Study on the decoupling effect of energy consumption and economic growth in the construction industry of Guangxi (People's Republic of China) from the perspective of the circular economy

Luo, Fa; Li, Xing; Peng, Cong

doi:10.1007/s42452-020-2855-4

Cited by 4 publications

(4 citation statements)

References 27 publications

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“…*e economic subsystem belongs to the power subsystem. In the system, future economic growth is determined by the economic growth rate and the economic aggregate in the base period, and affects energy consumption through three industries, it affects the total population through per capita GDP and, at the same time, excessive economic growth will have adverse effects on the environment [18]. *e flow of the economic subsystem is shown in Figure 2.…”

Section: Economic Subsystemmentioning

confidence: 99%

The Optimal Integration of Computer Information Technology and Energy Economic Management

Zhang

2022

International Transactions on Electrical Energy Systems

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The author proposes a method combining entropy weight method and TOPSIS method with computer information technology in order to save energy with maximum efficiency and improve efficiency. The author constructs the optimal integration of computer information technology and enterprise economic management. Managers use computer information technology to analyze data and problems more accurately and have stronger control ability. The noncooperative game model of gender warfare game and smart pig game are used to simulate negotiation and cooperation in reality, which is conducive to the formulation of cooperation mechanisms and the flexibility of negotiation to promote the realization of regional energy cooperation. Finally, combined with computer information technology, a comprehensive evaluation model of the energy economic system is constructed by using the entropy weight method and the TOPSIS method. The authors used a paired t test for the three evaluation results to examine whether their evaluation results were significantly different. Experimental results show that the correlation coefficient between method 1, method 2, and method 3 are both 0.984, and the correlation coefficient between method 2 and method 3 is 0.974, and the results are all significant. Conclusion. The method can effectively improve the efficiency and effectiveness of energy economy, and the detection results are better.

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Section: Economic Subsystemmentioning

confidence: 99%

The Optimal Integration of Computer Information Technology and Energy Economic Management

Zhang

2022

International Transactions on Electrical Energy Systems

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“…This study aims to ascertain whether the energy production or non-energy materials production sector has a more substantial influence on the Gross Domestic Product (GDP) or on enhancing company competitiveness. Energy production is a subset of energy consumption, while non-energy material manufacturing is an industry intricately linked to the circular economy (Luo, Li, & Peng, 2020;Marino, & Pariso, 2020). In pursuit of this objective, the Adaptive Neural Fuzzy Inference System (ANFIS) was implemented (Jang, 1993).…”

Section: Introductionmentioning

confidence: 99%

Improving competitiveness and economic growth in the Republic of Serbia through the concept of circular economy

Petković,

Milovančević,

Barjaktarović

2023

Int J Econ Practice & Policy

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The circular economy is a closed circular system in which material and energy losses are converted into resources that may be used for alternative objectives. Inextricably connected with sustainable development, it is primarily concerned with reducing material and energy losses. The optimal course of action would be to eradicate these losses and repurpose materials. Therefore, biodegradable items are used and commodities are disposed, reused and recycled. The primary aim of this study is to examine the impact of energy generation and non-energy materials on the gross domestic product (GDP) of Serbia and other OECD member states. The objective is to ascertain which energy or material production sector is more significant in GDP to enhance competitiveness. The findings reveal the present state of economic growth and the areas that need improvement to foster more business competitiveness. The Adaptive Neural Fuzzy Inference System (ANFIS) as it is well-suited for statistical analysis of highly nonlinear data. The most significant determinant of GDP in Serbia is the proportion of domestic material consumption devoted to the consumption of non-metallic minerals. Among OECD members, however, metal consumption as a proportion of domestic total material consumption is the most significant predictor of GDP. Additionally, the findings indicate that the ideal combination for forecasting GDP using two parameters is the sum of non-energy material output and total municipal trash generation. The findings may exemplify optimal strategies for incorporating the circular economy principle into operations to enhance corporate competitiveness, mitigate energy and material waste, and minimize adverse environmental effects.

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“…The purpose of the investigation was to determine which sector of energy or non‐energy material productivity has the more relevance on the GDP. Energy productivity represent energy consumption sector while non‐energy material productivity represents the sector closely connected to the circular economy (Luo et al, 2020; Marino & Pariso, 2020). For such a purpose adaptive neuro fuzzy inference system (ANFIS) (Jang, 1993; Sedghi et al, 2018; Shariati et al, 2020; Toghroli et al, 2014) was used since the methodology is suitable for statistical investigation of strongly nonlinear data sample due to features of fuzzy logic system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neuro fuzzy evaluation of energy and non‐energy material productivity impact on sustainable development based on circular economy and gross domestic product

Petković

Zandi

Agdas³

et al. 2021

Bus Strat Env

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Circular economy represents a concept for turning of material and energy wastes into resources for other purposes in a closed loop system. The purpose of circular economy is to minimize the energy and material wastes. The effect of energy and nonenergy material productivity on the gross domestic product (GDP) was analyzed in this study. The main contribution of the investigation was to determine which sector of energy or non-energy material productivity has the more relevance on the GDP.Energy productivity represent energy consumption sector while non-energy material productivity represents the sector closely connected to the circular economy. The used database covers OECD members in period 1990-2020. According to the results one can determine the current status of the economic development and what needs to be improved to reduce the energy and material wastes. On the contrary GDP needs to be tracked in order determine which factor has the more influence on the GDP. For such a purpose adaptive neuro fuzzy inference system (ANFIS) was used.The metals consumption represents the most relevant factor for GDP variation and prediction. The results show also the combination of non-energy material productivity and generated municipal waste is the best-case scenario for the GDP prediction.The obtained results could represent the best practices for implementation of circular economy concept.

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Study on the decoupling effect of energy consumption and economic growth in the construction industry of Guangxi (People's Republic of China) from the perspective of the circular economy

Cited by 4 publications

References 27 publications

The Optimal Integration of Computer Information Technology and Energy Economic Management

The Optimal Integration of Computer Information Technology and Energy Economic Management

Improving competitiveness and economic growth in the Republic of Serbia through the concept of circular economy

Adaptive neuro fuzzy evaluation of energy and non‐energy material productivity impact on sustainable development based on circular economy and gross domestic product

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