Introduction

China will build an economic model based on green, low-carbon, and sustainable development by 2025. From 2018 to 2022, tourism revenue in Sichuan Province contributed 9.3% to the GDP, indicating its significant role in economic development. By 2023, the Development and Reform Commission of Sichuan released a policy emphasizing the need for innovation in management to optimize STD. The Chengdu-Chongqing region, known for its abundant tourism resources, has witnessed increasing tourism development activities under the rural revitalization strategy. To ensure long-term sustainability, it is essential to incorporate systematic management frameworks. In recent years, researchers have employed both qualitative and quantitative analysis methods to study sustainable tourism development. E.g., Arora and Sharma (2024) explored the role of tourism in alleviating poverty. Zaman (2024) investigated promoting the benign development of tourism destinations through tourist behavior and local involvement. Schlesinger 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 and Valenzuela 2015), and tourist perception (Mukherjee et al. 2018). Additionally, scholars have analyzed the constraining factors and management approaches affecting STD, including policy enforcement (Yuan et al. 2024), sustainable development ideas (Nieuwland 2024), ecological and societal elements (Kim et al. 2024), performance assessment levels (Li et al. 2024), and low-carbon lifestyles (Sakcharoen 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), originally from the industrial sector, provides a structured approach to optimizing resources, enhancing service quality, and ensuring continuous improvement in tourism development. TQM fundamentally highlights the comprehensive management of products throughout their life cycle (Ahmed and Nahar 2024) and has been widely applied in infrastructure construction management (Anand 2024), corporate performance and innovation management (Anil and Satish 2016; 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 including ecological sustainability (Jum’a et al. 2023) and renewable energy (Deka et al. 2024). Despite its proven effectiveness in structured management, the application of TQM in tourism remains underexplored. Given the rapid expansion of tourism activities in the Chengdu-Chongqing region, a well-defined TQM framework tailored for STD is essential to support sustainable destination management. 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.

The Chengdu-Chongqing urban agglomeration, a major metropolitan area in Asia, is characterized by abundant tourism resources and diverse application scenarios, accompanied by a steadily increasing demand for tourism. In this context, the present study investigates the innovative application of Total Quality Management (TQM) in Sustainable Tourism Development (STD). Specifically, the study establishes the logical hypothesis relationship between TQM and STD, develops and designs a survey scale tailored to sustainable tourism development at the scale of tourism attractions, and constructs a structural equation model (SEM) for TQM and STD. The analysis focuses on examining the impact of various dimensions of TQM on STD, aiming to provide an innovative theoretical framework and empirical evidence for optimizing sustainable tourism management at the attraction scale. Additionally, the findings offer valuable theoretical insights and practical implications for the tourism development in the Chengdu-Chongqing urban agglomeration basin.

Literature review

STD dimensions

Tourism, as an integral component of the circular economy (Li et al. 2024), 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 (Fig. 1) on STD has primarily focused on three dimensions: economic benefits, social benefits, and ecological benefits (León-Gómez et al. 2021; Czernek-Marszałek 2020; Khan et al. 2020). These studies have explored aspects such as ecological awareness, fair development, resident livelihoods, tourism experiences, and environmental quality (Bramwell 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” (Spenceley and Rylance 2019; Zhao et al. 2024;Fernandez-Abila et al. 2024; Boluk et al. 2019). This definition underscores the necessity of balancing development with environmental responsibility. It further highlights the importance of advocacy and education, social participation, community culture, and green concepts in STD (Tabatabaei et al. 2024). Tourism management, tourism impact, and tourism relationships are also extensions of the connotations of STD. Some researchers emphasize that sustainable tourism development requires addressing the relationships between tourists, the environment, and local communities (Cheung and Li 2019). Achieving this balance requires long-term planning and layout (Angelevska-Najdeska and Rakicevik, 2012), broadening the perspectives of tourism managers (Ruhanen 2008), innovating management concepts (Martínez-Martínez 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 development concepts may limit sustainable tourism development. To achieve sustainable tourism development, strategies may involve enhancing performance assessment frameworks, altering energy consumption patterns (Hasan 2024), reducing carbon emissions (Sakcharoen et al. 2024), and enhancing overall tourism benefits (Rahman et al. 2024).

