]. In SEM, SMC values are analogous to R-squared values in regression analysis [60]. Additionally, to assess the causal relationships between variables, path coefficients were determined with consideration of their significance levels. These coefficients were then measured based on the analysis of the research model and the structural equation model.

The validity of the survey questionnaire in this study was assessed by analyzing the average variance extracted (AVE) and construct reliability (CR). To ensure the questionnaire’s suitability for statistical analysis, several criteria were considered: CR for each item should be at least 1.95, standardized regression weights should be a minimum of 0.5, AVE should be at least 0.5, and the constitutive reliability of the latent variables should be at least 0.7. The results of this analysis are presented in

Table 6. Validation of survey questionnaire (male).

Latent Variable	Variable Number	Estimate	SE	CR	Sig.	Standardized Regression Weights	AVE	Construct Reliability
Purpose of Use of the Product (Motivation for Wearing)	Q17	1.000				0.663	0.501	0.750
	Q12	1.042	0.157	6.647	***	0.72
	Q11	0.927	0.141	6.593	***	0.659
Functionality	Q25	1.000				0.744	0.639	0.876
	Q24	0.691	0.09	7.651	***	0.605
	Q23	0.989	0.115	8.633	***	0.73
	Q20	0.989	0.115	8.633	***	0.693
Dailiness	Q18	1.000				0.981	0.721	0.828
	Q19	0.587	0.338	1.736	0.083	0.559
Aesthetics	Q30	1.000				0.734	0.529	0.816
	Q29	0.898	0.143	6.291	***	0.569
	Q27	0.773	0.127	6.08	***	0.543
	Q26	0.876	0.127	6.872	***	0.671
Scarcity	Q43	1.000				0.804	0.688	0.898
	Q42	1.111	0.08	13.91	***	0.861
	Q41	1.092	0.083	13.087	***	0.822
	Q40	1.195	0.085	14.134	***	0.873
Customer Satisfaction	Q44	1.000				0.611	0.627	0.893
	Q45	0.905	0.129	7.036	***	0.62
	Q46	1.051	0.151	6.956	***	0.61
	Q49	0.958	0.133	7.228	***	0.643
	Q50	1.262	0.169	7.456	***	0.671
Intention to Repurchase	Q51	1.000				0.543	0.517	0.759
	Q52	0.976	0.151	6.45	***	0.69
	Q53	1.011	0.152	6.631	***	0.743

*** p-value < 0.01.

and

Table 7. Validation of survey questionnaire (female).

Latent Variable	Variable Number	Estimate	SE	CR	Sig.	Standardized Regression Weights	AVE	Construct Reliability
Purpose of Use of the Product (Motivation for Wearing)	Q17	1.000				0.745	0.522	0.764
	Q12	0.830	0.122	6.816	***	0.744
	Q11	0.800	0.123	6.515	***	0.596
Functionality	Q25	1.000				0.744	0.705	0.905
	Q24	1.058	0.109	9.700	***	0.776
	Q23	1.078	0.131	8.248	***	0.647
	Q20	1.335	0.137	9.766	***	0.784
Dailiness	Q18	1.000				0.791	0.721	0.838
	Q19	1.115	0.294	3.789	***	0.853
Aesthetics	Q30	1.000				0.671	0.625	0.869
	Q29	1.105	0.159	6.944	***	0.607
	Q27	1.240	0.153	6.944	***	0.770
	Q26	1.129	0.141	7.981	***	0.737
Scarcity	Q43	1.000				0.768	0.665	0.888
	Q42	1.043	0.088	11.886	***	0.810
	Q41	1.079	0.087	12.428	***	0.841
	Q40	1.275	0.094	13.554	***	0.919
Customer Satisfaction	Q44	1.000				0.666	0.723	0.928
	Q45	1.098	0.145	7.550	***	0.617
	Q46	1.179	0.145	8.116	***	0.670
	Q49	1.470	0.158	9.275	***	0.790
	Q50	1.366	0.157	8.714	***	0.730
Intention to Repurchase	Q51	1.000				0.415	0.563	0.783
	Q52	0.830	0.122	6.816	***	0.703
	Q53	0.800	0.123	6.515	***	0.827

*** p-value < 0.01.

, demonstrating that all survey questionnaires in this study met the criteria for validity.

5.5. Discriminant Validity and Convergent Validity

Additionally, in this study, the discriminant validity of the research model was analyzed as shown in

Table 8. Discriminant validity (male customer).

