Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (DMs), but also reflects the probability information of DMs. Score function of fuzzy number and weighting method are very important in multi-attribute group decision-making (MAGDM) issues. In many fuzzy environments, the score function and entropy measure have been proposed one after another. Firstly, based on the detailed analysis of the existed score function of PDHF element (PDHFE) and with the help of previous references, we build a novel score function for PDHFE. Secondly, a combined weighting method is built based on the minimum identification information principle by fusing PDHF entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) method. Thirdly, a novel PDHF MAGDM approach (PDHF-EDAS) is built by extending evaluation based on distance from average solution (EDAS) approach to the PDHF environment to solve the issue that the decision attribute information is PDHFE. Finally, the practicability and effectiveness of the PDHF MAGDM technique is verified by suppliers selection (SS) and comparing analysis with existing methods.
{"title":"EDAS METHOD FOR MULTIPLE ATTRIBUTE GROUP DECISION MAKING WITH PROBABILISTIC DUAL HESITANT FUZZY INFORMATION AND ITS APPLICATION TO SUPPLIERS SELECTION","authors":"Baoquan Ning, R. Lin, G. Wei, Xudong Chen","doi":"10.3846/tede.2023.17589","DOIUrl":"https://doi.org/10.3846/tede.2023.17589","url":null,"abstract":"Probabilistic dual hesitant fuzzy set (PDHFS) is a more powerful and important tool to describe uncertain information regarded as generalization of hesitant fuzzy set (HFS) and dual HFS (DHFS), not only reflects the hesitant attitude of decision-makers (DMs), but also reflects the probability information of DMs. Score function of fuzzy number and weighting method are very important in multi-attribute group decision-making (MAGDM) issues. In many fuzzy environments, the score function and entropy measure have been proposed one after another. Firstly, based on the detailed analysis of the existed score function of PDHF element (PDHFE) and with the help of previous references, we build a novel score function for PDHFE. Secondly, a combined weighting method is built based on the minimum identification information principle by fusing PDHF entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) method. Thirdly, a novel PDHF MAGDM approach (PDHF-EDAS) is built by extending evaluation based on distance from average solution (EDAS) approach to the PDHF environment to solve the issue that the decision attribute information is PDHFE. Finally, the practicability and effectiveness of the PDHF MAGDM technique is verified by suppliers selection (SS) and comparing analysis with existing methods.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"27 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86691391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of the current study is to search for the elements that determine the companies’ demand for technological services, and by doing so, to contribute to the advancement of a closer University-Company partnership in the sphere of activities in research, development and innovation. Based on the PLS-SEM methodology, an explanatory-predictive model was drawn up, which concluded that the four most influential variables are: the influence of the environment, market conditions, the technology adoption decision and the economic characteristics of the company. The originality and main contributions of this work lie in the construction and design of the proposed model, particularly the application of both the Confirmatory Tetrad Analysis and the Global Goodness-of-Fit measures adapted for the scope of PLS-SEM, both aiming to elaborate on its use and to provide a model that could be used by other researchers in different regions. By implementing this type of analysis, it is possible to better understand the drivers that push the choice of enterprises concerning the demand for technological services and, subsequently, policymakers, academy, and R&D agencies, as well as corporations leading to better strategies for closer and stronger cooperation and collaboration among themselves.