Fig. 1
Fig. 1
Full size image

A bibliometric analysis of recent research on sustainable tourism development (according to the PRISMA guidelines).

TQM impact on STD

Total Quality Management (TQM) is a significant management strategy (Ahmed and Nahar 2024) that has found wide application across various fields, such as transportation system management (Akhmatova et al. 2022), building quality control (Othman et al. 2020), managing corporate performance (Anil and Satish 2016; Singh et al. 2018), and fostering innovation (Yusr et al. 2017). Despite this, there remains a gap in the literature regarding TQM’s application to sustainable tourism development. TQM encompasses full participation, process management, and comprehensive oversight. For example, linking TQM’s process management principle to the practical challenge of stakeholder engagement in STD could offer a more structured approach to involving various stakeholders in decision-making. In this context, existing research results mainly analyze the impact of STD by studying single dimensions. Such as, studies suggest that community involvement is a prerequisite for sustainable tourism destination development (Iqbal et al. 2023). Tourism stakeholders and residents play a significant role in shaping sustainable tourism (Walas et al. 2024), highlighting the importance of stakeholder participation in tourism management to enhance visitor experiences (Roxas et al. 2020). Local governments, tourists, residents, and employees all contribute as key stakeholders in this process (Liu et al. 2019). Moreover, some studies have explored the entire process of tourism area development based on the concept of the whole process management, thereby revealing that tourism area development conforms to the lifecycle theory (Moore and Whitehall 2005). This ties into TQM’s emphasis on comprehensive process management, which could offer valuable insights into managing the lifecycle of tourism development more effectively. Scholars have analyzed the impact of comprehensive management on STD from multiple perspectives. For instance, Li (2024) suggests that community involvement, tourism certification, and public-private partnerships are important strategies for achieving sustainable tourism development. Likewise, Ahmad (2022) explores the impact of innovation management on sustainable development using panel data, while Roxas et al. (2020) employ systems thinking tools to establish causal relationships between sustainable tourism variables and analyze the impact of leadership management on STD.

TQM and 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. Building on these insights, 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 and Thomas 2020), and social responsibility (Wang 2023; Khurshid et al. 2022), with the number of dimensions typically ranging from 3 to 8. By contrast, scale development in the STD field mainly focuses on aspects such as residents (Lee 2013), as well as communities, tourism practitioners (Eslami et al. 2019), while also addressing environmental impacts (Rasoolimanesh et al. 2024; Chi and Liu 2023). These focal points align closely with previous literature on the fundamental aspects of STD. 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. Furthermore, direct comparisons with previous studies (as shown in Table 1) reveal significant differences in the dimensions and content of similar studies and our own, which further underscores the novelty of our perspective. To bridge this gap, we have developed a TQM-STD scale suitable for the scale of tourist areas, grounded in a comprehensive understanding of STD’s essence and the potential impact of TQM on STD.

Table 1 Comparative analysis between this study and relevant research.
Full size table

Literature synthesis and research gaps

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 FP, WPM, and CM. However, there is currently a lack of comprehensive research on the application of TQM to STD, with existing studies predominantly focusing on single dimensions, particularly emphasizing full participation and whole-process management. Thus, it is evident that there is a gap in the literature regarding the integration of TQM into sustainable tourism development research, indicating a need to encourage further exploration of TQM within the context of STD. Both TQM and STD have rich scales in their respective research fields. However, there is a clear gap in applicable scales for integrating TQM into the STD field, particularly in terms of assessing the impact of TQM on STD. Therefore, it is highly valuable to develop a TQM-STD scale that merges the essence of STD with 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.

Questions and hypotheses

Given the prosperous tourism development in the Chengdu-Chongqing urban agglomeration, especially when considering the diverse types and distribution of tourism resources, which make it an ideal experimental setting for this study, and in light of the identified research gaps, this study aims to explore how TQM can promote STD in this region. Specifically, the study will address the following questions:

Q 1. What is the impact of FP on STD?

Q 2. What is the impact of WPM on STD?

Q 3. What is the impact of CM on STD?

