Pub Date : 2022-02-25DOI: 10.1080/15567249.2022.2042428
Paola Tiranzoni, Alessandro Sapio, Alessia Casamassima, P. Falcone
ABSTRACT The present study investigates the determinants of differences between public preferences for energy sources and the actual country-level energy mix (“dissatisfaction”). Nineteen European countries have been examined, drawing on data from the 2016 European Social Survey. The main findings are that trusting individuals express lower dissatisfaction with the share of renewable energy sources and greater dissatisfaction with the share of fossil fuels and nuclear power; and individuals who are worried about energy security expressed an inflated preference for programmable energy sources (e.g. fossil fuels and nuclear power). The implications of the findings and the importance of public energy preferences for shaping policy views are briefly discussed.
{"title":"Assessing energy misperception in Europe: evidence from the European social survey","authors":"Paola Tiranzoni, Alessandro Sapio, Alessia Casamassima, P. Falcone","doi":"10.1080/15567249.2022.2042428","DOIUrl":"https://doi.org/10.1080/15567249.2022.2042428","url":null,"abstract":"ABSTRACT The present study investigates the determinants of differences between public preferences for energy sources and the actual country-level energy mix (“dissatisfaction”). Nineteen European countries have been examined, drawing on data from the 2016 European Social Survey. The main findings are that trusting individuals express lower dissatisfaction with the share of renewable energy sources and greater dissatisfaction with the share of fossil fuels and nuclear power; and individuals who are worried about energy security expressed an inflated preference for programmable energy sources (e.g. fossil fuels and nuclear power). The implications of the findings and the importance of public energy preferences for shaping policy views are briefly discussed.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"40 3 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85773780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-21DOI: 10.1080/15567249.2022.2038731
Tichinashe Mabugu, R. Inglesi‐Lotz
ABSTRACT Since 2008, the South African economy has experienced several power cuts (unplanned or as part of a load-shedding schedule), presumably because of the inability of the electricity supply to cover the demand. This paper examines the impact of such a demand-supply mismatch on the country’s economic growth within a production function framework. To do so, we use an Autoregressive Distributed Lag Model (ARDL) for the period 1985 to 2019. The paper finds that a positive mismatch (or surplus) of electricity (supply>demand) boosts economic growth in the long run. This finding provides evidence that supports the necessity of electricity supply expansion and the promotion of energy efficiency measures that both will create a mismatch (surplus) conducive to economic growth.
{"title":"The effect of mismatched supply and demand of electricity on economic growth in South Africa","authors":"Tichinashe Mabugu, R. Inglesi‐Lotz","doi":"10.1080/15567249.2022.2038731","DOIUrl":"https://doi.org/10.1080/15567249.2022.2038731","url":null,"abstract":"ABSTRACT Since 2008, the South African economy has experienced several power cuts (unplanned or as part of a load-shedding schedule), presumably because of the inability of the electricity supply to cover the demand. This paper examines the impact of such a demand-supply mismatch on the country’s economic growth within a production function framework. To do so, we use an Autoregressive Distributed Lag Model (ARDL) for the period 1985 to 2019. The paper finds that a positive mismatch (or surplus) of electricity (supply>demand) boosts economic growth in the long run. This finding provides evidence that supports the necessity of electricity supply expansion and the promotion of energy efficiency measures that both will create a mismatch (surplus) conducive to economic growth.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"9 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83073668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-19DOI: 10.1080/15567249.2022.2038729
Amirhossein Bolurian, H. Akbari, T. Daemi, S. A. Mirjalily, S. Mousavi
ABSTRACT Existing electricity networks do not have information about their endpoints due to their hierarchical structure. Internet of things technology allows two-way communication with customers. This work proposes an energy management system for optimal planning of a microgrid, considering demand response and uncertainties on the internet of things framework. The planning problem is solved using the first and the second-level Benders decomposition method. Then, the model third level is developed and optimized by genetic-fuzzy algorithm. For energy management in the internet of things platform, first the consumers are clustered based on their consumption by C-Means algorithm and then the network sensor energy consumption is optimized by genetic-fuzzy algorithm. To choose the optimal solution, a non-dominant fuzzy decision process beam is adopted. Based on the numerical results, the developed model outperforms the two-level model as well as the three-level model that uses particle swarm optimization.