		Purpose of Use of the Product (Motivation for Wearing)	Functionality	Dailiness	Aesthetics	Scarcity	Customer Satisfaction	Intention to Repurchase
Purpose of Use of the Product (Motivation for Wearing)	Pearson Correlation	1	0.321 **	0.241 **	0.273 **	0.364 **	0.388 **	0.509 **
	Sig. (2-tailed)		0.000	0.000	0.000	0.000	0.000	0.000
	N	205	205	205	205	205	205	205
Functionality	Pearson Correlation	0.103	1	0.290 **	0.480 **	0.191 **	0.555 **	0.355 **
	Sig. (2-tailed)	0.000		0.000	0.000	0.006	0.000	0.000
	N	205	205	205	205	205	205	205
Dailiness	Pearson Correlation	0.058	0.084	1	0.328 **	0.336 **	0.154 **	0.214 **
	Sig. (2-tailed)	0.000	0.000		0.000	0.000	0.007	0.002
	N	205	205	205	205	205	205	205
Aesthetics	Pearson Correlation	0.076	0.230	0.108	1	0.342 **	0.378 **	0.372 **
	Sig. (2-tailed)	0.000	0.000	0.000		0.000	0.000	0.000
	N	205	205	205	205	205	205	205
Scarcity	Pearson Correlation	0.132	0.036	0.113	0.117	1	0.369 **	0.505 **
	Sig. (2-tailed)	0.000	0.006	0.000	0.000		0.000	0.000
	N	205	205	205	205	205	205	205
Customer Satisfaction	Pearson Correlation	0.150	0.308	0.024	0.142	0.136	1	0.548 **
	Sig. (2-tailed)	0.000	0.000	0.027	0.000	0.000		0.000
	N	205	205	205	205	205	205	205
Intention to Repurchase	Pearson Correlation	0.259	0.126	0.046	0.138	0.255	0.300	1
	Sig. (2-tailed)	0.000	0.000	0.002	0.000	0.000	0.000
	N	205	205	205	205	205	205	205

** Correlation is significant at the 0.01 level (2-tailed).

and

Table 9. Discriminant validity (female customer).

		Purpose of Use of the Product (Motivation for Wearing)	Functionality	Dailiness	Aesthetics	Scarcity	Customer Satisfaction	Intention to Repurchase
Purpose of Use of the Product (Motivation for Wearing)	Pearson Correlation	1	0.312 **	0.165 **	0.205 **	0.171 **	0.306 **	0.374 **
	Sig. (2-tailed)		0.000	0.000	0.004	0.000	0.000	0.000
	N	195	195	195	195	195	195	195
Functionality	Pearson Correlation	0.097	1	0.296 **	0.271 **	0.158 **	0.446 **	0.374 **
	Sig. (2-tailed)	0.000		0.000	0.000	0.028	0.000	0.000
	N	195	195	195	195	195	195	195
Dailiness	Pearson Correlation	0.027	0.088	1	0.329 **	0.281 **	0.361 **	0.327 **
	Sig. (2-tailed)	0.021	0.000		0.000	0.000	0.000	0.000
	N	195	195	195	195	195	195	195
Aesthetics	Pearson Correlation	0.042	0.073	0.108	1	0.222 **	0.302 **	0.322 **
	Sig. (2-tailed)	0.004	0.000	0.000		0.002	0.000	0.000
	N	195	195	195	195	195	195	195
Scarcity	Pearson Correlation	0.029	0.025	0.079	0.049	1	0.114 **	0.335 **
	Sig. (2-tailed)	0.017	0.028	0.000	0.002		0.001	0.000
	N	195	195	195	195	195	195	195
Customer Satisfaction	Pearson Correlation	0.094	0.199	0.130	0.091	0.013	1	0.691 **
	Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.112		0.000
	N	195	195	195	195	195	195	195
Intention to Repurchase	Pearson Correlation	0.140	0.140	0.107	0.104	0.112	0.477	1
	Sig. (2-tailed)	0.000	0.000	0.000	0.000	0.000	0.000
	N	195	195	195	195	195	195	195

** Correlation is significant at the 0.01 level (2-tailed).

. In other words, to verify discriminant validity, the correlation between latent variables was calculated, and it was confirmed that the square value of the correlation was smaller than the AVE value. Through this analysis, it has been confirmed that the research model proposed in this study exhibited discriminant validity. Table 8 presents the discriminant validity analysis of the male customer research model, while Table 9 presents the results of the discriminant validity analysis of the female customer research model. The findings indicate that the discriminant validity of all research models was substantiated through the analysis.

Additionally, this paper analyzed the degree of consistency of the observed variables that measured the latent variables. The convergent validity of the research models in this paper is examined in

Table 10. Convergent validity (male customer).

