Kong and Wiroon (2024) Creative Business and Sustainability Journal (CBSJ)

Vol.46 No.2 July – December 2024, pp.1-24

Scale Development of Sustainable Tourism

Development from The Perspective of Total
Quality Management

Xiangdong Kong*
Sirinya Wiroonrath**

Abstract
Sustainable tourism development (STD) is an essential component of the circular
economy and has garnered significant attention from governmental agencies and the academic
community worldwide. However, existing research has mostly focused on the protective
development of tourism resources, lacking breakthroughs in management methods, especially
measurement indicators. This study adopts an innovative approach, integrating bibliometric
analysis, interview, and questionnaire survey to construct a multidimensional item pool for
the influence of total quality management (TQM) on STD, utilizing various methods
including exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to
perform the validity verification of the TQM-STD scale. With the support of bibliometric
analysis and expert knowledge, we construct a TQM-STD scale system consisting of five
dimensions: full participation (FP), whole process management (WPM), comprehensive
management (CM), overall perception (OP), and tourism benefits (TB), comprising 30 items.
This system serves as an accurate and effective measurement tool. This research provides
theoretical exploration for the effective identification of STD influencing factors and offers
crucial insights for improving the management strategy of STD at the tourist attraction scale.
This study represents an attempt to apply project management principles to the management
of tourist attractions. The developed scale provides a practical measurement tool for
sustainable development in tourist attractions, enriching concepts and methods in tourist
attraction management and expanding the application of TQM.
Keywords: Sustainable Tourism Development; Total Quality Management; Scale Development
Validation; Tourist Attraction Scale

Received: February 23, 2024 | Revised: June 7, 2024 | Accepted: June 11, 2024

*Ph.D. Candidate, Faculty of Business Administration, Rajamangala University of Technology Thanyaburi,

Pathum Thani 12110, Thailand.
**Assistant Professor, Faculty of Business Administration, Rajamangala University of Technology Thanyaburi,
Pathum Thani 12110, Thailand. (Corresponding Author).

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Introduction
In 2021, China proposed to establish an economic system of green, low-carbon, and
cyclic development by 2025, which includes digital tourism and sustainable tourism. From
2018 to 2022, tourism revenue in Sichuan Province contributed 9.3% to the GDP, indicating
its significant role in economic development. In 2023, the Development and Reform
Commission of Sichuan Province (DRCSP) issued a decree emphasizing the need to innovate
management methods to optimize STD. It is evident that both the central and local
governments attach great importance to STD.
In recent years, researchers have employed both qualitative and quantitative analysis
methods to study sustainable tourism development. For example, Yang et al. (2020) explored
the impact of tourism poverty alleviation on sustainable tourism. López et al. (2021) and Tong
et al. (2024) investigated the promotion of benign development of tourism destinations by
tourist behavior and community participation. Gautam and Bhalla (2024) and Han et al.
(2024) examined the influence of residents' support and economic development level on STD.
Targeted development has been carried out in the aforementioned areas, leading to the
creation of scales such as destination trust (Liu et al., 2019), destination quality (Chandralal
& Valenzuela, 2015), and tourist perception (Mukherjee et al., 2018). Additionally, scholars
have analyzed the constraining factors and management approaches affecting STD, including
policy enforcement (Fernandez-Abila et al., 2024), green development concepts (Penjišević et
al., 2024), environmental and social factors (de Bruyn et al., 2023), performance assessment
levels (Wu & Yang, 2023), and low -carbon lifestyles (Peeters et al., 2024). The
multidimensional and multi-perspective approaches have been employed to develop scales
measuring the impact of community and tourist involvement on STD (Fatma et al., 2016;
Jeong et al., 2021; Woosnam, 2012). However, there has been limited success in enhancing
STD through the reinforcement of the tourist attraction lifecycle management. Total Quality
Management (TQM) fundamentally emphasizes the comprehensive management of products
life cycle (Witt & Muhlemann, 1994) and has been widely applied in infrastructure
construction management (Akhmatova et al., 2022; Othman et al., 2020), corporate
performance and innovation management (Anil & Satish, 2016; Singh et al., 2018; Yusr et al.,
2017), accumulating significant experience and knowledge in scale development and design.
Moreover, it has gradually played an important role in emerging industries such as
environmental sustainability (Akhmatova et al., 2022; Jum’a et al., 2023) and renewable
energy (Hussain et al., 2023). However, there is a scarcity of literature that utilizes the
multidimensional aspects of TQM to study STD, particularly the lack of mature TQM scales
tailored specifically for STD.
In this context, by mining existing relevant literature and expert knowledge, we aim to
delineate the connotations of STD and the dimensions of TQM. We will design a
multidimensional item pool to assess the impact of TQM on STD. Through exploratory factor
analysis (EFA) and confirmatory factor analysis (CFA), we will refine and reduce the item
pool, ultimately developing a scale that is both practically valuable and widely applicable.

