Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-1-117-145
I. Solntsev
In Russia, sport historically belonged to the social sphere and only in recent years proved to have a commercial potential. Comparing with European countries, the sports industry of Russia should be recognized as emerging. The burden of financing professional sports clubs has not shifted to private investors and remains with regional budgets or state-owned companies. These funds are spent mainly on salaries of players (often legionnaires) and agents’ fees. Not earningon core business: media rights & match day, clubs lose their main part of earnings when the sponsor leaves, and are liquidated. The most popular sport in Russia (based on the number of people involved), and, consequently, the most promising from a commercial perspective, is football. Based on this, the aim of this research is to develop recommendations for improving the financial stability of football clubs as part of the licensing procedure. The current edition of the licensing rules for football clubs in England, Germany, France, Poland, Lithuania, Norway, Sweden and the scientific publications of domestic and foreign scientists dedicated to this issue acted as an analytical base. The paper provides a detailed analysis of the current level of football development in the Russian Federation, provides the main indicators characterizing its effectiveness, identifies problems and difficulties that impede positive dynamics. Based on this analysis and best European practices, the author proposed measures that will help to solve existing problems, attract private investors and increase the efficiency of spending budget funds. The proposed methods can be implemented in other team sports and accelerate development in terms of commercial potential, sports and social results.
{"title":"Improving the Financial Sustainability of Russian Football Clubs","authors":"I. Solntsev","doi":"10.17323/1813-8691-2020-24-1-117-145","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-1-117-145","url":null,"abstract":"In Russia, sport historically belonged to the social sphere and only in recent years proved to have a commercial potential. Comparing with European countries, the sports industry of Russia should be recognized as emerging. The burden of financing professional sports clubs has not shifted to private investors and remains with regional budgets or state-owned companies. These funds are spent mainly on salaries of players (often legionnaires) and agents’ fees. Not earningon core business: media rights & match day, clubs lose their main part of earnings when the sponsor leaves, and are liquidated. The most popular sport in Russia (based on the number of people involved), and, consequently, the most promising from a commercial perspective, is football. Based on this, the aim of this research is to develop recommendations for improving the financial stability of football clubs as part of the licensing procedure. The current edition of the licensing rules for football clubs in England, Germany, France, Poland, Lithuania, Norway, Sweden and the scientific publications of domestic and foreign scientists dedicated to this issue acted as an analytical base. The paper provides a detailed analysis of the current level of football development in the Russian Federation, provides the main indicators characterizing its effectiveness, identifies problems and difficulties that impede positive dynamics. Based on this analysis and best European practices, the author proposed measures that will help to solve existing problems, attract private investors and increase the efficiency of spending budget funds. The proposed methods can be implemented in other team sports and accelerate development in terms of commercial potential, sports and social results.","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76882935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/978-5-7598-2167-0
N. Vishnevskaya
In OECD countries, as a result of demographic changes that lead to slowdown in the growth of economically active population, the use of labour potential of older workers, including pensioners, is becoming increasingly urgent. The importance of this problem increases with the enlargement of this group in the total population. This article aims to analyze the dynamics and cross-country differences in the labour market situation of older workers in OECD countries, developed and transition. Particular attention is paid to the factors under which older workers’ participation in labour market is formed. The methodology of this work is based on institutional analysis of the labour market. The results of the study contribute to the understanding of the participation of certain groups of labour in employment. At the same time, this work is practically oriented, and its results can be used for formulating the population and labour market policy in the Russian Federation. We use the OECD Employment and Labor Market Statistics Database as the main source of statistical information. As results of the study, we state that in the OECD countries, since mid-1990s the older groups has significantly improved their position in the labour market, which is reflected in the growing level of economic activity and employment, lower, in comparison with other age cohorts, unemployment. Thus, the stable trend of the previous three decades was interrupted. At the same time there was a convergence of labour market indicators for male and female older age groups and convergence of official and effective retirement ages, including between gendergroups. Improvement of older workers employment is largely determined by their personal characteristics. Improving the health of elderly cohorts and lengthening the active period of life create conditions for longer working career. Structural changes in the branch and occupational composition of the employed also create favorable conditions for retaining and attracting older workers to the labour market. It would be wrong to link the "successes" of older workers in the labour market with the expansion of part-time employment – most of them work in full-time workplaces. The current policy of the OECD countries is mainly aimed at "pushing away" the employee's retirement age by legislative measures, including rising the retirement age. Still little is being done to create better employment conditions for these groups of labour, including retraining. Increasing the flexibility of the labour market could also contribute to a more active participation of older workers in the economic activity.
