Advancing Sustainable Development Through Urban Tourism: A Reflective Analysis of SDG 8.9 and 17 in Nanyang City, China

Abstract

This study investigates how urban tourism contributes to sustainable development, with a focus on SDGs 8.9 and 17 in Nanyang City. Drawing on a reflective measurement model and employing Partial Least Squares Structural Equation Modeling (PLS-SEM), this study examines the impact of urban tourism on cultural promotion, employment creation, and multi-stakeholder collaboration. A total of 300 surveys were collected from locals and visitors across Nanyang City to analyze these relationships. The results suggest that urban tourism promotes economic development but is also a means to preserve cultural heritage, and in turn directly supports SDG 8.9 for sustainable tourism, leading to job creation and local culture preservation. The analysis also shows that collaboration among governments, private organizations, and local communities is needed to achieve effective urban tourism governance, as stated in SDG 17. This study contributes a novel theoretical development to the literature, relating SDG-based governance with local tourism dynamics whilst providing an emic perspective of how mid-sized Chinese cities like Nanyang City, through collaborative and inclusive governance of tourism, put SDGs 8.9 and 17 into practice. The results contribute to current tourism–SDG frameworks by showing how the presence of local cultural endowments and decentralized governance structures homogenizes a specific pathway toward sustainable urban tourism. Additionally, the results provided practical guidance for tourism practitioners and policymakers on how to increase urban tourism systems’ diversity, inclusiveness, and resilience. This study’s limitations, being restricted to a single city with a small sample and a lack of longitudinal follow-up, may make findings difficult to generalize.

1. Introduction

Urban tourism has become an essential strategy for promoting sustainable development in many cities across China [1]. The United Nations’ global agenda, as noted in Sustainable Development Goal (SDG) 8.9, aims for countries to craft and implement policies that support sustainable tourism, offering local job opportunities and promoting the area’s unique culture and products by 2030 [2]. SDG 17 also points out that global support for development is improved by partnerships at the local, national and international levels [3]. Urban tourism allows for the combination of supporting the economy, saving cultural traditions and involving the world [4]. This study explores the role of urban tourism in Nanyang City, Henan Province, as a case for advancing SDG 8.9 and SDG 17. Nanyang City’s more than 10 million residents make it a prefecture-level city in the southwest region of Henan [5,6]. It is renowned for Nanyang City’s rich heritage and linked to Zhuge Liang, and there are many important heritage sites, among them Wuhou Temple, Dengzhou Ancient City, and Neixiang Ancient Government Office. In recent years, local governments in mid-sized Chinese cities have increasingly shifted from manufacturing and agriculture toward tourism to stimulate regional economic growth [7].

In 2023, Nanyang City received over 56 million domestic tourists, generating tourism revenue of approximately 46.3 billion yuan (about 6.5 billion USD), according to data from the Nanyang Municipal Bureau of Culture, Radio, Television, and Tourism. Many of the earnings from urban tourism were used to fund city festivals, art events, and culture events in Wolong District and Wancheng District [8]. As a result, many local people have new job opportunities in the service industry, while Nanyang City’s traditional handicrafts, calligraphy, and herbal medicine culture have gained attention [9]. Every year, the Zhuge Liang Cultural Festival draws crowds in Nanyang by combining academic events, cultural shows and activities to attract tourists [10]. In line with SDG target 8.9.1, which measures tourism’s contribution to GDP and employment, Nanyang’s tourism strategy prioritizes “slow tourism,” heritage revitalization, and cultural learning initiatives [11,12,13].

These gaps indicated a serious lack of knowledge of city-level SDG operationalization under the influence of urban tourism at mid-sized Chinese cities [14]. Furthermore, although the debate on mainstream integration of SDG into tourism planning has advanced [15,16], there is still not enough empirical evidence using PLS-SEM methods to assess how urban tourism contributes to SDG target 17.14.1 (strengthening policy coherence and partnerships for sustainable development). Thus, this research adopts the quantitatively tested PLS-SEM model to investigate how sustainable tourism innovation in Nanyang City promotes SDG 8.9 and SDG 17 as measured by economic growth, job creation, cultural conservation, multi-stakeholder participation, and principal coherence [17].

This study is guided by four key research questions that explore the intersection of urban tourism and sustainable development, with a particular focus on Sustainable Development Goals (SDG) 8.9 and 17. The first research question (RQ1) investigates how urban tourism in Nanyang City contributes to achieving SDG 8.9, specifically through the promotion of local culture, employment generation, and sustainable economic growth. The second research question (RQ2) seeks to explore the key challenges and opportunities associated with implementing sustainable tourism practices in Nanyang City in alignment with SDG 8.9. The third research question (RQ3) examines the extent to which multi-stakeholder partnerships, specifically collaborations among the public sector, private enterprises, and local communities, contribute to urban tourism development in Nanyang City, with reference to SDG 17. Finally, the fourth research question (RQ4) addresses how Nanyang City can strengthen its policy framework and community engagement mechanisms to further its contributions to SDG 8.9 and SDG 17 through urban tourism.

This study aligns with the aims of the Tourism Sustainomics framework by integrating economic, social, and environmental dimensions of urban tourism into a unified analysis of sustainability performance. Centering on SDGs 8.9 and 17, this study contributes to the debate on sustainability transformations in tourism governance, revealing how city-level partnerships, cultural industries, and digital platforms synergize to foster inclusive and resilient development. While existing studies have examined the adoption of SDG principles in urban tourism governance at a national scale, and in major cities, including Beijing, Shanghai, or Shenzhen, less attention has been paid to medium-sized cities like Nanyang, where governance arrangements, economic development, and community engagement are substantially different. As such, this research adds to the SDG–tourism literature by demonstrating how sustainable tourism development unfolds in a mid-tier city context and providing further empirical and conceptual weight to available tourism–SDG frameworks.

2. Literature Review

2.1. Sustainable Development Goals (SDGs) and Sustainable Tourism

Peace and prosperity around the world were guided by the Sustainable Development Goals (SDGs), which the United Nations approved in 2015 [18]. The UN continues to support the SDGs, as Goal 8.9 aims to make tourism sustainable by enhancing local culture and products, as well as Goal 17, focusing partnership development to ensure measurable progress in sustainable development and institutional or organizational interaction between all sectors. This twin purpose sets urban tourism not only as an engine of economic development, but also as a tool for sustainable inclusive growth and environmental conservation and cooperative governance. Although tourism is a major part of sustainable development, some researchers argued that existing methods have proven to be less sustainable than desired [19]. Those studying tourism have pointed out that there has been undue focus on coupling tourism with sustainability rather than restructuring the institutions underpinning the tourism system [20]. According to Rutty and his team [21], there is usually greater emphasis on profit than on caring for the environment and society. As a result, places like Venice have now faced local protests and pressure on their environment [22].

