From designation to development: Policy effects,business environment,and the effectiveness of cultural-tourism integration in China

Abstract

The integration of cultural and tourism industries serves as a pivotal engine for regional high-quality economic development; however, its economic performance exhibits significant heterogeneity in practice. Utilizing panel data from Chinese prefecture-level cities from 2000 to 2022, this study treats the designations of “National Historical and Cultural City” (NHCC) and “China Excellent Tourism City” (CETC) as quasi-natural experiments. By employing a staggered difference-in-differences (DID) framework, supplemented by instrumental variable (IV) estimation and a series of robustness checks, we identify the differentiated impacts of cultural policies, tourism policies, and their overlap on urban economic growth. The findings reveal a fundamental asymmetry in the transmission mechanisms of different policy orientations. Cultural designations primarily stimulate “passenger flow” through symbolic branding effects, whereas tourism-oriented policies are more effective at activating “logistics flow” channels due to their role in driving infrastructure and commercial networks, thereby generating stronger momentum for economic growth. To address how cultural and tourism sectors can be effectively integrated, this research further identifies two core pathways. First, the mere “stacking” of policies does not equate to functional integration; true synergy requires “synchronous implementation” to overcome the time lag in administrative and industrial coupling, thereby achieving coordinated growth in both passenger and logistics flows. Second, “culture-business-tourism integration” facilitated by a dynamic business environment serves as a critical moderating mechanism that amplifies policy dividends and optimizes economic outcomes. This study provides city-level evidence for understanding the complex mechanisms of cultural–tourism integration and offers policy insights for achieving high-quality, coordinated regional development.

Keywords

cultural-tourism integration National Historical and Cultural City (NHCC)Chinese Excellent Tourist City (CETC)passenger and logistics flows synchronous implementation culture-business-tourism integration

Introduction

In the context of global economic restructuring and the pursuit of high-quality development¹, the cultural and tourism industries have gained increasing prominence as engines of regional growth, industrial upgrading, and urban competitiveness (Richards, 2018). Their importance stems from distinctive resource endowments, extensive industrial linkages, and substantial value-added potential (OECD, 2022; UNWTO & UNESCO, 2018). A substantial body of literature documents the independent contributions of these sectors: tourism expansion can stimulate regional economic growth and contribute to balanced regional development (Goh et al., 2015), while vibrant cultural industries are associated with sustainable development and enhanced social welfare (Fang et al., 2023). Cultural tourism, in particular, has become one of the fastest-growing segments of the global tourism economy, as cultural and creative assets are increasingly leveraged to boost destination attractiveness and international competitiveness (OECD, 2009).

Nevertheless, much of the existing research still treats culture and tourism as separate domains, with relatively limited attention devoted to their integrated development (Qi and You, 2024). Cultural–tourism integration², which is broadly understood as the strategic alignment of cultural resources with tourism development, is widely viewed as a pathway to synergistic outcomes that exceed the contributions of either sector alone (Lv et al., 2025). Integrating intangible cultural heritage into tourism, for example, can transform traditional cultural assets into immersive visitor experiences and new economic opportunities while also supporting heritage preservation (He et al., 2025). Yet, robust empirical evidence on the regional economic implications of integration remains limited (Qi and You, 2024), and the mechanisms through which policy synergy facilitates high-quality integration are still not well understood (Tang et al., 2024).

China provides a particularly relevant setting to examine these issues. In 2018, China merged the former National Tourism Administration with the Ministry of Culture to establish the Ministry of Culture and Tourism, signaling a national commitment to promoting the “deep integration of culture and tourism.” Despite strong top-down support, the economic outcomes of integration initiatives remain uneven, and their value-added benefits are often unclear or insufficiently examined (Zeng et al., 2023). Several patterns illustrate this complexity. Some cities with abundant cultural assets do not see corresponding growth in tourism. Others achieve strong tourism performance even without deep cultural foundations. Even cities endowed with both cultural and tourism assets do not necessarily realize the expected economic gains from integration (Zhang et al., 2025). These discrepancies raise fundamental questions about how effective cultural–tourism integration actually is, and under what conditions policy interactions can be translated into sustained local development.

To address these questions, this study exploits two nationwide designation systems in China: the “National Historical and Cultural City” (NHCC) program and the “China Excellent Tourism City” (CETC) program, which represent institutionalized recognition of a city’s cultural and tourism status, respectively. The NHCC system was launched in 1982 and ratified by the State Council under the Law of the People’s Republic of China on the Protection of Cultural Relics; 144 cities have received NHCC status. The CETC designation was initiated in 1995 by the former National Tourism Administration to improve urban tourism environments and service quality; 339 cities were awarded CETC status across nine batches before the program concluded in 2013. These designations are well-suited for empirical identification for two reasons. First, both titles are awarded based on long-term cultural or tourism development indicators rather than short-term economic performance, mitigating concerns that designation is driven by contemporaneous growth. Second, the staggered timing and spatial diffusion of NHCC and CETC create a quasi-experimental setting for difference-in-differences (DID) strategies. The distribution of cities designated as NHCC only, CETC only, or both between 2000 and 2022 provides a natural comparative framework.

Figure 1 offers descriptive evidence on the cumulative number of designated cities and highlights asymmetric development trajectories. A substantial share of NHCC cities were later designated as CETC, suggesting that cultural heritage can provide foundational conditions for tourism development. This pattern resonates with the view that “culture is the soul of tourism” (Richards, 2011) and is consistent with a sequential linkage in which cultural recognition precedes tourism upgrading. By contrast, many CETC cities did not receive NHCC status, reflecting tourism growth paths driven more by natural endowments, geography, and targeted incentives than by officially recognized cultural assets. Importantly, dual-designation cities, recognized as both NHCC and CETC, provide a unique setting to examine whether policy overlap generates genuine synergy or merely administrative parallelism without functional integration.

Figure 1.

Comparison of the Cumulative Number of Cities Awarded the Two Types of Titles.

Accordingly, this study addresses three research questions: (i) Do cultural and tourism policies exert differentiated impacts on urban economic development, and through what mechanisms? (ii) Does the coexistence of both designations constitute effective cultural–tourism integration? (iii) What mechanisms and enabling conditions shape the realization of integrated economic effects? To answer these questions, we employ a two-way fixed effects DID model using panel data for Chinese prefecture-level cities from 2000 to 2022, complemented by instrumental variable (IV) estimation, dynamic effect analysis, heterogeneity tests, and moderation analysis.

Compared to existing literature, this paper makes three primary research contributions:

First, regarding the analytical framework, this study constructs a unified causal inference framework for policy interventions, addressing the limitations of existing literature that predominantly relies on descriptive research. Previous studies on cultural–tourism integration have mostly focused on qualitative discussions or coupling coordination analysis based on indicator systems, which struggle to eliminate confounding factors and identify the true net effects of core policies. By treating the designations of “National Historical and Cultural City” (NHCC) and “China Excellent Tourism City” (CETC) as quasi-natural experiments within a unified causal identification framework, this paper not only clarifies the independent contributions of cultural and tourism policies to regional economic growth but also reveals their complex interactive effects under policy overlap.