{"title":"Older Workers in the OECD Labour Market","authors":"N. Vishnevskaya","doi":"10.17323/978-5-7598-2167-0","DOIUrl":"https://doi.org/10.17323/978-5-7598-2167-0","url":null,"abstract":"In OECD countries, as a result of demographic changes that lead to slowdown in the growth of economically active population, the use of labour potential of older workers, including pensioners, is becoming increasingly urgent. The importance of this problem increases with the enlargement of this group in the total population. This article aims to analyze the dynamics and cross-country differences in the labour market situation of older workers in OECD countries, developed and transition. Particular attention is paid to the factors under which older workers’ participation in labour market is formed. The methodology of this work is based on institutional analysis of the labour market. The results of the study contribute to the understanding of the participation of certain groups of labour in employment. At the same time, this work is practically oriented, and its results can be used for formulating the population and labour market policy in the Russian Federation. We use the OECD Employment and Labor Market Statistics Database as the main source of statistical information. As results of the study, we state that in the OECD countries, since mid-1990s the older groups has significantly improved their position in the labour market, which is reflected in the growing level of economic activity and employment, lower, in comparison with other age cohorts, unemployment. Thus, the stable trend of the previous three decades was interrupted. At the same time there was a convergence of labour market indicators for male and female older age groups and convergence of official and effective retirement ages, including between gendergroups. Improvement of older workers employment is largely determined by their personal characteristics. Improving the health of elderly cohorts and lengthening the active period of life create conditions for longer working career. Structural changes in the branch and occupational composition of the employed also create favorable conditions for retaining and attracting older workers to the labour market. It would be wrong to link the \"successes\" of older workers in the labour market with the expansion of part-time employment – most of them work in full-time workplaces. The current policy of the OECD countries is mainly aimed at \"pushing away\" the employee's retirement age by legislative measures, including rising the retirement age. Still little is being done to create better employment conditions for these groups of labour, including retraining. Increasing the flexibility of the labour market could also contribute to a more active participation of older workers in the economic activity.","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86747033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-1-28-52
T. Erofeeva
{"title":"Assessment of the Functional Relationship between the Yield Spread and the Default Spread","authors":"T. Erofeeva","doi":"10.17323/1813-8691-2020-24-1-28-52","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-1-28-52","url":null,"abstract":"","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67833428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-3-340-371
N. Gorbacheva
{"title":"True Value of Electricity in Siberia: Cost-Benefit Analysis","authors":"N. Gorbacheva","doi":"10.17323/1813-8691-2020-24-3-340-371","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-3-340-371","url":null,"abstract":"","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67834717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-3-372-390
A. Votinov, S. Lazaryan
{"title":"The Influence of Trends in the Data on the Accuracy of DSGE Model Estimates","authors":"A. Votinov, S. Lazaryan","doi":"10.17323/1813-8691-2020-24-3-372-390","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-3-372-390","url":null,"abstract":"","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67834858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-1-101-116
Gleb Goncharov, T. Natkhov
{"title":"Textual Analysis of Pricing in the Moscow Residential Real Estate Market","authors":"Gleb Goncharov, T. Natkhov","doi":"10.17323/1813-8691-2020-24-1-101-116","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-1-101-116","url":null,"abstract":"","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67833367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-3-391-414
A. Zubarev, K. Rybak
{"title":"The Impact of Risk Premium on Russian Macroeconomic Indicators","authors":"A. Zubarev, K. Rybak","doi":"10.17323/1813-8691-2020-24-3-391-414","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-3-391-414","url":null,"abstract":"","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67834371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-4-598-621
A. Podrugina, A. Tabakh
The article analyzes the behavior of the credit cycle in the period after the global financial crisis, as well as the consequences of changes in the «inter-crisis» period of 2010-2019 for the future credit cycle after new economic recession in 2020 caused by COVID-19 pandemic The «credit crunch» phase, defined as a period of reduced credit activity under the low and declining interest rates, has been prolonged in many countries since the global financial crisis The reason for this were both some mistakes in monetary policy and the tightening of financial regulation, primarily in the banking sector Ultimately, this led to slower economic growth, reduced efficiency of the banking channel of monetary policy and the transition of non-financial companies to alternative funding sources and the transfer of financial risks to the non-banking financial sector (primarily the shadow banking sector) According to the authors, the new world recession, caused by COVID-19 pandemic, will lead to further changes in the model of the credit cycle - funding opportunities at low interest rates be even more restricted (excluding public financing programs) and the Central Bank will act as «lender of primary resort» and the main risk collector The level of interest rates will affect service of increasing public debts In fact, under the ultra-low interest rates, credit crunch may occur in the debt market (except for