{"title":"Energy management in microgrids considering the demand response in the presence of distributed generation resources on the IoT platform","authors":"Amirhossein Bolurian, H. Akbari, T. Daemi, S. A. Mirjalily, S. Mousavi","doi":"10.1080/15567249.2022.2038729","DOIUrl":"https://doi.org/10.1080/15567249.2022.2038729","url":null,"abstract":"ABSTRACT Existing electricity networks do not have information about their endpoints due to their hierarchical structure. Internet of things technology allows two-way communication with customers. This work proposes an energy management system for optimal planning of a microgrid, considering demand response and uncertainties on the internet of things framework. The planning problem is solved using the first and the second-level Benders decomposition method. Then, the model third level is developed and optimized by genetic-fuzzy algorithm. For energy management in the internet of things platform, first the consumers are clustered based on their consumption by C-Means algorithm and then the network sensor energy consumption is optimized by genetic-fuzzy algorithm. To choose the optimal solution, a non-dominant fuzzy decision process beam is adopted. Based on the numerical results, the developed model outperforms the two-level model as well as the three-level model that uses particle swarm optimization.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"88 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79437365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-15DOI: 10.1080/15567249.2021.1999346
Chin-Yu Lee, C. Tang
ABSTRACT The global temperature has increased since the past century due to the over-reliance on fossil fuels. This scenario has triggered an energy transition toward environmentally friendly sources of energy. Technological innovation plays a key role in this energy transition scenario. Therefore, we examine the threshold and contingency effects of technological innovation on renewable energy. The panel threshold regression model is applied to estimate the relationships. Our findings suggest that technological innovation is important in enhancing renewable energy. However, we find that the relationship between technological innovation and renewable energy is contingent upon the level of technological innovation itself and other determinants, namely institutional quality, financial development, FDI, and human capital. These findings suggest that the aims of policies should not only focus on strategies to improve technological innovation but should also consider measures to support the drivers that facilitate the impact of technological innovation on renewable energy.
{"title":"The Threshold and Contingency Effects of Technological Innovation on Renewable Energy","authors":"Chin-Yu Lee, C. Tang","doi":"10.1080/15567249.2021.1999346","DOIUrl":"https://doi.org/10.1080/15567249.2021.1999346","url":null,"abstract":"ABSTRACT The global temperature has increased since the past century due to the over-reliance on fossil fuels. This scenario has triggered an energy transition toward environmentally friendly sources of energy. Technological innovation plays a key role in this energy transition scenario. Therefore, we examine the threshold and contingency effects of technological innovation on renewable energy. The panel threshold regression model is applied to estimate the relationships. Our findings suggest that technological innovation is important in enhancing renewable energy. However, we find that the relationship between technological innovation and renewable energy is contingent upon the level of technological innovation itself and other determinants, namely institutional quality, financial development, FDI, and human capital. These findings suggest that the aims of policies should not only focus on strategies to improve technological innovation but should also consider measures to support the drivers that facilitate the impact of technological innovation on renewable energy.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"33 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79963875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-15DOI: 10.1080/15567249.2022.2037028
A. Viskovic, Vladimir Franki
ABSTRACT Global effort to reduce greenhouse gas emissions is continuously growing stronger. Realization of the direct correlation of quality of life to the environmental aspects of the energy sector has been at the heart of the new energy paradigm. In light of this, ensuring full awareness of current and potential emissions, with regard to market circumstances and policy implications, is crucial in acquiring a better overview on the current issues and the future development of the energy system. Research presented in this paper offers a method for calculating direct CO2 emissions from electricity generation. It also offers an insight into current issues and future prospects of the South East Europe electricity market. Observing various scenarios, the region’s emission intensity is evaluated, with special consideration given to the potential impact of varying carbon prices.
{"title":"Evaluating and forecasting direct carbon emissions of electricity production: A case study for South East Europe","authors":"A. Viskovic, Vladimir Franki","doi":"10.1080/15567249.2022.2037028","DOIUrl":"https://doi.org/10.1080/15567249.2022.2037028","url":null,"abstract":"ABSTRACT Global effort to reduce greenhouse gas emissions is continuously growing stronger. Realization of the direct correlation of quality of life to the environmental aspects of the energy sector has been at the heart of the new energy paradigm. In light of this, ensuring full awareness of current and potential emissions, with regard to market circumstances and policy implications, is crucial in acquiring a better overview on the current issues and the future development of the energy system. Research presented in this paper offers a method for calculating direct CO2 emissions from electricity generation. It also offers an insight into current issues and future prospects of the South East Europe electricity market. Observing various scenarios, the region’s emission intensity is evaluated, with special consideration given to the potential impact of varying carbon prices.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"8 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81232845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-19DOI: 10.1080/15567249.2021.2025170
P. Paliwal
ABSTRACT Solar based microgrids provide an environmentally benign alternative to conventional generation. However, their capital intensive structure and variability compels comprehensive examination of planning scenarios. This paper presents a bi-stage planning framework for a solar-battery microgrid. In the first stage of planning, sizing is carried out for autonomous operation. The second stage extends analysis to grid connected mode wherein four cases of microgrid operation are investigated. The analysis involves techno-socio-economic evaluation of constrained and unconstrained power flow. The parameters such as risk state probability, unmet load fraction, levelized cost of energy and social cost of carbon are used to evaluate and compare different cases for a solar-battery based microgrid located in Jaisalmer, Rajasthan, India. The results demonstrate that storage integration is essential for sustaining reliability in autonomous operation of microgrid. It can be inferred from the results that permitting reverse power flow renders considerable economic benefits and fetches lowest cost.
