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One aspect of agglomeration economies is economies of scale. When automobile production centered in Detroit in the early part of the twentieth century, this allowed more efficient production methods, which lowered the per-unit cost of output. Arrow (2000) emphasizes the tension between increasing returns to scale and equilibrium models, and as Young (1928) noted, increasing returns to scale is at the foundation of economic progress. Kaldor (1972), building on Young's insights, noted that static neoclassical economic models did not do a good job of depicting the economic progress that results from increasing returns to scale in production. This insight goes at least as far back as Adam Smith (1776), however, who noted the increased productivity that comes with an increased division of labor. Smith's example of the pin factory, where individuals specializing in one small part of a larger manufacturing operation increase productivity by, perhaps, hundreds of times, shows the benefits of agglomeration economies. The division of labor is limited by the extent of the market, Smith argued, so enlarging the extent of the market allows for a greater division of labor, which increases productivity and generates prosperity. By concentrating automobile production in Detroit rather than having automobiles locally built, the extent of the market is increased from one locality to an entire nation, and in some cases an entire world. The resulting agglomeration economies increase productivity and produce prosperity.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

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。

The purpose of this paper is to theorize how the industry life cycle unfolds differently across places and how economic agglomeration varies over time.

The paper relies on literature review and conceptual analysis.

It generates a dynamic geographic concentration model (i.e. an industry’s degree of geographic concentration drops in the growth stage, rises in the mature stage, and drops again in the new growth stage) and a localized industry life-cycle model (i.e. temporal dynamics differ between the center and the periphery).

It makes contribution by theorizing that the extent to which an industry is geographically concentrated changes over time, and by demonstrating how an industry’s center and periphery may experience different temporal dynamics.

The purpose of this paper is to indicate trade characteristics of Foreign direct investment (FDI) inflows in China and examine the dynamic interaction between FDI inflows and China’s international trade through empirical analysis.

At first, this paper builds the probability distribution model (Poisson and negative binomial (NB)) to capture the characteristics of spatial distribution of all kinds of FDI firms in Chinese cities and provinces based on count data, so as to indicate the potentials for further introducing FDI inflows in China; Second, this paper investigates the effects of trade on FDI firms inflows based on probability regress model (Binary Logit, Tobit, NB, Poisson, zero inflated negative binomial) and shows how international trade accelerates the different kinds of FDI firms to agglomerate in Eastern, Middle and Western region by the endowments of factors; third, this paper empirically examines the magnitude and characteristics of trade effects generated by FDI inflows by building dynamic panel model based on continuous data.

First, statistical tests of probability distribution model based on count data show that there are characteristics of spatial agglomeration of FDI firms such as manufacture firm, R & D firm, managing and marketing firm and total sectors, which obey NB distribution as whole; Second, this study indicate that FDI inflows have strong positive effects on the international trade in China’s provinces and on China’s regional trade, and that most of foreign firms in China are export oriented being strongly characterized as labor-intensive industries, especially, contributions of FDI to imports are greater than the contributions of FDI to exports in China’s Middle and Western trade, and the growth of FDI trade in China’s trade volume has been strong over the past years; third, the empirical results of models based on count data and continuous data indicate that FDI inflows have significantly positive relationship with international trade, that is, the relationship between FDI and international trade in the case of China is the characteristics with complement and imports substituting relationship.

Because of mixed data set for FDI inflows of processing and assembling trade and production-oriented FDI, efficiency-seeking and knowledge or technology – intensive FDI inflows in the past 36 years, the paper only investigate characteristics of FDI inflows in China before the turning point of financial crisis, but it is important for capturing the whole picture of trade characteristics of FDI inflows in China.

The derived quantitative results imply that there are still greater potentials for further introducing FDI inflows in China, and decision-maker should make policy of introducing FDI inflows which are favorable to supporting innovative activities and economic agglomeration, and preferably encourage efficiency-seeking and export-oriented FDI inflows so as enhance quality and efficiency of economic growth, which are also helpful to accelerate upgrade of Chinese industry and gradually shorten gap of growth among Eastern, Middle and Western region.