The World Tourism Organization (UNWTO) defines sustainable tourism as “tourism that takes full account of its current and future economic, social, and environmental impacts” [23]. The UNWTO, 2023 [24] believes that it should address the needs of visitors, tourism entrepreneurs and those who live at these destinations. The goal of sustainable tourism is to retain the natural and cultural value of the area, enhance the local community’s income, and lessen its harm to nature [25]. In this way, tourism constitutes a multi-faceted system articulating economic performance (accomplished through job creation and income generation), cultural vitality (achieved via heritage conservation and identity) and environmental responsibility (enacted through preservation and low carbon measures). Researchers have shifted more attention to tourism’s contribution to achieving the SDGs. According to a recent paper by Pahrudin et al. [26], sustainability is now a key aspect studied in tourism research, mostly in tourism marketing and management, since tourism must match up with global sustainability targets. These studies also emphasized the necessity to apply SDGs at the city level with quantifiable benchmarks such as SDG 8.9.1 (a proportion of tourism employment and share in GDP) and SDG 17.14.1 (policy coherence for sustainable development). In a parallel example, Puah et al. [27] reviewed the economic value of tourism in Malaysia and showed that the sector helps the local economy, adds jobs, and improves living standards, largely in urban areas undergoing economic development and growth. They demonstrate that sustainable tourism and economic development are mutually reinforcing, particularly in low middle-income countries looking for inclusion and resilience. The central government has made sure that SDG priorities are part of China’s tourism and countryside revival policies through its program called “Beautiful China Initiative” [28]. This policy direction resonates with the recent acknowledgment of the role that medium-sized cities like Nanyang can play as “living laboratories” for real-world experience in promoting SDG-centered tourism models to reconcile economic transformation and sustainability. The Sustainomics approach highlights the interconnectedness of economic development, social justice and environmental preservation in achieving sustainable development over the long term. In this perspective, sustainable urban tourism, as in Nanyang City, can become a practical expression of Sustainomics itself through the integration between (economic), preservation, and inclusivity (social) and resource conservation (environmental). Therefore, by focusing on SDG 8.9 and 17 in Nanyang City’s urban tourism governance, this study’s strategy helps to contextualize Sustainomics at the city level and model multi-dimensional sustainability assessment.

2.2. Urban Tourism and Sustainable Development in Nanyang City

Urban tourism in Nanyang City demonstrates how local governments can operationalize SDGs 8.9 and 17 through cultural events, economic inclusion, and cross-sector partnerships. A rising trend in urban tourism, especially in Chinese cities, is event tourism, guided by efforts to add value to unique cultural, historical, and artistic backgrounds and boost their appeal in the economy [29]. Exhibitions, art fairs, and local festivals encourage visitors to visit and let the area become known. In the bigger picture, Lee et al. [30] and Armbrecht and Andersson [31] noted that Ritchie and Beliveau [32] were the first to identify the economic value of tourism events. Later studies [33,34,35] investigated how events influence destination image, build brand equity, and local economic structures, linking cultural celebration to tourism marketing and emotional engagement. The Wuhou Temple Cultural Tourism Festival in Nanyang City is an excellent model for how the story of history, traditional music, and theater can be used to serve both tourism and community well-being [17,36]. The Zhuge Liang Cultural Festival is a festival with performances, storytelling, and community events that are good for business and locals alike [36]. As a result, the city uses its Han Dynasty history and success in Traditional Chinese Medicine (TCM) to hold events that bring together people from all over the world [37,38]. Instances like this serve not only to safeguard intangible heritage but also to build intersectoral relationships between artists, micro-businesses, and local government that generate employment opportunities and contribute to the achievement of SDG 8.9 through culture-led development.

In economic terms, tourism provides a local economic development vehicle. Researchers assess how tourism improves the economy by checking income, job creation in tertiary industries, and development in individual earnings. With the global COVID-19 outbreak and along with, tourism provided a 148% boost to the global economy, going from USD 983.5 billion to USD 1458.7 billion from 2010 to 2019, making it clear how powerful tourism is for the world’s economies [39,40]. The Henan Provincial Statistics Bureau pointed out that Nanyang’s tourism sector employs more than 150,000 people, highlighting its importance for urban job creation. Empirical investigations revealed that the expansion of tourism was positively associated with household income growth and job diversification, especially for younger households and those with lower incomes [19,41,42,43]. Hospitality, retail, and transportation services are driven by events and exhibitions that lead to inclusive growth [44]. In addition, Moore and Quinn [45] argue that art-based festivals have a greater economic impact in rural and peri-urban areas. Nanyang City’s tourism model reflects this process by passing on development benefits to its neighbouring Neixiang County, contributing to the harmonious development of regions under SDG 8.

Just as significant is Nanyang city’s shared governance, a theme of SDG 17 on partnership. MacDonald et al. [46] highlighted that strong partnership between the public and private sectors is fundamental for achieving sustainable development. In tourism, local governments, private investors, civil society, and international investors are expected to cooperate [47,48]. Nanyang City has developed innovative partnerships with local universities, the China Association of Tourism and Culture, and digital platforms, Ctrip and Meituan, which aid in data collection and evidence-based new policymaking. These partnerships lead to more money, greater knowledge exchange, and boost innovation and how the firm survives tough times [49]. As an example, data-sharing agreements give bureaus insights into tourism so they can distribute tourists better, improve how festivals are arranged, and lessen the burden on both infrastructure and the environment [50]. Further, organizations from different industries are now cooperating to organize green events [51]. In 2023, the TCM Expo in Nanyang launched “Low-Carbon Tourism Events,” including eco-friendly materials, waste sorting, and carbon-cutting transportation to lessen emissions. This co-governance model demonstrates how Nanyang’s policies align with SDG 17.14.1’s goal of improving policy coherence for sustainable development.

Tourism also functions as a socio-economic equalizer, provides employment for many, and influence city-country relationships, as well helps connect people doing informal jobs with formal work [52,53,54,55]. Due to tourism in Nanyang City, the Hospitality and cultural sector offers new jobs to youth and women as well as Artisans, while the transport sector provides additional logistics and service jobs. The most recent Nanyang Urban Development Report revealed that tourism-related services in 2023 created more than 20% of new jobs in the tertiary sector, proving that the industry helps support growth in employment outside major cities [56]. Furthermore, the Wuhou Festival helps to create a temporary market for local vendors, caterers, singers, and artisans. These short-term jobs usually help marginalized people become involved in urban economies, which supports inclusive development, as discussed in SDG 8 [57]. Also, by creating jobs that young people can take, city tourism can hold back or even reverse the migration of people from urban areas [58].

2.3. Challenges and Research Gaps

Although Nanyang City offers a strong blueprint for sustainable tourism, several issues stand in the way of fully adopting Sustainable Development Goals 8.9 and 17. A major issue is that many visitors to festivals can cause a lot of stress on the environment, using up water, leading to more waste, and raising the overload on transportation remain significant challenges in operationalizing SDG indicators at the municipal level. In addition, resources, for example, water and transportation, are strained by festival tourism, and commercialization can also challenge the authenticity of local culture [17,59]. The lack of access to tourism data limits academic research and policy comparison, also leading to a concentration in urban areas rather than peripheral areas [60]. These tensions are symptomatic of a much larger global discussion about the balance between growth and sustainability in tourism governance. According to Rutty et al. [21], argue that policymakers must weigh trade-offs between economic expansion, social inclusion, and environmental protection [61]. In addition, there is a theoretical and empirical blank on how partnerships at the city level, collaborative data sharing systems, and participatory governance structures can promote the achievement of SDGs, with an emphasis on urban tourism within medium-sized Chinese cities, such as Nanyang City.