{"title":"Bi-stage planning framework for a solar-battery based micro-grid using techno-socio-economic evaluation","authors":"P. Paliwal","doi":"10.1080/15567249.2021.2025170","DOIUrl":"https://doi.org/10.1080/15567249.2021.2025170","url":null,"abstract":"ABSTRACT Solar based microgrids provide an environmentally benign alternative to conventional generation. However, their capital intensive structure and variability compels comprehensive examination of planning scenarios. This paper presents a bi-stage planning framework for a solar-battery microgrid. In the first stage of planning, sizing is carried out for autonomous operation. The second stage extends analysis to grid connected mode wherein four cases of microgrid operation are investigated. The analysis involves techno-socio-economic evaluation of constrained and unconstrained power flow. The parameters such as risk state probability, unmet load fraction, levelized cost of energy and social cost of carbon are used to evaluate and compare different cases for a solar-battery based microgrid located in Jaisalmer, Rajasthan, India. The results demonstrate that storage integration is essential for sustaining reliability in autonomous operation of microgrid. It can be inferred from the results that permitting reverse power flow renders considerable economic benefits and fetches lowest cost.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"74 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72465809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-18DOI: 10.1080/15567249.2021.2018525
C. Ramos, M. Alvargonzález, B. Moreno
ABSTRACT The objective of this work is to measure the energy poverty in the European Union through the construction of an Energy Poverty Index by means of the multivariant technique of factorial analysis. The index is calculated for the 28 member countries of the European Union in the years 2008 and 2017. Moreover, the effect of distributed generation renewable resources (such as photovoltaic, small hydro or micro wind) on energy poverty is studied. The obtained results show that Bulgaria, Rumania, Greece, Latvia and Lithuania are among the countries that display the highest index. The countries with the lowest index are Denmark, Sweden, Finland, the Netherlands and Slovakia, among others. The distributed generation contributes to reduce energy poverty in all countries. In fact, Ireland, France, Luxembourg, Slovenia, Finland and Sweden, have shown greater capacity than others to respond to changes in the distributed generation.
{"title":"Study of energy poverty in the European Union: the effect of distributed generation","authors":"C. Ramos, M. Alvargonzález, B. Moreno","doi":"10.1080/15567249.2021.2018525","DOIUrl":"https://doi.org/10.1080/15567249.2021.2018525","url":null,"abstract":"ABSTRACT The objective of this work is to measure the energy poverty in the European Union through the construction of an Energy Poverty Index by means of the multivariant technique of factorial analysis. The index is calculated for the 28 member countries of the European Union in the years 2008 and 2017. Moreover, the effect of distributed generation renewable resources (such as photovoltaic, small hydro or micro wind) on energy poverty is studied. The obtained results show that Bulgaria, Rumania, Greece, Latvia and Lithuania are among the countries that display the highest index. The countries with the lowest index are Denmark, Sweden, Finland, the Netherlands and Slovakia, among others. The distributed generation contributes to reduce energy poverty in all countries. In fact, Ireland, France, Luxembourg, Slovenia, Finland and Sweden, have shown greater capacity than others to respond to changes in the distributed generation.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"25 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77655729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-05DOI: 10.1080/15567249.2021.2023707
Hangxing Zhou, Jian Sun
ABSTRACT Fossil-fired power generation is the most significant contributor to China’s carbon emissions. New energy such as wind and solar is rapidly deploying in China and is considered an alternative to fossil energy. This paper focuses on the comparison in financial performance between fossil-fired generation and new energy generation companies. To do so, we combine the listed companies’ financial data from 2010 to 2020 with the catastrophe progression method to evaluate the financial performance of China’s power generation companies. The results indicate that although the profitability of the fossil-fired generation industry has stagnated in the past ten years, its comprehensive financial performance is still better than that of the new energy industry. The profitability of new energy companies has increased significantly in the past decade, especially the wind energy companies, whose profitability has greatly improved from 2013 to 2020. Wind power generation also has outstanding operating capacity among new energy generations.
