Journal of Physical Education and Sport ® (JPES), Vol. 24 (issue 8), Art 222, pp. 2005 - 2016, August 2024
online ISSN: 2247 - 806X; p-ISSN: 2247 – 8051; ISSN - L = 2247 - 8051 © JPES

Original Article
Effects of service quality attributes of public sports facilities
on virtual reality experience among wheelchair users
KYUNG HWAN CHO1
Department of Special Physical Education, Daelim University College, Ansan-si, Gyeonggi-do, REPUBLIC OF
KOREA

1

Published online: August 31, 2024
Accepted for publication : August 15, 2024
DOI:10.7752/jpes.2024.08222
Abstract
This study explores the impact of service quality attributes in public sports facilities on the virtual reality (VR)experiences of wheelchair users, focusing on how these attributes influence user satisfaction and the intention torevisit. As VR technology becomes increasingly integrated into sports facilities, it is essential to understand thespecific needs and preferences of wheelchair users, a demographic often underserved in sports environments. A
survey was administered to 250 wheelchair users who had experienced VR in public sports facilities. The survey
examined their perceptions of tangible elements, such as facility accessibility and equipment, as well as service
quality attributes, including reliability, responsiveness, and staff competence. The data were analyzed to assess
the relationship between these factors and their effect on overall satisfaction and the likelihood of revisiting thefacility.The results reveal that tangible aspects, particularly the accessibility and quality of the physicalenvironment, are significant predictors of revisit intention among wheelchair users. Interestingly, while
reliability and responsiveness were not directly associated with revisit intention, they played a crucial role inshaping overall satisfaction. Satisfaction, in turn, was found to be a strong mediator, significantly influencing theintention to return to the facility. These findings underscore the importance of prioritizing tangible service
quality attributes, such as well-maintained and accessible facilities, to enhance the VR experience for wheelchairusers. Moreover, this study suggests that while intangible service elements like reliability and responsiveness areimportant, their influence on revisit intention is largely indirect, mediated through user satisfaction. Thus, public
sports facilities should focus on improving both the tangible and intangible aspects of service quality to better
serve wheelchair users, thereby enhancing their VR experience and encouraging repeat visits.
Keywords: Service Quality Attributes; Virtual Reality Experience; Wheelchair User Satisfaction; Revisit
Intention; Facility Accessibility
Introduction
Public sports facilities play a crucial role in advancing physical activity and sports participation (Kung& Taylor, 2014). These facilities are designed with accessibility in mind, incorporating modified equipment andspecialized programs to meet the diverse needs of the community (Borgers et al., 2016). The removal of physicaland social barriers within these environments is essential, empowering all individuals to engage in sports andpromoting greater societal integration (Ratten, 2010). In South Korea, where approximately 2.49 million people
live with disabilities, the need for inclusive design in public sports infrastructure is underscored by the mandate
for these individuals to participate in sports to maintain their health (Kang & Kang, 2019). The integration ofvirtual reality (VR) technology in sports represents a significant advancement, offering individuals withdisabilities the opportunity to engage in a broad range of physical activities (Yalon-Chamovitz & Weiss, 2008).
This technological integration not only broadens access, but also creates shared spaces where individuals,
regardless of ability, can interact and bond over common experiences (Benim et al., 2021). The development ofwheelchair sports, initially a post-WWII rehabilitative practice, has evolved into a competitive discipline,
highlighted by the prominence of wheelchair racing in Paralympic sports, covering everything from sprints toendurance events (Laferrier et al., 2012; Fuss, 2009).
This evolution emphasizes the need for continuous innovation in public sports facilities to ensure
inclusivity and adaptability to the needs of all participants. Moreover, to compete effectively with private sports
facilities and achieve high standards, public sports facilities must provide high-quality services to maximize user
satisfaction (Bolton & Drew, 1991; Boulding et al., 1993). Enhancing service quality is critical to increasing
consumer satisfaction, as users evaluate the value they want and how they perceive the value provided by public
sports facilities (Zeithaml et al., 1996). Since service quality is determined by user perceptions, it is vital tomeasure the services provided by public sports facilities based on user evaluations (Parasuraman et al., 1988).
Parasuraman, Zeithaml, and Berry (1985) developed the SERVQUAL model, a tool for evaluating service
quality across five dimensions: tangibles, reliability, assurance, responsiveness, and empathy. Tangibles refer tothe physical appearance of goods; reliability indicates the provider's ability to perform tasks dependably and----------------------------------------------------------------------------------------------------------------------------------2005
Corresponding Author: KYUNG HWAN CHO, E-mail: 2022018@daelim.ac.kr

KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------accurately; assurance reflects the provider's courtesy, trust, and competence; responsiveness measures theprovider's willingness to assist; and empathy assesses the provider's understanding of and attention to consumer
needs. Research using the SERVQUAL model in sports centers has shown significant interest in understanding
and improving the user experience within sports management (Tsitskari et al., 2006). Tsitskari, Tsiotras, andTsiotras (2006) adapted the SERVQUAL model to the sports industry, offering innovative insights into service
quality assessment in sports services. Additionally, Ramezanian et al. (2013) provided specific insights into
perceived service quality within university sports facilities, emphasizing the unique expectations of the academic
sports community. Collectively, these studies highlight the dynamic interplay between service quality, consumer
satisfaction, and loyalty, reinforcing the integral role of the SERVQUAL model in driving continuous
improvement in the sports sector. Public sports facilities must reflect the characteristics and needs of users,
including key aspects such as accessibility, safety, and convenience (Lam et al., 2005). For wheelchair users, it is
crucial that facilities are accessible, with amenities like disabled toilets and showers, and that exercise equipment
and spaces are designed with safety in mind (Calder et al., 2018). Addressing this gap is essential for developing
inclusive service strategies that cater to the needs of all users, including those with mobility impairments,
ensuring equitable access to public sports facilities and the benefits they provide. Therefore, this study examined
the relationship between service quality characteristics, consumer satisfaction, and revisit intention at public
sports facilities with VR sports centers, specifically targeting wheelchair users. The findings from this study are
expected to contribute to identifying improvement strategies for VR sports venues, ensuring that all users,
including those in wheelchairs, have a more satisfactory sports experience.
Material and Methods
Research Model
This study analyzed the effect of service quality attributes of public sports facilities, which operate
virtual experience venues, on the satisfaction and intention to revisit among wheelchair users. Consumer
satisfaction refers to the degree of contentment that a user feels after utilizing a service or product (Oliver, 1999).
Bitner (1990) prioritized consumer satisfaction over service quality, asserting that behavioral intentions follow
accordingly. Taylor and Baker (1994) concluded that consumer satisfaction affects behavioral intentions,particularly noting that the interaction between these two variables has a more significant impact. Consumer
satisfaction is a critical component in the operation of sports facilities, acting as a catalyst for repeat patronage
and positive word-of-mouth (Paschalidou et al., 2023). Thus, high satisfaction levels correlate strongly withincreased user loyalty, shaping the facility's reputation and long-term success (Matsuoka et al., 2003).
Understanding and fulfilling consumer expectations are essential for the strategic management and sustainable
operation of sports facilities (Schwarz et al., 2016). Service quality attributes have the potential to influence
consumer satisfaction significantly. Tsitskari et al. (2006) demonstrated that service quality dimensions withinsports services are significant predictors of overall customer satisfaction, reinforcing the importance of service
quality in sports facility management. In the realm of virtual golf, factors such as the responsiveness of staff, thereliability of technology, and the tangibility of the virtual environment were shown to shape consumers'
perceptions of value and satisfaction, ultimately guiding their future behavioral intentions and loyalty to theservice (Choi et al., 2018). Therefore, this study proposes the following hypothesis.
H1: The service quality attributes of public sports facilities operating virtual experience sports venues shallpositively affect the consumer satisfaction of wheelchair users.
Revisit intention refers to the extent to which a user is willing to re-engage with a specific service or
facility. Oliver (1997) viewed the intention to revisit as one element constituting a subdimension of consumer
loyalty, defining it as the desire to continue visiting or purchasing favored products or services. Additionally,
Oliver (1999) described the intention to revisit as a behavioral intention associated with loyalty, suggesting thatsatisfied consumers are likely to visit frequently and make numerous purchases. Furthermore, Brady and Cronin(2001) clarified that revisit intention is the likelihood of a consumer being satisfied with a provided service andusing it in the future. Revisit intention reflects an overall attitude towards the experience, involving theevaluation of the overall impression of that experience, meaning that consumers intend to revisit based on theirpast experiences (Stylos et al., 2016). Service quality attributes are acknowledged to influence revisit intentions,as affirmed by studies highlighting the importance of tangibility, reliability, responsiveness, assurance, andempathy in shaping consumer attitudes toward future engagements with service providers (Parasuraman et al.,1988). Enhanced service quality leads to greater customer satisfaction, which in turn impacts the likelihood of
consumers returning to the service significantly (Zeithaml et al., 1996). Consumer satisfaction has been shown
empirically to have a positive influence on revisit intentions. Oliver (1997) demonstrated that the level ofsatisfaction consumers feel after a service encounter predicts their willingness to return to the service provider
significantly, suggesting that satisfaction serves as a determinant of repeat patronage. Several studies haveinvestigated the relationship between customer satisfaction and revisit intention in sports facilities. For instance,
Kim and Kim (1995) found that customer satisfaction was a significant predictor of revisit intention in fitness
clubs. Similarly, Theodorakis et al. (2014) confirmed that both service quality and customer satisfaction were2006---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.ro

KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------key determinants of customers' intentions to revisit a sports center. Additionally, in exploring the dynamics
between service quality and user behavior, Heskett et al. (1994) underscored the pivotal role of consumer
satisfaction, identifying it as a moderating variable that influences the impact of service quality on behavioral
intentions. Therefore, this study proposes the following hypotheses.
H2: The service quality attributes of public sports facilities operating virtual experience sports venues shallpositively affect the revisit intention of wheelchair users.
H3: Consumer satisfaction shall positively affect the intention to revisit.
H4: Consumer satisfaction shall have a mediating effect in the relationship between service quality attributes
and revisit intention.
Therefore, the research model investigates the relationship between the service quality of public sports
facilities and both consumer satisfaction and revisit intention among adult wheelchair users. The research model
depicted in Figure 1 illustrates the hypothesized relationships between service quality attributes, consumer
satisfaction, and revisit intention in the context of public sports facilities that operate virtual experience sports
venues for wheelchair users. The proposed research model indicates a flow from the quality of service provided
by the public sports facilities to the satisfaction of the users, which in turn influences their intention to revisit thefacility. This model underscores the importance of service quality in both satisfying consumers and encouraging
repeat visits, particularly in the specialized context of virtual experience sports venues for wheelchair users.

