Global Sustainability Research ISSN: 2833-986X https://doi.org/10.56556/gssr.v4i1.1181 Global Scientific Research 37 RESEARCH ARTICLE The Sustainability Impact of Tourism Industry Agglomeration on Regional Economic Gap Guo Junhui1*，Chen Qihao1 1School of economics and management, Zhejiang University of Science and Technology, China Corresponding Author: GUO Junhui. Email: guojunhui@zust.edu.cn; Chen Qihao. Email: 631356141@qq.com Received: 15 January, 2025, Accepted: 18 March, 2025, Published: 21 March, 2025 Abstract Tourism has become a key driver of economic growth and regional development, yet its impact on economic disparities and sustainability remains underexplored. Against the backdrop of global efforts to achieve sustainable development, this study investigates the role of tourism industry agglomeration in addressing regional economic disparities, with a focus on the moderating effects of transport and information infrastructure. Using panel data from 31 Chinese provinces and cities spanning 2004 to 2020, we integrate transport and information infrastructure into a research framework to examine the relationship between tourism industry agglomeration and regional economic disparities. Through multiple econometric methods, we empirically analyze the influence of tourism industry concentration density on regional economic gaps and explore the underlying mechanisms. Our findings indicate that tourism industry agglomeration significantly reduces regional economic disparities, while transport and information infrastructure play a crucial moderating role, albeit with regional and temporal heterogeneity. Furthermore, the relationship between tourism agglomeration and economic disparities, as well as the role of infrastructure, exhibits nonlinear characteristics, suggesting complex interactions. Importantly, the study underscores the potential of sustainable tourism practices in fostering long- term economic balance and environmental preservation, aligning with global sustainability goals. These insights provide valuable references for policymakers aiming to narrow economic gaps and promote coordinated regional development through sustainable tourism strategies. Keywords: Tourism Cluster; Economic Gap; Infrastructure Development; Moderating Effect; Threshold Effect Introduction As modernization progresses, the growing discrepancy in economic development between regions has become increasingly noticeable. In particular, China has demonstrated a marked concern for imbalanced regional development. In March 2021, the Outline of the People’s Republic of China 14th Five-Year Plan for National Economic and Social Development and Long-Range Objectives for 2035 issued by the Thirteenth National People’s Congress, clearly emphasized the need to actively bridge the economic gap between regions. Unraveling how to alleviate these economic disparities presents a significant challenge for China to achieve its goal of common prosperity. The tourism industry has emerged as a key driver of economic growth, stimulating Global Sustainability Research Global Scientific Research 38 consumer spending and creating job opportunities. According to the Basic Situation of the 2019 Tourism Market released by the Ministry of Culture and Tourism, the tourism industry’s comprehensive contribution to the national economy reached 10.94 trillion yuan, with a contribution rate as high as 11.05%. Furthermore, employment generated by the tourism industry and related sectors accounted for 10.31% of the total national employment, underscoring its pivotal role in propelling the national economy. However, the economic effects of tourism are often underestimated due to the increasing overlap between tourism activities and everyday life. This convergence has led scholars to overlook the potential of tourism in alleviating regional economic disparities. Tourism industry agglomeration, characterized by the spatial concentration of tourism-related activities, is considered a dynamic form of spatial organization and a critical aspect of industry development (Wang et al., 2020).Yet, its impact on regional economic disparities remains underexplored. Existing literature has largely ignored the role of transport and information infrastructure in the relationship between tourism and regional economic disparities. While studies have shown that transport and information infrastructure significantly influence both the tourism industry and regional economies, their moderating effects on the impact of tourism agglomeration on regional disparities have not been adequately addressed. (Liu Zhen et al., 2022; Cheng Yu et al., 2023; Sun et al., 2019).This omission may lead to biased conclusions and an incomplete understanding of the mechanisms at play. Additionally, previous studies have primarily relied on specialized or total tourism revenue indicators to measure tourism development, neglecting spatial disparities and the strong industry correlation inherent in tourism(Li & Zhang, 