{"title":"Do new energy power generation companies have better financial performance? An analysis for China’s power generation industry","authors":"Hangxing Zhou, Jian Sun","doi":"10.1080/15567249.2021.2023707","DOIUrl":"https://doi.org/10.1080/15567249.2021.2023707","url":null,"abstract":"ABSTRACT Fossil-fired power generation is the most significant contributor to China’s carbon emissions. New energy such as wind and solar is rapidly deploying in China and is considered an alternative to fossil energy. This paper focuses on the comparison in financial performance between fossil-fired generation and new energy generation companies. To do so, we combine the listed companies’ financial data from 2010 to 2020 with the catastrophe progression method to evaluate the financial performance of China’s power generation companies. The results indicate that although the profitability of the fossil-fired generation industry has stagnated in the past ten years, its comprehensive financial performance is still better than that of the new energy industry. The profitability of new energy companies has increased significantly in the past decade, especially the wind energy companies, whose profitability has greatly improved from 2013 to 2020. Wind power generation also has outstanding operating capacity among new energy generations.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"1 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2022-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85766600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-28DOI: 10.1080/15567249.2021.2007178
I. Makris, Vassilis Babalos, P. Dimitrakopoulos
ABSTRACT In this article, we try to study the efficiency of energy indicators using the method of the analysis of the efficiency formula in 27 countries of EU with data drawn from Eurostat for the years from 1995 to 2014. Then, using the correlation of these data with the GDP of each country, we try to determine the energy policy of Greece as well as in each of EU countries. The novelty of this study is the division of the countries into two groups based on the contribution of industry to GDP. Our motivation for this research is the climate change and the need for redesigned policies to improve energy and economy efficiency. Findings indicate that such a quantitative analysis can provide useful measurable knowledge for policy makers in each of the 27 countries of the EU separately. The results indicate that EU policies can be smart, diversified, complementary and complete, aiming investment in the green economy.
{"title":"A study of the energy efficiency formula for the development of economic progress policies in Greece","authors":"I. Makris, Vassilis Babalos, P. Dimitrakopoulos","doi":"10.1080/15567249.2021.2007178","DOIUrl":"https://doi.org/10.1080/15567249.2021.2007178","url":null,"abstract":"ABSTRACT In this article, we try to study the efficiency of energy indicators using the method of the analysis of the efficiency formula in 27 countries of EU with data drawn from Eurostat for the years from 1995 to 2014. Then, using the correlation of these data with the GDP of each country, we try to determine the energy policy of Greece as well as in each of EU countries. The novelty of this study is the division of the countries into two groups based on the contribution of industry to GDP. Our motivation for this research is the climate change and the need for redesigned policies to improve energy and economy efficiency. Findings indicate that such a quantitative analysis can provide useful measurable knowledge for policy makers in each of the 27 countries of the EU separately. The results indicate that EU policies can be smart, diversified, complementary and complete, aiming investment in the green economy.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"43 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2021-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72974160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-21DOI: 10.1080/15567249.2021.2014604
Vicent Alcántara, Emilio Padilla, P. D. del Río
ABSTRACT We apply an index decomposition analysis to investigate the main drivers of CO2 emissions in the electricity generation sector in Spain over the period 1991–2017. We quantify the impact of five different effects: carbonization, transformation, fossil intensity, electricity intensity, and production effects. Four subperiods are identified. The relevance of the drivers changed over these subperiods. The fossil intensity, electricity intensity, and production effects played an important role in the increase in emissions during the first half of the period, and particularly from 1999 to 2005. In contrast, the carbonization and fossil intensity effects were the dominant drivers of emissions reductions between 2006 and 2010. The research allows an assessment of the impact of different measures on emissions by considering their influence on the different effects, and suggests which sets of measures could be more effective in reducing emissions.
{"title":"The driving factors of CO2 emissions from electricity generation in Spain: A decomposition analysis","authors":"Vicent Alcántara, Emilio Padilla, P. D. del Río","doi":"10.1080/15567249.2021.2014604","DOIUrl":"https://doi.org/10.1080/15567249.2021.2014604","url":null,"abstract":"ABSTRACT We apply an index decomposition analysis to investigate the main drivers of CO2 emissions in the electricity generation sector in Spain over the period 1991–2017. We quantify the impact of five different effects: carbonization, transformation, fossil intensity, electricity intensity, and production effects. Four subperiods are identified. The relevance of the drivers changed over these subperiods. The fossil intensity, electricity intensity, and production effects played an important role in the increase in emissions during the first half of the period, and particularly from 1999 to 2005. In contrast, the carbonization and fossil intensity effects were the dominant drivers of emissions reductions between 2006 and 2010. The research allows an assessment of the impact of different measures on emissions by considering their influence on the different effects, and suggests which sets of measures could be more effective in reducing emissions.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":"9 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80474565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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