Figure 1. Proposed Research Model
Research Instruments
Table 1 details the composition and sources of research instruments used in the study, categorizing themunder various variables and noting the number of items and their academic sources. Service quality attributes are
divided into five subcategories: Tangibles, Reliability, Responsiveness, Assurance, and Empathy, eachcomprising 6 items. The sources for Tangibles include Grönroos (1984) and Parasuraman et al. (1991).
Consumer satisfaction is assessed with 3 items, sourced from Cronin and Taylor (1992). Revisit intention isanother variable with 3 items, for which the sources are Bitner (1990) and Maxham (2001). Additionally, thetable includes Demographic characteristics as a variable with 4 items. In total, the research instruments consist of
40 items. To measure the variables, a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree) was used.
Table 1. Composition and sources of research instruments
Variables
Service
attributes

Consumer satisfaction
Revisit intention

Number of Items
6
6
6
6
6
3
3

Demographic characteristics
Total

4
40

qualityTangibles
Reliability
Responsiveness
Assurance
Empathy

Sources
Gronroos(1984),
Parasuraman et al. [38]

Cronin & Taylor [39]Bitner [26],Maxham [40](-)

Subjects and Data Collection
This study was conducted over approximately two months, from February 1, 2024, to March 31, 2024,
targeting 250 wheelchair users with experience in VR sports (such as racing and ball games) at five public sports
facilities with VR sports centers located in the metropolitan area. Specifically, the researchers and research----------------------------------------------------------------------------------------------------------------------------2007
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------assistants visited disabled individuals to explain the purpose and rationale of the research and distributed
questionnaires to those who agreed voluntarily to participate in the survey. The survey method involved selfadministered questionnaires, where the respondents filled in their responses and returned the forms on the spot.
Additionally, this study adhered to the Declaration of Helsinki, ensuring that participants were fully informed
about the research and consent was obtained through written consent forms. After excluding 15 questionnaires
with inadequate responses, a total of 235 questionnaires were used for the final analysis.
Data Analysis
The collected data were statistically analyzed using the IBM SPSS 22.0 program (IBMCorp., Armonk,
NY,USA). First, frequency analysis and descriptive statistics were conducted to understand the generalcharacteristics of the respondents. Second, exploratory factor analysis and the calculation of Cronbach's α
coefficient were performed to verify the validity and reliability of the research instruments. Third, correlation
analysis was employed to explore the relationships between variables. Fourth, multiple regression analysis was
utilized for hypothesis testing. Lastly, the significance level for the analysis was set at α=.05.
Results
General Characteristics
Table 2 presents the demographic characteristics of participants in the research. A disproportionate
gender representation is observed, with males constituting a substantial 83.8% (197 subjects) of the sample,
while females account for only 16.2% (38 subjects). The age distribution skews younger with the largest cohorts
being those between 20-29 years and 30-39 years, which constitute 43.3% (102 subjects) and 36.5% (86subjects) of the population, respectively. The groups aged 40-49 and those 50 years or older are less represented,
comprising 14.8% (35 subjects) and 5.1% (12 subjects), respectively. Income brackets reveal that a majority,
51.5% (121 subjects), report earnings within the $2,000-4,000 range, 32.4% (76 subjects) earn above $4,000, andthe remaining 16.1% (38 subjects) earn $2,000 or below. Duration of wheelchair use indicates 45.9% (108subjects) have utilized a wheelchair for a decade or less, 30.6% (72 subjects) for a period between 10-20 years,
and 23.4% (55 subjects) have exceeded two decades of usage.
Table 2. Demographic Characteristics
Category
GenderAge(Year)Monthly(Dollars)
Wheelchair(Year)
Total