Second, in terms of action mechanisms, this paper provides a city-level explanation for the heterogeneity of policy effects by distinguishing between “passenger flow” and “logistics flow” as two transmission channels. Existing research often treats the impact of cultural–tourism integration as a monolithic whole, overlooking the fundamental differences in transmission pathways across different policy orientations. This paper finds that cultural designations primarily stimulate consumer demand centered on “tourists” (the passenger flow channel) by enhancing city brand attractiveness, whereas tourism-oriented policies rely more on the improvement of infrastructure and commercial networks to drive the flow of production factors in supporting industries (the logistics flow channel). This finding provides empirical support for understanding the structural differences between “culture-driven” and “tourism-driven” development models.

Third, regarding the logic of policy integration, this paper challenges the traditional perception that “simple policy stacking is inherently effective” by analyzing implementation sequencing and coordination conditions. This study explicitly posits that policy overlap does not equate to functional integration. The findings indicate that the sequencing of implementation significantly affects the degree of alignment between demand activation and supply-chain formation. In the absence of effective temporal coordination, simple policy stacking may lead to functional mismatches, thereby weakening the economic dividends of integration. Furthermore, this paper identifies the enabling role of the business environment, demonstrating how the external institutional context determines the effectiveness of policy coordination. This offers a dynamic explanatory framework for regional governments on how to achieve “deep integration” through precise sequencing management and environmental optimization.

Review of related literature and hypotheses

Review of related literature

As emerging industries, the cultural and tourism sectors are increasingly regarded as pivotal drivers of regional economic transformation and high-quality development. A growing body of literature has examined their contributions to GDP growth, employment, and urban competitiveness from both theoretical and empirical perspectives (Alberti and Giusti, 2012; Ladkin et al., 2023; Lee and Chang, 2008). Within this broader landscape, tourism economics has long emphasized tourism’s demand-side stimulus through revenue generation, job creation, and investment attraction, giving rise to the well-established “Tourism-Led Growth” (TLG) hypothesis (Balaguer and Cantavella-Jordá, 2002; Tang and Tan, 2018). In practice, tourism has become a cornerstone of economic activity in many countries and regions (Cárdenas-García and Pulido-Fernández, 2019). Although tourism may entail environmental costs and other externalities, its overall net effects are often considered positive under the principles of sustainable development (Liu, 2003). In parallel, the cultural economy literature highlights the role of cultural capital, symbolic assets, and creative industries in producing high value-added growth, innovation, and place-based competitiveness (Scott, 2000; Throsby, 2001). In China, the expansion of cultural industries has been increasingly linked to regional development by meeting rising cultural consumption demand and fostering cross-sector linkages (Li et al., 2024), with many empirical studies documenting a positive association between cultural-industry development and economic growth.

Building on these foundations, an expanding body of research views cultural tourism as a key arena where culture and tourism interact: cultural resources are transformed into experiential products and visitor demand, while tourism markets provide incentives and channels for the protection and revitalization of cultural heritage. This mutually reinforcing relationship is particularly salient in regions with dense cultural resources—such as red tourism zones, World Heritage Sites, historical urban landscapes and literature-based cultural heritage—where culture-based tourism tends to flourish (Kot et al., 2024; Tan et al., 2024). At the same time, this stream also stresses the governance tension embedded in cultural tourism development: cultural assets gain new life when reimagined through the tourism economy, yet such repackaging can generate both preservation and commodification (Yamashita, 2024). More critically, heritage-oriented development may trigger risks such as “museumification,” authenticity loss, or over-commercialization when regulatory capacity is limited (Winter, 2013). These tensions imply that the economic dividends of cultural tourism are not automatic but depend on institutional arrangements that shape commercialization practices, community participation, and long-term sustainability.

Recent empirical studies further enrich this perspective by emphasizing the place-based and socially embedded nature of cultural–tourism development. Evidence suggests that intangible cultural heritage (ICH) and tourism can exhibit complementary dynamics and coordinated evolution (Lv et al., 2025), while socioeconomic factors such as GDP, population density, and urbanization influence the spatial mobilization and tourism utilization of cultural resources (Zhang et al., 2025). The social dimension is also central: residents’ support for tourism depends on perceived benefits and place attachment (He et al., 2025), and tourists’ satisfaction and behavior in heritage settings are shaped by spatial configurations and environmental quality (Song et al., 2025). Taken together, these studies highlight that cultural–tourism outcomes are contingent on local development stages, governance capacity, and societal acceptance—reinforcing the view that successful integration requires adaptive, context-sensitive policy design rather than reliance on resource endowments alone.

Against this background, a key strand of the literature focuses explicitly on policy instruments and their differentiated objectives. Cultural policy tools—such as UNESCO World Heritage designation, national ICH protection, and the NHCC program—prioritize preservation and transmission, while also producing branding externalities and increased cultural visitation; yet they may generate unintended consequences in the absence of effective governance (Winter, 2013). By contrast, tourism policy tools—such as CETC designation and 5A scenic ratings—are oriented toward destination marketing, visitor attraction, and infrastructure and service upgrading (Buhalis, 2001; Mariani et al., 2018), often producing rapid increases in visitor numbers, tourism receipts, and hospitality employment, but risking homogenization if detached from local cultural foundations (Bilen et al., 2017). This policy distinction is crucial for mechanism reasoning: cultural policies may primarily strengthen symbolic value and attract culturally motivated visitors, while tourism policies more directly mobilize market expansion and supporting facilities—suggesting potentially asymmetric effects across different economic channels.

Finally, the emerging cultural–tourism integration literature argues that synergy is possible but not self-executing. International syntheses emphasize that realizing tourism–culture synergies requires coordination across planning, product development, and stakeholder governance (Richards and Marques, 2012; UNWTO & UNESCO, 2018). For China, quasi-experimental evidence indicates that integration policies can improve tourism performance, but effects are heterogeneous across places (Jin et al., 2022), and configurational research suggests that high integration levels often arise from specific combinations of policy instruments rather than single tools (Tang et al., 2024). More broadly, the policy-integration literature cautions that when multiple designations and agencies coexist, coordination failures and sequencing-induced path dependence are common: early investments and institutional priorities may lock destinations into difficult-to-reverse trajectories (Peters, 2018). Moreover, place-based development research emphasizes that enabling environments—market efficiency, infrastructure, financing access, human capital, and regulatory quality—shape whether policy opportunities can be translated into measurable economic gains (OECD, 2015; Pike et al., 2016). Furthermore, empirical evidence from Tourism Economics highlights the “double-edged” nature of institutions, suggesting that while tourism arrivals naturally stimulate wealth, weak governance and corruption can actually reverse these benefits, turning a potential growth engine into a negative economic impact (Adedoyin et al., 2022).

Taken together (Table 1), existing studies clarify both the development relevance of culture and tourism and the practical reasons why integration is not guaranteed by “stacking” labels. However, the literature remains relatively limited in directly identifying how different designation types transmit through distinct flow-based channels (e.g., passenger versus logistics flows) and in explaining why sequential versus synchronous implementation strategies may yield counterintuitive outcomes—especially for logistics-related effects.

Table 1.

Key literature on cultural–tourism integration.

