The world surrounded by plastics generates a lot of uncertainty and the first victims are sea animals, plastic in contact with the sun is able to disintegrate and generate toxins that are harmful to health. It is for this reason that this research in bibliographic review allows us to know the different solutions to counteract microplastics through the analysis of the Scopus database and the VOSviewer tool that allows us to analyze the data, considering the essential characteristics that are plants, animals, bacteria, algae and technologies that allow the disintegration, elimination and purification of microplastics, graphs and tables were obtained which allow us to recognize the analyzed data, the countries that carry out these investigations and the bibliometric maps worldwide. The results allow us to understand that the existence of microplastics generates many negative consequences for planet earth, however, there are different solutions which we can use and apply to counteract these microplastics, also considering that countries like Peru do not find published scientific research relevant to this matter. The purpose of this research is to allow us to make better decisions and not lose heart in the face of microplastics since it can be fought with the different solutions that we find on planet earth, technology and the other objective is to motivate readers to take action in the issue and allow generating change in the use of plastics.
{"title":"A bibliometrics study of plants, animals, bacteria, algae and technologies that reduce, filter and eliminate microplastics from planet earth, ecological solutions for the environment","authors":"Cristian Andres Arias Verastegui, Norma Elizabet Clemente Gilvonio, Michelle Esthefani Retamozo Flores","doi":"10.5267/j.dsl.2023.6.004","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.6.004","url":null,"abstract":"The world surrounded by plastics generates a lot of uncertainty and the first victims are sea animals, plastic in contact with the sun is able to disintegrate and generate toxins that are harmful to health. It is for this reason that this research in bibliographic review allows us to know the different solutions to counteract microplastics through the analysis of the Scopus database and the VOSviewer tool that allows us to analyze the data, considering the essential characteristics that are plants, animals, bacteria, algae and technologies that allow the disintegration, elimination and purification of microplastics, graphs and tables were obtained which allow us to recognize the analyzed data, the countries that carry out these investigations and the bibliometric maps worldwide. The results allow us to understand that the existence of microplastics generates many negative consequences for planet earth, however, there are different solutions which we can use and apply to counteract these microplastics, also considering that countries like Peru do not find published scientific research relevant to this matter. The purpose of this research is to allow us to make better decisions and not lose heart in the face of microplastics since it can be fought with the different solutions that we find on planet earth, technology and the other objective is to motivate readers to take action in the issue and allow generating change in the use of plastics.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784366","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.7.006
P. N. V. L. Sasikala, P. Phani Bushan Rao
It is admissible that fuzzy numbers (FNs) are apt for representing imprecise or vague data in real-world problems. While using FNs in decision-making problems, selecting the best alternative among available alternatives is challenging, and therefore, ranking FNs is essential. We can find different studies in the literature, but to our knowledge, no one attempted to rank FNs using the concept of volume. This paper proposes a new method for ranking generalized fuzzy numbers (GFNs) using the volume of the solid obtained by revolving its membership function (MF) about the x-axis. We calculate the volumes of positive and negative sides along with the centroid of a generalized fuzzy number(GFN) to define the fuzzy number(FN) score. This score represents the defuzzified value of FN, is used to select the best alternative, and overcomes the limitations in some existing methods like ranking FNs having the same centroid, crisp numbers, symmetric fuzzy numbers, and FNs with the same core.
{"title":"Ranking fuzzy numbers by volume of solid of revolution of membership function about axis of support","authors":"P. N. V. L. Sasikala, P. Phani Bushan Rao","doi":"10.5267/j.dsl.2023.7.006","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.7.006","url":null,"abstract":"It is admissible that fuzzy numbers (FNs) are apt for representing imprecise or vague data in real-world problems. While using FNs in decision-making problems, selecting the best alternative among available alternatives is challenging, and therefore, ranking FNs is essential. We can find different studies in the literature, but to our knowledge, no one attempted to rank FNs using the concept of volume. This paper proposes a new method for ranking generalized fuzzy numbers (GFNs) using the volume of the solid obtained by revolving its membership function (MF) about the x-axis. We calculate the volumes of positive and negative sides along with the centroid of a generalized fuzzy number(GFN) to define the fuzzy number(FN) score. This score represents the defuzzified value of FN, is used to select the best alternative, and overcomes the limitations in some existing methods like ranking FNs having the same centroid, crisp numbers, symmetric fuzzy numbers, and FNs with the same core.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784369","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.1.007
M. Afif
The website of higher educational institutes is considered a vital communication channel to provide main resources to their stakeholders. It plays an important role in disseminating information about an institute to a variety of visitors at a time. Thus, the quality of an academic website requires special attention to respond to the users’ demands. This study aims to explore the quality of the PSAU website based on data mining techniques. The first step: was collecting opinions about the PSAU website using a survey. After that, data mining processes were used as descriptive and predictive models. The descriptive model was applied to describe and extract the major indicators of website quality. Besides, the predictive model was applied to create models for predicting the website quality level. More than one classification algorithm was used. Naive Bayes and Support Vector Machine have given the best results in all performance indicators, and the achieved accuracy rate for both algorithms was 86% and 84% respectively. The results revealed that the overall quality level of the PSAU website is very good. The usability quality and content quality were very good. The service quality needs more attention. which indicated that the service level is inadequate and needs to be further enhanced. The results of the study should be useful to the deanship of Information Technology at PSAU, and website developers, in redesigning with high quality in terms of its usability, content, and service.