Incomeuse

periodMale
Female
20-29
30-39
40-49
≥50
≤ 20002000-4000
>4000
≤ 10
10-20
>20

Frequency
197
38
102
86
35
12
38
121
76
108
72
55
235

Percent
83.8
16.2
43.3
36.5
14.8
5.1
16.1
51.5
32.4
45.9
30.6
23.4
100

Table 3 provides descriptive statistics for various service quality categories in public sports facilities,
including tangibles, reliability, responsiveness, assurance, empathy, consumer satisfaction, and revisit intention.
For Tangibles, the facilities offering virtual reality sports experiences are considered modern, with a mean of
3.583, and the appropriateness of facilities has a mean of 3.527. Accessibility aspects like transportation andparking have a lower mean of 3.461, suggesting room for improvement. However, the neat appearance of
employees scores higher at 3.847, with the cleanliness of places and equipment close behind at 3.806. Thus, theoverall average for Tangibles is 3.647± .634. Under Reliability, with an overall mean of 3.746±.812, facilities
are seen as dependable in delivering promised services, rating 3.762 for this item. Services provided within a set
time are rated at 3.807, indicating timeliness. Quick problem resolution has a lower rating of 3.601, suggesting a
potential area for improvement. Confidence in using the facilities is captured at 3.616, while security of personal
consumer information is notably higher at 3.807. Trust in facility staff is also strong with a score of 3.822.
Responsiveness has a slightly higher overall mean of 3.807± .798, reflecting the agility of staff interactions. Staff
explanations of facility usage score highly at 3.881, showing good communication. Faithful responses to
consumer questions and quick responses to consumer requirements are both solidly rated at 3.801 and 3.807,
respectively. The ability to respond to accidents is scored at 3.846, indicating readiness to manage emergencies.
Good information about future services is slightly lower at 3.652, and proactive help from employees is anotherstrong point, scoring 3.847. In the Assurance category, public sports facilities are perceived as safe, with a meanof 3.834. The staff at these facilities are considered polite and courteous, scoring a mean of 3.841.
Professionalism is indicated by a mean of 3.807 for providing professional answers to inquiries. Knowledge andexperience offered by the staff are rated with a mean of 3.722, while the seriousness of staff attitudes receives a
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------mean of 3.761. Additionally, the cost of using public sports facilities is deemed appropriate by users, as reflected
in a mean of 3.793. The overall mean for Assurance is 3.746±.578. The Empathy category, with an overall meanof 3.758±.573, assesses how public sports facilities and their employees relate to their consumers. Facilities are
rated as very considerate of consumers’ perspectives, scoring 3.807. The ability of employees to fully understandconsumer needs is similarly high at 3.803. Taking an interest in each consumer is valued at 3.841, indicating apersonalized approach to consumer care. However, the score for employees considering the interests of users issomewhat lower at 3.576. The provision of optimal service to consumers is rated at 3.807, demonstrating acommitment to quality service delivery. Lastly, the ease with which users can communicate their circumstances
to employees is rated at 3.681, suggesting good two-way communication between staff and patrons. Also, themean of consumer satisfaction is measured at 3.843±0.562, while the mean of Revisit Intention is registered at
3.561±0.614.
Table 3. Descriptive Statistics
Category

Items

Tangibles(3.647± .634)

Public sports facilities that provide virtual reality experience sports aremodern.
Public sports facilities are equipped with appropriate facilities.
Accessibility to public sports facilities (transportation, parking, etc.) isconvenient.
Employees of public sports facilities dress neatly and appear neatly.
The places and equipment of public sports facilities are clean.
There are various types and functions of virtual reality experiencesports at public sports facilities.

Reliability(3.746±.812)

Responsiveness(3.807± .798)

Assurance(3.746±.578)

Empathy(3.758±.573)

Consumersatisfaction(3.843±.562)

Revisit Intention(3.561±.614)

Public sports facilities provide promised services.
Public sports facilities provide services within a set time.
Public sports facilities solve problems quickly.
Consumers can use public sports facilities with confidence.
Public sports facilities are strict about consumer personal information
security.
I can trust the staff working at public sports facilities.
Staff at public sports facilities explain how to use them well.
Employees of public sports facilities faithfully respond to consumer
questions.
Employees of public sports facilities respond quickly to consumer
requirements.
Public sports facilities have the ability to quickly respond to various
accidents.
Public sports facilities provide good information about future service
provision plans.
Employees of public sports facilities voluntarily provide help.
I think public sports facilities are safe.
Employees at public sports facilities are polite and courteous.
Employees of public sports facilities provide professional answers toquestions.
Employees of public sports facilities provide knowledge andexperience.
The attitude of staff at public sports facilities is serious.
The cost of using public sports facilities is appropriate.
Public sports facilities are very considerate of consumers’ perspectives.
Employees of public sports facilities fully understand the needs ofconsumers.
Public sports facilities take interest in each consumer.
Employees of public sports facilities consider the interests of users.
Public sports facilities provide optimal service to consumers.
Users of public sports facilities can easily tell employees about theircircumstances.
I am satisfied with the quality of service provided by public sports
facilities.
I am satisfied with the exercise experience provided by public sports
facilities.
I am overall satisfied with public sports facilities.
I will continue to use public sports facilities.
I will recommend this public sports facility to others.
If I need to exercise, I will consider public sports facilities first.

Mean±
Deviation
3.583± .637

Standard

3.527± .723
3.461± .458
3.847± .629
3.806± .511
3.738± .739
3.762± .443
3.807± .645
3.601± .543
3.616± .726
3.807± .734
3.822± .526
3.881± .634
3.801± .729
3.807± .732
3.846± .828
3.652± .727
3.847± .626
3.834± .463
3.841± .576
3.807±. 629
3.722±. 623
3.761± .726
3.793± .942
3.807± .632
3.803± .574
3.841± .667
3.576± .463
3.807± .618
3.681± .713
3.938± .726
3.806± .733
3.732± .842
3.614± .617
3.652± .533
3.423± .672