This study aims to fill the gaps in the existing literature by conducting an in-depth analysis of the role of TQM in sustainable tourism development, particularly in the context of the Chengdu-Chongqing urban agglomeration. To address the above questions, based on bibliometric analysis (Moher et al. 2010), relevant literature was reviewed (Table 1), and the potential impacts of the three dimensions of TQM on STD were examined, as illustrated in Fig. 2.

Fig. 2: Research questions and hypotheses.
Fig. 2: Research questions and hypotheses.
Full size image

Blue circle indicates the independent variables (endogenous variables), the green circle denotes the mediating variables, and the red circle signifies the dependent variables (exogenous variables).

Methodology

Materials and declarations

This study adhered to the Declaration of Helsinki and the ethical guidelines for academic research set forth by the National Science and Technology Ethics Committee of China. Ethical approval was granted by the Ethics Committee of Sichuan University of Science and Engineering (Approval No. SUSE20250107-001) on 31 August 2024, ensuring compliance with ethical standards for human research. All participants were informed about the study’s purpose, procedures, potential risks, and voluntary nature before participating in interviews and surveys. They provided written informed consent to confirm their voluntary participation. Personal information was kept strictly confidential, and all data were processed anonymously, accessible only to the research team, and securely stored to prevent unauthorized access. Participants had the right to withdraw from the study at any time without any negative consequences.

The materials for this study were divided into three stages. The first stage involved interviews with tourists, employees, and local officials, resulting in 66 interview records used to analyze the logical relationship between TQM and STD. The second stage was the pilot testing of the scale, during which 180 questionnaires were collected (response rate: 91.7%). The third stage was the formal testing phase, with 1050 questionnaires collected (response rate: 90.2%). Data collection was conducted in 13 tourist attractions within the Chengdu-Chongqing urban agglomeration (Fig. 3), with assistance from tourist attraction management departments, utilizing both online and offline methods.

Fig. 3: Survey sampling information in the study area.
Fig. 3: Survey sampling information in the study area.
Full size image

A Geographical location of the study area within China; B distribution of sampling sites within graded tourist attractions (1A–5A classes); C sampling site map with representative landscape photographs from each investigated tourist attraction.

Methodology

The framework of this paper is mainly divided into four sections (Fig. 4). The first section is the establishment of the logical relationship between TQM and STD. Based on bibliometric analysis and interview data, the construction relationship between TQM and STD is developed. The second section is scale development, where an item pool is constructed based on the logical relationship between TQM and STD and a small sample survey (180), using Discriminatory analysis (DA) and EFA analysis methods (Kvale and Brinkmann 2009; Worthen et al. 2014; Shrestha 2020). The third section involves a large sample survey (700) based on the item pool, and EFA is used to optimize the scale items, resulting in the formal scale. The fourth section verifies the impact of TQM on STD using an SEM model based on the formal scale. The CFA and path analysis conducted at this stage used the remaining 350 questionnaires from the total sample.

Fig. 4
Fig. 4
Full size image

Research framework and flowchart.

Analysis and findings

Item development

The settings of each construct dimension were evaluated through expert scoring and subjected to Item-Objective Congruence (IOC) testing, with the results shown in Table 2. Among them, the IOC value for TB is 0.71 (greater than 0.5), which is relatively lower compared to other constructs. This is due to either insufficient clarity in the definition of the construct or excessive complexity in the design of the items. Before the pre-survey, the dimensions of TB were optimized in the questionnaire to address this issue. TQM’s effect 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: whole process management (WPM), full participation (FP), overall perception (OP), comprehensive management (CM), and tourism benefits (TB). For the concepts of each dimension, please consult Table 2.

Table 2 Definition and explanation of the construct (dimension).
Full size table

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. Supported by the tourism administration agencies of the surveyed attraction were carried out. 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 then 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 (Fig. 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.

Fig. 5: Analysis results of the discriminant coefficient and critical ratio.
Fig. 5: Analysis results of the discriminant coefficient and critical ratio.
Full size image

A–C Discriminant coefficients of individual items across five dimensions: FP, WPM, CM, TB, and OP, respectively. The item marked in red has a t-value less than 3, and p > 0.05, indicating that it is not significant.