{"title":"PLS-SEM MODEL ON BUSINESS DEMAND FOR TECHNOLOGICAL SERVICES AND R&D AND INNOVATION ACTIVITIES","authors":"Juan J. García-Machado, W. Sroka, M. Nowak","doi":"10.3846/tede.2023.17968","DOIUrl":"https://doi.org/10.3846/tede.2023.17968","url":null,"abstract":"The aim of the current study is to search for the elements that determine the companies’ demand for technological services, and by doing so, to contribute to the advancement of a closer University-Company partnership in the sphere of activities in research, development and innovation. Based on the PLS-SEM methodology, an explanatory-predictive model was drawn up, which concluded that the four most influential variables are: the influence of the environment, market conditions, the technology adoption decision and the economic characteristics of the company. The originality and main contributions of this work lie in the construction and design of the proposed model, particularly the application of both the Confirmatory Tetrad Analysis and the Global Goodness-of-Fit measures adapted for the scope of PLS-SEM, both aiming to elaborate on its use and to provide a model that could be used by other researchers in different regions. By implementing this type of analysis, it is possible to better understand the drivers that push the choice of enterprises concerning the demand for technological services and, subsequently, policymakers, academy, and R&D agencies, as well as corporations leading to better strategies for closer and stronger cooperation and collaboration among themselves.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"10 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85080194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the long- and short-run effects of crude oil price (COP) and economic policy uncertainty (EPU) on China’s green bond index (GBI) using the quantile autoregressive distributed lag model. The empirical results show that COP and EPU produce a significant positive and negative influence on GBI in the long-run across most quantiles, respectively, but their short-run counterparts are opposite direction and only significant in higher quantiles. Thus, major contributions are made accordingly and shown in the following aspects. The findings emphasise the importance of understanding how COP and EPU affect China’s green bond market for the first time. In addition, both the long- and short-run effects are captured, but long-run shocks primarily drive the green bond market. Finally, time- and quantile-varying analyses are adopted to explain the nexus between COP and EPU to GBI, which considers not only different states of the bond market but also events that occur in different time periods. Some detailed policies, such as a unified and effective green bond market, an early warning mechanism of oil price fluctuation, and prudent economic policy adjustments, are beneficial for stabilising the green finance market.
{"title":"OIL PRICE SHOCKS, ECONOMIC POLICY UNCERTAINTY, AND GREEN FINANCE: A CASE OF CHINA","authors":"Kai-Hua Wang, Chiwei Su, Muhammad Umar, O. Lobonț","doi":"10.3846/tede.2022.17999","DOIUrl":"https://doi.org/10.3846/tede.2022.17999","url":null,"abstract":"This study investigates the long- and short-run effects of crude oil price (COP) and economic policy uncertainty (EPU) on China’s green bond index (GBI) using the quantile autoregressive distributed lag model. The empirical results show that COP and EPU produce a significant positive and negative influence on GBI in the long-run across most quantiles, respectively, but their short-run counterparts are opposite direction and only significant in higher quantiles. Thus, major contributions are made accordingly and shown in the following aspects. The findings emphasise the importance of understanding how COP and EPU affect China’s green bond market for the first time. In addition, both the long- and short-run effects are captured, but long-run shocks primarily drive the green bond market. Finally, time- and quantile-varying analyses are adopted to explain the nexus between COP and EPU to GBI, which considers not only different states of the bond market but also events that occur in different time periods. Some detailed policies, such as a unified and effective green bond market, an early warning mechanism of oil price fluctuation, and prudent economic policy adjustments, are beneficial for stabilising the green finance market.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"166 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80476226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates the interaction between fear sentiments and gold price (GP) by utilising the full-sample and sub-sample rolling-window bootstrap causality tests. It can be observed that GP can hedge the risk of fear sentiments in a certain period. The result supports the inter-temporal capital asset pricing model, which demonstrates that the increase in fear sentiments can promote the rise in gold prices. Due to excessive panic, fear sentiments also have negative effects on GP. In contrast, GP positively impacts fear sentiments, which manifests that market sentiment can be forecasted based on changes in the gold market. In addition, the negative influences from GP to fear sentiments indicate there are diversified assets that can be alternatives to gold. In the complicated international environment and volatile market sentiments, investors can benefit by optimising their asset portfolio. The governments can mitigate the adverse effects of large fluctuations in both markets by grasping the movement of gold and fear sentiments.