Analysis of Reliability and Validity
Table 4 presents an exploratory factor analysis on participation intention, examining the relationshipbetween various factors and their corresponding items. The analysis employs a Varimax rotation for the rotatedcomponent matrix, and five factors have been extracted. The "Tangibles" attribute includes six items (T1-T6)----------------------------------------------------------------------------------------------------------------------------2009
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------that load heavily on Factor 1, with values ranging from .762 to .832, indicating that this factor is primarily
associated with tangible aspects. The "Reliability" attribute is represented by six items (R1-R6), which load
predominantly on Factor 2, with values from .694 to .807, suggesting that this factor captures elements related toreliability. The "Responsiveness" attribute is captured by six items (RS1-RS6) and is mostly associated with
Factor 3, where the loadings range from .727 to .809, indicating a strong relation to responsiveness attributes.
The "Assurance" attribute involves six items (A1-A6) with the highest loadings on Factor 4, values between .782
and .827, showing that assurance is a distinct factor. Lastly, the "Empathy" attribute comprises six items (E1E6), which have the strongest loadings on Factor 5, ranging from .757 to .823, thus identifying empathy as aseparate factor influencing participation intention. The eigenvalues for each factor range from 3.923 for Factor 1
to 1.433 for Factor 5. The percentage of variance explained by the factors ranges from 27.327% for Factor 1 to
5.487% for Factor 5, with a cumulative percentage increasing from 27.327% to 67.852% as additional factors are
considered. Cronbach’s alpha values for each factor indicate the reliability of the items, with Factor 4 showing
the highest internal consistency at .834 and Factor 2 the lowest at .729. The Kaiser-Meyer-Olkin measure ofsampling adequacy is strong at .841, indicating that the sample is suitable for the analysis. Bartlett's test of
sphericity is highly significant with a value of 831.673 (p<.001).
Table 4. Exploratory factor analysis on participation intention
Factors

Items

Rotated component matrix (Varimax)
Factor 1
Factor 2
Factor 3
Tangibles
T1
.178
.224
.762
T2
.211
.207
.805
T3
.114
.196
.776
T4
.275
.114
.812
T5
.097
.163
.785
T6
.109
.183
.832
Reliability
R1
.204
.165
.694
R2
.163
.138
.752
R3
.212
.788
.167
R4
.185
.283
.807
R5
.138
.096
.769
R6
.176
.213
762
Responsiveness RS1
.283
.245
.727
RS2
.269
.166
.693
RS3
.157
.179
.722
RS4
.087
.238
.764
RS5
.194
.135
.809
RS6
.292
.201
.781
Assurance
A1
.144
.162
.213
A2
.292
.312
.182
A3
.196
.168
.137
A4
.113
.226
.148
A5
.269
.232
.193
A6
.157
.138
.237
Empathy
E1
.088
.202
.283
E2
.243
.163
.097
E3
.285
.224
.211
E4
.132
.212
.201
E5
.179
.278
.186
E6
.277
.307
.194
Eigenvalues
3.923
3.187
2.591
% of variance27.32715.76811.027
Accumulated %27.32743.09554.122
Cronbach’s α
.757
.729
.806
Kaiser-Meyer-Olkin test = 0.841, Bartlett‘s test= 831.673 (p<.001)

Factor 4
.301
.248
.161
.329
.096
.266
.189
.252
.297
.119
.227
.267
.139
.215
.174
.099
.184
.132
.782
.821
.767
.809
.811
.827
.176
.134
,229
.187
.126
.238
1.842
8.243
62.365.834

Factor 5
.103
.149
.291
.138
.215
.173
.098
.149
.193
.287
.216
.168
.131
.114
.228
.114
.275
.183
.182
.169
.133
.225
.218
.114
805
.812
.761
.823
.757
.729
1.433
5.487
67.852.812

Table 5 presents an exploratory factor analysis conducted on consumer satisfaction and revisit intention.
The analysis employs a Varimax rotation for the rotated component matrix, revealing two factors. For consumer
satisfaction (CS), which comprises three items (CS1, CS2, CS3), loadings are higher than 0.7 on Factor 1,
indicating that the variables can be well represented by that factor. Revisit intention (RV), with items RI1, RI2,
and RI3, shows a contrasting pattern where loadings are high on Factor 2, indicating that revisit intention ismainly related to Factor 2. The eigenvalues for Factors 1 and 2 are 3.862 and 2.738, accounting for 44.734% and25.682% of the variance, respectively. The cumulative percentage of variance explained by the two factors is
70.416%. Cronbach’s alpha values for Factor 1 and Factor 2 are .816 and .827, respectively, indicating goodinternal consistency for the items within each factor. The Kaiser-Meyer-Olkin measure of sampling adequacy is
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------.823, which is above the commonly accepted threshold of .6, suggesting that the sample is suitable for the factor
analysis. Bartlett’s test of sphericity has a value of 278.548, with a significance level of p<.001, indicating thatthe observed correlation matrix is not an identity matrix and is appropriate for factor analysis.
Table 5. Exploratory factor analysis on consumer satisfaction and revisit intention
Factors

Items

Rotated component matrix (Varimax)
Factor 1
Consumer
CS1.784
satisfaction(CS)
CS2
.822
CS3
.748
Revisitintention RI1
.188
(RV)
RI2
.367
RI3
.285
Eigenvalues
3.862% of variance44.734
Accumulated %44.734
Cronbach’s α.816
Kaiser-Meyer-Olkin test = 0.823, Bartlett‘s test= 278.548 (p<.001)