Based on the discriminant analysis of items, a reliability analysis was also conducted. As shown in Fig. 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 the scale. After deletion, the Cronbach’s α coefficients for the scale exceeded 0.8, indicating excellent internal consistency of the scales. From a theoretical perspective, the removal of these items suggests that certain aspects of FP, WPM, and OP may not align well with the core constructs being measured. This refinement ensures that each dimension of the scale remains conceptually coherent while improving reliability. 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.

Fig. 6: Cronbach’s coefficient reliability analysis.
Fig. 6: Cronbach’s coefficient reliability analysis.
Full size image

The second column shows the Cronbach’s alpha for OP-FP, while the fourth column displays the Cronbach’s alpha for OP-FP after removing FP1, WPM5, and OP6.

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 0.85, with a chi-square value of 2836.16 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 highly suitable for factor analysis. Upon examining the communalities (Table 3), 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 3 Communalities and factor loadings for each variable.
Full size table

Exploratory factor analysis

After conducting item analysis and validation, an initial scale was obtained. A total of 700 surveys were handed out, with 643 collected. After excluding 11 entries due to extremely short completion times or uniform answers, 632 were deemed valid, leading to an effective response rate of 90.2%.

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 4). Initially, the valid questionnaires (N = 632) were imported into SPSS software 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.

Table 4 EFA results (n = 632).
Full size table

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

1050 questionnaires were distributed (90.2% response rate), with 25 invalid questionnaires, 632 valid for EFA, and 290 for CFA. In this study, AMOS software was used to conduct CFA to validate the structural stability of the scale. As shown in Fig. 7, the goodness-of-fit indices for the overall dimension measurement model were examined. It was found that X2/df = 1.377, CFI = 0.99, GFI = 0.95, AGFI = 0.93, IFI = 0.99, TLI = 0.99, RMSEA = 0.02. All of these indices met the standard criteria for goodness-of-fit, indicating that the measurement model met the fit criteria.

Fig. 7
Fig. 7
Full size image

Fit test of the CFA model.

Convergence analysis results (Table 5) indicate that the factor loading values of the 30 items range from 0.69 to 0.87, 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 0.88 to 0.93, all exceeding the standard of 0.70. Additionally, the AVE values for each dimension were all greater than the standard value of 0.50, 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 5) 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 5) are all below the standard of 0.75 (Kline 2015), demonstrating ideal discriminant validity among the dimensions.

Table 5 Convergence evaluation of the formal scale.
Full size table

Hypothesis demonstration

SEM construction

Grounded in the theoretical framework of the hypotheses and the reliability and validity assessments of scale data, AMOS software was employed to construct a structural equation model (SEM) to explore the factors shaping the interaction between TQM and STD (Fig. 8). The values ranged from 0.78 to 0.79 for the SFLs of the five FP indicators, whereas those for WPM fell between 0.74 and 0.80. Similarly, the SFLs for CM were between 0.77 and 0.82, while those for OP spanned from 0.74 to 0.80. For the nine items of STD, the SFLs varied from 0.68 to 0.80, and for TB, they ranged from 0.71 to 0.83. All 39 observed variables achieved SFLs above the threshold of 0.6. Moreover, the SEM model demonstrated robust fit indices, with CFI = 0.98, IFI = 0.98, TLI = 0.98, GFI = 0.93, AGFI = 0.92, X²/df = 1.28 (<3), and RMSEA = 0.02 (below the cutoff of 0.08). These findings confirm that the SEM model adheres to the proposed theoretical structure and achieves excellent fit as validated by the goodness-of-fit metrics.

Fig. 8
Fig. 8
Full size image

Hypothesis demonstration of TQM’s influence on STD.