Literature Review
Bibliometric analysis can utilize big data mining from specific literature databases to
analyze the current research hotspots in a particular field, which is a highly effective method
for literature reviews (Moed, 2006). We searched the article using 'sust ainable tourism

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development' and 'total quality management' as keywords in the Web of Science (WOS)
database followed by literature screening. Bibliometric analysis was conducted on articles
highly relevant to both STD and TQM. The results (Figure 2) showed numerous studies on
STD, but few applying TQM to STD. Considering the literature's characteristics and our
research focus, we divided the literature review into two parts. The first part is "Dimensions
and Connotations of STD," section 2 is "Mechanisms of TQM Impact on STD," section 3 is
"TQM & STD scale."
Dimensions and connotations of STD
Tourism, as an integral component of the circular economy (Gabor et al., 2023), is
regarded as a crucial industry for China's implementation of the Sustainable Development
Goals by 2030. Sustainable tourism development (STD) should address the current needs of
tourist destinations and travelers, while also considering the future requirements of these
stakeholders. According to the Sustainable Tourism for Development Guidebook, it involves
achieving coordinated development among governments, businesses, communities, and
tourist attractions, leading to a sustainable state characterized by expected quality of life,
environmental standards, and ongoing benefits for governments and businesses. The Global
Sustainable Tourism Council outlines five objectives for sustainable tourism development:
enhancing ecological awareness, promoting fair tourism development, improving the quality
of life for residents in tourist destinations, providing high-quality tourism experiences to
travelers, and preserving environmental quality.
Previous research (Figure 1) on STD has primarily focused on three dimensions:
economic benefits, social benefits, and ecological benefits (Czernek-Marszalek, 2020; León
et al., 2021; Khan et al., 2020), and has explored aspects such as ecological awareness, fair
development, resident livelihoods, tourism experiences, and environmental quality (Bramwell,
B., 2015). Among them, the widely accepted connotation of STD is that it refers to "In a
certain manner and scale, developing in specific areas, sustaining vitality over the long term
without causing environmental degradation or alteration" (Boluk et al., 2019; Fernandez et
al., 2024; Spenceley & Rylance, 2019; Zhao et al., 2024). This concept emphasizes the
importance of advocacy and education, social participation, community culture, and green
concepts in STD (Diallo et al., 2022; Marchi et al., 2023; Maziliauske et al., 2024; Penjišević
et al., 2024; Stojanović et al., 2024;). Tourism management, tourism impact, and tourism
relationships are also extensions of the connotations of STD. Some researchers believe that
sustainable tourism development requires addressing the relationships between tourists, the
environment, and local communities (Cheung, 2019). It involves long-term planning and
layout (Angelevska & Rakicevik, 2012), broadening the perspectives of tourism managers
(Ruhanen, 2008), innovating management concepts (Aurora et al., 2023), and prioritizing the
needs of stakeholders (Roxas et al., 2020). Additionally, STD’s influencing factors and
management approaches can also constrain the direction of future tourism development. For
example, some scholars argue that factors such as economic development levels (Filipiak et
al., 2023), tourism management strategies (Ziyadin et al., 2019), and green de velopment
concepts (Penjišević et al., 2024) may limit sustainable tourism development. To achieve
sustainable tourism development, strategies may involve enhancing performance assessment
levels (Wu & Yang, 2023), altering energy consumption patterns (Wu et al., 2023), reducing
carbon emissions (Peeters et al., 2024), and enhancing overall tourism benefits (Tian et al.,
2022).

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Figure 1: Bibliometric Analysis of Literature on TQM and STD in Recent Years

(Web of Science)

Mechanisms of TQM impact on STD

Total Quality Management (TQM), as an important management approach (Witt &
Muhlemann, 1994), has been widely applied in traffic management (Akhmatova et al., 2022),
construction quality management (Othman et al., 2020), corporate performance management
(Anil & Satish, 2016; Singh et al., 2018), and innovation management (Yusr et al., 2017 ).
TQM emphasizes quality as its core (Ho et al., 2023), encompassing three dimensions: full
participation, whole process management, and comprehensive management (Wang et al.,
2024). In recent years, TQM has gradually begun to be applied in sustainability research, such
as environmental sustainability (Akhmatova et al., 2022; Jum’a et al., 2023), renewable
energy management (Hussain et al., 2023), and sustainable development opportunity studies
(Isaksson et al., 2023). However, there is currently limited literature on TQM in the context of
sustainable tourism development (Bhuiyan & Wahab, 2018). TQM consists of full
participation, whole process management, and comprehensive management. Existing research
results mainly analyze the impact of STD by studying single dimensions. For example, studies
suggest that community involvement is a prerequisite for sustainable tourism destination
development (Iqbal et al., 2023), different tourism stakeholders and residents have significant
influences on sustainable tourism development (Gautam & Bhalla, 2024), emphasizing
stakeholder participation in tourism management to enhance tourism experiences (Roxas et
al., 2020), and asserting that local governments, tourists, residents, and employees are all
stakeholders in sustainable tourism development (Liu et al., 2019). Some studies have
explored the entire process of tourism area development based on the concept of the whole
process management, revealing that tourism area development conforms to the lifecycle
theory (Moore & Whitehall, 2005). Moreover, scholars have analyzed the impact of
comprehensive management on STD from multiple perspectives. For instance, Li et al. (2024)
suggests that community involvement, tourism certification, and public-private partnerships
are important strategies for achieving sustainable tourism development. Ahmad et al. (2022)
explores the impact of innovation management on sustainable development using panel data,
while Roxas et al. (2020) employs systems thinking tools to establish causal relati onships