{"title":"CAN GOLD HEDGE THE RISK OF FEAR SENTIMENTS?","authors":"Chiwei Su, Yiru Liu, T. Chang, Muhammad Umar","doi":"10.3846/tede.2022.17302","DOIUrl":"https://doi.org/10.3846/tede.2022.17302","url":null,"abstract":"This paper investigates the interaction between fear sentiments and gold price (GP) by utilising the full-sample and sub-sample rolling-window bootstrap causality tests. It can be observed that GP can hedge the risk of fear sentiments in a certain period. The result supports the inter-temporal capital asset pricing model, which demonstrates that the increase in fear sentiments can promote the rise in gold prices. Due to excessive panic, fear sentiments also have negative effects on GP. In contrast, GP positively impacts fear sentiments, which manifests that market sentiment can be forecasted based on changes in the gold market. In addition, the negative influences from GP to fear sentiments indicate there are diversified assets that can be alternatives to gold. In the complicated international environment and volatile market sentiments, investors can benefit by optimising their asset portfolio. The governments can mitigate the adverse effects of large fluctuations in both markets by grasping the movement of gold and fear sentiments.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"9 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81514145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Conventional credit scoring models evaluated by predictive accuracy or profitability typically serve the financial institutions and can hardly reflect their contribution on financial stability. To remedy this, we develop a novel regulatory scoring framework to quantify and compare the corresponding regulatory capital charge errors of credit scoring models. As an application of RegTech, the proposed framework considers the characteristic of example-dependence and costsensitivity in credit scoring, which is expected to enhance the ability of risk absorption of financial institutions and thus benefit the regulators. Validated on two real-world credit datasets, empirical results reveal that credit scoring models with good predictive accuracy or profitability do not necessarily provide low capital charge requirement error, which further highlights the importance of regulatory scoring framework. The family of gradient boosting decision tree (GBDT) provides significantly better average performance than industry benchmarks and deep multilayer perceptron network, especially when financial stability is the primary focus. To further examine the robustness of the proposed regulatory scoring, sampling techniques, cut-off value modification, and probability calibration are employed within the framework and the main conclusions hold in most cases. Furthermore, the analysis on the interpretability via TreeSHAP algorithm alleviates the concerns on transparency of GBDT-based models, and confirms the important roles of loan characteristics, borrowers’ solvency and creditworthiness as powerful predictors in credit scoring. Finally, the managerial implications for both financial institutions and regulators are discussed.
{"title":"FROM CREDIT SCORING TO REGULATORY SCORING: COMPARING CREDIT SCORING MODELS FROM A REGULATORY PERSPECTIVE","authors":"Yufei Xia, Zijun Liao, Jun Xu, Yinguo Li","doi":"10.3846/tede.2022.17045","DOIUrl":"https://doi.org/10.3846/tede.2022.17045","url":null,"abstract":"Conventional credit scoring models evaluated by predictive accuracy or profitability typically serve the financial institutions and can hardly reflect their contribution on financial stability. To remedy this, we develop a novel regulatory scoring framework to quantify and compare the corresponding regulatory capital charge errors of credit scoring models. As an application of RegTech, the proposed framework considers the characteristic of example-dependence and costsensitivity in credit scoring, which is expected to enhance the ability of risk absorption of financial institutions and thus benefit the regulators. Validated on two real-world credit datasets, empirical results reveal that credit scoring models with good predictive accuracy or profitability do not necessarily provide low capital charge requirement error, which further highlights the importance of regulatory scoring framework. The family of gradient boosting decision tree (GBDT) provides significantly better average performance than industry benchmarks and deep multilayer perceptron network, especially when financial stability is the primary focus. To further examine the robustness of the proposed regulatory scoring, sampling techniques, cut-off value modification, and probability calibration are employed within the framework and the main conclusions hold in most cases. Furthermore, the analysis on the interpretability via TreeSHAP algorithm alleviates the concerns on transparency of GBDT-based models, and confirms the important roles of loan characteristics, borrowers’ solvency and creditworthiness as powerful predictors in credit scoring. Finally, the managerial implications for both financial institutions and regulators are discussed.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"4 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86961881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under intense industry competition, decision makers must ensure that products demanded by consumers can be quickly produced with minimum production cost. However, because uncertainties are unavoidable and inevitably affect decision makers, numerous studies have discussed how to control uncertainties or minimize their effects. Multiple uncertainties that interact simultaneously may cause a combined effect in actual systems. Therefore, this study presents a robust optimization model with two uncertainties, extending the method of robust optimization with one uncertainty. To demonstrate the applicability of the proposed model with two uncertainties, this study uses the supplier selection problem with component purchase quantity allocation in supply chain management as an analysis case. This considers the reliability of production and transportation and develops a multi-objective robust optimization model with two uncertainties. In addition, a nondominated sorting genetic algorithm is proposed for solving the proposed multi-objective robust optimization model. The relationship between price of robustness and budget parameters is explored by considering the robust optimization model with production and transportation uncertainties proposed in this study. Finally, there is a comparative analysis between the results for price of robustness in the proposed two-uncertainty model and in the one-uncertainty model.