companies with high credit rating), and financial risks will accumulate even more in the shadow banking sector The results of the analysis allow us to form a «frame» for further research of the credit cycle after a current economic recession В статье анализируется поведение кредитного цикла в период после глобального финансового кризиса, а также последствия изменений «межкризисного» периода 2010-2019 гг для будущего кредитного цикла после экономической рецессии 2020 г , вызванной пандемией COVID-19 Фаза «кредитного сжатия», определяемая как период сокращения кредитной активности на фоне низких и снижающихся процентных ставок, после глобального финансового кризиса затянулась во многих странах Причиной тому были как некоторые ошибки монетарной политики, так и ужесточение финансового регулирования - в первую очередь банковского сектора В конечном счете, это привело к замедленному экономическому росту, снижению эффективности кредитного канала монетарной политики, а также переходу нефинансовых компаний к альтернативным источникам финансирования и переносу финансовых рисков в небанковский финансовый сектор (в первую очередь в теневой банковский сектор) По мнению авторов, новая мировая рецессия, вызванная пандемией COVID-19, станет причиной дальнейших изменений в модели кредитного цикла Возможности фондирования под низкий процент будут еще более ограничены (за исключением государственного финансирования), а центральные банки будут выступать в роли «кредитора основной инстанции» и основного накопителя рисков От уровня ставок процента будет зависеть обслуживание возрас
{"title":"Next Credit Cycle: Danger of New «Euthanasia for the Rentiers»","authors":"A. Podrugina, A. Tabakh","doi":"10.17323/1813-8691-2020-24-4-598-621","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-4-598-621","url":null,"abstract":"The article analyzes the behavior of the credit cycle in the period after the global financial crisis, as well as the consequences of changes in the «inter-crisis» period of 2010-2019 for the future credit cycle after new economic recession in 2020 caused by COVID-19 pandemic The «credit crunch» phase, defined as a period of reduced credit activity under the low and declining interest rates, has been prolonged in many countries since the global financial crisis The reason for this were both some mistakes in monetary policy and the tightening of financial regulation, primarily in the banking sector Ultimately, this led to slower economic growth, reduced efficiency of the banking channel of monetary policy and the transition of non-financial companies to alternative funding sources and the transfer of financial risks to the non-banking financial sector (primarily the shadow banking sector) According to the authors, the new world recession, caused by COVID-19 pandemic, will lead to further changes in the model of the credit cycle - funding opportunities at low interest rates be even more restricted (excluding public financing programs) and the Central Bank will act as «lender of primary resort» and the main risk collector The level of interest rates will affect service of increasing public debts In fact, under the ultra-low interest rates, credit crunch may occur in the debt market (except for companies with high credit rating), and financial risks will accumulate even more in the shadow banking sector The results of the analysis allow us to form a «frame» for further research of the credit cycle after a current economic recession В статье анализируется поведение кредитного цикла в период после глобального финансового кризиса, а также последствия изменений «межкризисного» периода 2010-2019 гг для будущего кредитного цикла после экономической рецессии 2020 г , вызванной пандемией COVID-19 Фаза «кредитного сжатия», определяемая как период сокращения кредитной активности на фоне низких и снижающихся процентных ставок, после глобального финансового кризиса затянулась во многих странах Причиной тому были как некоторые ошибки монетарной политики, так и ужесточение финансового регулирования - в первую очередь банковского сектора В конечном счете, это привело к замедленному экономическому росту, снижению эффективности кредитного канала монетарной политики, а также переходу нефинансовых компаний к альтернативным источникам финансирования и переносу финансовых рисков в небанковский финансовый сектор (в первую очередь в теневой банковский сектор) По мнению авторов, новая мировая рецессия, вызванная пандемией COVID-19, станет причиной дальнейших изменений в модели кредитного цикла Возможности фондирования под низкий процент будут еще более ограничены (за исключением государственного финансирования), а центральные банки будут выступать в роли «кредитора основной инстанции» и основного накопителя рисков От уровня ставок процента будет зависеть обслуживание возрас","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67834743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-2-295-310
Ngadiman
The purpose of this research is to obtain empirical evidence about the relationship between the effects of leverage, dividend policy, and relational capital on corporate performance of the manufacturing companies listed in the Indonesia Stock Exchange over the period of 2016-2018. This is a quantitative study used secondary data of 117 companies listed on the Indonesian Stock Exchange (IDX) cover period of two years (2016-2018). The study made use of ex-post facto research design . Purposive sampling method employed for selecting data of sample to obtain sample of 117 companies and the unit analyze are 39. Data collection method used in this research is documentation. Methods of data analysis used descriptive statistical analysis and regression moderation with the test of absolute difference value. The data was analyzed using multiple regressions. Three formulated research hypotheses were achieved after tested. The findings from this study show that all the independent variables have effects on corporate performance (ROA) simultaneously (F-test). The t-test results showed that leverage (DAR), which is measured by a debt-to-asset ratio and dividend policy (DPR) which is proxies by a dividend payout ratio have significant effect on corporate performance, while relational capital (RCE) in this study was measured by relational capital efficiency has no significant effect on corporate performance (ROA).