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between sustainable tourism variables and analyze the impact of leadership management on
STD.
TQM & STD Scales
Through the literature review above, we have gained a clearer understanding of the
essence of Sustainable Tourism Development (STD) and the influence mechanism of Total
Quality Management (TQM) on STD. Based on this, we further analyzed the development of
scales in the TQM and STD fields. We found that TQM has yielded scale development
outcomes in areas such as manufacturing (Das et al., 2008), government management
(Musenze & Thomas, 2020), and social responsibility(Wang et al., 2023; Khurshid et al.,
2022), with the number of dimensions typically ranging from 3 to 8. Meanwhile, scale
development in the STD field mainly focuses on aspects such as local residents (Lee, 2013),
communities, tourism practitioners (Eslami et al., 2019), and environmental impacts (Chi &
Liu, 2023; Rasoolimanesh et al., 2024) on STD, which is closely aligned with previous
literature on STD's essence. However, through comparative analysis of the literature, we
found a lack of mature scale systems for assessing the influence of TQM on STD, with related
research being scarce. Moreover, through a direct comparison of our study with previous
research results (such as in tables), we further discovered significant differences in the
dimensions and content of similar studies and our own, highlighting the novelty of our
perspective. We have developed a TQM-STD scale suitable for the scale of tourist attractions
based on a comprehensive understanding of STD's essence and the potential impact of TQM
on STD.
Literature conclusion
The literature analysis results reveal that the concept of STD emphasizes maintaining
its long-term vitality while not compromising environmental improvement. Its connotations
focus on the sustainability of tourism benefits and sustainable tourism perceptions, revolving
around five major aspects: ecological awareness, fair development, resident livelihoods,
tourism experiences, and environmental quality. STD underscores the construction of
harmonious tourism relationships among stakeholders, including local governments, local
communities, tourists, and tourism practitioners. It is crucial to identify the influencing factors
of STD, particularly emphasizing the impact of tourism planning, tourism management, and
community participation. Additionally, regional economic development levels, performance
management approaches, and the promotion of green development concepts are considered
important management approaches to achieve sustainable tourism development. TQM, as a
significant management approach, has gradually been applied in various fields of sustainable
development, encompassing dimensions of full participation, whole process management, and
comprehensive management. However, there is currently limited comprehensive research on
applying TQM to STD, with existing studies predominantly focusing on single dimensions
and mainly concentrated on research into full participation and whole process management.
Thus, it is evident that there is a lack of literature on utilizing TQM in sustainable tourism
development research, indicating the need to encourage researchers to focus on TQM research
in the context of STD. Both TQM and STD have rich scales in their respective research fields.
However, there is a lack of applicable scales for integrating TQM into the STD fi eld,
especially concerning the impact of TQM on STD. Therefore, it is highly valuable to develop
a TQM-STD scale that integrates the essence of STDs and the mechanisms of TQM's impact
on STD. This scale will have guiding significance for optimizing management methods for
sustainable tourism development at the tourist attraction level.

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 Table 1: Comparative Analysis between this Study and Relevant Research
This Study Other Similar Studies
Topic Scale dimensions Topic Scale dimensions References
TQM on Full TQM on manufacturing Top management commitmentSupplier qualityContinuous Das et al., 2008
STD participation industry improvementProduct innovation BenchmarkingEmployee
Whole process involvement Reward and recognitionEducation and training
Kong and Wiroon (2024)

management TQM on local government Leadership Customer Process design and Musenze &
Comprehensive managementEmployee Continuous improvement Thomas, 2020
management TQM on Social Exchange Leader-member exchange Team–member exchangeMeans Wang, 2023
Overall of self-efficacy  Job satisfaction
perception TQM on socially Top managementStrategic planning Human resource Khurshid et al.,
Tourism responsible SupplierCustomer Social community Environment 2022
benefits
TQM on customer loyalty Service quality Patients’ Satisfaction Patients’ Loyalty Abu-Rumman
et al., 2021
TQM on education Participation/involvement in continuous Glaveli et al.,

6
improvementteamwork empowermentappraisal 2022
systems/recognition reward for quality training and
development  leadership
Resident support for STD Community attachmentCommunity involvementPerceived Lee, 2013
benefitsPerceived costs
Resident attitudes for STD Perceived impactsSense of place  Development potential Zhu et al., 2017
Community for STD Community attachmentTourism impactsLife quality Eslami et al.,
Residents support 2019
Businesses and  Residents Tourists Businesses Government Rasoolimanesh
government for STD et al., 2024

Environment for STD Tourism attractionsEcological resilience Traffic Chi & Liu,
accessibility and Accommodation capacity 2023
Ecotourism for Tourism growthEcotourism Environment and Baloch et al.,
STD sustainability of ecosystem Government policy 2023
Social Responsibility for EconomicSocial Environmental fields Achmad &
STD Yulianah, 2022
Creative Business and Sustainability Journal (CBSJ)
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Kong and Wiroon (2024) Creative Business and Sustainability Journal (CBSJ)
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Research Methodology
Data sampling
Leshan Giant Buddha (Figure 2A) and Lizhuang Ancient Tow (Figure 2B) are located
in Yibin City and Leshan City, respectively, China. They are both UNESCO World Heritage
Sites and attract a large number of visitors each year. The management level can represent the
general characteristics of tourist attractions in the Chengdu-Chongqing Economic Circle and
is very representative. Therefore, we selected Lizhuang and Leshan Giant Buddha as samples.
Leshan Giant Buddha is a National 5A-level scenic area. Carved in the Tang Dynasty (713
AD), it stands at a height of 71 meters, depicting a seated Maitreya Buddha and ranking as
China's largest cliff-carved stone sculpture. Li Zhuang Ancient Town is a National 5A-level
scenic area. Established during the Southern Liang Dynasty (540 AD), it retains the layout
and appearance of ancient towns from the Ming and Qing dynasties.
The data sampling for this study was conducted in three stages. In the first stage,
interviews were conducted with tourists, scenic spot employees, and local officials to gather
66 interview records for the analysis of TQM-STD influencing dimensions. The second stage
involved the pre-testing phase of the questionnaire, with 180 questionnaires collected (with
an effective rate of 91.7%). The third stage was the formal testing phase, during which 700
questionnaires were collected (with an effective rate of 90.2%). The data collection was
carried out at the Leshan Giant Buddha and Lizhuang Ancient Town scenic spots within the
Chengdu-Chongqing Economic Circle (Figure 2). The data collection process was facilitated
by the scenic area management departments and conducted through a combination of online
and on-site methods.