Key studies	Main findings	Methods & data	Research gaps
Balaguer and Cantavella-Jordá (2002); Tang and Tan (2018)	Tourism expansion can stimulate long-run economic growth (tourism-led growth).	Time-series/panel econometrics using national tourism indicators and GDP.	Limited causal identification; no clear distinction between demand-side and supply-side channels; little attention to the policy instruments through which these effects are generated.
Throsby (2001); Scott (2000); Li et al. (2024)	Cultural industries, cultural capital support innovation and place competitiveness; cultural-industry expansion is associated with regional growth in China.	Conceptual frameworks and regional empirical analyses using cultural-industry output indicators.	Weak causal identification; limited connection to tourism-related policy instruments; mechanisms are not specified in terms of demand-side versus supply-side transmission..
Winter (2013); Yamashita (2024)	Heritage-based development can boost branding and visitation but faces authenticity and over-commercialization risks; cultural assets are repackaged through tourism markets.	Qualitative analyses and case-based evidence in heritage and cultural tourism contexts.	Evidence is largely qualitative or case-based; emphasis is placed on visitation and other demand-side outcomes; supply-side effects such as logistics and value-chain formation remain underexplored.
Buhalis (2001); Mariani et al. (2018); Bilen et al. (2017)	Tourism policy tools and destination upgrading can raise tourism performance but risk homogenization if detached from local culture.	Conceptual and empirical destination-management research; evidence typically at sector levels.	Limited causal identification; insufficient differentiation across policy types; weak attention to supply-side linkages beyond tourism itself.
Richards and Marques (2012); UNWTO & UNESCO (2018); Zhang et al. (2018); Liu and Xie (2022); Wang et al. (2022)	Integration can generate synergies via coordinated planning, product innovation, and spillovers, but fragmented planning and low coordination constrain outcomes.	Policy syntheses, management studies, and applied empirical evidence in integration contexts.	Focuses mainly on conceptual integration rather than causal effects; insufficient attention to policy coordination and sequencing; supply-side outcomes are not explicitly examined.
Jin et al. (2022); Tang et al. (2024)	Integration policies improve tourism performance with heterogeneity; high integration often requires instrument combinations.	Staggered DID with China provincial panel (31 provinces); fsQCA using policy-instrument configurations.	Provides causal evidence at an aggregate level, but offers limited mechanism analysis; does not distinguish passenger-flow and logistics-flow channels; does not examine sequencing effects.
Yu and Chen (2022); Peters (2018); Pike et al. (2016); OECD (2015)	Coordination failures and path dependence are common; enabling environments and local capacity condition policy effectiveness.	Policy integration theory and place-based development and policy coherence frameworks.	Offers strong theoretical insights but limited causal empirical evidence; applications to cultural–tourism policy settings remain limited; mechanisms are not linked to observable economic channels.
Lv et al. (2025); Zhang et al. (2025); He et al. (2025); Song et al. (2025); Tan et al. (2025)	Cultural-tourism outcomes depend on local development stage, spatial allocation of resources, and social acceptance; urbanization and spatial or environmental factors shape tourism experience and support.	Regional case-based quantitative analyses (province/city-level).	Rich in contextual detail but limited in causal identification and external validity; insufficient attention to policy timing, sequencing, and channel-specific transmission mechanisms.

Theoretical framework and hypotheses

The systematic review in Table 1 reveals a critical gap in the existing cultural–tourism literature: while the potential for synergy is widely acknowledged, the specific causal channels and policy sequencing that translate integration into economic outcomes remain underexplored. Specifically, most studies treat tourism outcomes as a monolithic demand-side phenomenon, overlooking the supply-side logistics and value-chain integration. To bridge these gaps, this section develops a flow-based analytical framework that distinguishes between “passenger flow” (demand-side) and “logistics flow” (supply-side), and theorizes how their structural alignment—conditioned by implementation timing and local environments—determines the success of functional integration.

Under this framework, we distinguish cultural versus tourism designation instruments by their primary objectives and governance logics. We link these differences to two flow-based outcomes, which proxy for distinct layers of local economic activation. Passenger flow mainly captures demand-side visitation and consumption. Logistics flow, by contrast, reflects the intensity of goods movement and distribution activities that accompany commercialization, supply replenishment, and the formation of local value chains; it therefore signals deeper integration between the visitor economy and local production–circulation systems rather than “tourist arrivals” alone. This distinction aligns with the broader tourism–culture synergy view that sustainable gains depend on connecting attractions and experiences to market channels and supply systems, not merely increasing visitation (UNWTO & UNESCO, 2018). In essence, cultural designations focus on demand-side stimulation via city branding, while tourism-oriented policies emphasize supply-side support through infrastructure and service capacity. Based on this discussion, we propose the following hypothesis.

Cultural policies, tourism policies, and their combined implementation affect urban economic development, but their effects differ.

To explain why such effects may differ, this paper emphasizes differentiated transmission channels implied by policy orientation. Cultural designations (e.g., heritage-oriented programs) prioritize protection, transmission, and place branding. They can raise passenger flows by enhancing reputation, signaling quality, and attracting culturally motivated segments. However, cultural designations do not necessarily relax supply-side constraints: conservation-oriented rules, land-use restrictions, and limited commercialization capacity may slow the expansion of retail, warehousing, and distribution networks, implying a weaker logistics response unless complementary market and governance arrangements are in place (Winter, 2013). Tourism designations, in contrast, are explicitly oriented toward market expansion and destination management. They typically mobilize investment in transport connectivity, facilities, and service capacity, which can increase passenger flows and—when local enterprises scale up—strengthen logistics flows through higher procurement, inventory turnover, and distribution intensity. In this sense, tourism policies are more likely to activate both “front-end” demand and “back-end” supply activities, yielding broader economic linkages than visitor growth alone. This suggests that while cultural policies cultivate the ‘soft’ identity of a city, tourism policies strengthen the ‘hard’ foundation of industrial services. Therefore, we propose the following hypothesis.

Differences in the orientation of cultural and tourism policies lead to distinct impacts on passenger and logistics flows, resulting in differentiated economic outcomes.

Given these asymmetric channels, effective integration is a coordination outcome rather than a mechanical result of policy overlap. Coordinating logistics and supply chains requires deliberate planning and deep integration between cultural institutions and tourism markets (Richards, 2018). Where inter-agency coordination, product innovation, and business participation are weak, regions endowed with both cultural and tourism resources may still experience limited economic benefits (Boccella and Salerno, 2016). In such contexts, dual-designation may generate strong branding and visitor inflows, yet fail to induce corresponding logistics upgrading and commercial deepening—producing “visitor-heavy but supply-light” outcomes and constraining overall economic impacts (Smith and Diekmann, 2017). Moreover, policy effectiveness can depend critically on timing and sequencing. Sequential approaches (“culture first” or “tourism first”) may generate path dependence and imbalances: conservation-first strategies can postpone infrastructure and market formation, limiting logistics activation; tourism-first strategies may lock destinations into standardized, externally supplied models that weaken local value-chain deepening. In contrast, synchronous implementation has greater potential to align conservation objectives, infrastructure development, market strategies, and industrial linkages, thereby promoting concurrent growth in both passenger and logistics flows (UNWTO & UNESCO, 2018). This indicates that the timing and coordination of policy implementation are critical; otherwise, a functional mismatch between visitor growth and supply-chain readiness may occur. Therefore, we propose the following hypothesis.

The economic impacts of cultural–tourism integration are contingent on the timing and coordination of policy implementation; synchronous implementation is more likely to yield synergistic outcomes.