Path analysis

The SEM model’s goodness-of-fit underscores the suitability of its framework. To better understand the intricate dynamics between latent variables and assess their mutual impacts, a path analysis was performed using AMOS. The findings (Fig. 8; Table 6) reveal that all the expected associations in the framework are noteworthy (p < 0.05), except for the non-significant impact of TB on OP (p > 0.05). These results verify the robustness of the research hypotheses. Path analysis indicates that FP, WPM, and CM influence STD directly in a positive direction, with values of 0.19 (p ≤ 0.001), 0.12, and 0.10 (p ≤ 0.05). FP demonstrates the strongest direct influence, emphasizing its pivotal role among the TQM dimensions. Additionally, these independent variables influence STD indirectly through mediating variables, with CM-TB-STD emerging as the most influential pathway, characterized by a mean of 0.31 (p ≤ 0.001). The subsequent pathways are WPM-TB-STD (0.30, p ≤ 0.001) and FP-TB-STD (0.30, p ≤ 0.001). The results suggest that TQM primarily affects STD via indirect mechanisms, particularly by enhancing tourism benefits. In contrast, TQM’s indirect effects on STD through tourism perceptions are relatively moderate, with FP-OP-STD identified as the most impactful path, averaging a coefficient of 0.25 (p ≤ 0.001). Overall, the indirect effect of TQM on STD (0.28) through tourism benefits substantially exceeds its direct impact (0.13).

Table 6 Significance tests for hypotheses on variables.
Full size table

Discussion and conclusion

Discussion

Scale development validation

Based on bibliometric analysis and expert knowledge, the relationship between three dimensions of TQM and STD was established, successfully developing a TQM-STD scale consisting of five dimensions: FP, WPM, CM, TB, and OP, comprising 30 items. The construction process of the scale 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 (Fig. 9) are all below the standard of 0.75 (Kline 2015), indicating no model collinearity or overlap issues. This suggests that the first-order model (Fig. 8) is appropriate for this study, with no second-order constructs present.

Fig. 9
Fig. 9
Full size image

Two-dimensional correlation of the TQM-STD Scale System.

In the TQM-STD scale, the FP mainly revolve around tourists, residents, and scenic area staff, covering stakeholders in tourism (Roxas et al. 2020) and reflecting the concept of full participation. The WPM 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 lifecycle management (Ahmed and Nahar 2024). 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 (Li et al. 2024; Ahmad et al. 2022). 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 (León-Gómez et al. 2021; Czernek-Marszałek 2020; Khan et al. 2020). Timothy and Said (2023) proposed that residents’ perception of tourism includes positive and negative aspects, with positive perception showing high consistency with the OP item 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 and Qu 2023). This underscores the importance of tourism perception for sustainable tourism, which is highly relevant to the content included in the OP item of this study.

The five extracted factors (FP, WPM, CM, TB, and OP) are interrelated to enhance STD through both synergies and potential conflicts. FP and WPM are closely connected, with FP relying on effective WPM for the structured engagement of stakeholders. Strong WPM ensures that the inclusivity of FP is translated into actionable tourism strategies. CM serves as the operational framework that integrates FP and WPM, promoting synergy through coordinated resource management and policy implementation. However, if CM becomes overly rigid or lacks flexibility, it may limit stakeholder participation, potentially leading to conflicts. TB and OP act as mediators: when TB aligns with sustainable goals, it fosters positive OP, reinforcing support for the tourism system. However, disparities in TB can lead to negative OP, undermining the sustainability of the tourism development. Therefore, while these dimensions generally work together to drive STD, balancing their interrelations is crucial to avoid conflicts and enhance the overall effectiveness of the TQM-STD framework.

Hypotheses verification

The structural path analysis sheds light on the ways TQM dimensions (FP, WPM, CM) contribute to STD. FP emerges as the most impactful factor, showing the highest direct effect on STD (coefficient = 0.189, p < 0.001). Additionally, both OP and TB play crucial roles as mediators, amplifying the indirect impact of TQM on sustainable tourism development. To verify the reliability of these findings, a robust bootstrapping method (Edwards and Lambert 2007) was applied, performing 5000 resampling iterations at a 95% confidence interval. This analysis corroborates the findings obtained from the SEM model. The partial mediation role of OP and TB is evident, with VAF (Variance Accounted For) values ranging between 20 and 80%. Notably, TB demonstrates a stronger mediating influence compared to OP, as reflected in the standardized effect values: 0.10 for CM-TB-STD. These patterns indicate that TB serves as a more dominant channel for TQM’s impact on STD. Overall, the cumulative effects of TQM dimensions reveal FP as the leading contributor (total effect = 0.34), followed by WPM (0.28) and CM (0.26). This ranking highlights the pivotal role of FP in driving STD development. The alignment of these results with the path analysis further substantiates the research hypotheses and underscores the layered influence of TQM on STD through both direct and indirect mechanisms.