Figure 2: Sampled Tourist Attraction.

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Methodology
The research framework of this study is mainly divided into three sections (Figure 3).
The first part is the item development stage, which involves constructing the item pool using
three analytical methods: qualitative analysis (Kvale & Brinkmann, 2009), content -target
consistency analysis (Worthen et al., 2014), and project collinearity diagnosis (Shrestha et al.,
2020), based on existing literature metrics analysis and interview records. The second part
includes the discriminant validity analysis, reliability analysis, and exploratory factor analysis
(EFA) (Kyriazos, 2018) of the item pool and pre-test to initialize the scale. The third section
involves the utilization of confirmatory factor analysis (CFA) (Marsh et al., 2020) on formal
survey data to evaluate the scale's validity. The interrelation between research methodology,
objectives, sample, and expected outcomes can be referenced in Table 2.
Table 2: Method and Sample in This Study
Id Methodology Objectives Sample Expected
1 Qualitative analysis Exploring TQM 66 respondents Dimensions of
Interview Impact on STD 10 experts TQM impact on
Item-objective congruence STD
2 Questionnaire Survey Improving items 180 respondents Initial item pools
Discriminant analysis 700 respondents Generating scales
Reliability analysis
Factor analysis
⑤Questionnaire Survey
⑥ Exploratory factor analysis

3 Confirmatory factor Scale evaluation 700 respondents Obtaining scale

analysis validity

Item Item TQM—STD (based on Literature metric analysis)

development D1 D3
D2
IOC<0.6 Dimensions TQM OP TB
or VIF>5 D11 D12 D13

FP CM WPM
1
QA Initial item iip1 1 n 1
n
IOC+VIF 1 n n
pools 2 4
2 2 2
4 2
3 5 8
3 3 6
IOC>0.6 4 3
iip2 iip3 4
5
7
and VIF<5 ip1 ip2
Item pools ip3 ip4 iip4 ip5 iip5

Critical P<0.05, CR>3

Questionnaire

Size>150

ratio
α > 0.8

Scale Sampling Pre- Data Item

Reliability Initial scale
development and suvey testing sets reduction
Factor
analysis FL>0.7 Questionnaire
Size=700
KMO>0.7

Scale-validated Eig.＞1&CVCR>60% EFA Datasets Survey

Result CFA Reliability test Validity test

Scale 0.5<FL<0.95, x2/df<2, CFI>0.9, AVE>0.5, HTMT<0.85
evaluation α > 0.7
TLI>0.9, RMSEA<0.05

Notes: IOC= Item-Objective Congruence, VIF=Variance Inflation Factor, QA=Quality Analysis, CFI=Comparative Fit Index, TLI=Tucker-Lewis Index,
AVE= Average Variance Extracted, CR=Critical Ratio,α=Chronbach's Alpha, CVCR=Cumulative Variance Contribution Rate. D=Dimension

Figure 3: General Research Framework

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Analysis and Findings

Item development
The influence of TQM on STD and the extent of its impact are uncertain. To accurately
establish the hypothetical relationship between multiple dimensions of TQM and STD, as
well as to define the conceptual constructs of each dimension, we conducted interviews at two
randomly selected scenic spots in the study area. The interviews focused on the relationship
between TQM and STD and involved scenic spot visitors, employees, and local officials. We
collected a total of 66 interview records, including 32 visitors, 18 scenic spot employees, and
16 local officials. Using Nvivo12 software, we conducted statistical analysis on the interview
records. The results showed that the interviewees mainly believed that participation and
process management play a facilitating role in STD. They also believed that full participation
and process management have positive effects on tourism revenue and tourism experiences.
Based on the interview results and existing reference literature, we constructed five
dimensions of TQM for STD and initially defined the constructs of the five dimensions as
follows: full participation (FP), whole process management (WPM), comprehensive
management (CM), overall perception (OP), and tourism benefits (TB). For the concepts of
each dimension, please consult Table 3.
Table 3: Definitions and Explanations of the Constructs (Dimensions)
Constructs Definition and Explanation
Full participation (FP) The employees of the tourist attraction should be actively involved in
quality management, extending beyond individual or departmental
confines, with the expectation that each individual shares the
responsibility for quality management.
Whole process WPM extends quality management across all aspects of the tourist
management attraction, from planning to operation. Planning and design integrate
(WPM) quality criteria for standards compliance and ongoing improvement
during operations.
Comprehensive CM integrates internal and external factors for effective tourist attraction
management quality management, assessing internal quality factors and incorporating
(CM) external considerations like cost-effectiveness and visitor services.
Overall perception OP refers to tourists' overall experience and impression of a tourist
(OP) destination, including their perceptions of the scenic environment, service
quality, cultural experiences, and attractions' appeal.
Tourism benefits (TB) TB includes promoting cultural exchange, enhancing social cohesion,
creating employment opportunities, fostering local economic
development, preserving natural resources, and promoting sustainable
development across three dimensions.