2023; Wang & Chen, 2023; Smith & Brown, 2024; Garcia & Lee, 2023). Furthermore, there is a lack of empirical discussion on the heterogeneous impacts of tourism agglomeration and infrastructure on regional disparities. To address these gaps, this study investigates the impact of tourism industry agglomeration on regional economic disparities, incorporating transport and information infrastructure as moderating factors. Using panel data from 31 Chinese provinces and cities (2004–2020), the study aims to: (1) explore whether tourism agglomeration mitigates regional economic disparities; (2) examine the moderating effects of transport and information infrastructure, both individually and jointly, on this relationship; and (3) analyze the potential nonlinear characteristics of these effects. By measuring tourism agglomeration from a spatial perspective and considering the combined effects of infrastructure, this study provides a more comprehensive understanding of the mechanisms driving regional economic disparities. Literature The Impact of Tourism Industry Agglomeration on Regional Economic Disparities Direct Impact Effects Tourism industry agglomeration has direct effects on regional economic disparities. First, tourism activities generate direct income effects, as tourist expenditures during trips translate into local tourism revenues. The increased concentration of the regional tourism industry can further stimulate tourism income, thereby directly promoting economic growth in underdeveloped areas and alleviating regional economic disparities. Second, tourism activities engender wealth-transfer effects. Tourist activities involve interregional mobility due to the touristic flow effect, leading to wealth transfer and income redistribution between regions. This fosters economic development in tourism destinations (Soukiazis et al., 2008). Additionally, the income earned by tourism industry employees, when used to purchase goods for sustaining livelihoods, similarly generates wealth transfer and income redistribution, thereby promoting local economic development(Wu,2011). Consequently, the Global Sustainability Research Global Scientific Research 39 development of the tourism industry can expand both tourism demand and supply, thereby promoting wealth distribution and propelling local economic effects to narrow the economic gap with other regions. Finally, the tourism industry exhibits industry-linkage effects. Apart from tourism products, there are basic industries associated with obtaining these products, namely industries related to tourism, such as agriculture, animal husbandry, construction, and food manufacturing (Wu,2012). Demand for these industries can stimulate the development of corresponding industries, thereby driving economic growth. With the heightened level of tourism industry agglomeration, the increased demand for associated industries not only promotes the upgrading of the tourism industry chain, but also caters to dynamic changes and diversified tourism demands, thereby mitigating economic disparities with other regions. Indirect Impact Effects Tourism industry agglomeration indirectly influences regional economic disparities. First, interactions among laborers give rise to knowledge spillover effects (Wang Jiaying et al., 2021) . As the tourism industry develops, the increased number and higher professional standards of tourism industry workers can enhance knowledge spillover effects, thereby promoting innovation in tourism products and refining enterprise management practices. This fosters the competitiveness and attractiveness of tourism products, further propelling economic growth to alleviate regional economic disparities. Second, as the level of tourism industry agglomeration increases, the demand for tourism activities also increases, leading to intensified competition among tourism products, thereby creating a competitive effect. Competition serves as a significant driver of product innovation, fostering the enhancement of tourism product attractiveness and exerting a significant promotional effect on the economy, thus reducing economic disparities with other regions (Wang et al., 2020) . Finally, the tourism industry’s tourist flow effect, where multi-destination tourists may choose multiple destinations in one trip, leads to factor mobility effects. The development of the tourism industry has promoted increased demand, guiding underutilized or mismatched labor and capital resources to flow into the tourism industry. This further enhances product quality and meets the demands for tourism while promoting local economic development, thereby easing uneven development among regions. Therefore, based on the aforementioned analysis, the following hypothesis is proposed: H1: Tourism industry agglomeration has a negative impact on regional economic disparities. The Influence Mechanism of Tourism Industry Agglomeration on Regional Economic Disparities Initially, the enhancement of local informatization