2.4. Development of Research Hypotheses

To develop survey items aligned with each research question, this study adapted and integrated measurement indicators from established scholarly works and institutional frameworks relevant to sustainable urban tourism and the Sustainable Development Goals (SDGs). This study extends existing tourism–Sustainable Development Goals (tourism-SDG) models by incorporating governance theory and context-based sustainability perspectives, to understand how urban tourism can facilitate the delivery of SDGs in a mid-sized Chinese city. In contrast with previous studies on enclave tourism or high-level indicators of development, this study prioritises the governance practices at the local level, the involvement of stakeholders, and heritage flows from an urban standpoint, identifying Nanyang City as a unique paradigm for region-specific considerations in developing sustainable tourism projects. Special attention was paid to how SDG indicators 8.9.1 (tourism contributions to GDP and jobs) and 17.14.1 (policy coherence for sustainable development) could be operationalised using measuring constructs as well as empirical data where such were available or feasible. For Research Question 1 (RQ1), which explores how urban tourism in Nanyang contributes to achieving SDG 8.9, focusing on the promotion of local culture, employment generation, and sustainable economic growth, the survey items were adapted from the United Nations World Tourism Organization [62]. In addition, items were grounded and adapted from [63], who emphasized the relationship between community involvement and sustainable tourism development. Reports published by the World Travel and Tourism Council in 2021 and the United Nations Development Programme in 2020 provided valuable insights into the role of tourism in driving economic growth and creating opportunities for local people. For Research Question 2 (RQ2), which investigates the challenges and opportunities related to implementing sustainable tourism practices in alignment with SDG 8.9, the survey items were informed by [64]. Thanks to the scale, it is easy to contrast opinions on how to deal with infrastructure demands, the environment, and sustainable abilities. More opinions came from [65,66], showing that problems mainly stem from having no laws, too many tourists, and harm to nature.

For Research Question 3 (RQ3), which examines the extent to which multi-stakeholder partnerships, specifically collaborations among public institutions, private enterprises, and local communities, contribute to urban tourism development in line with SDG 17, the survey items were developed using governance frameworks from the Organisation for Economic Cooperation and Development [67]. Supporting theory was found in [68], who directed attention to the benefits of community involvement and partnering in tourism policies. Lastly, for Research Question 4 (RQ4), which explores how strengthening policy frameworks and community engagement can improve Nanyang City’s capacity to achieve SDG 8.9 and SDG 17 through urban tourism development, survey items were developed with reference to [69] Tourism Planning and Policy, which stresses participatory governance, community empowerment, and integrative policy frameworks. Indicators 17.14.1 of the UN SDGs on “enhancing policy coherence for sustainable development” were also looked at, stressing the importance of both cross-sectoral cooperation and including all groups in decisions. Drawing from the objectives and questions of this research, hypotheses are set up to determine the links between urban tourism and sustainable development in Nanyang City, mostly focusing on Goals 8.9 and 17 of the Sustainable Development Goals. Below is the list of hypotheses used in this research:

H1a: 

Urban tourism in Nanyang City positively contributes to the promotion of local culture, thereby supporting the achievement of SDG 8.9.

H1b: 

Urban tourism in Nanyang City positively influences employment generation in the local tertiary sector, facilitating progress toward SDG 8.9.

H1c: 

Urban tourism in Nanyang City significantly promotes sustainable economic growth in alignment with SDG 8.9.

H2: 

Various challenges negatively affect the implementation of sustainable tourism practices in Nanyang City, whereas identified opportunities facilitate their successful adoption in alignment with SDG 8.9.

H2a: 

Structural, environmental, and policy-related challenges negatively affect the implementation of sustainable tourism practices in Nanyang City, thereby hindering progress toward SDG 8.9.

H2b: 

Institutional innovation, cultural resources, and stakeholder collaboration positively influence the successful adoption of sustainable tourism practices in Nanyang City, facilitating alignment with SDG 8.9.

H3a: 

Institutional coordination among governmental agencies, private enterprises, and tourism organizations (Multi-stakeholder partnerships) significantly enhances policy coherence and governance effectiveness in urban tourism development in Nanyang City, consistent with SDG 17.

H3b: 

(Multi-stakeholder partnerships) Community co-production that, through local participation, shared decision-making, and cultural co-creation, can strengthen the sustainability and long-term impact of urban tourism initiatives in Nanyang City, contributing to both SDG 8.9 and SDG 17.

H4: 

Policy coherence and participatory governance mechanisms jointly impacting the relationship between partnerships and SDG advancement, significantly improving Nanyang City’s capacity to achieve SDG 8.9 and SDG 17 through sustainable urban tourism development.

3. Research Methodology

This study adopts a quantitative research approach to examine the relationship between urban tourism and sustainable development in Nanyang City, Henan Province, China, with a specific focus on Sustainable Development Goals (SDG) 8.9 and 17. This study employs a cross-sectional survey design of a structured nature, using validated scales reported earlier. Structured questionnaires were administered face-to-face and digitally (via tablets) to both residents and tourists in urban tourism locations around Nanyang City. From a set of individuals living in and visiting Wolong District, Wancheng District, and sites, including Wuhou Temple, Zhang Zhongjing TCM Park, and the Dengzhou Ancient City, a total of 300 respondents were selected using a combination of convenience and purposive sampling methods to ensure the participation of local and visitor opinions. Whilst convenience and purposive sampling were deemed appropriate for the purposes of exploratory analysis within PLS-SEM through SmartPLS 4, this may have influenced bias, especially given that data gathering took place during festive periods when tourism is at its prime. Accordingly, the sample may be over-representative of festival-goers and under-representative of residents or visitors participating in non-festival tourist activities. Future research should attempt to gain a more stratified sample for both peak and off-peak tourist seasons so that tourism’s diverse economic, social, and cultural impacts will be better represented in Nanyang City.

This study purposefully incorporated both tourists and local residents in order to provide a total perspective on the role that tourism plays in the sustainable development of Nanyang City. External visitors were included to measure the peripheral profile of Nanyang City’s cultural attractiveness, service quality, and urban tourism experience; whereas residents were incorporated to assess the social, cultural, and economic impact of tourism on the local population. Including both those groups seemed to be most suitable in terms of addressing tourism’s contribution to SDG 8.9 and SDG 17. Nevertheless, this may have driven the homogeneity of the sample down because visitors and locals are dissimilar in motivation, expectations, and knowledge about tourism products in Nanyang City. Yet, the combination was judged to be methodologically appropriate for exploratory PLS-SEM analysis, as it allowed for obtaining a view of tourism impacts from several stakeholder categories.

3.1. Instrument Development

On-site participants will be able to fill out the questionnaire using the digital survey forms on their iPads. The research team walked around selected high-traffic urban tourism areas during festivals and peak visitation periods, inviting individuals to voluntarily participate. Every participant received a short spoken explanation of why this study is being carried out and asked to sign a consent form before taking the questionnaire. All questions in the questionnaire are closed, with answers ranging from 1 for strongly disagree to 5 for strongly agree on the Likert scale. Items are designed to measure key constructs related to urban tourism benefits, challenges, sustainability practices, and partnership perceptions. These constructs are aligned with the research questions addressing how urban tourism supports SDG 8.9 (promotion of local culture [70,71], job creation [72,73], sustainable economic growth [74,75,76,77,78]) and SDG 17 (multi-stakeholder partnerships [79,80] and governance mechanisms [81,82]). More details information can be found in Supplementary Materials.