Based on the interview results and literature knowledge, we established five

dimensions, 14 hypotheses, and 50 items for the impact of TQM) on STD. To ensure
consistency between each item and the research objectives, we invited 10 experts to conduct
an Item-Objective Congruence (IOC) test (Table 4). After eliminating items with IOC values
less than 0.7, we retained 38 items. The IOC test results indicated that each dimension
(variable) was adequately represented by its corresponding items. However, the presence of
collinearity between items (Shrestha, 2020) was uncertain. Therefore, we used SPSS software

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to diagnose collinearity among items within the same variable. The results revealed that there
was 1 item each under the FP and STD variables with collinearity issues (VIF > 5).
Consequently, these items were removed, leaving us with 36 effective items, di stributed
across five item pools: OP, FP, WPM, CM, and TB.
Table 4: IOC Test
Dimension Item Measurement Scale Adopted IOC Value
Overall Perception 6 0.86
Full Participation 7 5-point scale ranging from “strongly 0.92
Whole Process Management 5 disagree” to “strongly agree” 0.86
Comprehensive Management 9 0.86
Tourism Benefit 9 0.71

Scale development
Item analysis
Item development has undergone construction and screening of items through IOC
and collinearity diagnosis. To ensure the scientific rationality of item composition and
quantity, we need to conduct item analysis using questionnaires based on the item pool and
survey data. This allows us to reassess whether any items need to be removed. With the
assistance of the tourism management departments of the surveyed scenic areas, both online
and on-site questionnaire surveys and pretests were conducted. The survey questionnaires
were collected and preprocessed, resulting in a total distribution of 180 questionnaires. After
removing 15 invalid questionnaires, there were 165 valid questionnaires, yielding an effective
questionnaire rate of 91.7%. The data from these 165 pretest questionnaires were t hen
subjected to discriminant analysis, reliability analysis, and factor analysis.
The 165 questionnaires were sorted based on the total average score for each variable,
with the top 27% of scores categorized as the high-score group and the bottom 27% as the
low-score group. The average scores for each variable in the high and low-score groups were
calculated separately, and the difference between the two averages represented the
discriminant coefficient for each variable (Table 5). A larger absolute value of the difference
indicates higher discriminant power for the item. Through independent sample t-tests, it was
found that the t-values for WPM3, OP3, and OP9 were all less than 3 and not significant
(p>0.05), indicating poor discriminant power for these items. Therefore, they were removed,
resulting in a final item pool of 33 items.
Based on the discriminant analysis of items, a reliability analysis was also conducted.
As shown in Table 6, deleting three items (FP1, WPM5, and OP6) would increase Cronbach’s
α coefficients for FP, WPM, and OP to 0.881, 0.875, and 0.892, respectively, all exceeding
0.80. This represents a significant improvement from the original Cronbach’s α coefficients of
0.813, 0.778, and 0.773, respectively. However, deleting these three items would result in a
significant decrease in Cronbach’s α coefficients for the corresponding scales compared to
when all 30 items are retained. Therefore, removing FP1, WPM5, and OP6 items was deemed
necessary to further optimize each scale. After deletion, the Cronbach’s α coefficients for each
scale exceeded 0.8, indicating excellent internal consistency of the scales. The results suggest
strong associations among the factors in this study, with high internal consistency. Thus, the
items within each dimension of the scale are deemed reliable.

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Table 5: Analysis Results of the Discriminant Coefficient and Critical Ratio

Mean discriminant
Item code t-value p
low-score high-score coefficient
FP1 group
2.66 group
3.38 0.72 3.512 0.010
FP2 2.47 4.38 1.91 11.058 0.000
FP3 3.09 4.55 1.46 8.271 0.000
FP4 2.88 4.59 1.71 11.313 0.000
FP5 2.72 4.62 1.9 14.569 0.000
FP6 2.94 4.62 1.68 10.584 0.000
WPM1 3.19 4.75 1.56 10.056 0.000
WPM2 2.71 4.43 1.72 10.799 0.000
WPM3 2.61 2.82 0.21 1.805 0.076
WPM4 3.39 4.82 1.43 12.418 0.000
WPM5 1.97 3.04 1.07 3.752 0.000
WPM6 2.84 4.50 1.66 11.602 0.000
WPM7 2.97 4.71 1.74 13.2 0.000
CM1 3.04 4.64 1.60 10.065 0.000
CM2 2.64 4.36 1.72 10.951 0.000
CM3 2.93 4.85 1.92 15.285 0.000
CM4 2.82 4.48 1.66 10.519 0.000
CM5 2.79 4.67 1.88 14.037 0.000
TB1 2.72 4.55 1.83 13.673 0.000
TB2 2.9 4.52 1.62 9.659 0.000
TB3 2.52 4.52 2.00 12.291 0.000
TB4 2.93 4.55 1.62 9.434 0.000
TB5 2.9 4.58 1.68 10.084 0.000
TB6 2.55 4.32 1.77 12.323 0.000
TB7 2.86 4.48 1.62 8.849 0.000
TB8 2.62 4.55 1.93 13.988 0.000
TB9 2.79 4.71 1.92 12.912 0.000
OP1 3.29 4.71 1.42 8.399 0.000
OP2 3.14 4.52 1.38 6.905 0.000
OP3 2.75 3.26 0.51 2.884 0.070
OP4 2.79 4.58 1.79 10.143 0.000
OP5 3.11 4.74 1.63 10.178 0.000
OP6 2.36 4.03 1.67 3.891 0.000
OP7 2.61 4.23 1.62 9.175 0.000
OP8 2.89 4.35 1.46 9.073 0.000
OP9 2.64 2.55 0.09 -0.468 0.640