Factor 2
.113
.148
.193
.767
.838
.759
2.738
25.68270.416.827

Correlation Analysis
Table 6 presents a correlation analysis of variables. Tangibles may have a strong positive correlation
with Reliability (r = .692, p < .001), indicating that as tangible aspects of service quality improve, perceptions ofreliability also tend to be higher. Responsiveness is significantly correlated with Reliability (r = .711, p < .001),
suggesting that timely and efficient responses are associated with the overall reliability of services. A moderate
positive correlation is observed between Assurance and Tangibles (r = .518, p < .05), while Responsiveness andAssurance are more strongly correlated (r = .654, p < .001). These results suggest that as the perception of safety
and security (assurance) improves, so does the perception of the facility's responsiveness.
Empathy has a notable positive correlation with Reliability (r = .681, p < .001) and a moderate relationship with
Responsiveness (r = .495, p < .01). The strongest correlation for Empathy is with Assurance (r = .678, p < .001),
highlighting the importance of empathetic service as a component of consumers feeling secure and well-caredfor. Consumer Satisfaction is strongly linked with Reliability (r = .753, p < .001), Responsiveness (r = .614, p <.001), and particularly Assurance (r = .814, p < .001). Finally, Revisit Intention has the strongest correlation with
Tangibles (r = .802, p < .001), demonstrating that the physical aspects of the service environment are significant
predictors of whether consumers intend to return. Additionally, Revisit Intention is highly correlated with
Consumer Satisfaction (r = .797, p < .001), reinforcing the concept that satisfaction levels are predictive ofrepeat patronage.
Table 6. Correlation analysis of variables
Category
1.Tangibles
2.Reliability
3.Responsiveness4.Assurance
5. Empathy
6.Consumer
satisfaction
7.Revisit
intention

1
1.692***.573**.518*.584**.622***

2

3

4

5

6

1
.711***.647**.681***.753***

1.654***.495**.614***

1.678***.814***

1.783***

1.802***.797***.673***.792***.748***.797***

7

1*

p<.05,**p<.01,***p<.001

Verification of Hypotheses
Table 7 details the regression analysis on the effect of service quality attributes on consumer
satisfaction, with their associated unstandardized (B) and standardized (β) coefficients, standard errors (SE), tvalues, p-values, tolerance, and variance inflation factor (VIF) scores. The unstandardized coefficient for theconstant is 1.322, which can be interpreted as the baseline level of revisit intention when all other variables areheld at zero. Its standardized coefficient is 0.532, with a standard error of 2.468, and it is not statisticallysignificant at the p < 0.05 level (p = .198). The model’s goodness-of-fit measures indicate a strong fit with an R²of 0.812, which means that approximately 81.2% of the variance in revisit intention is explained by the model.
The Adjusted R² of 0.761 accounts for the number of predictors in the model, still indicating a strong fit. The
Durbin-Watson statistic of 1.837 suggests that there is no serious autocorrelation issue. Finally, the F-value of
16.891 with a p-value of less than .001 indicates that the model is statistically significant overall. The VIF values
range from 1.482 to 1.885, which are all below the commonly used threshold of 5 or 10, suggesting thatmulticollinearity is not a concern in this model. The "Tangibles" attribute shows a positive relationship withrevisit intention, with an unstandardized coefficient of 0.312 and a standardized coefficient of 0.352, although----------------------------------------------------------------------------------------------------------------------------2011
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------this relationship is not statistically significant (p = .211). The "Reliability" attribute has an unstandardized
coefficient of 0.334, but the standardized coefficient is negative (-0.396), which could suggest a coding error or anegative relationship when standardized (p = .339). "Responsiveness" attribute has a negative impact on revisit
intention, with both unstandardized and standardized coefficients being negative (-0.482 and -0.469,
respectively), which is not statistically significant (p = .489). Conversely, "Assurance" attribute is negatively
associated with revisit intention with a coefficient of -0.482 and a standardized coefficient of -0.463, which issignificant at the p < 0.01 level (p = .007). The "Empathy" attribute has a strong positive association with revisit
intention, with the highest standardized coefficient in the model at 1.059 (p=.081). Therefore, Hypothesis 1 ispartially accepted.
Table 7. Effects of service quality attributes on consumer satisfaction
Variables

Revisit intention
Unstandardized
coefficient (B)(Constant)

1.322

Tangibles.312

Reliability

Standardized Standard
coefficient (β) (SE)

error

t

p

Tolerance VIF

.532

2.468

.198

.352

.243

1.302

.211

.823

1.589

.334

-.396

.389

-.977

.339

.726

1.673

Responsiveness -.482

-.469

.457

.712

.489

.747

1.482

Assurance

-.482

-.463

.124

-2.883

.007

.778

1.885

Empathy

.921

1.059

.502

1.849

.081

.693

1.668

R2=.812, Adjusted R2= .761, Durbin-Watson=1.837, F-value=16.891, p-value<.001

Note: VIF=Variance inflation factor
Table 8 illustrates the investigation into how various service quality attributes, specifically tangibles,
reliability, responsiveness, assurance, and empathy, affect consumers' intentions to return to a service provider.
The model's goodness of fit is indicated by an R2 value of .817, suggesting that 81.7% of the variance in revisit
intention is explained by the service quality attributes included in the model. The adjusted R2 value of .779
accounts for the number of predictors in the model and indicates a high level of explanatory power. The DurbinWatson statistic of 1.796 is close to 2, suggesting there is no significant autocorrelation in the residuals. The Fvalue of 16.428 with a p-value of less than .001 indicates that the model is statistically significant. The tolerance
and VIF values for each variable indicate that there is no significant multicollinearity affecting the model, with
all VIF values being well below the common threshold of 10. The “Tangibles” attribute show a significant
positive impact on revisit intention, with a high standardized coefficient (β=.892, p=.003), indicating a strong
and positive effect of tangible aspects of service quality on consumers' intention to revisit. The “Reliability”
attribute, however, has a negative unstandardized coefficient (β=-.579, p=.173), suggesting a negative but notstatistically significant impact on revisit intention. The “Responsiveness” attribute has a positive but notstatistically significant influence on revisit intention (p=.382). The “Assurance” and “Empathy” attributes also
show nonsignificant negative and positive impacts, respectively (p=.397, p=.458). Therefore, Hypothesis 2 ispartially accepted, in that only Tangibles influences revisit intention significantly.
Table 8. Effects of service quality attributes on revisit intention
Variables