{"title":"A ROBUST OPTIMIZATION MODEL WITH TWO UNCERTAINTIES APPLIED TO SUPPLIER SELECTION","authors":"Z. Che, T. Chiang, Chung-Chi Tsai","doi":"10.3846/tede.2022.17850","DOIUrl":"https://doi.org/10.3846/tede.2022.17850","url":null,"abstract":"Under intense industry competition, decision makers must ensure that products demanded by consumers can be quickly produced with minimum production cost. However, because uncertainties are unavoidable and inevitably affect decision makers, numerous studies have discussed how to control uncertainties or minimize their effects. Multiple uncertainties that interact simultaneously may cause a combined effect in actual systems. Therefore, this study presents a robust optimization model with two uncertainties, extending the method of robust optimization with one uncertainty. To demonstrate the applicability of the proposed model with two uncertainties, this study uses the supplier selection problem with component purchase quantity allocation in supply chain management as an analysis case. This considers the reliability of production and transportation and develops a multi-objective robust optimization model with two uncertainties. In addition, a nondominated sorting genetic algorithm is proposed for solving the proposed multi-objective robust optimization model. The relationship between price of robustness and budget parameters is explored by considering the robust optimization model with production and transportation uncertainties proposed in this study. Finally, there is a comparative analysis between the results for price of robustness in the proposed two-uncertainty model and in the one-uncertainty model.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"47 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78717327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research investigates and robustly verifies the impact of expansionary monetary policy actions on green innovation, conducted on a panel covering 133 countries from 1960 to 2018. Overall, we find that such actions have a significantly positive effect on green innovation performance, no matter in the static or dynamic model. A lower degree of central bank independence and poorer property rights protection in developing countries may hinder monetary policies’ effect to be transmitted to green innovation activities smoothly. Moreover, stringent environmental regulation contributes to magnifying the expansionary monetary policy’s positive effect on green innovation, but such a positive moderating effect should be supported by good national governance quality (including better control over corruption, higher efficiency of governments and a complete law system). Accordingly, several policy suggestions are provided.
{"title":"THE IMPACT OF MONETARY POLICY ON GREEN INNOVATION: GLOBAL EVIDENCE","authors":"H. Yin, Chun-ping Chang, Haijie Wang","doi":"10.3846/tede.2022.17020","DOIUrl":"https://doi.org/10.3846/tede.2022.17020","url":null,"abstract":"This research investigates and robustly verifies the impact of expansionary monetary policy actions on green innovation, conducted on a panel covering 133 countries from 1960 to 2018. Overall, we find that such actions have a significantly positive effect on green innovation performance, no matter in the static or dynamic model. A lower degree of central bank independence and poorer property rights protection in developing countries may hinder monetary policies’ effect to be transmitted to green innovation activities smoothly. Moreover, stringent environmental regulation contributes to magnifying the expansionary monetary policy’s positive effect on green innovation, but such a positive moderating effect should be supported by good national governance quality (including better control over corruption, higher efficiency of governments and a complete law system). Accordingly, several policy suggestions are provided.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"9 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83114192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Q. Han, Li Jin, M. A. S. Khan, Prince Asare Vitenu-Sackey, Bojan Obrenovic
Our study focuses on the role of foreign capital which includes foreign direct investment, foreign aid, and economic freedom in poverty alleviation in developing and underdeveloped countries by using panel data from 1995 to 2018 for 71 countries. In the pursuit of achieving our objective, we employed several econometric techniques such as dynamic ordinary least square, fully modified ordinary least square, dynamic fixed effect, and pooled mean group regression methods. Furthermore, we performed the Granger causality test, impulse response function, and variance decomposition analysis. In our long-run estimations, we found that foreign direct investment could significantly alleviate poverty but increases poverty in the short run. Instead, foreign aid plays no significant role in poverty alleviation. Moreover, economic growth and economic freedom are essential as our findings consistently exhibited that they play a crucial role in poverty alleviation. We also found bidirectional causality between poverty alleviation and population growth, while a unidirectional causal linkage was found from poverty alleviation to foreign aid. We conclude that policymakers should look at a new paradigm of developmental assistance, and governments should also create an aiding environment for foreign investment to support their growth plan.