The instrument was divided into sections reflecting each hypothesis:

• Urban tourism benefits (local culture, employment, economic growth)
• Sustainable tourism challenges and opportunities
• Multi-stakeholder partnerships and community participation
• Policy and engagement effectiveness

3.2. Pilot Testing

A pilot study with 30 respondents was conducted to test the clarity and reliability of the questionnaire. Based on pilot feedback, minor adjustments were made to simplify wording. Cronbach’s alpha values for all constructs exceeded 0.70, indicating satisfactory reliability for the main survey

3.3. Data Handling and Analysis

The data then be put into Microsoft Excel and checked for missing or questionable entries before anything else is carried out. After the data are cleaned, they are then imported into SmartPLS (PLS-SEM) for analysis. The field chooses PLS-SEM as it is appropriate for early research stages, global concept frameworks, and research groups that are not very large. Since this study uses a reflective measurement model, the first step of analysis was to check both the indicator reliability and internal consistency of the measurement model [83]. Among other things, review outer loadings, Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) to examine if the construct converges with itself. Essential analysis for confirming that constructs in the model are measurably distinct is carried out by following the Fornell-Larcker criterion and cross-loadings [84]. When the psychometric qualities of the observations are determined, the next task is to assess the connections among the different variables in the structural model [85]. After selecting significant variables, the researchers watch out for their path coefficients, R² values, and f² values. Bootstrapping using 5000 subsamples was carried out to test whether the path coefficients have a significant effect [86]. Through this strong strategy, the values for the parameters can be trusted, and the precise evaluation of the theory becomes possible.

3.4. Second-Order Model Strategy

For analyses, this study utilises a model that is reflective and second-order, in which first-order constructs (e.g., local culture, employment, economic growth) are dimensions of larger second-order models (e.g., Urban Tourism Benefits). For both methods, this study used the Path Weighting Scheme with up to 300 iterations and a convergence criterion of 1 × 10⁻⁷. This study formulated a second-order structural model that reflects the complexity of urban tourism as well as its impact on sustainable development results. In particular, “Urban Tourism Benefits” is represented as a second-order construct that includes three first-order reflective factors (Cultural Promotion (H1a), Employment Generation (H1b), and Economic Growth (H1c)) embedded in the simultaneous socio-economic contribution of tourism towards SDG 8.9 [87]. This prioritization provides a more comprehensive view of how different types of tourism benefits articulate and, in combination, shape the sustainability dynamics [88,89]. Likewise, the second-order factor “Collaborative Governance” is considered an amalgam of two first-order, yet correlated factors: “Institutional Coordination” (H3a) and “Community Co-Production” (H3b). This modeling choice is based on theoretical differentiations in governance theories and forms of participatory approaches to development [90,91], which posit that successful partnerships in sustainable tourism arise as a consequence of institutional alignment from top-down and empowerment at the bottom-up levels.

3.5. Ethical Consideration

Every effort was made to ensure that ethical procedures were followed the entire time. No one’s name will be revealed, and the data will only be used for investigation in this research. The pilot group made sure the methods and tools would be straightforward, appropriate, and reliable for everyone before data was actually collected.

4. Findings

4.1. Measurement Model Assessment

4.1.1. Reliability and Convergent Validity

To evaluate the reliability and convergent validity of constructs, Cronbach’s Alpha, Composite Reliability (CR), and Average Variance Extracted (AVE) were examined (refer to

Table 1. Construct Reliability and Validity—Second Order.

Construct	Cronbach’s Alpha	Composite Reliability (rho_a)	Composite Reliability (rho_c)	AVE
Advancement of SDG 8.9 and 17 (DV)	0.830	0.872	0.877	0.525

). The values for Cronbach’s Alpha (0.830), rho_a (0.872), and rho_c (0.877) exceed the recommended threshold of 0.70, indicating good internal consistency. The AVE value of 0.525 also exceeds the 0.50 cutoff, suggesting that the construct explains more than half of the variance in its indicators [88,89], which confirms convergent validity [83].

Table 2. Construct Reliability and Validity—First order.

	Cronbach’s Alpha	Composite Reliability (rho_a)	Composite Reliability (rho_c)	Average Variance Extracted (AVE)
Economic Growth	0.844	0.857	0.889	0.616
Employment	0.898	0.899	0.924	0.710
Local Culture	0.767	0.779	0.840	0.512
Multi-Partnership	0.875	0.878	0.909	0.666
Partnerships	0.884	0.889	0.915	0.683
Policy & Engagement	0.889	0.891	0.918	0.693
Sustainable Tourism Challenges	0.859	0.864	0.898	0.639

presents the reliability and validity metrics for the first-order constructs in this study. The test results for the constructs are very strong, as their Cronbach’s alpha scores range from 0.767 for Local Culture to 0.898 for Employment, all of which are well above the acceptable overall level of 0.70. Composite reliability assessed using both rho_a and rho_c further confirms the constructs’ reliability, with values consistently above 0.75 for rho_a and above 0.84 for rho_c, suggesting that the indicators reliably measure their respective constructs. For convergent validity, values ranging from 0.512 (Local Culture) to 0.710 (Employment) indicate that each construct explains a sufficient portion of the changes observed in its indicators, which is why all values exceed 0.50. In general, the study results indicate that the first-order constructs are reliable and confirm their relationship with related variables, allowing for further analysis.

4.1.2. Discriminant Validity—Fornell-Larcker Criterion

This study assessed discriminant validity using the Fornell-Larcker criterion, which says that the square root of the AVE from a construct should be greater than its correlations with other constructs [88,89]. The diagonal values represent the square roots of the AVE, which are all greater than the inter-construct correlations (refer to

Table 3. Fornell-Larcker Discriminant Validity.

Construct	DV: SDG 8.9 & 17	Contribution to Local Culture	Employment Generation	Sustainable Economic Growth	Challenges & Opportunities	Multi-Stakeholder Partnerships	Multi-Stakeholder Partnerships	Policy Frameworks & Community Engagement
DV: SDG 8.9 & 17	0.725
Contribution to Local Culture	0.216	1.000
Employment Generation	0.832	0.171	1.000
Sustainable Economic Growth	0.860	0.116	0.851	1.000
Challenges & Opportunities	0.735	0.039	0.573	0.752	1.000
Multi-Stakeholder Partnerships	0.740	0.121	0.427	0.403	0.333	1.000
Multi-Stakeholder Partnerships	0.724	0.125	0.413	0.389	0.300	0.878	1.000
Policy Frameworks & Community Engagement	0.764	0.167	0.550	0.570	0.486	0.487	0.472	1.000

). This supports the discriminant validity of the constructs.

4.2. Structural Model Assessment

4.2.1. Hypotheses Testing and Path Coefficients

The structural model was assessed using path coefficients, T-statistics, and p-values to evaluate the significance of each hypothesis. All paths are statistically significant at p < 0.01, indicating strong support for all hypothesized relationships (refer to

Table 4. Path Coefficients and Hypotheses Testing.

Hypothesis	Path Coefficient (O)	Sample Mean (M)	Std. Dev (STDEV)	T-Statistic	p-Value
H1a: Contribution to Local Culture → DV	0.059	0.058	0.019	3.051	0.002
H1b: Employment Generation → DV	0.226	0.226	0.007	30.785	0.000
H1c: Sustainable Economic Growth → DV	0.234	0.234	0.008	31.166	0.000
H2: Challenges & Opportunities → DV	0.200	0.200	0.008	26.062	0.000
H3a: Multi-Stakeholder Partnerships A → DV	0.201	0.201	0.006	33.874	0.000
H3b: Multi-Stakeholder Partnerships B → DV	0.197	0.197	0.006	33.374	0.000
H4: Policy Frameworks & Community Engagement → DV	0.208	0.208	0.008	27.124	0.000

Note: DV → Advancement of SDGs 8.9 and 17.