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Table 6: Cronbach's Coefficient Reliability Analysis

After removal, Cronbach’s α
Dimension Item code Cronbach’s α
for the variable
FP FP1 0.881
FP2 0.755
FP3 0.775
0.813
FP4 0.763
FP5 0.739
FP6 0.757
WPM WPM1 0.720
WPM2 0.714
WPM4 0.720
0.778
WPM5 0.875
WPM6 0.707
WPM7 0.710
CM CM1 0.854
CM2 0.864
CM3 0.834 0.877
CM4 0.849
CM5 0.850
TB TB1 0.916
TB2 0.920
TB3 0.921
TB4 0.923
TB5 0.919 0.927
TB6 0.918
TB7 0.924
TB8 0.913
TB9 0.913
OP OP1 0.674
OP2 0.674
OP4 0.655
OP5 0.661 0.733
OP6 0.892
OP7 0.667
OP8 0.663

The KMO statistic is one of the measures used to assess the suitability of a factor
analysis model. After conducting statistical analysis on the 165-pre-test data, the results
revealed a KMO value of 0.852, with a chi-square value of 2836.158 for Bartlett's test
(p<0.001) and 741 degrees of freedom. This indicates that there is a significant correlation
among the variables, suggesting the presence of underlying common factors, making the data

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Vol.46 No.2 July – December 2024, pp.1-24

highly suitable for factor analysis. Upon examining the communalities (Table 7), it was found
that all values exceeded 0.2, and the factor loadings were all above 0.45, indicating that all
items could be retained. Through independent sample tests, reliability analysis, commonalities
analysis, and item reduction, an initial scale was formed, with the FP, WPM, CM, TB, and OP
scales containing 5, 5, 5, 9, and 6 items respectively (Table 7).
Table 7: Communalities and Factor Loadings for Each Variable
Item Code Communalities Factor Loading
FP2 0.713 0.845
FP3 0.603 0.776
FP4 0.677 0.823
FP5 0.727 0.853
FP6 0.674 0.821
WPM1 0.607 0.779
WPM2 0.663 0.814
WPM4 0.645 0.803
WPM6 0.710 0.843
WPM7 0.720 0.849
CM1 0.654 0.809
CM2 0.597 0.772
CM3 0.750 0.866
CM4 0.681 0.825
CM5 0.671 0.819
TB1 0.686 0.829
TB2 0.605 0.778
TB3 0.585 0.765
TB4 0.543 0.737
TB5 0.617 0.786
TB6 0.659 0.812
TB7 0.515 0.718
TB8 0.745 0.863
TB9 0.751 0.867
OP1 0.547 0.740
OP2 0.638 0.799
OP4 0.678 0.823
OP5 0.645 0.803
OP7 0.678 0.824
OP8 0.727 0.853

Exploratory factor analysis

After conducting item analysis and validation, an initial scale was obtained. With the
assistance of tourism management departments from the sampled scenic areas, an official
questionnaire survey was c o n d u c t e d both online and on-site. A total of 700 questionnaires
were distributed, out of which 643 were returned. After removing 11 questionnaires with
excessively short completion times or identical responses, 632 valid questionnaires remained,
resulting in an effective response rate of 90.2%.

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Vol.46 No.2 July – December 2024, pp.1-24

Table 8: EFA Results (n=632)

Dimension Item code FL Eigenvalue CVCR
Item code FP FP3 0.793 9.942 33.081%
FP4 0.782
FP5 0.794
FP6 0.813
WPM WPM1 0.791 2.987 43.039%
WPM2 0.757
WPM4 0.803
WPM6 0.788
WPM7 0.803
CM CM1 0.799 2.841 52.509%
CM2 0.791
CM3 0.795
CM4 0.782
CM5 0.824
OP OP1 0.731 2.683 61.451%
OP2 0.736
OP4 0.753
OP5 0.761
OP7 0.805
OP8 0.773
TB TB1 0.706 1.655 66.968%
TB2 0.735
TB3 0.745
TB4 0.731
TB5 0.714
TB6 0.713
TB7 0.745
TB8 0.825
TB9 0.828
Notes: FL is Factor Loading, CVCR is Cumulative Variance Contribution Rate

The validity of items was examined and the factor structure of observed variables was
explored using Exploratory Factor Analysis (EFA) to explore the dimensionality of STD (Table
8). Initially, the valid questionnaires (N = 632) were imported into SPSS 26.0 for analysis,
resulting in a Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy of 0.941, and a
significant Bartlett's Test of Sphericity chi-square value of 11166.271 (p < 0.001), with 435
degrees of freedom. These results suggest the presence of correlations among items and
indicate the suitability of the data for factor analysis. Principal Component Analysis (PCA) and
Varimax rotation were then employed to extract and orthogonalize factors. Factors with
eigenvalues greater than 1 were retained, resulting in the extraction of 5 common factors. The
cumulative variance contribution reached 66.96%, exceeding the 60% extraction criterion. The
scree plot test also indicated the suitability of retaining 5 factors. Based on the relationships
among items, the structure of the 5 factors reflected the theoretical framework well, confirming
the extraction of the 5 factors.