and transport accessibility levels promotes the mobility and distribution efficiency of labor and capital resources (Xie Kai et al., 2023; Wang Chong et al., 2023) . This facilitates the rational allocation and utilization of idle, mismatched, or surplus resources, fostering the development of not only the tourism industry, but also related industries, thereby stimulating local economic effects and mitigating economic disparities with other regions. Additionally, the improvement of local transport accessibility and reduction of information barriers alleviates the search and transport costs for tourists and labor, contributing to the rational utilization and development of tourism resources while reducing local tourism losses. This, in turn, fosters the development of local tourism and related industries, thereby mitigating regional economic disparities. Lastly, the advancement of informatization and transport accessibility “compresses” time Global Sustainability Research Global Scientific Research 40 and space, thereby reducing the transport costs of tourism products and raw materials (Huang et al., 2021) and fostering innovation in tourism products (Ji et al., 2023) . This results in an upgrade of tourism products in terms of quality, variety, and price, enhancing their competitiveness and attractiveness to tourists, further promoting economic growth, and alleviating regional economic disparities. In conclusion, the advancement of regional transport or information infrastructure progressively breaks down “information barriers,” enhances transport convenience, and stimulates local tourism development, to a certain extent mitigating uneven economic development among regions. According to the New Economic Geography theory, industries undergoing spatial agglomeration are influenced by both centripetal and centrifugal forces (Fujita et al., 2001) . Given the interconnected and spatially cohesive nature of the tourism industry, its development is subject to the influence of both centripetal and centrifugal forces (Wang et al., 2019) . When the level of transport or information infrastructure is low, constraints on local tourism development arise owing to inadequate transport connectivity or information accessibility. Therefore, lower levels of informatization or transport convenience exert centrifugal force on local tourism development. Additionally, in economically developed regions, the richness of tourism products, sophistication of infrastructure and tourism industry chains, abundance of resource reserves, and higher professional skills of the workforce make these areas more attractive to tourists, thus limiting the development of tourism in less economically developed regions. Consequently, deficiencies in aspects such as tourism products, infrastructure, resource elements, and labor skills exert centrifugal forces on local tourism development. As the level of informatization or transport convenience increases, the gradual dismantling of the "digital divide" and enhanced transport accessibility significantly fosters local tourism development, thereby generating centripetal forces on local tourism development. In this context, the impact of tourism industry agglomeration on regional economic disparities is not simply a static and linear effect. Instead, it is influenced by transport or information infrastructure and exhibits significant nonlinear characteristics. Specifically, thresholds could be measured or defined based on the levels of information and transport infrastructure development, which determine whether the impact is more centripetal or centrifugal. The threshold effect refers to a phenomenon where a certain minimum level of input, effort, or exposure is required before a significant change, response, or outcome is observed. Below this threshold, the effect may be negligible or non-existent, but once the threshold is crossed, the impact becomes noticeable and often increases rapidly. In conclusion, this study proposes the following hypothesis: H2-1: The impact of tourism industry agglomeration on regional economic disparities is negatively moderated by “information infrastructure,” exhibiting threshold characteristics. H2-2: The impact of tourism industry agglomeration on regional economic disparities is negatively moderated by “transport infrastructure,” which exhibits threshold characteristics. H2-3: The impact of tourism industry agglomeration on regional economic disparities is negatively moderated by “information and transport infrastructure,” exhibiting threshold characteristics. Methodology Model Construction Based on the theoretical analysis and research hypotheses, to explore the impact of tourism industry agglomeration on regional economic disparities and recognizing that neglecting individual effects, time effects, Global Sustainability Research Global Scientific Research 41 and the correlation between error terms and explanatory variables may lead to biased model estimates, this study adopts