To substantiate the effect of TQM on sustainable tourism development, our findings were compared with prior studies (Achmad et al. 2022; Fatma et al. 2016; Ho et al. 2023; Jum’a et al. 2023; Khurshid et al. 2022), to ensure methodological precision and consistency. The first dimension, Full Participation (FP), highlights the involvement of all stakeholders such as employees in tourism destinations, local businesses, governing bodies, and residents in tourism initiatives. Our findings underscore the positive direct influence of FP on STD, as evidenced by a path coefficient of 0.34 (p < 0.001). This supports the notion that broader engagement can directly enhance STD, aligning with previous research (Yang et al. 2023; He et al. 2020). STD encapsulates multiple phases, including strategy development, implementation, and evaluation. Whole Process Management (WPM), the second TQM dimension, focuses on orchestrating all stages of tourism activities systematically. Our analysis confirms WPM’s significant effect on sustainable tourism development, having a path coefficient of 0.28 at the significance level of p < 0.001. Literature underscores the importance of WPM in fostering sustainability through streamlined planning and execution, especially under green tourism management frameworks (Waligo et al. 2013). Integrating WPM into TQM practices thus emerges as a well-justified approach for promoting STD (Xiaorong et al. 2013). The third dimension, Comprehensive Management (CM), involves a diverse range of practices, including personnel oversight (Singh et al. 2024), performance tracking (Erden Ayhun et al. 2024), and safety protocols (Efunniyi et al. 2024). Our study establishes that CM contributes to STD through both direct and mediated pathways, with total effects quantified at 0.26 (p < 0.001). TB and OP function as key mediators, amplifying the influence of CM on STD. Ultimately, the empirical results confirm that TQM significantly drives STD both directly and indirectly. The findings provide actionable recommendations for fostering sustainable tourism in the Chengdu-Chongqing region by leveraging TQM’s multidimensional framework.

Limitations

Some valuable findings were obtained during the study. However, the study also has certain limitations due to various reasons. 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 2014). Moreover, we should also clearly recognize that the sample collection was limited to a specific region. Future research can be expanded to different areas or cross-cultural contexts to validate the generalizability of the findings. 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. Furthermore, although the study employed path analysis and bootstrapping methods to validate the hypotheses, the impact of TQM on STD may be influenced by other potential variables not included in the model, such as policy interventions and technological innovations. Future research could enhance the explanatory power of the model by incorporating more advanced causal inference methods.

Conclusion

This study offers substantial insights into the integration of Total Quality Management (TQM) principles with Sustainable Tourism Development (STD). By validating a robust TQM-STD scale, this research introduces a comprehensive framework for understanding how TQM dimensions, including Full Participation (FP), Whole Process Management (WPM), and Comprehensive Management (CM), influence STD both directly and indirectly. The empirical findings demonstrate that FP is the most significant driver of STD. WPM and CM also make substantial contributions, with their effects mediated by factors such as tourism benefits (TB) and overall perceptions (OP).

From a theoretical perspective, this research advances our understanding of the multidimensional relationship between TQM and STD, offering a reliable measurement tool and contributing to the literature on sustainable tourism. The interdisciplinary approach, blending project management and tourism management principles, enriches the conceptualization of tourist attraction management and has the potential to drive future theoretical innovations. From a practical standpoint, the study’s methodology, which employs both online and on-site surveys, provides valuable insights for tourism practitioners. It guides the implementation of TQM strategies to enhance tourism sustainability. The findings also underscore the importance of stakeholder engagement, systematic planning, and comprehensive management in achieving sustainable tourism outcomes.

Overall, this research provides actionable recommendations for tourism destinations, particularly in the Chengdu-Chongqing region, and establishes a framework that can be applied globally to foster sustainable tourism practices. Further research should explore broader contexts and incorporate additional variables to deepen the understanding of how TQM can effectively contribute to sustainable tourism development.