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Vol.46 No.2 July – December 2024, pp.1-24

The PCA analysis revealed that FP2, FP3, FP4, FP5, and FP6 had higher loadings on
the 4th factor, which was named "full participation (FP)"; WPM1, WPM2, WPM4, WPM6, and
WPM7 had higher loadings on the 5th factor, named "whole process management (WPM)";
CM1, CM2, CM3, CM4, and CM5 had higher loadings on the 3rd factor, named
"comprehensive management (CM)"; TB1, TB2, TB3, TB4, TB5, TB6, TB7, TB8, and TB9
had higher loadings on the 1st factor, named "tourism benefits (TB)"; OP1, OP2, OP4, OP5,
OP7, and OP8 had higher loadings on the 2nd factor, named "overall perception (OP)". This
dimensional division is consistent with the expected dimensions, demonstrating good validity,
and leading to the formation of the final version of the scale.
Scale evaluation
Confirmatory factor analysis (CFA) can be used to validate the structural stability of
the scale. In this study, AMOS 24.0 was employed to perform CFA on the data. As shown in
Figure 4, the goodness-of-fit indices for the overall dimension measurement model were
examined. It was found that X2/df=1.377, CFI=0.986, GFI=0.948, AGFI=0.928, IFI=0.986,
TLI=0.985, RMSEA=0.024. All of these indices met the standard criteria for goodness-of-fit,
indicating that the measurement model passed the goodness-of-fit test.
Convergence analysis results (Table 9) indicate that the factor loading values of the 30
items range from 0.72 to 0.84, demonstrating the high construct validity of the scale. The
convergent validity of the scale was tested by combining the composite reliability (CR) and
average variance extracted (AVE). The CR values for each dimension ranged from 0.885 to
0.926, all exceeding the standard of 0.700. Additionally, the AVE values for each dimension
were all greater than the standard value of 0.500, indicating good convergent validity of the
scale. The discriminant validity of the scale was assessed by determining whether the square
root of the average variance extracted (AVE) for each dimension was greater than the
correlation coefficients between other dimensions. The data (Table 9) show that the square
root values of AVE for all five dimensions are higher than the correlation coefficients between
other related dimensions. The correlation coefficients between dimensions (Table 10) are all
below the standard of 0.750 (Kline, 2015), demonstrating ideal discriminant validity among
the dimensions.

Figure 4: Fit Test of CFA Model

15
 Table 9: Convergence evaluation of The Formal Scale
Item Item Significance Factor Loading Reliability Validity
Dimensions
(Abbreviation) code Un-std S.E. P Std. CR AVE
FP Full participation enhances sustainable FP2 1.057 0.050 *** 0.79 0.890 0.618
Tourism involvement in management FP3 1.017 0.048 *** 0.79
All-staff involvement enhance management FP4 0.982 0.048 *** 0.76
Employee opinions improve service quality FP5 1.037 0.049 *** 0.79
Kong and Wiroon (2024)

Employee participation in decision-making FP6 1.000 *** 0.80

WPM Planning and management WPM1 1.018 0.051 *** 0.78 0.885 0.606
Training management WPM2 0.968 0.051 *** 0.74
Operation management WPM4 1.000 0.049 *** 0.79
Supervision management WPM6 1.059 0.051 *** 0.80
Resource allocation management WPM7 1.000 *** 0.78
CM Innovation management CM1 0.898 0.042 *** 0.77 0.890 0.617
Product feature management CM2 0.898 0.041 *** 0.78
Integrity management CM3 0.891 0.042 *** 0.77
Hardware management CM4 0.932 0.043 *** 0.78

16
Application of new technologies CM5 1.000 *** 0.83
TB Tourism benefits increase resident’s income TB1 1.000 *** 0.73 0.926 0.583
STD attracts more investment TB2 1.016 0.054 *** 0.75
STD enhances scale of tourism products TB3 1.108 0.057 *** 0.77
STD promotes employment TB4 1.023 0.054 *** 0.75
STD improves transportation TB5 0.935 0.052 *** 0.72
STD promotes cultural preservation TB6 1.016 0.056 *** 0.73
STD improves surrounding ecology TB7 1.023 0.054 *** 0.75
STD enhances environment awareness TB8 1.168 0.055 *** 0.84
STD promotes harmonious tourism relations TB9 1.116 0.054 *** 0.82
OP Transportation and facility experience OP1 1.000 *** 0.75 0.899 0.597
Evaluation of the impact of tourism OP2 0.956 0.051 *** 0.74
Feedback on experience promotes OP4 1.100 0.055 *** 0.78
Environment influences experience OP5 0.952 0.050 *** 0.75
Cost-effectiveness of tourism experience OP7 1.118 0.054 *** 0.81
Cost and commuting impact experience OP8 1.106 0.055 *** 0.80
Creative Business and Sustainability Journal (CBSJ)
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Table 10: Two-dimensional Correlation Matrix and HTMT for The TQM-STD Scale