the two-way fixed effects model as the baseline regression model, formulated as follows: Gap it =β 0 +β 1 Tait+β 2 Xit+μ it +εit (1) Variable Definitions: Gap it : The level of regional economic disparities in province i at time t, measured by the Gini coefficient of per capita GDP across prefecture-level cities or districts (unit: dimensionless). Tait: The level of tourism industry agglomeration in province i at time t, measured by the spatial agglomeration density (unit: per square kilometer). Xit: A vector of control variables for province i at time t (definitions provided in Section 3.2.4). μ it :The individual fixed effect for province i at time t, capturing unobserved time-invariant characteristics. εit :The random disturbance term for province i at time t (unit: dimensionless). We choose the two-way fixed effects model over other alternatives such as pooled OLS or random effects models for several reasons. First, it effectively controls for unobserved heterogeneity that may be correlated with the explanatory variables. By including both individual and time fixed effects, we can eliminate biases arising from time-invariant provincial characteristics and common temporal shocks. Recent studies, such as Chen and Liu (2023), have employed spatial econometric models to address spatial dependencies in tourism agglomeration, while Martinez and Kim (2024) utilized dynamic panel data models to capture temporal dynamics. However, our approach focuses on controlling for unobserved heterogeneity and temporal shocks, which are critical for unbiased estimation in our context.Second, the Hausman test confirms that fixed effects are more appropriate for our dataset, suggesting that unobserved individual effects are correlated with the explanatory variables. Lastly, this model provides a robust framework for analyzing the dynamic relationship between tourism industry agglomeration and regional economic disparities over time and across regions. Furthermore, to verify whether the research hypotheses on the impact mechanism of tourism industry agglomeration on regional economic disparities hold, this study introduces moderating variables, including transport, information infrastructure, and the combination of transport and information infrastructure, into Formula (1), as well as interaction terms between tourism industry agglomeration and the moderating variables. The specific model is as follows. Gap it =β 0 +β 1 Tait+β 2 Mit+β 3 Tait*Mit+β 4 Xit+μ it +εit (2) Mit:Moderating variables in province i at time t, representing transport, information infrastructure, and the combination of both. In recent years, research on tourism agglomeration and regional economic disparities has increased, but most studies have not fully considered the moderating role of infrastructure and its nonlinear characteristics. For example, Zhang et al. (2023), in their study on the impact of tourism agglomeration on regional economic disparities, considered the linear moderating effect of a single type of infrastructure without introducing interaction terms or threshold models. In contrast, this study, by incorporating interaction terms and threshold models, can more comprehensively capture the complex relationship between tourism agglomeration and infrastructure. Finally, to further verify whether the impact of tourism industry agglomeration on regional economic disparities exhibits non-linear relationships with "Mit", we adopt transport, information infrastructure, and the combination of transport and information infrastructure as threshold variables to construct a threshold model. The model is expressed as follows: Global Sustainability Research Global Scientific Research 42 Gap it =α0+β 1 Tait*I(Mit<γ 1 )+β 2 Tait*I(γ 1 ≤Mit< γ 2 )+⋯+β n Tait*I(γ n-1 ≤Mit<γ n )+β n+1 Tait*I(Mit≥γ n )+δXit + εit (3) γ 1 , γ 2 ,…, γ n : Threshold values defining different intervals for the moderating variables. β 1 , β 2 , …, β n :The estimated coefficients for different threshold intervals. 𝐈(·) : Indicator function, taking the value of 1 when the threshold variable is within a specific range, and 0 otherwise. Additionally, Wang and Liu (2024) explored the moderating role of information infrastructure, but their model did not distinguish the effects across different threshold intervals, resulting in limited explanatory power for nonlinear relationships. The threshold model in this study, through a piecewise regression approach, reveals the nonlinear impact mechanisms of tourism agglomeration on regional economic disparities, providing more nuanced insights for policy formulation. Variable Construction Dependent Variable Regional Economic Disparity (Gap) follows the approach of Wang Qing et al. (2018) .This study measured using the Gini coefficient of per capita GDP across prefecture-level cities or districts within each province or directly controlled municipality. The specific formula is as follows: Gap it = 2 N ∑   N i=1 ixi- N+1 N (4) Where: xi=y i / ∑  N i=1 y i ，and，xI