Search results

The interaction between the culture and tourism industries is naturally concentrated in cities. However, the effect of their co-agglomeration on urban tourism development depends on their level of integration. This study aims to answer the following questions: Can culture–tourism co-agglomeration promote the development of the tourism economy? Is the effect of culture–tourism co-agglomeration on tourism development moderated by culture–tourism integration? Does culture–tourism co-agglomeration have spatial spillover effects?

Taking 262 prefecture-level cities in China from 2009 to 2019 as the research sample, this study measures the degree of culture–tourism co-agglomeration using a co-agglomeration index and measured culture–tourism integration using a coupling coordination degree model. Using a threshold model and a spatial econometric model, this study examined the effect of culture–tourism co-agglomeration on urban tourism development.

Culture–tourism co-agglomeration had a positive effect on the urban tourism economy, and the effect differed according to geographical location and city grade. Moreover, culture–tourism co-agglomeration’s effect on the urban tourism economy was affected by the level of culture–tourism integration. When the level of culture–tourism integration crossed the threshold, the positive effect of culture–tourism co-agglomeration on the urban tourism economy will be enhanced. Finally, culture–tourism co-agglomeration had positive spatial spillover effects on surrounding cities.

This study integrated culture–tourism co-agglomeration, culture–tourism integration and urban tourism economy into the same research framework and innovatively analyzed the effect of the scale and quality of culture–tourism interaction on the urban tourism economy.

文化产业和旅游产业之间的互动性使其天然地在城市中集聚发展。然而, 文化和旅游协同集聚对城市旅游发展的影响取决于它们的融合发展水平。本研究旨在回答以下问题：文化和旅游协同集聚能否促进旅游经济的发展？文化和旅游协同集聚对城市旅游发展的作用是否受到文化和旅游融合发展水平的调节影响？文化和旅游协同集聚对城市旅游发展的影响是否具有空间溢出效应？

本文以2009-2019年中国262个地级及以上城市为研究样本, 采用协同集聚指数测度城市文化和旅游集聚水平, 采用耦合协调度模型测度城市文化和旅游融合发展水平, 并通过构建面板门槛模型和空间计量模型, 检验文化和旅游协同集聚对城市旅游发展的影响。

文化和旅游协同集聚对城市旅游发展具有正向的促进作用, 而且这种影响会因为地理位置和城市等级的不同而存在差异。此外, 文化和旅游协同集聚对城市旅游发展的促进作用还受到文旅融合发展水平的影响, 当文旅融合发展水平跨越发展门槛后, 文化和旅游协同集聚对城市旅游发展的正向影响得到增强。最后, 文化和旅游协同集聚对周边城市具有积极正向的空间溢出效应。

本文将文化和旅游协同集聚、文化和旅游融合发展、城市旅游发展纳入统一框架, 创新性地分析了文化和旅游互动发展的规模和质量对城市旅游发展的影响。

This study examines the contribution of urban development to Vietnam's economic progress over the period 1986–2020. The study uses an augmented Solow framework, where urbanization is included as a shift variable in addition to capital per worker and accounts for structural breaks. It examines the cointegration and the long-run and short-run effects of urban development from four different cases of cointegration (constant, restricted constant, restricted trend and trend options), with each case accounting for the effect of a significant structural break. Also, the study provides causality nexus to check the presence of urbanization-led growth hypothesis. From the results, we note a long-run positive effect of urbanization on economic growth, but no short-run effects. In all cases, a 1% increase in population results in 0.8–0.9 increase of output, hence supporting a positive and momentous effect of urbanization over the long-term. We note a significant positive effect of a single structural break period (1991), which is a period of major shift towards economic progress. We note bidirectional causality between capital and output and a unidirectional causality from output and capital to urbanization. The former suggests a mutually reinforcing effect of capital accumulation and economic growth, and the latter indicates that urban development necessitates economic growth and capital accumulation. The findings derived from this study provide further impetus for urban development and urban policies and consider urbanization as a critical source of economic growth for Vietnam.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

This study aims to investigate the factors affecting urban economic development in emerging economic market countries and to provide a new research perspective on urban skyscraper construction.

An empirical analysis based on a difference-in-differences (DID) model is conducted using data of urban data in China that expand into developed markets from 2003 to 2018.

The results of the spatial heterogeneity test indicate that the construction of skyscrapers has a significant promotional effect on the eastern city's economy. In contrast, it has a significant inhibitory effect in the central and western regions. Further findings demonstrate that the construction of skyscrapers can influence urban economic development by promoting industrial agglomeration, especially when the transmission effect of the diversified accumulation of tertiary industry is more prominent. The expansion analysis shows that skyscrapers have increased the level of trade in the city, and the impact on trade has an optimal height.

This paper focuses on the economic and trade effects of skyscrapers, and the optimal height of skyscrapers needs to be discussed in more depth, which is also the next problem the researchers need to study.

The government should attach importance to and promote the construction of urban skyscrapers, and do a good job in overall planning and design. The city should formulate preferential policies in land, taxation, finance, system and other aspects to increase support for urban skyscraper construction and promote local economic development.

This study focuses on the impact of urban skyscraper construction on the economic and trade development of cities in developing countries, which not only complements the relevant research on the economic effects of urban skyscraper construction, but also helps to provide reference for the sustainable development of urbanization in many developing countries.

This conceptual paper aims to develop the vision of a novel policy tool called the digital industrial cluster (DIC) thought for a future context shaped by digital economies and Industry 4.0. The DIC departs from the industrial cluster’s precepts and take them into the digital agglomeration phenomenon.