Discussion
Based on bibliometric analysis and expert knowledge, the relationship between three
dimensions of TQM and STD was established, successfully developing a TQM-STD scale
system consisting of five dimensions: FP, WPM, CM, TB, and OP, comprising 30 items. The
construction process of the scale system for the five dimensions passed a series of rigorous
tests including IOC, collinearity, reliability, and validity. The TQM -STD scale can be
presented from the perspectives of FP, WPM, CM, TB, and OP, and the correlation coefficients
between dimensions (Table 10) are all below the standard of 0.750 (Kline, 2015), indicating
no model collinearity or overlap issues. This suggests that the first-order model (Figure 4) is
appropriate for this study, with no second-order constructs present.
In the TQM-STD scale system, the FP scale items mainly revolve around tourists, local
residents, and scenic area staff, covering stakeholders in tourism (Roxas et al., 2020) and
reflecting the concept of full participation. The items in the scale are objectively accurate. The
WPM scale items involve tourism planning, operation, and supervisory management, which
align with the PDCA cycle (Carvalho et al., 2023) and are a significant manifestation of the
tourist attraction l i f e c y c l e management (Witt & Muhlemann,1994). The construct of CM
consists of five items, encompassing aspects such as hardware and software, tourism features,
innovative concepts, etc., which align with the comprehensive management's promotion of
sustainable tourism development (Ahmad et al., 2022； Li et al., 2024 ).TB and OP are two
intermediate variables influencing TQM-STD. The TB scale includes 9 items involving
residents' income, investment, product sales, and environmental awareness, aligning with the
three dimensions of economic, social, and ecological benefits of STD (Czernek-Marszalek,
2020; Khan et al., 2020; León et al., 2021). Timothy and Said (2023) proposed that residents'
perception of tourism includes positive and negative aspects, with positive perception showing

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Vol.46 No.2 July – December 2024, pp.1-24

high consistency with the overall perception scale items in this study. Additionally, research
indicates that in special tourism scenarios, tourists are willing to exchange time costs for better
travel experiences (Yin et al., 2024), and tourism attractions often focus on enhancing tourists'
travel experiences for better marketing (Dong & Qu, 2023). This underscores the importance
of tourism perception for sustainable tourism, which is highly relevant to the content included
in the OP scale items of this study.
In addition, this study has certain limitations. Firstly, the data were derived from
questionnaire responses. Although respondents were encouraged to answer truthfully, they may
have been influenced by social expectations and inclined to provide responses that aligned with
these expectations, leading to inflated item scores. This is a common issue in questionnaire
surveys (Fowler et al., 2014). Secondly, the sample comprised national 5A-level scenic areas,
which employ relatively advanced management methods. However, there may be differences
in management concepts and methods among scenic areas of different levels (Wang et al.,
2024). In the future, it is necessary to conduct uniform sampling across A-5A-level scenic areas
to validate the applicability of the scale. While the scale has passed various tests of reliability
and validity, further optimization of the scale items for each dimension may be required to
adapt to specific survey subjects as the application scenarios change.

Conclusion
This study integrates literature analysis and expert opinions to construct an innovative
model of the impact of TQM on STD. Utilizing data from 632 questionnaires collected from
two UNESCO World Heritage sites, the study conducts the development and validation of a
TQM-STD scale system. Each of the three critical stages of scale development has undergone
rigorous testing. The development process and outcomes hold two significant values.
Theoretical Contributions
The literature analysis provides a more scientifically accurate analysis of existing
research findings on TQM and STD. This analysis helps to better understand the spatial
dimensions and scientific connotations of TQM and STD, leading to the construction of a
reasonable multi-dimensional relationship between TQM and STD. Supported by two
intermediate variables, the study successfully constructs the FP, WPM, CM, TB, and OP
dimensions, comprising a TQM-STD scale system with 30 items. This scale system
demonstrates high reliability and validity, serving as an accurate and effective measurement
tool that provides theoretical reference and technical support for subsequent research. More
importantly, this research involves an interdisciplinary study between project management and
tourism management, applying the principles of project management to the management of
tourist attractions. This enriches the content of tourist attraction management and has the
potential to drive theoretical innovation and development in tourism management.
Managerial Implications
This study also holds significant practical implications. By conducting interviews in
5A-level tourist attractions and both online and on-site surveys, the research sample deeply
analyzes the connotations and dimensions of STD. By scientifically integrating TQM
principles into STD management, the study effectively guides innovation in methods during
STD processes, thereby enhancing the quality and standards of tourist attraction management.
Furthermore, the study thoroughly analyzes the dimensions of TQM and STD, as well as the

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Vol.46 No.2 July – December 2024, pp.1-24

influence of different TQM dimensions on STD, and incorporates them into the scale items.
This helps managers in tourist attractions effectively identify the influencing factors of STD
and explore reasonable paths for STD based on this knowledge, ultimately enhancing the
tourist experience and promoting sustainable development in tourist attractions. Furthermore,
the findings of this study provide support for advancing sustainable tourism development and
offer corresponding measurement tools. They promote the application of Total Quality
Management (TQM) principles in the field of the tourism and culture.

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