{"title":"Exploring the quality of the higher educational institution website using data mining techniques","authors":"M. Afif","doi":"10.5267/j.dsl.2023.1.007","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.1.007","url":null,"abstract":"The website of higher educational institutes is considered a vital communication channel to provide main resources to their stakeholders. It plays an important role in disseminating information about an institute to a variety of visitors at a time. Thus, the quality of an academic website requires special attention to respond to the users’ demands. This study aims to explore the quality of the PSAU website based on data mining techniques. The first step: was collecting opinions about the PSAU website using a survey. After that, data mining processes were used as descriptive and predictive models. The descriptive model was applied to describe and extract the major indicators of website quality. Besides, the predictive model was applied to create models for predicting the website quality level. More than one classification algorithm was used. Naive Bayes and Support Vector Machine have given the best results in all performance indicators, and the achieved accuracy rate for both algorithms was 86% and 84% respectively. The results revealed that the overall quality level of the PSAU website is very good. The usability quality and content quality were very good. The service quality needs more attention. which indicated that the service level is inadequate and needs to be further enhanced. The results of the study should be useful to the deanship of Information Technology at PSAU, and website developers, in redesigning with high quality in terms of its usability, content, and service.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"116 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79165528","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.5.003
Digna Jatiningsih, Winwin Yadiati, C. Sukmadilaga, Dini Rosdini
The performance of the manufacturing industry lies in the managers who hold crucial roles. In the revolution industry, data or knowledge holds an important role besides managers’ commitment to work optimally. As intrinsic factors, psychological capital is fundamental for managers’ behavior such as commitment and initiative to share knowledge that simultaneously enables managers’ performance. This research aimed to find the psychology capital’s effect on managers’ performance in manufacturing companies by taking into account sharing knowledge and organization commitment as moderation. Hypothesis testing was done by using data measured with a Likert Scale from 208 managers of a manufacturing company as a representative from each company stationed in the Indonesia Stock Exchange. The results of empirical testing using SEM Lisrel shows that psychological capital affects performance moderated by a variable such as managers’ commitment and knowledge sharing. Based on affected value, the initiative to share knowledge gives greater value to the correlation between psychological capital and managers’ performance in manufacturing companies; compared to commitment. Manufacturing practitioners should be able to facilitate a conducive climate to encourage their managers to share knowledge voluntarily so that the decision-making process and performance are better.
{"title":"The role of psychology capital, knowledge sharing and commitment toward managers’ performance in manufacturing company","authors":"Digna Jatiningsih, Winwin Yadiati, C. Sukmadilaga, Dini Rosdini","doi":"10.5267/j.dsl.2023.5.003","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.5.003","url":null,"abstract":"The performance of the manufacturing industry lies in the managers who hold crucial roles. In the revolution industry, data or knowledge holds an important role besides managers’ commitment to work optimally. As intrinsic factors, psychological capital is fundamental for managers’ behavior such as commitment and initiative to share knowledge that simultaneously enables managers’ performance. This research aimed to find the psychology capital’s effect on managers’ performance in manufacturing companies by taking into account sharing knowledge and organization commitment as moderation. Hypothesis testing was done by using data measured with a Likert Scale from 208 managers of a manufacturing company as a representative from each company stationed in the Indonesia Stock Exchange. The results of empirical testing using SEM Lisrel shows that psychological capital affects performance moderated by a variable such as managers’ commitment and knowledge sharing. Based on affected value, the initiative to share knowledge gives greater value to the correlation between psychological capital and managers’ performance in manufacturing companies; compared to commitment. Manufacturing practitioners should be able to facilitate a conducive climate to encourage their managers to share knowledge voluntarily so that the decision-making process and performance are better.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87387337","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.3.003
Angela Denisse Huaman Meza, Gian Carlos Meza Soto, Jahir Chuquillanqui Guillen, Giovene Pérez Campomanes
The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.
{"title":"The odds of accident-type casualties in a Peruvian jungle road","authors":"Angela Denisse Huaman Meza, Gian Carlos Meza Soto, Jahir Chuquillanqui Guillen, Giovene Pérez Campomanes","doi":"10.5267/j.dsl.2023.3.003","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.3.003","url":null,"abstract":"The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"21 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75442614","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.4.006
M. Premkumar, Pradeep Jangir, R. Sowmya, L. Abualigah
Many-objective optimization (MaO) deals with a large number of conflicting objectives in optimization problems to acquire a reliable set of appropriate non-dominated solutions near the true Pareto front, and for the same, a unique mechanism is essential. Numerous papers have reported multi-objective evolutionary algorithms to explain the absence of convergence and diversity variety in many-objective optimization problems. One of the most encouraging methodologies utilizes many reference points to segregate the solutions and guide the search procedure. The above-said methodology is integrated into the basic version of the Moth Flame Optimization (MFO) algorithm for the first time in this paper. The proposed Many-Objective Moth Flame Optimization (MaOMFO) utilizes a set of reference points progressively decided by the hunt procedure of the moth flame. It permits the calculation to combine with the Pareto front yet synchronize the decent variety of the Pareto front. MaOMFO is employed to solve a wide range of unconstrained and constrained benchmark functions and compared with other competitive algorithms, such as non-dominated sorting genetic algorithm, multi-objective evolutionary algorithm based on dominance and decomposition, and novel multi-objective particle swarm optimization using different performance metrics. The results demonstrate the superiority of the algorithm as a new many-objective algorithm for complex many-objective optimization problems.