Purpose of Use of the Product (Motivation for Wearing)	→	q17	0.75
	→	q12	0.74
	→	q11	0.60
Functionality	→	q25	0.74
	→	q24	0.78
	→	q23	0.65
	→	q20	0.78
Dailiness	→	q18	0.79
	→	q19	0.85
Aesthetics	→	q30	0.67
	→	q29	0.61
	→	q27	0.77
	→	q26	0.74
Scarcity	→	q43	0.77
	→	q42	0.81
	→	q41	0.84
	→	q40	0.92
Customer Satisfaction	→	q44	0.67
	→	q45	0.62
	→	q46	0.67
	→	q49	0.79
	→	q50	0.73
Intention to Repurchase	→	q51	0.52
	→	q52	0.70
	→	q53	0.83

and

Table 11. Convergent validity (female customer).

Purpose of Use of the Product (Motivation for Wearing)	→	q17	0.745
	→	q12	0.744
	→	q11	0.596
Functionality	→	q25	0.744
	→	q24	0.776
	→	q23	0.647
	→	q20	0.784
Dailiness	→	q18	0.791
	→	q19	0.853
Aesthetics	→	q30	0.671
	→	q29	0.607
	→	q27	0.770
	→	q26	0.737
Scarcity	→	q43	0.768
	→	q42	0.810
	→	q41	0.841
	→	q40	0.919
Customer Satisfaction	→	q44	0.666
	→	q45	0.617
	→	q46	0.670
	→	q49	0.790
	→	q50	0.730
Intention to Repurchase	→	q51	0.515
	→	q52	0.703
	→	q53	0.827

; it was found to be valid for both models.

5.6. Research Model Fit

The criterion employed to evaluate the suitability of the research model was the fit index, a widely adopted metric in the social sciences.

Table 12. Analysis of the fit of the research model.

Model		NFI	GFI	AGFI	CFI	χ2/df	RMESA
Reference value		≥0.9	≥0.9	≥0.8	≥0.9	≤3.0	≤0.100
Measurement value	Male	0.913	0.939	0.896	0.893	2.468	Measurement value
	Female	0.933	0.940	0.897	0.913	2.373	0.045

presents the outcomes of the analysis regarding the fit of the research model. The table also includes a list of prevalent fit indices commonly utilized in the information systems literature, as illustrated in Table 12 [61,62].

For this study, the research model and hypotheses were analyzed through statistical analysis and the results are presented in

Table 13. Research model analysis (male).

Latent Variable		Standardized Regression Weight	Regression Weights	SE	CR	Sig.	Research Hypothesis
Purpose of Use of the Product (Motivation for Wearing)	Customer Satisfaction	0.322	0.193	0.050	3.826	***	H1	Accept
Functionality		0.575	0.395	0.066	5.971	***	H2	Accept
Dailiness		0.157	0.078	0.055	1.426	0.154	H3	Reject
Aesthetics		0.127	0.090	0.051	1.751	0.080	H4	Reject
Product Scarcity		0.340	0.163	0.035	4.628	***	H5	Accept
Customer Satisfaction × Brand Value of Distribution Channel (Moderate)	Intention to Repurchase	0.114	0.113	0.070	1.627	0.104	H6	Reject
Customer Satisfaction	Intention to Repurchase	0.802	1.127	0.199	5.657	***	H7	Accept

*** p-value < 0.01.

and

Table 14. Research model analysis (female).

Latent Variable		Standardized Regression Weight	Regression Weights	S.E.	C.R.	Sig.	Research Hypothesis
Purpose of Use of the Product (Motivation for Wearing)	Customer Satisfaction	0.255	0.109	0.036	3.007	0.003	H1	Accept
Functionality		0.364	0.271	0.063	4.295	***	H2	Accept
Dailiness		0.264	0.129	0.041	3.126	0.002	H3	Accept
Aesthetics		0.167	0.124	0.059	2.107	0.035	H4	Accept
Product Scarcity		0.007	0.003	0.030	0.102	0.919	H5	Reject
Customer Satisfaction × Brand Value of Distribution Channel (Moderate)	Intention to Repurchase	0.035	0.037	0.063	0.588	0.557	H6	Reject
Customer Satisfaction	Intention to Repurchase	0.894	0.980	0.196	4.987	***	H7	Accept

*** p-value < 0.01.

.

6. Research Hypothesis Test (Multi-Group Analysis)

6.1. Analysis of Research Hypothesis (Multi-Group Analysis)

In this study, both the research model and hypotheses were subjected to statistical analysis, with the outcomes detailed in Table 13 and Table 14.