). The highest path coefficient is for H1c (0.234), suggesting Sustainable Economic Growth is the strongest predictor of the advancement of SDGs 8.9 and 17, followed closely by H1b (Employment Generation) and H4 (Policy Frameworks & Community Engagement).

4.2.2. Outer Loadings

These loadings reflect the degree to which observed variables are associated with their underlying constructs. With the exception of Contribution to Local Culture (0.216), every other loading meets or even exceeds the 0.70 target (see

Table 5. Outer Loadings.

Indicator	Loading
LV Scores—Economic Growth	0.860
LV Scores—Employment	1.000
LV Scores—Local Culture	1.000
LV Scores—Multi-Partnership A	1.000
LV Scores—Partnerships B	1.000
LV Scores—Policy & Engagement	1.000
LV Scores—Sustainable Tourism Challenges & Opportunities)	1.000
Contribution to Local Culture (H1a)	0.216 (Dropped (below 0.70 threshold))
Employment Generation (H1b)	0.832
Sustainable Economic Growth (H1c)	1.000
Multi-Partnership A (H3a)	0.724
Multi-Partnership B (H3b)	0.740
Policy & Engagement (H4)	0.764
Sustainable Tourism Challenges & Opportunities (H2)	0.735

Notes: 1. Confidence intervals (CIs) were calculated using bootstrapping with 5000 resamples. 2. Items with outer loadings below 0.70 were considered for removal. Only “Contribution to Local Culture (H1a)” did not meet the threshold and was dropped from further analysis. 3. All other indicators demonstrated acceptable convergent validity, supporting the measurement model’s reliability.

).

4.2.3. Coefficient of Determination (R²)

The R² value indicates the proportion of variance in the dependent variable that is explained by the independent variables. With an R² equal to 0.886, the variation in SDGs 8.9 and 17 is explained by the independent variables, as shown in

Table 6. Coefficient of Determination.

Dependent Variable	R2	Adjusted R2
Advancement of SDG 8.9 and 17 (DV)	0.886	0.883

. These findings demonstrate that the model is highly effective in explaining the data.

4.2.4. Heterotrait–Monotrait Ratio (HTMT)

Table 7. HTMT.

	DV	EG	EMP	LC	MP	P	P&E	STCO
DV
EG	0.847
EMP	0.833	0.862
LC	0.404	0.139	0.204
MP	0.844	0.444	0.463	0.140
P	0.814	0.463	0.479	0.148	0.798
P&E	0.806	0.655	0.617	0.193	0.534	0.547
STCO	0.720	0.805	0.654	0.066	0.345	0.382	0.556

Notes: DV → SDG 8.9 & 17; EG → Economic Growth; EMP → Employment; LC → Local Culture; MP → Multi-Stakeholder Partnerships; P → Partnerships; P&E → Policy & Engagement; STCO → Sustainable Tourism Challenges & Opportunities.

reports the Heterotrait–Monotrait Ratio (HTMT) statistics for discriminant validity of this study’s constructs. All HTMT values are less than the threshold of 0.90, which reflects good evidence of discriminant validity and suggests that each construct is a distinct empirical entity. The strongest associations were found between Economic Growth (EG) and Employment (EMP) (HTMT = 0.862) and Multi-Stakeholder Partnerships (MP) and Partnerships (P) (HTMT = 0.798), which corresponded to the narrow connection in terms of concepts within the sustainable urban tourism development. In contrast, Local Culture (LC) had generally low HTMT values with other constructs (from 0.066 to 0.463), indicating that it contributed uniquely to the model. The dependent variables, SDG 8.9 & 17 (DV) reported moderate correlations as well with other dimensions, particularly with Economic Growth (0.847) and Employment (0.833), which means that a highly significant strong relationship on sustainable tourism performance is associated with economic–social outcomes. The HTMT analysis provides evidence for the construct validity and discriminant validity of the measurement model.

4.2.5. f² Analysis

The f² was used to test the effect size of each independent variable on the dependent construct (see

Table 8. f² Analysis Outcomes for Constructs.

	DV	EG	EMP	LC	MP	P	P&E	STCO
DV
EG	0.057
EMP	0.155
LC	0.022
MP	0.066
P	0.061
P&E	0.286
STCO	0.063

Notes: DV → SDG 8.9 & 17; EG → Economic Growth; EMP → Employment; LC → Local Culture; MP → Multi-Stakeholder Partnerships; P → Partnerships; P&E → Policy & Engagement; STCO → Sustainable Tourism Challenges & Opportunities.

). In accordance with Cohen’s [92] interpretation, effects were the strongest for Policy and Engagement (f² = 0.286) with medium-to-large practical significance to the dependent variable influence. This result emphasizes the need for effective policy and stakeholders’ input to entrench sustainable tourism development. Employment (f² = 0.155) has a moderate effect, but the explanation of variance in the dependent construct is substantial. The Economic Growth, Multi-Partnership, Partnerships and Sustainable Tourism Challenges & Opportunities showed weak, but meaningful effects to the model (f² from 0.057 to 0.066), maintaining that those constructs do contribute little but minimal contributions into the explanatory capacity of the model, in the model’s explanatory power. In contrast, Local Culture (f² = 0.022) shows a minimal effect, suggesting that cultural factors have a relatively limited impact in this context.

4.2.6. The Variance Inflation Factor (VIF) Analysis

The Variance Inflation Factor (VIF) scores were further checked to see if there was an indication of multicollinearity among the predictor constructs (see

Table 9. VIF Outcomes.

	VIF
H1a A	1.017
H1a A	1.311
H1a B	1.506
H1a C	1.421
H1a D	1.448
H1a E	1.422
H1b A	1.661
H1b A	2.069
H1b B	2.226
H1b C	2.362
H1b D	2.403
H1b E	2.379
H1c A	1.775
H1c A	1.994
H1c B	2.044
H1c C	2.160
H1c D	1.686
H1c E	1.608
H2 A	1.325
H2 A	2.015
H2 B	1.801
H2 C	1.837
H2 D	1.833
H2 E	1.826
H3a A	1.717
H3a A	2.238
H3a B	1.991
H3a C	2.098
H3a D	2.159
H3a E	2.081
H3b A	1.829
H3b A	1.671
H3b B	2.113
H3b C	2.150
H3b D	1.937
H3b E	2.018
H4 A	1.360
H4 A	2.070
H4 B	2.133
H4 C	2.167
H4 D	2.253
H4 E	2.141

Notes: A, B, C, D, E after each H1a and etc. representing the second-order of constructs.

). As recommended by Hair et al. [93], values of VIF less than 3.0 indicate that there is a lack of serious collinear issues, and VIFs greater than 5.0 could be highly indicative of problematic multicollinearity. The results of this analysis showed that the value for each VIF ranged from 1.017 to 2.403, and were all well below the commonly accepted cutoff limit of 3.0. These findings verify that the potential problem of collinearity is avoided in the structural model, and each individual construct contributes independently to explain the variance in the dependent variables. Therefore, the path coefficient estimates can be interpreted with confidence, as the model satisfies the assumption of minimal multicollinearity.