Finally, even well-designed integration strategies are conditioned by local enabling environments. The effects of place-based policies are shaped by institutional and market contexts (Pike et al., 2016). A favorable business environment—efficient markets, reliable infrastructure, access to finance, skilled labor, and supportive regulation—facilitates firm entry, specialization, and scaling, which strengthens the conversion of visitor inflows into broader production, distribution, and logistics activities. In cultural–tourism contexts, a dynamic business ecosystem with specialized service providers and active cultural markets can enhance commercialization and distribution of cultural assets and tourism demand (Brida et al., 2013; Richards and Marques, 2012), thereby improving the likelihood that overlapping cultural and tourism policies translate into sustained economic gains. The study thus moves beyond the traditional ‘status coupling’ view to a ‘functional integration’ perspective, emphasizing that the economic dividends of integration depend on the structural alignment of policy instruments. Based on this discussion, we propose the following hypothesis.

The local business environment positively moderates the economic effects of jointly implemented cultural and tourism policies; it is a critical enabler of effective policy integration.

Data and methodology

Identification strategy

Treating the designation of NHCC and CETC titles as a quasi-natural experiment, we construct a two-way fixed effects staggered DID model to evaluate the effects of cultural policies, tourism policies, and their combined implementation on regional economic development:

{D e v e l o p m e n t}_{i t} = α + β ({P o l i c y}_{i t}) + γ ({Controls}_{i t}) + ρ_{i} + σ_{t} + ε_{i t}

(1)

where

{D e v e l o p m e n t}_{i t}

is the dependent variable representing the level of economic activity in region

i

at time

t

;

{P o l i c y}_{i t}

is the core explanatory variable, indicating whether a city was exposed to a particular type of policy intervention in a given year, with separate regressions estimating the effects of NHCC designation, CETC designation, and their dual designation (NHCC–CETC).

The coefficient $β$ reflects the net effect of the corresponding policy shock on economic development. ${Controls}_{i t}$ represents a set of city-level covariates included to account for potential confounding variables. The terms $ρ_{i}$ and $σ_{t}$ denote city and year fixed effects, respectively, which control for unobserved heterogeneity across cities and time-specific shocks. $ε_{i t}$ is the random error term. This identification strategy leverages the staggered timing of policy adoption to isolate the causal impact of cultural and tourism policy interventions on economic outcomes.

Although the DID method addresses endogeneity to some extent, we cannot completely rule out reverse causality, as cities receiving these designations are not randomly selected and tend to be stronger or more developed, potentially causing selection bias. Therefore, we employ an Instrumental Variable (IV) analysis as a robustness check. Specifically, we use the number of national-level ICH items and the number of national-level scenic areas (LAND) in a city as instruments for the dual NHCC and CETC designation (policy intervention). The logic is that these counts serve as proxies for a city’s underlying cultural or natural endowments potential for receiving the respective titles. Cities with more ICH and LAND resources are more likely to obtain both NHCC and CETC titles, but these endowments are not directly affected by short-term economic fluctuations, thus satisfying the relevance and exogeneity requirements. Building on equation (1), we apply a Two-Stage Least Squares (2SLS) specification as follows:

{P o l i c y}_{i t} = θ_{0} + θ_{1} {I V}_{i t} + θ_{2} {C o n t r o l s}_{i t} + ρ_{i} + σ_{t} + ε_{i t}

(2)

{D e v e l o p m e n t}_{i t} = μ_{0} + μ_{1} \hat{{P o l i c y}_{i t}} + μ_{2} {C o n t r o l s}_{i t} + ρ_{i} + σ_{t} + ε_{i t}

(3)

In equation (2), ${I V}_{i t}$ represents the instrumental variables. In equation (3), $\hat{{P o l i c y}_{i t}}$ is the predicted value of ${P o l i c y}_{i t}$ obtained from the first-stage regression (2); $ρ_{i}$ and $σ_{t}$ , respectively, are city and year fixed effects; and $ε_{i t}$ is the random error term.

Variable description

${D e v e l o p m e n t}_{i t}$ is the dependent variable, which represents the level of economic development in region $i$ in year $t$ . We use the regional Gross Domestic Product (GDP) level to measure overall local economic development. Annual passenger transport volume (Passenger Flow) and freight transport volume (Logistics Flow) are used to measure two distinct aspects of economic activity.

${P o l i c y}_{i t}$ is the core explanatory variable, which is constructed using the annual list of NHCCs. If a city is designated as an NHCC in or before year $t$ , Policy_culture equals 1 for that year and subsequent years, 0 otherwise. The variable Tourism Policy (Policy_tourism) is constructed using the annual list of CETCs. If a city is designated as an CETC in or before year $t$ , Policy_tourism equals 1 for that year and subsequent years, 0 otherwise. Cultural-tourism policy intervention (Policy_merge) refers to cities that eventually received both titles, Policy_merge equals 1 in the year both titles are held and subsequent years, 0 otherwise.

Control variables ( ${Controls}_{i t}$ ) are used to mitigate omitted variable bias. Based on existing literature, these variables include transport infrastructure, openness level, education, geographical factors, and population (Dogru and Bulut, 2018; Fayissa et al., 2011; Rodríguez-Pose and Ketterer, 2020). These variables are known to be important determinants of economic development. Transport infrastructure (Railway) is a dummy variable indicating whether high-speed rail is operational. Openness (FDI) is the actual amount of foreign direct investment. Education (Edu) is proxied by government expenditure on education. The Geographical Factor (Port) considered in the distance to the nearest major port, and Population scale (People) is the population density.

We also considered two instrumental variables ( ${I V}_{i t}$ ): ICH: Cumulative number of national-level Intangible Cultural Heritage items and LAND is the cumulative number of national-level Scenic Areas.

Samples with missing data were excluded, and variables were winsorized at the 1% level to handle extreme values. Descriptive statistics for the variables included in the sample are shown in Table 2.

Table 2.

Descriptive statistics.

Variable	Definition	Obs	Mean	Std. Dev.	Min	Max
Dependent Variables
GDP	Gross Domestic Product (100 million yuan)	6637	1840	3210	17.93	44,700
Passenger flow	Total passenger volume (10,000 persons)	4291	8516.11	13,601.72	2	286,597
Logistics flow	Total freight volume (10,000 tons)	4290	8962.93	13,874.42	32	554,458
Core explanatory variables
Policy_culture	=1 if designated NHCC, 0 otherwise	7958	0.32	0.46	0	1
Policy_tourism	=1 if designated CETC, 0 otherwise	7958	0.60	0.49	0	1
Policy_merge	=1 if designated both NHCC & CETC, 0 otherwise	8050	0.26	0.44	0	1
Control variables
Railway	=1 if high-speed rail operational, 0 otherwise	5328	0.28	0.45	0	1
Port	Distance to nearest port (km)	6308	638.24	665.55	1.77	3564.53
FDI	Utilized foreign direct investment (100 million USD)	4351	3.89	8.96	0	104.96
Edu	Government education expenditure (100 million yuan)	5330	35.84	55.56	0	887.38
People	Population density (persons/sq km)	4590	418.68	320.07	5	2707
Instrumental variables
ICH	Cumulative number of national intangible heritage items (count)	6574	4.37	7.72	0	108
LAND	Cumulative number of national scenic areas (count)	6574	0.57	0.88	0	7

Empirical results

Baseline regression

To satisfy the assumption of normality, logarithmic transformations are applied to the relevant continuous variables. Based on equation (1), we employ a DID estimation strategy to evaluate the respective effects of cultural policy (NHCC designation), tourism policy (CETC designation), and their combined implementation on regional economic development. The regression results are presented in Table 3.

Table 3.

Baseline regression results.