{"title":"The Effect of Leverage, Dividend Policy, and Relational Capital on Corporate Performance","authors":"Ngadiman","doi":"10.17323/1813-8691-2020-24-2-295-310","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-2-295-310","url":null,"abstract":"The purpose of this research is to obtain empirical evidence about the relationship between the effects of leverage, dividend policy, and relational capital on corporate performance of the manufacturing companies listed in the Indonesia Stock Exchange over the period of 2016-2018. This is a quantitative study used secondary data of 117 companies listed on the Indonesian Stock Exchange (IDX) cover period of two years (2016-2018). The study made use of ex-post facto research design . Purposive sampling method employed for selecting data of sample to obtain sample of 117 companies and the unit analyze are 39. Data collection method used in this research is documentation. Methods of data analysis used descriptive statistical analysis and regression moderation with the test of absolute difference value. The data was analyzed using multiple regressions. Three formulated research hypotheses were achieved after tested. The findings from this study show that all the independent variables have effects on corporate performance (ROA) simultaneously (F-test). The t-test results showed that leverage (DAR), which is measured by a debt-to-asset ratio and dividend policy (DPR) which is proxies by a dividend payout ratio have significant effect on corporate performance, while relational capital (RCE) in this study was measured by relational capital efficiency has no significant effect on corporate performance (ROA).","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89805905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-01-01DOI: 10.17323/1813-8691-2020-24-1-9-27
H. Penikas
We study the world largest credit risk losses from the year of 1972. We expect that such events drove the credit risk regulation development by the Basel Committee on Banking Supervision, including that of the Internal Ratings-Based (IRB) one of the Basel II Accord. By choosing a round threshold of current USD 100m equivalent of loss amount and the entity total assets in excess of current USD 500m as ofthe loss announcement date, we collected the dataset of 56 cases with the total credit loss of the current USD 700bn (or ca. 900 constant 2018 USD bn) which occurred during the last half of a century. We provide granular description of the stylized facts that characterize five typical credit risk evolution scenarios. The two most unexpected findings are as follows. First, we verified the announced loss amounts by analysis of stock quotes dynamics around the loss announcement dates. Thus we were able to trace three cases where announced by mass media losses may seem to have been exaggerated. Second, there is a series of events when there was a disclosure combination of credit risk loss and operational one. It is likely that the latter might have been used to partially cover the former.
{"title":"History of the World Largest Credit Risk Losses in 1972–2018","authors":"H. Penikas","doi":"10.17323/1813-8691-2020-24-1-9-27","DOIUrl":"https://doi.org/10.17323/1813-8691-2020-24-1-9-27","url":null,"abstract":"We study the world largest credit risk losses from the year of 1972. We expect that such events drove the credit risk regulation development by the Basel Committee on Banking Supervision, including that of the Internal Ratings-Based (IRB) one of the Basel II Accord. By choosing a round threshold of current USD 100m equivalent of loss amount and the entity total assets in excess of current USD 500m as ofthe loss announcement date, we collected the dataset of 56 cases with the total credit loss of the current USD 700bn (or ca. 900 constant 2018 USD bn) which occurred during the last half of a century. We provide granular description of the stylized facts that characterize five typical credit risk evolution scenarios. The two most unexpected findings are as follows. First, we verified the announced loss amounts by analysis of stock quotes dynamics around the loss announcement dates. Thus we were able to trace three cases where announced by mass media losses may seem to have been exaggerated. Second, there is a series of events when there was a disclosure combination of credit risk loss and operational one. It is likely that the latter might have been used to partially cover the former.","PeriodicalId":37657,"journal":{"name":"HSE Economic Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91212109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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