{"title":"POVERTY ALLEVIATION IN DEVELOPING AND UNDERDEVELOPED COUNTRIES. DO FOREIGN CAPITAL AND ECONOMIC FREEDOM MATTER?","authors":"Q. Han, Li Jin, M. A. S. Khan, Prince Asare Vitenu-Sackey, Bojan Obrenovic","doi":"10.3846/tede.2022.17691","DOIUrl":"https://doi.org/10.3846/tede.2022.17691","url":null,"abstract":"Our study focuses on the role of foreign capital which includes foreign direct investment, foreign aid, and economic freedom in poverty alleviation in developing and underdeveloped countries by using panel data from 1995 to 2018 for 71 countries. In the pursuit of achieving our objective, we employed several econometric techniques such as dynamic ordinary least square, fully modified ordinary least square, dynamic fixed effect, and pooled mean group regression methods. Furthermore, we performed the Granger causality test, impulse response function, and variance decomposition analysis. In our long-run estimations, we found that foreign direct investment could significantly alleviate poverty but increases poverty in the short run. Instead, foreign aid plays no significant role in poverty alleviation. Moreover, economic growth and economic freedom are essential as our findings consistently exhibited that they play a crucial role in poverty alleviation. We also found bidirectional causality between poverty alleviation and population growth, while a unidirectional causal linkage was found from poverty alleviation to foreign aid. We conclude that policymakers should look at a new paradigm of developmental assistance, and governments should also create an aiding environment for foreign investment to support their growth plan.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"131 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87971503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowledge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.
{"title":"THE ROLE OF DOUBLE-LOOP LEARNING IN MANUFACTURING SUPPLY CHAINS. THE STUDY OF THE DISRUPTIONS DRIVEN BY COVID-19 IN POLAND","authors":"M. Frankowska, Artur Świerczek, Katarzyna Cheba","doi":"10.3846/tede.2022.17799","DOIUrl":"https://doi.org/10.3846/tede.2022.17799","url":null,"abstract":"A global pandemic of coronavirus COVID-19 affects the manufacturing supply chains significantly. This study aims to identify and evaluate the reaction of manufacturing supply chains in using the concept of double-loop learning to mitigate the disruptions induced by COVID-19 at the early stage of pandemic. A two-stage research process has been developed that firstly involves determining the learning pattern of enterprises in industrial supply chains and identifying actions taken. Then, the relationship between taking actions in the field of double-loop learning in the manufacturing supply chains and expecting a change in their market situation, and having knowledge in the field of adaptation to changes caused by the COVID-19 pandemic was examined. The study shows that there is a high level of caution in taking proactive measures in supply chains and a lack of knowledge in the field of adapting industrial supply chains to sudden disruptions caused by the COVID-19 pandemic.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"9 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75744104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Environmental Kuznets Curve (EKC) hypothesis has become a centre of interest for empirical research, as it serves to identify the relationships between economic growth and environmental degradation that will lead to a sustainable development path. The aim of the paper is to investigate these relationships for each of the EU15 countries, which are responsible for the largest amount of carbon dioxide emissions in Europe. Based on the results of the analysis of ARDL bounds cointegration approach, for the 1960–2019 period, it was found that there is a great diversity between the countries in the EU15 regarding the existence and shape of EKC, from the identification of N shape, Inverted U-shape or monotonic relationships to the absence of statistically significant relationships. Thus, there are countries that have managed to implement environmental protection measures early and now ensure GDP growth while significantly reducing CO2 emissions. The similarities and differences identified among EU15 countries can serve as a guide for EU policymakers in developing recommendations adapted to specific situations in order to facilitate economic growth taking into consideration environmental protection.
{"title":"INVESTIGATING THE RELATIONSHIPS BETWEEN ECONOMIC GROWTH AND ENVIRONMENTAL DEGRADATION: EVIDENCE FROM EU15 COUNTRIES","authors":"M. Hatmanu, Cristina Căutișanu","doi":"10.3846/tede.2022.17874","DOIUrl":"https://doi.org/10.3846/tede.2022.17874","url":null,"abstract":"The Environmental Kuznets Curve (EKC) hypothesis has become a centre of interest for empirical research, as it serves to identify the relationships between economic growth and environmental degradation that will lead to a sustainable development path. The aim of the paper is to investigate these relationships for each of the EU15 countries, which are responsible for the largest amount of carbon dioxide emissions in Europe. Based on the results of the analysis of ARDL bounds cointegration approach, for the 1960–2019 period, it was found that there is a great diversity between the countries in the EU15 regarding the existence and shape of EKC, from the identification of N shape, Inverted U-shape or monotonic relationships to the absence of statistically significant relationships. Thus, there are countries that have managed to implement environmental protection measures early and now ensure GDP growth while significantly reducing CO2 emissions. The similarities and differences identified among EU15 countries can serve as a guide for EU policymakers in developing recommendations adapted to specific situations in order to facilitate economic growth taking into consideration environmental protection.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":"16 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87153753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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