	(1) lnGDP	(2) lnGDP	(3) lnGDP
Policy_culture	0.113^*** (0.013)
Policy_tourism		0.173^*** (0.014)
Policy_merge			0.119^*** (0.014)
Controls	Y	Y	Y
Year	Y	Y	Y
City	Y	Y	Y
N	3347	3347	3347
adj. R²	0.827	0.831	0.827

Notes: Standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.10.

The findings indicate that all three policy treatments—NHCC, CETC, and dual designation—significantly contribute to regional economic development, as measured by the natural logarithm of gross domestic product (lnGDP). Among these, the CETC (tourism) designation produces the most pronounced positive effect on economic growth, with a coefficient exceeding those associated with both the cultural policy (NHCC) and the dual designation. These results provide empirical support for Hypothesis 1.

This pattern is consistent with real-world cases. Cities emphasizing cultural heritage—such as Pingyao Ancient City in Shanxi—have achieved notable economic gains following NHCC designation. Likewise, cities with integrated cultural and tourism assets—such as Hangzhou, known for its rich cultural heritage and vibrant tourism industry—have benefited significantly from dual designation. However, cities such as Sanya, which attained CETC status primarily by capitalizing on natural scenery or modern tourism infrastructure, demonstrate even stronger economic performance. This reinforces the conclusion that tourism-focused policies, relative to cultural or combined approaches, exert the most substantial stimulative impact on regional economic development.

Channel analysis: Differences in “dual flow” effects

To investigate the mechanisms behind the stronger impact of tourism policy, we replace the dependent variable in equation (1) with measures of passenger flow and logistics flow and re-estimate the models. Results in Table 4 indicate marked differences in the channels through which policies influence economic development.

Table 4.

“Passenger flow” versus “Logistics flow” effects.

	(1)	(2)	(3)	(1)	(2)	(3)
	ln (Passenger flow)			ln(Logistics flow)
Policy_culture	0.083^*** (0.023)			0.001 (0.025)
Policy_tourism		0.110^*** (0.025)			0.052^* (0.027)
Policy_merge			0.113^*** (0.024)			−0.010 (0.026)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	3080	3080	3080	3080	3080	3080
adj. R²	0.557	0.559	0.559	0.414	0.415	0.414

Notes: Standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.10.

NHCC designation significantly increases passenger flow, likely reflecting the role of cultural signalling in attracting visitors. However, its effect on logistics flow is negligible and statistically insignificant. In contrast, CETC designation improves both passenger and logistics flows. The logistics effect may be attributed to infrastructure upgrades or expansion of tourism-related goods trade.

Cities with dual designation exhibit the highest increase in passenger flow across all categories, indicating successful attraction of tourists through the combination of cultural and tourism attributes. However, these cities do not experience a statistically significant improvement in logistics flow; in fact, the coefficient is slightly negative. This suggests that while combined policy implementation enhances a city’s appeal to tourists, it does not automatically translate into expanded freight movement or commercial interconnectivity.

This finding explains the baseline result that tourism policy outperforms the other two in terms of economic impact. Freight logistics typically generate higher economic multipliers by supporting trade, supply chains, and broader productivity. Although tourism contributes to GDP via consumption, its marginal returns diminish without corresponding logistics growth. This inference is supported by Table 5, which shows the coefficient for logistics flow on GDP exceeds that of passenger flow.

Table 5.

Differential impact of passenger and logistics flows on economic growth.

	(1) lnGDP	(2) lnGDP
ln(Passenger flow)	0.699^*** (0.011)
ln(Logistics flow)		0.757^*** (0.011)
Controls	Y	Y
Year	Y	Y
City	Y	Y
N	4290	4290
adj. R²	0.485	0.522

Notes: Standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.10.

Based on the results presented in Table 5, it can be argued that tourism policies are more effective in driving regional economic development because they activate both passenger and logistics channels. Dual designation, while stronger than cultural policy in attracting tourists, resembles cultural policy in its limited effect on logistics. Hence, combined designation without functional integration may underperform relative to tourism policy alone, supporting Hypothesis 2.

Robustness checks

Parallel trends test

To ensure the validity of the DID model, we conduct a parallel trends test using an event study framework based on the relative year of policy adoption. The treatment variable is expressed as a set of leads and lags around the policy year, omitting the policy year as the reference category. Following Angrist and Pischke (2010), coefficients are centred relative to the pre-treatment mean.

Figure 2(a)–(c) present the dynamic effects of NHCC, CETC, and dual designation on lnGDP. Pre-treatment coefficients are statistically indistinguishable from zero, confirming the parallel trends assumption. After policy implementation, statistically significant and increasing treatment effects emerge, indicating cumulative and growing policy impacts over time. These patterns validate the baseline results and reinforce the robustness of the findings.

Figure 2.

Parallel Trends Test Results.

Instrumental Variable (IV) method

To address potential endogeneity concerns arising from policy selection bias—specifically, the possibility that cities with superior governance or inherent economic momentum are more likely to receive national-level designations—this study employs an Instrumental Variable (IV) strategy within a Two-Stage Least Squares (2SLS) framework. We select the cumulative number of national-level Intangible Cultural Heritage items (ICH) and the cumulative number of national-level scenic areas (LAND) as instruments for the dual NHCC-CETC designation.

The integrated IV regression results, comprising both first-stage and second-stage estimations, are reported in Table 6. The first-stage results (Columns 1, 3, and 5) confirm the relevance of the chosen instruments: the coefficients for both ICH and LAND are positive and highly significant at the 1% level across all specifications. This indicates that a city’s cultural and natural resource endowments are robust predictors of its likelihood of obtaining dual policy status. Methodologically, the Kleibergen-Paap rk Wald F-statistics significantly exceed the conventional rule-of-thumb threshold of 10, effectively dismissing concerns regarding weak instrument bias. Furthermore, the Kleibergen-Paap rk LM statistics are significant at the 1% level, rejecting the null hypothesis of underidentification.

Table 6.

Instrumental variable estimation results.

	(1)	(2)	(3)	(4)	(5)	(6)
	1st-Policy_merge	2nd-lnGDP	1st-Policy_merge	2nd-lnPass	1st-Policy_merge	2nd-lnLogi
Policy_merge		0.153^** (0.070)		0.748^*** (0.114)		0.144 (0.107)
LAND	0.077^*** (0.010)		0.082^*** (0.010)		0.082^*** (0.010)
ICH	0.014*** (0.002)		0.015*** (0.002)		0.015*** (0.002)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	3347	3347	3080	3080	3080	3080
Weak_IV_F		79.427>10		77.802>10		77.802>10
Underid_LM		137.889		132.797		132.797
Underid_p		0.000		0.000		0.000
Hansen_J	0.000	48.952	0.000	26.734	0.000	0.643
Overid_p		0.000		0.000		0.423

1st: Dependent variable is Policy_merge; 2nd: Dependent variables are GDP/Flows. K-P rk Wald F is used for weak identification test. *p < 0.1, **p < 0.05, ***p < 0.01. Standard errors in parentheses.

The second-stage results (Columns 2, 4, and 6) demonstrate that the economic effects of policy integration remain significant after controlling for endogeneity. The estimated coefficient of dual designation on lnGDP is 0.153, significant at the 5% level. Regarding the transmission mechanisms, policy integration exerts a substantial positive impact on passenger flows (lnPass), with a coefficient of 0.748 (p < 0.01). However, its effect on logistics flows (lnLogi), while positive (0.144), does not reach statistical significance. These findings corroborate our baseline results, suggesting that the economic multiplier effect of dual designations is currently driven by population mobility and tourism consumption rather than deep integration of the logistics infrastructure.