For this study, the research model and hypotheses were examined using statistical analysis, and the findings are presented in Table 13 and Table 14. In this study, customers who repurchased athleisure wear were divided into two groups: male and female customers. The results in Table 13 and Table 14 demonstrate that the reasons for customer satisfaction and repurchase intentions differed between these two groups.

In this paper, the survey participants were categorized into male and female groups. Consequently, the research hypotheses (H1, H2, H5, and H7) were supported in the case of male customers. Male customers investigated the purpose of wearing athleisure clothing, the functional attributes of athleisure apparel, and the uniqueness of products that impact customer satisfaction. Athleisure wear offers distinct functionality and comfort inherent to the product, along with a unique design and style set apart from typical casual clothing.

Furthermore, considering that athleisure wear is predominantly manufactured by sports apparel brands, the brand image and design elements assume significant importance. Consequently, athleisure wear tends to have a limited production volume compared to general clothing, making it potentially challenging to acquire. This scarcity factor contributes to increasing the perceived value of the product among male customers. Nevertheless, male customers did not exhibit a substantial interest in the everyday lifestyle and aesthetic aspects of athleisure wear. They primarily recognized athleisure wear as attire worn for specific activities like exercise rather than considering it suitable for daily wear.

Hence, the functionality of the clothing was examined as a crucial determinant of satisfaction. Additionally, it was determined that the moderating variables related to customer satisfaction and distribution channels did not reach statistical significance levels in the analysis.

Within the female group, it was determined that product scarcity had no discernible impact on customer satisfaction. Additionally, the analysis revealed that the moderating variables related to customer satisfaction and distribution channels did not achieve statistical significance.

Conversely, among female customers, the research hypotheses (H1, H2, H3, H4, and H7) proposed for male customers were validated. Notably, in contrast to their male counterparts, female customers emphasized the significance of daily life and aesthetics as essential factors contributing to customer satisfaction. In particular, the analysis highlighted that female customers exhibit a preference for athleisure wear that combines stylish design with functionality and comfort suitable for daily activities.

6.2. Analysis of Moderate Effect (Multi-Group Analysis)

A distribution channel represents a place where consumers directly interact when acquiring a product, serving as a crucial touchpoint for consumers to become acquainted with and recognize a brand.

Hence, the better the quality of products and services offered by distribution channels and the greater customer satisfaction with the product, the more likely consumers are to have the intention to repurchase.

However, this study revealed that in both groups, the brand associated with the distribution channel did not significantly impact customers’ intentions to repurchase athleisure wear.

7. Discussion

The results of this study provide insights into the influence of athleisure wear customer behavior antecedents on intentions to repurchase athleisure wear.

The findings of this study corroborate previous research demonstrating the positive impact of purchase motivation for athleisure wear and product functionality on customer satisfaction.

Nevertheless, it is noteworthy that the determinants influencing satisfaction diverged between male and female customers.

Unlike previous studies, which did not conduct separate analyses for male and female customers when examining factors influencing customer satisfaction, our study intentionally disaggregated the data by gender.

This methodological approach was employed to furnish nuanced insights into the interplay of factors influencing consumer behavior within distinct gender cohorts.

In this paper, a customer repurchasing behavior model for customers’ intentions to repurchase athleisure wear according to gender is presented as shown below in Figure 3 and Figure 4. Figure 3 is the research model that analyzed the repurchase intentions of male customers in this study and Figure 4 is the research model that analyzed the repurchases intentions of female customers.

According to previous research, athleisure wear has so far focused on functional aspects. In other words, it was developed to be lightweight, warm, and dry sweat well. However, as people’s desires have changed, preferences for products that are casual from design to color and that go well with everyday clothes have begun to increase.

In response to these market demands, companies have recently been producing products that take both design and functionality into consideration, considering the suitability of athleisure wear for everyday wear. To date, athleisure wear has predominantly been marketed as a women’s product. Nevertheless, to broaden market reach, it is imperative to diversify the customer base by encompassing men and exploring diverse product categories aligned with evolving lifestyles and perspectives.

In line with the findings of this study, a distinct variance in preferences for athleisure wear attributes was observed between male and female respondents. This implies the necessity for tailored designs for products catering to each gender. The distinction in design can be attributed to the distinct perceptions that male and female customers hold regarding athleisure wear. For male customers, highlighting the exclusivity of athleisure items becomes crucial to evoke a sense of desire for purchase. The incorporation of unique limited-edition products can underscore the notion that those acquiring the item stand out from others.

