Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network

Hao, Xiaoqing; Qi, Hai; Gao, Xiangyun

doi:10.1016/j.apenergy.2015.04.032

Cited by 128 publications

(21 citation statements)

References 37 publications

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“…Complex network is an effective method by which to understand the essence of real economic systems [14][15][16][17][18][19][20][21]. The main idea is to consider the relationships among various parts of real complex systems as a complex network.…”

Section: Complex Network Methodsmentioning

confidence: 99%

Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions

Qian

Cao

2019

Sustainability

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With the in-depth implementation of the “Belt and Road” initiative (BRI), the investment patterns between Belt and Road countries have also become more complicated. The impact of this complex investment network on regional economic development is also growing. To reveal the complexity of this investment pattern, and to better promote the sustainable development of the region’s economy, this paper used the complex network method to study the foreign direct investment(FDI) network of 50 countries along the Belt and Road from 2003 to 2017, revealing its structural and behavioral characteristics and evolution process. The results showed that the imbalance of the investment network structure is outstanding, and preferential selection behavior is obvious. The Central and Eastern European countries show significant clustering behavior. In addition, the network evolved slowly and followed the “Pareto rule” in the early stages of its evolution. The BRI was a turning point in the evolution process. On this basis, the quadratic assignment procedure (QAP) regression analysis method was used to further study the factors affecting the formation process of this investment pattern. It found that economic development level, geographical distance, and bilateral trade were the main influencing factors. Among them, bilateral trade had the greatest impact on the pattern of network.

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Section: Complex Network Methodsmentioning

confidence: 99%

Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions

Qian

Cao

2019

Sustainability

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“…Russia cannot get rid from the economic addiction to deliveries of hydrocarbons for half a century already (Drozd & Nosal, 2012). Therefore, new structural reforms envisaged by the government in the "basic" and "target" development scenarios for the economy and the foreign trade in particular must become the main trend of the Russian foreign trade within the medium term perspective (Hao, An, Qi, & Gao, 2016). https://doi.org/10.15405/epsbs.2019.12.05.32 Corresponding Author: I.…”

Section: Problem Statementmentioning

confidence: 99%

Development Particulars And Trends Of Foreign Trade Activities Of The Russian Federation

Тимофеева¹

2019

The European Proceedings of Social and Behavioural Sciences

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“…Many studies focused on the roles of countries or areas in the network, using indicators for properties of individual countries such as unweighted and weighted degree, clustering coefficient (Hao et al 2018), centrality (Ge et al 2016), and competitiveness (Chen et al 2016). Others described the overall structure of trade networks with indicators characterizing the network as a whole, such as density, diameter, average pathlength (Hao et al 2016), and trade stability (Ji, Zhang, and Fan 2014). To describe the internal structure of a network, trade communities were often detected using the indicator modularity (Ji, Zhang, and Fan 2014;Zhong et al 2014Zhong et al , 2017.…”

Section: Introductionmentioning

confidence: 99%

Evolution of the global polyethylene waste trade system

Chen

Jiang

et al. 2020

Ecosyst Health Sustain

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Introduction: China's import bans on solid wastes starting from 2017 have challenged the global trade system of plastic wastes, which remains poorly characterized. This study chooses polyethylene (PE) as a case and aims to map out the global trade networks of PE waste (GPETN) from 1976 to 2017. Outcomes: We find that the size and complexity of the GPETN had been growing until 2016. After the mid-1990s, PE waste basically flowed from developed economies, mainly the EU and the US, to developing economies such as China. Since 2001 when admitted into the WTO, China's PE waste import surged until 2014 when it absorbed over 60% of global export. Regulations on solid waste import following the Green Fence campaign in 2013 resulted in substantial reductions in China's import as well as the global export of PE waste after 2014. Several other developing economies, such as Malaysia, Turkey, and Vietnam, had transitioned to net importers, but their imports were insufficient to replace China as new recycling bases for PE waste. Conclusion: The results highlight the urgent need of a joint effort for developed and developing countries to build a stronger global circular economy system with sufficient capacity to treat PE waste locally.

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Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network

Cited by 128 publications

References 37 publications

Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions

Pattern and Influencing Factors of Foreign Direct Investment Networks between Countries along the “Belt and Road” Regions

Development Particulars And Trends Of Foreign Trade Activities Of The Russian Federation

Evolution of the global polyethylene waste trade system

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