Crucially, to satisfy the exclusion restriction, we performed overidentification tests. In the logistics model (Column 6), the Hansen J statistic yields a p-value of 0.423, well above the 0.1 threshold. This statistical evidence fails to reject the null hypothesis that the instruments are exogenous, confirming that ICH and LAND influence regional economic outcomes solely through the channel of policy designation, rather than through other unobserved direct paths. Collectively, these diagnostic tests provide strong empirical support for our IV strategy, ensuring the reliability and robustness of our principal findings.

Temporal exogeneity

To further verify the temporal exogeneity of our identification strategy and rule out anticipatory bias, we re-estimated the 2SLS models using lagged values (T-1) of ICH and LAND as instruments. This approach ensures that the policy effects are driven by historical resource endowments that precede current economic shocks.

As shown in Table 7, the results support the robustness of our findings. The impact remains positive and statistically significant (1.069, p < 0.05), confirming that the contribution of cultural-tourism integration to economic growth is consistent over time. While the coefficient for ln(Passenger) remains positive, its significance decreases compared to the baseline, suggesting that policy-driven branding effects are most potent in the immediate period following designation. The effect on ln(Logistics) remains insignificant, reinforcing the long-term nature of supply chain integration.

Table 7.

Lagged IV analysis.

	(1) lnGDP_Lag	(2) lnPass_Lag	(3) lnLogi_Lag
Policy_merge	1.069** (0.465)	0.088 (0.476)	0.447 (0.565)
Controls	Y	Y	Y
Year	Y	Y	Y
City	Y	Y	Y
N	3344	3077	3077
Hansen_J_p	0.145	0.270	0.109

All models pass the Hansen J overidentification test with p-values above 0.1, validating the exclusion restriction even under a lagged framework. In conclusion, these results substantiate the causal interpretation of our findings and confirm that the estimates are not biased by forward-looking behaviors or contemporaneous error correlations.

CS-DID

To further scrutinize the driving mechanism of cultural-tourism integration and isolate the potential interference of individual policies, this study employs the doubly robust estimator (CS-DID) proposed by Callaway and Sant’Anna (2021). We separately evaluate the dynamic impacts of a single cultural designation, a single tourism designation, and the synergistic implementation of both on regional economic growth (lnGDP).

The empirical results reveal that the economic effects of independent cultural or tourism policies are statistically insignificant and exhibit considerable volatility, suggesting a lack of sustained growth momentum from isolated industrial interventions. In contrast, under the “coordination” framework where both policies are implemented, the lnGDP shows a clear and stable stepwise upward trajectory, with its long-term impact significantly outperforming that of either single-policy setting. These findings provide robust evidence that cultural-tourism integration is not a mere summation of policies but a strategic coupling that generates a super-additive effect. Furthermore, the pre-treatment coefficients in all specifications are statistically indistinguishable from zero, confirming that the parallel trends assumption holds and ensuring the internal validity of our causal identification (Figure 3).

Figure 3.

Parallel Trends Test Results of CS-DID.

Placebo tests

To further rule out the possibility that the estimated results are driven by unobserved random factors and to ensure that the economic effects identified for cultural policy (NHCC), tourism policy (CETC), and cultural-tourism integration (dual designation) are not artifacts of mechanical data coding, this study conducts a series of placebo tests using Monte Carlo simulations. Specifically, while maintaining the treated group constant, we randomly assign a “placebo activation year” to each treated city within the sample period to construct randomized policy shocks. This regression process is repeated 500 times to observe the distribution of the placebo coefficients and their corresponding p-values.

The test results (Figure 4) indicate that the kernel density distributions of the placebo estimates for cultural policy, tourism policy, and dual designation are all centered around zero, with the vast majority of p-values far exceeding the 0.1 significance threshold. In contrast, the true estimated coefficients from the baseline regressions lie significantly outside the range of these randomized distributions, appearing as extreme outliers in the right tail. These outcomes provide strong empirical evidence that the observed economic growth is a result of genuine policy-driven causal effects rather than random data fluctuations or mechanical coding rules, thereby confirming the robustness of the primary findings.

Figure 4.

Placebo tests result.

Adjusting the policy identification window

To ensure the robustness of the findings, this study further adjusts the policy timing identification rules by excluding 131 early-designated cities that received titles before the year 2000 (including 90 National Historical and Cultural Cities and 54 China Excellent Tourism Cities, with 13 overlapping cases). This procedure aims to eliminate potential interference from the first-mover advantages of early adopters in terms of resource endowment and policy accumulation.

The results of this robustness check indicate that after restricting the sample to policy changes occurring post-2000, the positive driving coefficients of cultural policy, tourism policy, and synergistic coordination on lnGDP are 0.154, 0.206, and 0.148, respectively—all of which remain highly significant at the 1% level. These findings demonstrate that the conclusions of this study are not dependent on specific early-stage samples or policy time-coding standards, confirming that the promotional effect of cultural-tourism integration on regional economies is highly robust across different policy implementation windows (Table 8).

Table 8.

Baseline Regression Results of small sample.

	(1) lnGDP	(2) lnGDP	(3) lnGDP
Policy_culture	0.154** (0.018)
Policy_tourism		0.206*** (0.017)
Policy_merge			0.148** (0.019)
Controls	Y	Y	Y
Year	Y	Y	Y
City	Y	Y	Y
N	1963	1963	1963
adj. R²	0.749	0.757	0.747

Notes: Standard errors in parentheses. ***p < 0.01, **p < 0.05, *p < 0.10.

Urbanization heterogeneity

To further verify the robustness and external validity of our primary findings, we examine whether the identified mechanisms hold across different stages of urban development by stratifying the sample by urbanization level. The results reveal that while the positive contribution of these policies to overall economic growth (lnGDP) is universally robust—with tourism policy consistently serving as a potent driver—the underlying transmission channels exhibit significant heterogeneity. A notable “activation gap” emerges in passenger flow: whereas highly urbanized cities experience substantial increases across all policy categories, particularly under dual designation, low-urbanization cities only realize significant gains through tourism-oriented policies, with cultural and integrated designations failing to generate statistically significant visitor inflows.

Furthermore, the logistics channel demonstrates a distinct threshold effect. Significant positive impacts on logistics flows from tourism policies are exclusively observed in highly urbanized cities, whereas in less urbanized areas, tourism policies fail to mobilize freight movement and NHCC-CETC dual designation (Policy_merge) even exerts a significant negative shock. This suggests a potential “coordination failure” in resource-constrained regions, where administrative integration without sufficient commercial infrastructure may temporarily suppress existing logistics vitality. Overall, these findings indicate that while the aggregate economic effect is stable, the developmental logic shifts from a “dual-flow synergy” in developed urban centers to a model primarily constrained to passenger consumption in less developed areas, where growth remains hindered by underdeveloped logistics support (Table 9, 10 and 11).

Table 9.

Heterogeneity analysis of economic development by urbanization level.