4.2.7. Q² Analysis

The Q²predicted value of 0.879 indicates that the model possesses a strong predictive capability for the dependent construct (DV) (refer to

Table 10. Q² Outcomes for DV.

	Q2predict	RMSE	MAE
DV	0.879	0.348	0.275

). Both RMSE (0.348) and MAE (0.275) are low, further confirming the model’s high predictive accuracy and minimal error. Therefore, the model demonstrates substantial out-of-sample predictive power and reliability in forecasting outcomes related to sustainable tourism development indicators.

The predictive relevance of the model was assessed using the PLSpredict procedure. As shown in

Table 11. Q² predict values for the hypothesized relationships.

	Q2Predict	PLS-SEM_RMSE	PLS-SEM_MAE	LM_RMSE	LM_MAE	IA_RMSE	IA_MAE
Contribution to Local Culture	0.011	0.014	0.058	0.000	0.000	1.020	0.871
Employment Generation	0.452	0.302	0.347	0.000	0.000	1.218	0.980
Sustainable Economic Growth	0.481	0.361	0.306	0.000	0.000	1.195	0.968
Challenges & Opportunities	0.303	0.050	0.077	0.000	0.000	1.257	1.083
Multi-Stakeholder Partnerships A	0.396	0.401	0.329	0.000	0.000	1.286	1.077
Multi-Stakeholder Partnerships B	0.338	0.369	0.293	0.000	0.000	1.191	0.984
Policy Frameworks & Community Engagement	0.410	0.454	0.275	0.000	0.000	1.242	1.054

, the Q²predict values for the hypothesized relationships ranged from 0.011 to 0.481. Except for H1a A (Q²predict = 0.011), which exhibited very weak predictive power, all other constructs, which included H1b A (0.452), H1c A (0.481), H2 A (0.303), H3a A (0.396), H3b A (0.338), and H4 A (0.410), showed moderate to strong predictive relevance. This suggests that the structural model possesses adequate out-of-sample predictive capability for most endogenous constructs. In addition, the PLS-SEM model demonstrated lower RMSE and MAE values compared to the linear model (LM) and indicator average (IA) benchmarks. For instance, in H3a A, the PLS-SEM RMSE (0.401) was substantially lower than IA RMSE (1.286), and similarly for H4 A, the PLS-SEM RMSE (0.454) was lower than IA RMSE (1.242). These results indicate that the PLS-SEM model produces smaller prediction errors and greater accuracy in estimating the target constructs.

4.2.8. Model Fits

The Standardized Root Mean Square Residual (SRMR) values for both the saturated and estimated models fall below the threshold of 0.08, indicating a satisfactory model fit. Specifically, the SRMR value of 0.071 for the estimated model suggests that the discrepancy between the observed and predicted correlations is minimal (

Table 12. Model Fit Summary (SRMR Values).

Model Type	SRMR Value
Saturated Model	0.072
Estimated Model	0.071

). This demonstrates that the structural equation model used in this study exhibits strong goodness-of-fit, confirming that the model adequately represents the observed data and can be considered reliable for hypothesis testing.

4.2.9. Graphical Outputs

Figure 1 shows the Graphical Output for Second Order while Figure 2 shows the Graphical Output for overall analysis (model diagram with standardized coefficients and R²).

5. Discussions

5.1. Discussion for Research Question 1 (RQ1)

This study confirms that promoting culture, creating new jobs, and supporting sustainable economic development in Nanyang City can contribute to Goal 8.9 of the Sustainable Development Goals (SDGs). When asked about H1a, most participants noted that cultural festivals, reenactments of historic moments, and the preservation of heritage sites are significant efforts in promoting and celebrating cultural heritage. Featured figures from China’s past, such as Zhuge Liang, and the opportunity to learn about heritage crafts draw more tourists and help local residents take pride. These efforts help the city’s reputation as a leader in culture and provide for its future cultural growth. In terms of H1b, the results highlight a strong positive impact of urban tourism on the tertiary sector, especially in hospitality, retail, cultural activities, and creative fields. Both types of workers are found in these sectors, and, in particular, these sectors help young people, women, and poor communities gain employment. As a result, it is understood that tourism helps by including all sections of society and sharing jobs, which is part of SDG 8.9 [94].

However, the results also reveal that employment-related impacts (H1b) and economic growth outcomes (H1c) dominate over cultural promotion (H1a). This dominance reflects a common pattern in rapidly urbanizing cities, where short-term economic and labor benefits outweigh long-term cultural preservation objectives. This imbalance between the supply and demand can have trade-offs with the city’s resilience regarding its cultural authenticity and environmental support, such as those brought up by carrying capacity and event crowding literature, in that there might be levels of tourism growth tolerated below that of locals. Their responses to large-scale festivals and heritage-themed events, despite their economic benefits, can either create pressure on infrastructure/pollution or deterioration of the quality of life for residents if not managed well. Therefore, Nanyang’s Sustainable tourism development should try its best to balance its economic benefit growth with the visitor carrying capacity management, historical site protection, and green infrastructure investment to prevent over-commercialization of cultural resources. Due to H1c, updating dated industrial areas into hubs for tourism and culture has enhanced and multiplied economic growth in the area. Due to these developments, cities are becoming less reliant on mainstream industries and are instead supporting greener ways of redeveloping urban areas [95].

This transition reflects that it is not just GDP-related development but sustainable experience-based economy growth that can take place through a focus on tourism-based regeneration. These studies also point to the imperative for closer operationalisation of SDGs in cities, through indicators that can be readily measured indicators, such as 8.9.1 (proportion of tourism employment and GDP), or 17.14.1 (policy coherence for sustainable development), which will ensure that we trace economic benefits alongside cultural and environmental impacts from tourism. That is why Nanyang’s urban tourism spurs local culture, boosts the city’s economy, and promotes new ideas. It backs up literature that bonds cultural tourism with economic growth and city renovation [41]. By confirming H1 and its components, we demonstrate that urban tourism plays various roles in promoting SDG 8.9.

5.2. Discussion for Research Question 2 (RQ2)

This study indicates that H2 is correct and that challenges and opportunities are crucial for the implementation of sustainable tourism in Nanyang City. The biggest obstacles included deficient infrastructure, natural challenges, and the difference between city and village areas of the country [96]. Since cities become busier and attract more people, the services supporting them cannot meet the same rate of growth. Large crowds at peak festivals pose a risk of environmental damage. The results further show, as before, that poor infrastructure accompanied by deficits connected to nature reduces the capability of cities in promoting sustainable tourism. As before, the results indicate that inadequate infrastructure and issues related to nature make it challenging for cities to support sustainable tourism. This research revealed important chances for developing sustainable tourism approaches. The region is striving to encourage slow travel, mix classic architecture with recent additions, and make its big events green. Eco-friendly travel and recycling, among other low-carbon ideas, are being explored by the tourism industry and local leaders who want to help many others adopt sustainability. To meet these challenges, policymakers must develop smart and targeted regulatory levers: (1) crowd control systems leveraging real-time visitor data on digital platforms like Ctrip and Meituan to spread tourists across destinations; (2) eco-event certification criteria requiring festivals to leave behind a minimum waste footprint or consume a maximum amount of energy; (3) vendor inclusionary programs reserving cultural marketplace space for local artists and SMEs; and (4) deeper urban–rural ties that open new channels for lower-income workers outside downtown cores while diluting the pressure facing traditional central areas. This study finds that Nanyang City experiences infrastructure and waste challenges, but solutions and city projects are also available. Because of this, it is important for policymakers to organize early, work on their skills, and cooperate so they can achieve sustainable tourism and meet SDG 8.9 demands.