Revisit intention
Unstandardized
coefficient (B)Standardized
coefficient (β)

Standard
(SE)

error

t

p

.782

-.663

.518

Tolerance

VIF(Constant)-.498

Tangibles

1.213

.892

.353

3.624

.003

.794

1.624

Reliability

-.814

-.579

.567

-1.431

.173

.736

1.761

Responsiveness .612

.528

.674

.903

.382

.737

1.493

Assurance

-.443

-.303

.513

869

.397

.768

1.784

Empathy

.554

.438

.722

.761

458

.694

1.677

R2=.817, Adjusted R2= .779, Durbin-Watson=1.796, F-value=16.428, p-value<.001

Note: VIF=Variance inflation factor
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------Table 9 presents the effects of consumer satisfaction on the intention to revisit. The model's goodnessof fit is reflected in the R² value of .642, indicating that approximately 64.2% of the variance in the intention torevisit is explained by consumer satisfaction. The adjusted R² value, which accounts for the number of predictors
in the model, stands at .621, suggesting that consumer satisfaction is a strong predictor of revisit intention evenafter adjusting for the number of variables in the model. The Durbin-Watson statistic of 1.837 implies that there
is no serious autocorrelation problem within the regression model, indicating that the residuals are independentof each other. Also, the tolerance value of .727 and the variance inflation factor (VIF) of 1.738 are well within
acceptable limits, signifying that multicollinearity does not distort the results of the regression analysis. The
analysis reveals that consumer satisfaction has a strong and positive relationship with the intention to revisit, as
indicated by a significant unstandardized coefficient (B) of 1.143 and a standardized coefficient (β) of .814
(t=6.068, p<.001). Therefore, Hypothesis 3 is accepted.
Table 9. Effects of consumer satisfaction on revisit intention
Variables(Constant)
Consumersatisfaction

Revisit intention
Unstandardized
coefficient (B)-.498Standardized Standard errortcoefficient (β) (SE)
.782
-.663

.518

1.143

.814

<.001

.193

p

6.068

Tolerance

VIF

.727

1.738

R2=.642, Adjusted R2= .621, Durbin-Watson=1.837, F-value=36.863, p-value<.001

Note: VIF=Variance inflation factor
Table 10 details the mediating role of consumer satisfaction in the nexus between service quality
attributes and the intention to revisit. During Step 1, service quality attributes are shown to predict consumer
satisfaction substantially, as indicated by an unstandardized coefficient (B) of .869 and a standardized coefficient(β) of .881. This positive relationship is strongly supported by a high t-value of 8.324, with an R-squared valueof .772, demonstrating that 77.2% of the variation in consumer satisfaction can be accounted for by service
quality attributes alone. The significant F-value of 69.283 at the .001 level further reinforces the model's robust
fit. Advancing to Step 2, the analysis reveals that service quality attributes also have a substantial impact onrevisit intention (B=1.203, β=.839, t=7.108). The R-squared value for this step is .712, suggesting that service
quality attributes explain 71.2% of the variation in revisit intention. The model remains strong, evidenced by an
F-value of 50.548, which is also significant at the .001 level. In Step 3, when the effects of both service quality
attributes and consumer satisfaction are considered simultaneously, the influence of service quality attributes onrevisit intention is still positive but insignificant (B = .382, β = .273, t=1.092, p>.05). However, consumer
satisfaction emerges as a significant predictor of revisit intention (B=.864, β=.612, t= 2.484, p<.05). The Rsquared value increases slightly to .718, and the F-value, though reduced to 26.087, remains significant at the .01
level. This demonstrates that consumer satisfaction serves as a complete mediator in the relationship between
service quality attributes and revisit intention. Therefore, Hypothesis 4 is accepted.
Table 10. The mediating effect of consumer satisfaction in the relationship between service quality attributes andrevisit intention
Category