On the other hand, it is evident that female customers exhibit a preference for athleisure wear designs seamlessly integrated into everyday styling, as opposed to the predominantly exercise-oriented products currently available. Specifically, women favor athleisure wear featuring timeless silhouettes, vibrant colors that appear attractive and appealing in photographs, and materials with high sensitivity, ensuring comfort. These research findings signify the potential to develop diverse athleisure wear types tailored for time, place, and occasion (TPO). Therefore, expanding the market involves not only widening the target audience but also diversifying product offerings to resonate with consumers and foster a deeper connection with athleisure culture.

Furthermore, this study observed that the brand power of the distribution channel had no impact when customers expressed satisfaction with the product and opted for repurchase.

In other words, customers are unlikely to contemplate repurchasing a product, even if it is available at a renowned department store or a well-known e-commerce site, if they are dissatisfied with its fundamental elements. This analysis suggests that customers prioritize the essential qualities and attributes of athleisure wear over the reputation of the retail venue.

However, a notable limitation of this study is the small sample size of only 400 valid survey subjects. In particular, in order to obtain managerial implications through analysis by gender and age, it was necessary to secure additional consumer data by gender and age. Additionally, these data were collected from consumers residing in Korea. There was a need to secure the versatility of the research model by securing data through surveys targeting consumers in regions where athleisure wear has a high market share in various parts of the world.

Therefore, it is imperative to address these limitations by conducting further investigations with a more substantial sample and exploring customers’ intentions to revisit using diverse survey methods, including questionnaires and interviews. Additionally, it is essential to acknowledge the constraints associated with SEM as a research method in this study.

In other words, latent variables and unmeasured variables, which were not considered during the development of the research model, may necessitate the creation of a more appropriate research model than the one currently employed. Furthermore, potential issues may have arisen due to errors in data measurement and resulting errors in causality. It is worth noting that altering the direction of the causal relationship between latent variables in SEM had a limited impact on the fit of the research model.

7.1. Research Implications

This study examined consumer repurchasing behavior of athleisure wear through the lens of the SOR (stimulus–organism–response) theory. In essence, the research delved into the factors and behavioral patterns influenced by various aspects of the physical external environment on consumers. To achieve this, this study analyzed consumer behavior in relation to the reasons behind product purchases and the factors that influence these choices, subsequently constructing a structural equation model.

Furthermore, this paper segmented product purchasers into two distinct groups, namely, males and females, and conducted a comprehensive analysis of their consumer buying behavior models. These research findings contribute to the development of an enhanced SOR model, offering a systematic understanding of consumer demands encompassing their perceptions, attitudes, behaviors, and purchasing patterns.

7.2. Managerial Implications

This study underscores the importance of accounting for gender differences in the marketing and sale of athleisure wear products as male and female consumers exhibit distinct priorities and interests when it comes to apparel products.

As male customers primarily prioritize functionality and efficiency, it can be effective to highlight technical aspects, practicality, and durability when marketing athleisure wear products to them. Furthermore, underscoring the uniqueness or rarity of athleisure wear items can contribute to boosting brand loyalty among male customers.

Conversely, as female customers predominantly prioritize daily life and aesthetics, it can be advantageous to emphasize the style, design, and comfort aspects of athleisure wear products when targeting this demographic. Additionally, it is crucial to facilitate the integration of athleisure wear into female customers’ everyday attire seamlessly. To achieve this, suggesting methods for coordinating athleisure wear products with daily items in a harmonious fashion can be beneficial.

Hence, it is imperative to formulate a tailored marketing strategy that takes into account the distinct priorities and interests of both male and female consumers when promoting athleisure wear products. Such an approach can elevate brand awareness and exert a positive influence on customers’ purchasing decisions.

8. Conclusions

Athleisure wear is typically associated with sports or exercise, but it has recently gained popularity as everyday attire. Specifically, contemporary individuals who prioritize health and comfort seek clothing that allows them to feel like they are exercising in their daily lives. As evident from the research findings presented in Table 12 and Table 13, consumers place significant value on the functionality of athleisure wear.

However, there are gender-based differences in consumer preferences. Male customers tend to prioritize the purpose of athleisure wear, whereas female customers, in contrast to their male counterparts, place a higher emphasis on its suitability for daily life and aesthetics. Therefore, in response to these distinct customer needs, athleisure wear should be crafted from comfortable, highly elastic materials and feature designs suitable for everyday wear. Moreover, it is crucial to consider launching products with stylish designs and colors alongside functional elements as this trend is gaining traction and is highly favored by consumers. Nevertheless, it is worth noting that there are discernible variations in preferences between male and female customers when it comes to selecting athleisure wear.