This research uses a discursive and theoretical approach. To create a clear picture related to the research topic, this paper reviews the literature on how industrial clusters deal with digital transformation. The review takes a particular interest in industrial clusters, information and communication technologies, Industry 4.0 and policy tools for digital agglomeration.

The research develops the vision of the DIC as a new policy tool, building its foundations on both industrial clusters and digital economies; furthermore, the DIC was compared with other policy tools based on digital agglomeration to understand the similarities, differences and advantages of the former. Finally, this paper discussed where the DIC could find its way toward implementation and what externalities could be expected from doing so.

This research could be useful for policymakers and cluster organizations looking to deploy policy tools that take advantage of industrial clusters and digital transformation. Besides, the theoretical foundations presented could lead researchers to empirical identification of early incarnations of the DIC.

This paper develops theoretical principles for a new policy tool that connects industrial clusters, digital agglomeration and Industry 4.0 for the first time.

Indirect knowledge leakage to rivals located near alliance partners represents a significant risk that has received limited scholarly attention. Hence, the question of how to manage this risk – which the authors term “partner-rival co-location risk” – in nonequity alliances remains unanswered, and this study aims to suggest establishing a steering committee to oversee the partnership.

Drawing on the agglomeration economies and alliance governance literatures, the authors develop a set of hypotheses and perform a series of empirical tests on 470 nonequity alliances in the US biopharmaceutical industry.

The authors propose that there is a positive linkage between partner-rival co-location risk and the formation of a steering committee in a nonequity alliance, which receives strong empirical support. Further, this relationship is significantly moderated by the breadth (alliance scope) but not the depth (reciprocal interdependence) of interaction between the partnering firms.

This paper is a pioneer to shed light on “partner-rival co-location risk” and how partner-rival co-location risk affects the governance decision of whether to establish a steering committee in a nonequity alliance, thus offering important theoretical and practical insights into competition and cooperation in alliance management.

This study investigates the impact of smart city construction (SCC) on urban energy consumption.

The focus is on a panel of 285 prefecture level cities in China from 2010 to 2021. The empirical evidence is based on the difference-in-difference (DID) method. We uses per capita coal consumption as a proxy variable to measure urban energy consumption energy consumption. We set the SCC as a policy dummy variable, with pilot cities set to 1 and non-pilot cities set to 0. We also selected a series of control variables that affect urban energy consumption, such as urbanization rate, labor force, road density, number of college students per 10000 people, regional economic development level and so on.

(1) SCC significantly reduces urban energy consumption, and the conclusion still holds after conducting robustness testing; (2) SCC reduces urban energy consumption is mainly effective in those cities with larger scale, stronger human capital, larger financial services and better information infrastructure construction; (3) The technological innovation and industrial structure upgrading are the main mechanisms for the SSC policy to reduce urban energy consumption.

The results in this study provide evidence for achieving an environmentally friendly society.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.

The paper aims to examine the digital economy's influence on China's regional innovation and development. It focuses on direct effects and spatial spillover across regions, and the mediating role of human capital. This analysis is vital for policy and strategic planning in the digital era.

This study uses panel data from 30 Chinese provinces (2004–2019) and uses the entropy method to quantify the digital economy's development. It investigates its impact on regional innovation using a dynamic spatial Durbin model (SDM) and mediation effect model, assessing direct effects, spatial spillover and human capital's mediating role. Various control variables are included for comprehensive analysis.

Findings show the digital economy significantly boosts regional innovation, acting as a growth driver. However, impacts vary regionally, with the central region gaining more than the eastern and western areas. Spatial spillover effects are mixed, showing negative short-term and positive long-term impacts under different weight matrices. Human capital is crucial for fostering innovation through the digital economy.

The paper offers unique insights into the spatial dynamics of the digital economy's impact on regional innovation in China. It advances understanding of the digital economy's role in regional development using innovative methods like the entropy method and dynamic SDM. Highlighting human capital as a key mediating factor enriches discussions on digital economy strategies for regional innovation.

The purpose of this paper is to develop an index for measuring urban house price affordability that integrates spatial considerations and to explore the drivers of housing affordability using the post-least absolute shrinkage and selection operator (LASSO) approach and the ordinary least squares method of regression analysis.

The study is based on time-series data collected from 2005 to 2021 for 256 prefectural-level city districts in China. The new urban spatial house-to-price ratio introduced in this study adds the consideration of commuting costs due to spatial endowment compared to the traditional house-to-price ratio. And compared with the use of ordinary economic modelling methods, this study adopts the post-LASSO variable selection approach combined with the k-fold cross-test model to identify the most important drivers of housing affordability, thus better solving the problems of multicollinearity and overfitting.

Urban macroeconomics environment and government regulations have varying degrees of influence on housing affordability in cities. Among them, gross domestic product is the most important influence.

The paper provides important implications for policymakers, real estate professionals and researchers. For example, policymakers will be able to design policies that target the most influential factors of housing affordability in their region.

This study introduces a new urban spatial house price-to-income ratio, and it examines how macroeconomic indicators, government regulation, real estate market supply and urban infrastructure level have a significant impact on housing affordability. The problem of having too many variables in the decision-making process is minimized through the post-LASSO methodology, which varies the parameters of the model to allow for the ranking of the importance of the variables. As a result, this approach allows policymakers and stakeholders in the real estate market more flexibility in determining policy interventions. In addition, through the k-fold cross-validation methodology, the study ensures a high degree of accuracy and credibility when using drivers to predict housing affordability.