Independant
Variables

Step 1Service
attributes

quality Consumer
satisfaction

Step 2Service
attributes

quality

Service
attributes

quality

Step 3

Depentant
Variables

Consumersatisfaction

B

β

t

R2

F

.869

.881

8.324***.772

69.283***

Revisit intention 1.203.839

7.108**.712

50.548***

Revisit intention .382

.273

1.092
.718

26.087**.612*

Revisitintention

.864

2.484

*

p<.05,**p<.01,***p<.001

Discussion and conclusion
This study explored the impact of service quality in public sports facilities with VR centers on thesatisfaction and revisit intentions of wheelchair users in South Korea. The research aimed to fill a gap byexamining the relationship between service quality attributes, consumer satisfaction, and revisit intentions,focusing particularly on the needs of individuals with disabilities. The study utilized the SERVQUAL model,
assessing five dimensions of service quality—tangibles, reliability, responsiveness, assurance, and empathy.
Each attribute was measured using items validated by previous academic studies, emphasizing critical aspects for----------------------------------------------------------------------------------------------------------------------------2013
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KYUNG HWAN CHO--------------------------------------------------------------------------------------------------------------------------------------wheelchair users, such as accessibility, safety, convenience, and staff professionalism. This study sampled 250
wheelchair users over two months, with 235 valid responses collected via self-administered questionnaires atvarious VR sports centers. The findings supported the hypothesis that service quality attributes positively
influence consumer satisfaction (H1) and revisit intention (H2) among wheelchair users. Moreover, consumer
satisfaction was found to have a positive effect on revisit intention (H3) and mediated the relationship between
service quality attributes and revisit intention (H4). The regression analysis confirmed that tangible aspects ofservice quality influenced revisit intentions significantly. Specifically, "Tangibles" showed a significant positive
impact on revisit intention, indicating that the physical elements of the sports facilities affect users' decisions toreturn substantially. In contrast, "Reliability," "Responsiveness," "Assurance," and "Empathy" exhibited
nonsignificant relationships with revisit intention. This partial acceptance of H1 suggests that not all service
quality attributes exert the same influence on satisfaction or revisit intention. Consumer satisfaction emerged as astrong predictor of revisit intention, confirming H3, and fully mediated the relationship between service quality
attributes and revisit intention, supporting H4. These findings align with established theories and prior researchemphasizing the pivotal role of tangible elements in shaping consumer perceptions and intentions. The positive
correlation between consumer satisfaction and revisit intention found in this study corroborates the findings ofOliver (1997) and Brady and Cronin (2001), who posited that satisfaction is a key driver of loyalty behaviors,such as the intention to revisit. The findings are consistent with the service-profit chain model, highlighting
satisfaction as a crucial link between service quality and consumer loyalty. The nonsignificant findings for some
service quality factors may be attributed to the unique context of public sports facilities with VR sports centerscatering to wheelchair users. This suggests that while tangibles are vital, other service quality attributes like
empathy or responsiveness may not have a straightforward impact on revisit intention, possibly due to thespecific needs and experiences of wheelchair users in VR sports environments. The results also imply that theSERVQUAL model's dimensions might require adaptation or further investigation in the context of VR sports
experiences for disabled individuals. Comparing these results with other studies, it was found that integrating
virtual reality (VR) with physical activities, such as FES cycling, significantly enhances physical function anduser engagement in rehabilitation contexts (Duffell et al., 2019). Similarly, this study highlights the positive
impact of modern, well-equipped facilities on user satisfaction and revisit intentions. Herbison et al. (2023)
emphasized the importance of improving access to physical activities for people with disabilities, which aligns
with our findings that tangible service quality attributes are critical for user satisfaction and return intentions. Lee
et al. (2023) explored the current status of esports participation among people with disabilities in South Korea,
underscoring the importance of accessibility and user experience in promoting engagement—findings that
support the role of accessibility and facility quality as vital components of service quality influencing user
satisfaction and revisit intentions. Furthermore, Vella et al. (2023) emphasized the mental health benefits ofphysical activity and the need for inclusive, well-managed sports facilities, which this study corroborates byshowing that high-quality service and well-maintained facilities significantly enhance user satisfaction andencourage repeat visits. Sahoo and Choudhury (2023) discussed the broader implications of accessibility for
equality and inclusion, which is crucial for public sports facilities aiming to serve all users effectively. This study
underlines the importance of improving tangible aspects of service quality, such as accessibility and facility
appropriateness, to significantly impact user satisfaction and loyalty, thereby promoting greater inclusion andparticipation among wheelchair users.
Therefore, this study confirms the significant role of service quality, particularly tangible attributes, ininfluencing consumer satisfaction and revisit intentions at public sports facilities with VR centers for wheelchairusers. While tangible, such as the modernity of facilities and equipment, affects revisit intentions significantly,
other dimensions of service quality, such as reliability and responsiveness, do not have a straightforward impact,
highlighting the nuanced nature of service quality in VR sports environments. Consumer satisfaction has
emerged as a robust mediator, establishing that it is not just the service quality attributes directly, but thesatisfaction they engender that influences the likelihood of revisits. This aligns with established service-profit
chain models, suggesting that quality leads to satisfaction, which in turn drives loyalty behaviors like revisits.
The study's implications emphasize the importance of tangible improvements in public sports facilities toencourage revisits, stressing the need for a physical environment conducive to the specific needs of wheelchairusers. Additionally, our findings highlight the importance of enhancing overall consumer satisfaction to foster
loyalty, suggesting a complex interplay between service quality attributes and satisfaction. The limitations of thisstudy include its specific focus on wheelchair users in South Korea, which may not represent the experiences of
all individuals with disabilities or those in different cultural contexts. This study predominantly emphasizes
tangible aspects of service quality, potentially overlooking subtleties of other attributes like empathy andassurance in the unique setting of VR sports. Lastly, the study's cross-sectional design does not allow for theobservation of changes over time, limiting the ability to infer causality between service quality and revisit
intentions. For subsequent research, it is recommended to adopt a longitudinal approach to observe the evolutionof consumer satisfaction and revisit intentions over time. Additionally, expanding the scope to include diverse
types of disabilities and cultural backgrounds will provide a more comprehensive understanding of service
quality in public sports facilities globally. Further exploration into how non-tangible attributes of service quality
impact consumer satisfaction in VR sports settings would also be valuable.
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