5.3. Discussion for Research Question 3 (RQ3)

The results clearly propose that H3a and H3b are well supported since multi-stakeholder partnerships play a key role with reference to urban tourism in Nanyang City, commensurate with SDG 17’s goal. Researchers found, according to H3a, that cooperation between the government, businesses, and local partners plays a key role in successful tourism development. Together with Ctrip and Meituan, this study has enabled more tourists to access information about their destination and enjoy convenient tourist services. Useful developments from these partnerships include the construction of contemporary tourism kiosks and a makeover of cultural sites. Furthermore, H3b is supported in light of how community participation ensures that tourism programmes are sustainable and inclusive. Resident communities, cultural associations, and academia have contributed to the program design, cultural studies, and training of tourism experts. By participating, the locals become more included and provide authentic cultural experiences that are trustworthy for the community. These collaborations reflect tourism governance literature, which emphasizes decision-making, pooling resources, and the inclusion of all [47,97]. But in addition to social participation, these partnerships must be widened with data governance mechanisms fostering policy coherence on SDG 17.14.1. For example, creating common data platforms among public tourism bureaus, digital service providers (Ctrip, Meituan), and local businesses could enable real-time management of visitor spread, monitoring sustainability efforts, and transparent disclosure of the environmental footprint of tourism. The mechanisms do not only improve coordination between the departments, but also provide evidence-based inputs for systematic urban tourism policies.

5.4. Discussion for Research Question 4 (RQ4)

Findings for RQ4 validate H4, demonstrating that enhanced policy frameworks and community engagement mechanisms significantly contribute to achieving both SDG 8.9 and SDG 17 in Nanyang’s urban tourism development. It was said that tourism policies that are direct, dependable, and designed for the long term have a big impact on the tourism sector. Policy instruments targeting event sustainability, cultural site protection, and urban-rural tourism coordination have created an enabling environment for balanced development. The findings agree with ideas that stress how stable institutions and known regulations help tourism remain sustainable [98]. Strong community involvement proved to play a major role in the success of tourism. Building unity and increasing authority among local communities has resulted from including them in consultations, educational activities, and plans for tourism. So, they encourage the public to participate in policy decisions, ensure the effectiveness of the policies made, and increase support from all those affected. Future frameworks should integrate cross-sector coordination platforms, digital monitoring systems, and participatory planning units that operationalize SDG 17.14.1 indicators on policy coherence. This would help Nanyang align its tourism, environmental, and cultural policies, reduce inter-agency conflicts, and ensure coherence between local and provincial sustainability goals. Furthermore, these frameworks should embed eco-event standards, vendor diversity guidelines, and equitable tourism certification systems to institutionalize sustainability principles at the policy level. As a result of H4, it is proposed to implement participatory initiatives in future Nanyang tourism policies, overcome inter-agency problems, and update their strategy to match ongoing changes in social and environmental conditions. Doing so will ensure that urban tourism remains both sustainable and aligned with the broader goals of SDGs 8.9 and 17.

5.5. Discussion from a Global and Asia Pacific Perspective

All findings of this study are in line with initial hypotheses and provide a significant contribution to the global debate on sustainable urban tourism through informing about both SDG 8.9 (tourism for job generation and preservation of local cultural heritage) and SDG 17 (partnerships for the achievement of sustainable development). These results highlight the relevance of incorporating specific SDG metrics, such as 8.9.1 and 17.14.1, as a reference for city-level impacts on sustainability cultivation. For the world as a whole, confirmation of H1a, H1b, and H1c suggests that urban tourism in Nanyang City is conducive to the maintenance of local culture, development towards the service industry can generate employment opportunities, and human resources are an economic growth point for cities. The findings of this research confirm international trends observed in cities such as Barcelona, Vienna, and Amsterdam using cultural tourism as a tool for maintaining heritage and reinvigorating the city. As already in Europe and Latin America, the cities of Asia-Pacific (e.g., Singapore, Seoul, and Sydney) can learn from urban tourism as an important element to enhance economy and safeguard cultural heritage [65]. The convergence of Nanyang City’s tourism approaches with the global models indicates a strategic opportunity offered by urban tourism to drive inclusive and sustainable development in localized terms, particularly for collections of mid-range culturally rich cities in developing countries.

The identification of challenges and opportunities in urban tourism presents a common narrative in Asia Pacific cities. City infrastructure limitations, environmental issues, and city governance division are several problems that are faced by the cities in that region, including Nanyang. Nevertheless, this study showed new opportunities for Nanyang, especially digitalized tourism services in the direction of green actions and raising stakeholder awareness of sustainable principles. It is evident that from such research, the efficient and adaptable governance approach is strong, underpinned by regional best practices based on united city planning and innovation led by stakeholders [99]. Because of this, Nanyang shows that local government might manage to balance competing issues but also to promote sustainability simultaneously.

Findings H3a and H3b are consistent with global findings to illustrate the partnership between organizations is a significant factor in developing tourism. Nanyang’s success has been attributed to involving the goodwill of public institutions, leading digital corporations (like Meituan and Ctrip) as well as from local players thus stimulating more infrastructure buildout, more events and greater participation on all sides. Similar project work has been undertaken in Kyoto and Bali, with partnerships across the public, private and community sectors working to support not just profit but the quality of local community life and its sustaining cultural practices [100]. This study proved the example, that only collaborated partnership for a community engagement are significant to reach SDG 17 of new sector partnerships supporting sustainable urban development. In particular, dual governance models and common platforms taking into account wider reporting for transparency, fair resource sharing and regional planning.

Furthermore, H4 recognises the importance of concrete policies and participation from the community, in line with other experts on urban tourism planning. In Nanyang, bottom-up such as governance is not there are in the place value tourism and protection of culture connected, integrating local people to participate in under munity planning for promoting a sustainable development project. Cities like Melbourne and Medellín are also incorporating local residents, intersecting policies, and expanding resources into their tourism offer [3]. The experience in Nanyang indicates that coordinated policy and an engaged public permits a comprehensive, vigorous and directed tourism pathway towards SDG 8.9 and SDG 17.

5.6. Theoretical Implications

This study advances theoretical understanding in the field of sustainable urban tourism by empirically linking tourism development with key Sustainable Development Goals (SDGs), particularly SDG 8.9 (promoting sustainable tourism that creates jobs and promotes local culture and products) and SDG 17 (strengthening partnerships for sustainable development). The evidence presented in this research supports the view that urban tourism helps local culture, creates jobs, and promotes economic growth, confirming that it acts as a strong contributor to inclusive and sustainable development. Theoretically, a contribution to knowledge is provided by linking the SDG framework with urban (collaborative) governance theories and showing how the abstraction of sustainability objectives can be conceptually linked to policy instruments for their implementation. It thereby illustrates how SDG-aligned governance can enact sustainability principles in tourism, broadening the theoretical base regarding how various multilevel governance forms drive sustainable change. As a result, this study demonstrates that sustainable tourism has numerous possible outcomes, depending on the challenges related to infrastructure and general regulations, as well as the opportunities presented by new technology and collaboration with stakeholders. It stresses that using flexible and relative strategies benefits sustainable tourism management. Moreover, this study contributes empirical richness to sustainability and governance theories as it is less developed in emerging urban contexts such as Nanyang City by using Partial Least Squares Structural Equation Modeling (PLS-SEM) for relationships of cultural promotion, employment creation, and multi-stakeholder collaboration and proves its applicability. The importance of multi-stakeholder partnerships now supports and expands theories related to collaboration and governance, especially when communities, governments, and companies join forces. This multi-actor perspective further justifies the relevance of Quintuple Helix and collaborative governance approaches, as well as related concerns with innovation, environmental sustainability, and exchange of knowledge in pursuit of urban sustainable development. Further, this study offers theoretical innovation by embedding the SDG–tourism relationship in a mid-sized Chinese city context and the implications it has for local governance practice to contribute to global sustainability objectives. Both approaches expand the scope of conversations on unified city governance and cooperative planning, which are crucial for achieving the SDG goals related to tourism in towns.