FDI inflows in China not only stimulate the remarkable growth of bilateral trade between host country and home country, but also promote the growth of international trade between China and the rest of the world. Thus, policies of bilateral or multilateral free-trade and investment area should be encouraged, which will be also favorable to promote the growth and welfare in all the regions.

This paper demonstrates that spatial distributions of FDI firms in Chinese cities and provinces obey NB probability distribution pattern, and puts forward the methodology of model based on count data and continuous data. Besides, this paper quantitatively indicates trade characteristics of FDI inflows in China as well as the dynamic interaction between FDI inflows and China’s international trade.

The purpose of this paper is to test geographic and economic distance of industrial agglomeration.

Based on a recent census database in China, we estimate the production function of Chinese firms, focusing on the impact of agglomeration economies.

The estimation results provide strong evidence that agglomeration effects decline with increasing geographic and economic distance.

Previous studies examine agglomeration effects at certain geographic and industrial level, but largely ignore that agglomeration benefit may be different at different levels of geography and industry. This paper contributes to the literature by examining the geographic and economic distance of agglomeration economies, and shows a clear pattern on geographic and industrial scope of agglomeration economies.

By observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.

In the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.

It is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.

The Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.

This study aims to understand how the institutional and populational characteristics of a Brazilian city, that is, size, gross domestic product (GDP), life expectancy, education, violence and amount of workers benefiting from PAT (Workers’ Food Program) bias the agglomeration of fast-food companies.

The research involved 7,653 units distributed among 270 brands of fast-food chains (9 foreign and 261 Brazilian) operating in 542 Brazilian cities in 2015 and institutional and populational characteristics information about them. It calculated the Herfindahl index and implemented mixed inflated beta models.

The study found out that the agglomeration of establishments is mainly associated with the city’s income per capita, education, GDP and with some differences regarding the origin of the company, Brazilian or foreign.

The limitations of the study are the availability of Brazilian cities' data and information about the fast-food companies, such as governance-related information and general infrastructure. The study was cross-sectional, which does not analyze the business installation speed.

This work provides data collection and analyzes which factors may contribute to the knowledge of the Brazilian fast-food market. It stands out that foreign companies do not seem to contemplate city violence. The proposed models can serve as an investors’ foundation to start, expand business and predict the number of establishments in a city.

The study highlights the relation between the cities’ institutional and populational characteristics and the aggregation of fast-food chains in Brazilian cities, using index commonly applied in industrial agglomeration.

The purpose of this paper is to offer clarity on a central concept introduced in Porter’s The Competitive Advantage of Nations, i.e. the cluster. The authors situate the concept introduced by Porter (1990) relative to two of its antecedents, the industrial district and industrial complex. Placing the cluster in a historical context permits consideration of the extent to which it, as a concept for analysis, may be differentiated from other geography-based approaches to economic phenomena. In this way, this paper examines the added value of the cluster concept derived from economic factors.

The paper provides a detailed literature review tracing the evolution of theories of location and agglomeration into which Porter’s cluster fits. The evolution of Porter’s own conceptualisation of the cluster and how this relates to theoretical clarity surrounding the concept is explored. Comparative analysis of theories of location, agglomeration and clustering is provided to identify similarities and differences across the approaches and identify the added value of the cluster concept in relation to other approaches.

Clustering represents a process associated with spatial organisational form which may offer advantages in efficiency, effectiveness and flexibility. Cluster benefits can be appreciated through the lens of Young’s (1928) identified sources of increasing returns. A key aspect in clustering is revealed in terms of its role in enabling four sources of increasing returns. The authors outline how these sources of increasing returns are related to “soft” processes of networking, interaction and individual and collective learning. Porter’s Diamond is a self-reinforcing system which can permit increasing returns and reinforce such tendencies of economic activity within agglomerations.

Added value from Porter’s cluster concept is identified in the context of both its locational anchoring and in terms of its potential for understanding the role of exploitation of increasing returns for development. This points to the importance of focusing on clustering as a process rather than on cluster within typologies of organisational form. This implies that the nature of relationships (and how they change) within and across markets, institutions and actors lies at the heart of clustering because of their roles in knowledge-generation, including innovation, knowledge sharing and upgrading.