	(1)	(2)	(3)	(4)	(5)	(6)
	lnGDP
	urban_Low	urban_High	urban_Low	urban_High	urban_Low	urban_High
Policy_culture	0.087*** (0.020)	0.130*** (0.017)
Policy_tourism			0.173*** (0.020)	0.169*** (0.019)
Policy_merge					0.104*** (0.021)	0.127*** (0.018)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	1368	1979	1368	1979	1368	1979
adj. R²	0.832	0.828	0.839	0.830	0.833	0.827

Standard errors in parentheses Grouped by the median of urbanization rate. p < 0.1, ^**p < 0.05, ^***p < 0.01.

Table 10.

Heterogeneity analysis of passenger flow by urbanization level.

	(1)	(2)	(3)	(4)	(5)	(6)
	ln(Passenger flow)
	urban_Low	urban_High	urban_Low	urban_High	urban_Low	urban_High
Policy_culture	−0.003 (0.032)	0.147*** (0.032)
Policy_tourism			0.075** (0.032)	0.148*** (0.037)
Policy_merge					0.028 (0.034)	0.172*** (0.033)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	1368	1712	1368	1712	1368	1712
adj. R²	0.548	0.566	0.549	0.565	0.548	0.568

Standard errors in parentheses Grouped by the median of urbanization rate. p < 0.1, ^**p < 0.05, ^***p < 0.01.

Table 11.

Heterogeneity analysis of logistics flow by urbanization level.

	(1)	(2)	(3)	(4)	(5)	(6)
	ln(Logistics flow)
	urban_Low	urban_High	urban_Low	urban_High	urban_Low	urban_High
Policy_culture	−0.053 (0.037)	0.045 (0.034)
Policy_tourism			−0.009 (0.037)	0.106*** (0.038)
Policy_merge					−0.074* (0.039)	0.035 (0.035)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	1368	1712	1368	1712	1368	1712
adj. R²	0.405	0.420	0.404	0.422	0.406	0.420

Standard errors in parentheses Grouped by the median of urbanization rate. p < 0.1, ^**p < 0.05, ^***p < 0.01.

Mechanism analysis: Achieving effective cultural-tourism integration

Heterogeneity analysis: The importance of synchronicity

The results in columns 1 and 2 (Table 12) show that cities following a culture-first, tourism-second sequence (history1_tourism2) experience a significant increase in passenger flow but a decline in logistics flow. This asymmetric pattern is consistent with insights from the cultural-economy and heritage governance literature. Heritage-oriented designations primarily operate through symbolic value, reputation, and place branding, which can quickly stimulate visitation and consumption on the demand side (Scott, 2000; Throsby, 2001). However, heritage governance often entails conservation-oriented rules and stricter land-use and development constraints, which may limit or delay the commercialization capacity needed to expand retail space, warehousing, and distribution networks (Winter, 2013). As a result, tourism expansion that occurs after a heritage-led phase can be “visitor-heavy” but relatively “supply-light,” generating immediate passenger responses while the logistics channel, which reflects deeper production–circulation linkages, remains weak or even contracts.

Columns 3 and 4 indicate that cities adopting a tourism-first, culture-second strategy (history1_tourism2) do not show robust gains in either passenger flow or logistics flow. This finding aligns with the destination management and policy-integration literature emphasizing path dependence and coordination frictions. Tourism-first development often prioritizes rapid market expansion through standardized products, marketing, and facility upgrading (Buhalis, 2001; Mariani et al., 2018). Such trajectories may lock destinations into mass-tourism models that rely on external procurement, weak local sourcing, and limited cultural differentiation, thereby constraining both repeat visitation dynamics and the deepening of local value chains (Bilen et al., 2017). From a policy-integration perspective, the later addition of cultural designation may have limited marginal returns if institutional priorities, governance routines, and business models have already been shaped by a tourism-first trajectory, making cross-sector coordination and product innovation harder to achieve (Peters, 2018).

In contrast, columns 5 and 6 show that synchronous implementation is associated with significant gains in both passenger flow and logistics flow. This pattern is consistent with the synergy view that integration outcomes depend on coordinated alignment across conservation objectives, market development, and industrial linkages rather than on policy “stacking” alone (UNWTO & UNESCO, 2018). When cultural protection and tourism upgrading are pursued simultaneously, destinations are more likely to build complementary capacities on the demand side while also strengthening the supply-side ecosystem needed for commercialization, distribution, and value-chain formation. This mechanism is also consistent with cultural–tourism integration studies emphasizing the need for coordinated planning and governance to connect cultural assets with market channels and supporting systems (Richards, 2018; Richards and Marques, 2012).

Overall, Table 12 helps reconcile the counterintuitive underperformance of dual-designation cities on logistics outcomes in baseline regressions. Dual designation is not equivalent to functional integration; the average logistics effect is attenuated by sequential strategies that increase visitation without comparable supply-chain upgrading, reflecting coordination failures and path-dependent trajectories highlighted in the policy-integration literature (Peters, 2018). Only when implementation is synchronized does policy overlap translate into dual-channel gains, providing direct support for Hypothesis 3.

Table 12.

Heterogeneity analysis results by policy implementation sequence.

	(1) ln(Pass. Flow)	(2) ln(Log. Flow)	(3) ln(Pass. Flow)	(4) ln(Log. Flow)	(5) ln(Pass. Flow)	(6) ln(Log. Flow)
history1_tourism2	0.106^*** (0.031)	−0.071^** (0.034)
tourism1_history2			0.0086 (0.039)	0.0049 (0.042)
Policy_merge					0.095^*** (0.032)	0.057^* (0.034)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	3080	3080	3080	3080	3080	3080
adj. R²	0.557	0.415	0.556	0.414	0.557	0.415

Notes: Standard errors in parentheses. Pass. Flow = Passenger Flow; Log. Flow = Logistics Flow. ***p < 0.01, **p < 0.05, *p < 0.10.

Moderation mechanism analysis: The role of cultural-business-tourism integration

To test Hypothesis 4, we examine whether local enabling conditions moderate the effectiveness of dual cultural and tourism designations. Place-based development and policy-implementation theories suggest that policy impacts depend on local market and institutional capacity to translate policy-induced opportunities into scalable economic activity (OECD, 2015; Pike et al., 2016). Existing cross-country studies underscore this by demonstrating that without a robust institutional framework, the positive correlation between tourism and GDP can vanish (Adedoyin et al., 2022). In cultural–tourism integration, overlapping designations may raise visibility and visitor demand, but sustained gains, especially on the supply side, require commercialization capacity and cross-sector coordination (Brida et al., 2013; Richards and Marques, 2012).

We proxy the business environment by the logarithm of employment in leasing and business services (ln_business_emp), which captures the local density of producer services that reduce transaction costs and support firm scaling and value-chain formation. This ecosystem should strengthen the conversion of visitor inflows into supply-chain and distribution activities, implying a stronger moderating effect on logistics-related outcomes. We capture the institutional cultural environment using a cultural system reform dummy (cul_reform), following Chang and Zhang (2024). Such reforms increase market-oriented governance and operational flexibility in the cultural sector, facilitating commercialization, product innovation, and coordination with tourism markets. We interact both moderators with the dual-designation indicator, and report the estimation results in Table 13.

Table 13.

Testing the effect of cultural-business-tourism integration (moderation analysis).

