Complex Network Analysis of Carbon Emission Transfers under Global Value Chains

Author(s):  
Yanfang Wang ◽  
Jingmin Yao

Abstract Accompanied with the increasing complicated global value chain (GVC) networks is the carbon emission transfers among countries. Utilizing the complex network analysis alongside quadratic assignment procedure (QAP), this paper detects the community structure and influencing forces of the emission transfers under GVCs. The results imply that the bipolar structure of the network transformed gradually to tripolar owing largely to the surging of carbon emissions from China. Evidence on the existence of environmental Kuznets curve (EKC) in the emission transfers from high-income countries to low-income countries, and a U-shape relationship in the transfers in the reverse direction, suggesting that growing carbon emissions from both low- and high-income countries transferred to other high-income countries gradually. Gaps in technology, especially in patent applications, between source and destination countries played an important role therein. JEL: F14, F18, Q56, R15

2021 ◽  
Vol 2 (1) ◽  
pp. 113-139
Author(s):  
Dimitrios Tsiotas ◽  
Thomas Krabokoukis ◽  
Serafeim Polyzos

Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.


2020 ◽  
Vol 67 (6) ◽  
pp. 1134-1138 ◽  
Author(s):  
Zhongke Gao ◽  
Hongtao Wang ◽  
Weidong Dang ◽  
Yongqiang Li ◽  
Xiaolin Hong ◽  
...  

Author(s):  
Emerson Luiz Chiesse da Silva ◽  
Marcelo De Oliveira Rosa ◽  
Keiko Veronica Ono Fonseca ◽  
Ricardo Luders ◽  
Nadia Puchaslki Kozievitch

2018 ◽  
Vol 55 ◽  
pp. 133-142 ◽  
Author(s):  
Wenyu Hou ◽  
Huifang Liu ◽  
Hui Wang ◽  
Fengyang Wu

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