5.7. Practical Implications

The results provide specific and practical recommendations for city managers and policymakers to promote sustainable urban tourism development in Nanyang City, China, or other cities with similar situations. In order to support action and obtain policies in line with the SDGs, the following six measures are suggested:

• Develop official MoUs and data-sharing arrangements between government entities, e-commerce platforms (e.g., Ctrip, Meituan), and tourism operators to enhance coordination, transparency, and evidence-based decision-making in line with SDG 17.14.1 (policy coherence for sustainable development).
• Institutionalize environmentally responsible event management practices, including waste reduction, sustainable transportation, and energy efficiency in festivals and cultural events, so that conservation is as important an aspect of preservation.
• Invest in local skills pipelines by sponsoring women and youth artisans, heritage tradesmen, and hospitality trainees in micro-credential programs and cultural apprenticeships run with communities to drive inclusive employment related to SDG 8.9. Visitors on a culinary tour of a famous food destination.
• Set targets and monitoring of vendor inclusion to ensure all small, rural, and minority businesses are given a fair opportunity to benefit from tourism on both social inclusion and economic equity grounds.
• Implement slow-tourism projects on the heritage corridors of Nanyang to promote longer visits by tourists, enrich cultural experience, and minimise the environmental footprint.
• Create open access tourism dashboards offering real-time information on visitor flows, sustainability indicators and event impacts in order to stimulate open governance and participatory supervision.

Together, these make local authorities feel that urban tourism is not just a sector for HR and the businesspeople, but a transformative tool to include people, protect the environment, and help decentralize certain decisions from the central government. Development of strong local, private sector, and civil society partnerships will enhance accountability, inclusivity, and resilience, which will establish Nanyang City as a best practice example for sustainable urban tourism development in China and elsewhere.

5.8. Limitations

Despite its implications, this study is aware of some methodological and situational limitations that might affect the interpretation and generalization of this finding.

• First, the data was drawn from one city (Nanyang), so it may have difficulty generalizing our results to other urban areas that have different governance regimes, cultures, or stages of development of tourism.
• Second, self-reported survey data may be affected by social desirability and recall bias, as respondents may overemphasize positive tourism outcomes while minimizing negative perceptions.
• Third, the use of non-probability (convenience and purposive) sampling limits the representativeness of findings and may exclude underprivileged or informal workers who are crucial voices in evaluating inclusive tourism outcomes, as stressed by the SDG frameworks.
• Fourthly, the seasonality bias as a result of when the survey was conducted over the festive and peak tourism periods may have further boosted the perceived economic and cultural impacts.
• Lastly, this study employs a cross-sectional design, and it is impossible to capture any temporal or dynamic evolution of the tourism-sustainable development relationship. Lack of longitudinal or panel data precludes an analysis of how seasonal variations, policy reforms, or external shocks (e.g., pandemics, economic slumps) inform tourism’s effects on SDG progress over time.

While the adoption of PLS-SEM offered a number of statistical advantages, it is less capable of resolving concerns regarding temporal stability and causal inference or assessing behavior patterns over time. Quantitative and qualitative methods, such as interviews, focus groups, or participatory mapping that can account for the lived experiences of informal workers, community leaders, and oppressed individuals, should thus be used in future research. These methodological enhancements would serve to expand inclusivity, contextual validity, and depth of interpretation in future tourism research.

5.9. Future Directions

Based on these findings and limitations, future studies might further investigate sustainable urban tourism governance following the approaches:

• Longitudinal and/or panel research designs could be applied in order to capture how the relationships between urban tourism, SDG 8.9 (sustainable economic growth), and SDG 17 (partnerships for the goals) develop over time, i.e., across seasons or after policy interventions.
• Develop multi-city comparisons between multiple regional locales in China and/or the broader Asia-Pacific to examine how Nanyang’s tourism governance model works elsewhere.
• Mix-method designs that involve combining quantitative modeling methods with qualitative interviews, participatory workshops, or ethnographic case studies can be used to gain a more comprehensive understanding of how marginalized populations (small vendors and informal workers) experience the transition of urban tourism.
• Develop experimental or quasi-experimental designs (such as A/B tests of eco-event nudges, digital ticketing systems, and waste reduction prompts) to assess behavioural change and the effectiveness of policy in real-world tourism contexts.
• Utilize smart tourism technologies and open data ecosystems for real-time monitoring, predictive analytics, and cooperative governance to enable adaptive policy-making and sustainable destination management.
• It can help to investigate tourism activity in seasonal and temporal perspectives through repeated measures or time-series data, and it offers a more subtle reflection of how tourism as social, cultural, and environmental dynamism varies throughout periods.
• Future research should also include a stratified sampling for the seasons containing events and non-events that allow scholars to investigate how the role of tourism on SDGs dynamically evolves during the year, provoking more questions around seasonality

Through these ways, the dynamic relationship will be more easily captured in the following studies, and there may be an enhancement in predictive validity, but also with extending theoretical and practical implications for sustainable urban tourism governance. This line of work would help fill the void between SDG frameworks and governance theory, providing a more comprehensive, evidence-driven path to achieving long-term sustainability outcomes in the context of fast urbanizing areas.

6. Conclusions

This study has provided vital insights into the link between urban tourism and sustainable development in Nanyang City, focusing on SDGs 8.9 and 17. The results prove that growth in the sector of urban tourism contributes to the development of local culture, creation of new workplaces and well-balanced economic growth with SDG 8.9. Furthermore, this report points out important challenges and benefits in the use of sustainable tourism, showing that different situations require diverse strategies for success. The findings show that strong cooperation among the public sector, companies, and local communities plays a key role in achieving SDG 17. In addition, it points out that filling policy gaps and increasing community action are key to tourism that supports various SDGs. Studying the case in this way also contributes to sustainable urban tourism studies by connecting its analysis to the SDG targets and illustrating how economic, social, and governance aspects are interlinked. It helps both policymakers and those in the tourism industry develop plans that pay attention to every group, consider local cultures, and produce profit. Even so, due to its specific research site, methodology, and actors involved, it may be best to use this study’s findings with caution in other urban places. Additional comparisons between cities based on the same model help us see how urban tourism grows over different periods. Reviewing the roles of all participants and current matters, for example, digital tourism and coping with climate change will expand what we know about tourism’s influence on urban sustainability. In short, these actions make it easier for cities to achieve sustainable development, and thus the city pays closer attention to its economy, history, and community.