	(1) lnGDP	(2) ln(Pass. Flow)	(3) ln(Log. Flow)	(4) lnGDP	(5) ln(Pass. Flow)	(6) ln(Log. Flow)
Policy_merge * ln_business_emp	0.036^*** (0.010)	0.006 (0.019)	0.064^*** (0.021)
ln_business_emp	0.113^*** (0.007)	0.034^*** (0.013)	0.121^*** (0.014)
Policy_merge * cul_reform				−0.072*** (0.027)	0.007 (0.046)	0.171*** (0.051)
cul_reform				0.064*** (0.017)	0.145*** (0.029)	−0.074** (0.031)
Policy_merge	−0.224^** (0.088)	0.050 (0.163)	−0.595^*** (0.174)	0.144*** (0.017)	0.099*** (0.030)	−0.073** (0.032)
Controls	Y	Y	Y	Y	Y	Y
Year	Y	Y	Y	Y	Y	Y
City	Y	Y	Y	Y	Y	Y
N	3296	3029	3029	3347	3080	3080
adj. R²	0.846	0.559	0.436	0.828	0.563	0.425

Notes: Standard errors in parentheses. ln_business_emp = log of employment in leasing & business services. cul_reform = dummy for cultural system reform. Pass. Flow = Passenger Flow; Log. Flow = Logistics Flow. ***p < 0.01, **p < 0.05, *p < 0.10.

In Table 13, the interaction between dual designation and the local business environment is positive and statistically significant for both GDP and logistics flow. This pattern is consistent with place-based development and institutional perspectives arguing that policy effects depend on local market capacity to convert policy-induced demand into scalable production and circulation activities (OECD, 2015; Pike et al., 2016). In particular, a thicker producer-service ecosystem can reduce transaction costs, facilitate firm entry and specialization, and strengthen supply-chain coordination, thereby improving the translation of tourism-related demand into distribution and freight activity. This mechanism helps explain why the moderating role is especially salient for logistics outcomes, which capture deeper value-chain embedding beyond visitation alone.

Similarly, the interaction between dual designation and cultural system reform is significant, most notably for logistics flow. This result aligns with the cultural-economy and governance literature suggesting that market-oriented institutional arrangements in the cultural sector can enhance commercialization capacity, product innovation, and cross-sector collaboration (Chang and Zhang, 2024; Scott, 2000; Throsby, 2001). By lowering coordination frictions between cultural institutions and tourism markets, cultural reforms make it more feasible for overlapping designations to translate cultural resources into marketable products and for tourism development to build local sourcing and distribution linkages. Taken together, these findings reinforce Hypothesis 4 by showing that effective cultural–tourism integration is conditional on both commercial ecosystems and institutional readiness, rather than being an automatic outcome of policy overlap.

Conclusion and policy implications

Using panel data from Chinese prefecture-level cities over the period 2000–2022, this study evaluates the economic effects of two national designation policies—the National Historical and Cultural City (NHCC) and the China Excellent Tourism City (CETC)—within a quasi-natural experimental framework. By applying a difference-in-differences strategy and explicitly distinguishing passenger flow and logistics flow as transmission channels, the analysis moves beyond conventional policy evaluation to examine how different policy orientations, implementation strategies, and local contexts shape the effectiveness of cultural–tourism integration.

The results yield several interrelated findings. First, cultural and tourism policies both contribute positively to regional economic development, but their effects are asymmetric. Tourism-oriented designations exert a stronger overall impact on GDP growth, largely because they are more effective in activating logistics-related channels that are closely linked to supply chains, distribution networks, and broader production–circulation systems. Cultural designations, by contrast, primarily stimulate passenger flows through symbolic value and place branding, with more limited effects on logistics. Second, although dual designation significantly enhances a city’s attractiveness to visitors, it does not automatically translate into deeper economic integration. Without coordinated implementation, overlapping cultural and tourism policies tend to raise human mobility while leaving goods mobility and supply-chain upgrading constrained. Third, the sequencing of policy implementation matters. Only cities that pursue synchronized cultural and tourism development achieve simultaneous gains in passenger and logistics flows, confirming that functional integration depends on timing and coordination rather than on policy coexistence alone. Finally, the effectiveness of dual designation is strongly conditioned by local enabling environments. A stronger business ecosystem and market-oriented cultural reforms significantly amplify the economic returns of integration, particularly through logistics-related channels.

These findings generate several policy implications. First, policymakers should move beyond symbolic recognition and explicitly design cultural–tourism policies around functional transmission channels. While attracting visitors remains important, sustained economic gains depend on whether cultural and tourism development is connected to logistics systems, supply chains, and commercial networks. Urban governments should therefore integrate cultural assets into broader economic strategies that support product commercialization, local sourcing, and distribution capacity, rather than focusing narrowly on visitor numbers or branding outcomes.

Second, the synchronization of cultural and tourism policy design and implementation is critical. Sequential approaches that prioritize one domain in isolation risk creating path dependence and coordination failures that weaken integration effects, particularly on the supply side. Integrated master planning, joint project pipelines, and coordinated budgeting and approval processes across cultural, tourism, and economic development agencies can help align conservation objectives, infrastructure investment, and market development within a single policy trajectory.

Third, improving the business environment and institutional capacity is essential for translating cultural–tourism integration into broader economic development. Support for producer services, creative industries, and local supply chains can strengthen the conversion of cultural consumption and tourism demand into logistics activity and value-chain deepening. At the same time, cultural system reforms that enhance market orientation and operational flexibility can reduce coordination frictions between cultural institutions and tourism markets. Together, these enabling conditions allow integrated policies to move beyond administrative overlap and generate substantive economic outcomes.

Overall, this study contributes to the literature on cultural economy and policy integration by demonstrating that cultural–tourism integration is not an automatic consequence of policy stacking, but a conditional process shaped by policy orientation, timing, and local institutional environments. By clarifying the channels and conditions under which integration translates into economic growth, the findings offer both theoretical insights and practical guidance for regions seeking to leverage cultural and tourism resources for high-quality and sustainable development.

Several limitations of this study should be acknowledged. First, the empirical analysis focuses on prefecture-level cities in China, which are generally characterized by relatively higher levels of urbanization, administrative capacity, and infrastructure development. Although additional robustness checks based on urbanization levels indicate that the core mechanisms identified in this paper remain valid, the magnitude and composition of policy effects may differ in smaller cities or less urbanized areas. In lower-urbanization contexts, cultural and tourism policies may play a more foundational role in stimulating visitor inflows and supporting basic service development, while their capacity to activate logistics and broader economic linkages may be more constrained. Therefore, caution is warranted when directly extrapolating the estimated effects to smaller urban centers or rural regions. Nevertheless, the analytical framework developed in this study offers a replicable approach for future research. Applying this framework to smaller cities, rural destinations, or cross-country settings represents a promising direction for extending the understanding of cultural–tourism integration and its development impacts.

Footnotes

ORCID iDs

Na Tan

Peng Yan

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: National Social Science Fund of China (Project No. 24BJY116).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data supporting the findings presented in this paper are available from the authors upon reasonable request.*

Notes

Author biographies

Na Tan is currently the Professor in School of International Trade and Economics, Shanghai Lixin University of Accounting and Finance, China. She obtained her Ph.D from DongHua University of China. She was visiting scholar in Queensland University of Technology. Her research interest includes cultural economy, tourism economy, cultural and creative industries. Her work has been published in International Journal of Tourism Research, Journal of Tourism and Cultural Change, China soft science magazine etc. Email: tanna@lixin.edu.cn

Peng Yan, who is working in School of Economics, Yunnan University, Kunming, China. He got Doctor’s degree in economics from Yunnan University. His main research field is Industrial Economics. His work has been published in China Industrial Economics etc. Email: whutyp@163.com

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