Global and local governance, industrial and geographical dynamics: A tale of two clusters

Zhu, Shengjun; He, Canfei

doi:10.1177/0263774x15621760

Cited by 23 publications

(17 citation statements)

References 43 publications

(73 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…China's State Council released the Water Pollution Prevention Action Plan in 2015, whereby development zones were required to establish centralized sewage treatment facilities and install automatic online monitoring devices by 2017. Many industrial parks have responded to the plan by improving their pollutant processing systems [27]. It is particularly efficient to combine waste treatment and pollutant recycling, thereby creating a circular economy in industrial agglomerations [9].…”

Section: Industrial Agglomeration Spatial Network and Pollutant Emmentioning

confidence: 99%

Effects of Agglomeration, Environmental Regulations, and Technology on Pollutant Emissions in China: Integrating Spatial, Social, and Economic Network Analyses

Wang

Wei

2019

Sustainability

View full text Add to dashboard Cite

Using prefecture-level panel data and social media data, this study investigates how industrial agglomeration, environmental regulations, and technology affect the pollutant intensity and spillover channels of pollutant emissions by integrating social and economic networks into a Spatial Durbin Model. The results show that industrial agglomeration, environmental regulations, and technological inputs facilitate the emissions intensity abatement. The outcomes also confirm that these factors affect the intensity of pollutant emissions in neighboring regions through social, economic, and spatial networks. Agglomeration has a negative spillover effect on the intensity of pollutant emissions in surrounding cities via social and spatial networks, while environmental regulations affect pollutant emissions intensity in related cities through social networks. Technology can effectively lower pollutant emissions through economic networks. These findings highlight the network linkages and spillover channels affecting the intensity of pollutant emissions.

show abstract

Section: Industrial Agglomeration Spatial Network and Pollutant Emmentioning

confidence: 99%

Effects of Agglomeration, Environmental Regulations, and Technology on Pollutant Emissions in China: Integrating Spatial, Social, and Economic Network Analyses

Wang

Wei

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…Such place‐specificity has been reinforced by the third type of transformation – decentralisation, which enabled Chinese localities to pick different development routes. Although all local authorities attempt to adopt pro‐business policies, some regions are more active and capable in providing a variety of subsidies, tax credits, fiscal and technological supports than others (Zhu & He ). Such regional variations of institutional arrangements could be integrated into our calculation of institutional proximity.…”

Section: Regional Industrial Diversification: Geographical Cognitivementioning

confidence: 99%

Proximity Matters: Inter‐Regional Knowledge Spillovers and Regional Industrial Diversification in China

Zhu

et al. 2018

Tijd voor Econ & Soc Geog

Self Cite

View full text Add to dashboard Cite

The effects of knowledge spillovers from neighbouring regions on regional industrial diversification should not be overlooked. Here we are referring to not only intra-industry knowledge spillovers from neighbouring regions, but also the spread of knowledge from related industries in neighbouring regions. This paper also develops an analytical framework that pays more attention to the role of institutional proximity between regions and how it is associated with geographical and cognitive proximity, and acknowledges that institutional proximity may generate asymmetric effects in the process of inter-regional knowledge spillovers. Using the Chinese custom database during 2002-11, we confirm that knowledge spillovers from neighbouring regions play a key role in regional industrial diversification. More importantly, inter-regional knowledge spillovers are likely to occur more efficiently if two regions have similar institutional contexts. It is also shown that institutional proximity could generate asymmetric effects in inter-regional knowledge spillovers.

show abstract

“…Industrial relocation, in particular, does not necessarily work for industrial clusters that are organically grown, locally embedded, and specialized in one function in an industry. Moreover, industrial attributes, territorial (national) socio‐economic contexts, and broader socio‐technical factors are also important in shaping certain trajectories and outcomes of cluster evolution (Isaksen, 2016; Yang & Dunford, 2017; Zhu & He, 2016). Nevertheless, the existing literature on cluster evolution has focused primarily on geographical dynamics of production‐side firms in the cluster but neglected demand‐side economic activities as an integral part of industrial cluster.…”

Section: Introductionmentioning

confidence: 99%

Spatio‐temporal dynamics of technical efficiency in China’s specialized markets: A stochastic frontier analysis approach

Zhang

2020

Growth and Change

View full text Add to dashboard Cite

China’s specialized markets as a special form of bottom‐up capital agglomeration have played a key role in fostering regional development. It once exhibited positive externalities with high efficiencies. However, given the rapid proliferation of specialized markets and the penetration of E‐commerce, their advantages may have shifted and the understanding of this shift is limited. The paper explores the spatio‐temporal dynamics of China’s specialized markets in terms of technical efficiency. Based on turnover data from Statistical Yearbooks of China Commodity Exchange Market from 2000 to 2016, technical efficiencies in specialized markets are measured by a Stochastic Frontier Analysis (SFA) approach using panel data. The results show that (a) the technical efficiencies in China’s specialized markets are significantly divergent in space over time; (b) labor input has notable effect on efficiency increase, while capital input has no significant effect; (c) informatization level, cluster size, and degree of market openness are identified to have a positive effect on specialized market’s technical efficiency. This paper argues that specialized markets should be taken seriously in the cluster evolution research. The role of proximity and the bounded links between specialized markets and their local clusters is the key to understanding their changing forms, performances, and trajectories.

show abstract

Global and local governance, industrial and geographical dynamics: A tale of two clusters

Cited by 23 publications

References 43 publications

Effects of Agglomeration, Environmental Regulations, and Technology on Pollutant Emissions in China: Integrating Spatial, Social, and Economic Network Analyses

Effects of Agglomeration, Environmental Regulations, and Technology on Pollutant Emissions in China: Integrating Spatial, Social, and Economic Network Analyses

Proximity Matters: Inter‐Regional Knowledge Spillovers and Regional Industrial Diversification in China

Spatio‐temporal dynamics of technical efficiency in China’s specialized markets: A stochastic frontier analysis approach

Contact Info

Product

Resources

About