{"title":"MaOMFO: Many-objective moth flame optimizer using reference-point based non-dominated sorting mechanism for global optimization problems","authors":"M. Premkumar, Pradeep Jangir, R. Sowmya, L. Abualigah","doi":"10.5267/j.dsl.2023.4.006","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.4.006","url":null,"abstract":"Many-objective optimization (MaO) deals with a large number of conflicting objectives in optimization problems to acquire a reliable set of appropriate non-dominated solutions near the true Pareto front, and for the same, a unique mechanism is essential. Numerous papers have reported multi-objective evolutionary algorithms to explain the absence of convergence and diversity variety in many-objective optimization problems. One of the most encouraging methodologies utilizes many reference points to segregate the solutions and guide the search procedure. The above-said methodology is integrated into the basic version of the Moth Flame Optimization (MFO) algorithm for the first time in this paper. The proposed Many-Objective Moth Flame Optimization (MaOMFO) utilizes a set of reference points progressively decided by the hunt procedure of the moth flame. It permits the calculation to combine with the Pareto front yet synchronize the decent variety of the Pareto front. MaOMFO is employed to solve a wide range of unconstrained and constrained benchmark functions and compared with other competitive algorithms, such as non-dominated sorting genetic algorithm, multi-objective evolutionary algorithm based on dominance and decomposition, and novel multi-objective particle swarm optimization using different performance metrics. The results demonstrate the superiority of the algorithm as a new many-objective algorithm for complex many-objective optimization problems.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"78 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75156478","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.1.003
Ammar Y. Alqahtani, Anas A. Makki, R. Abdulaal
Quality standards must be fulfilled to satisfy a base level of quality. Despite using this idea as a foundation, evaluations of academic programs still rely on the evaluators' experiences and may differ from one evaluator to the next. As a result, more precise evaluation approaches must be created to ensure quality is accurately reflected. The main goal of this research paper is to propose and evaluate an approach to assessing higher educational programs using the Self-Evaluation Scale (SES) developed by the Saudi National Commission for Academic Accreditation and Evaluation (NCAAA). The proposed approach is a breakdown of the original performance criteria and standards into sub-criteria and elements to ensure the required data quality. The second goal is to compare the NCAAA's original performance criteria and the proposed evaluation sub-criteria. A comparison framework that uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is developed. Data from eight programs offered in a Middle Eastern University was used for the application and comparison between the two evaluation approaches. Results show that both approaches provide different quality performance rankings. The proposed approach demonstrated more conservative and accurate overall quality performance ratings, indicating that application decisions for accreditation are affected.
{"title":"A proposed NCAAA-based approach to the self-evaluation of higher education programs for academic accreditation: A comparative study using TOPSIS","authors":"Ammar Y. Alqahtani, Anas A. Makki, R. Abdulaal","doi":"10.5267/j.dsl.2023.1.003","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.1.003","url":null,"abstract":"Quality standards must be fulfilled to satisfy a base level of quality. Despite using this idea as a foundation, evaluations of academic programs still rely on the evaluators' experiences and may differ from one evaluator to the next. As a result, more precise evaluation approaches must be created to ensure quality is accurately reflected. The main goal of this research paper is to propose and evaluate an approach to assessing higher educational programs using the Self-Evaluation Scale (SES) developed by the Saudi National Commission for Academic Accreditation and Evaluation (NCAAA). The proposed approach is a breakdown of the original performance criteria and standards into sub-criteria and elements to ensure the required data quality. The second goal is to compare the NCAAA's original performance criteria and the proposed evaluation sub-criteria. A comparison framework that uses the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is developed. Data from eight programs offered in a Middle Eastern University was used for the application and comparison between the two evaluation approaches. Results show that both approaches provide different quality performance rankings. The proposed approach demonstrated more conservative and accurate overall quality performance ratings, indicating that application decisions for accreditation are affected.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"61 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79599366","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 : 2023-01-01DOI: 10.5267/j.dsl.2023.2.001
Vahid B abaveisi, E. Teimoury, M. Gholamian
Today, improving machine availability is vital for industries to compete in the global market. Spare parts play an essential role in the maintenance and repair of equipment, but planning an extensive network in strategic industries with various spare parts can be very challenging due to the existence of different decision factors. The spare parts supply chain deals with inventory management issues, which necessitates considering the related decisions such as determining the stock level and order quantity. Moreover, demand uncertainty and long supply time make decision-making more complex. This paper presents a repair and supply planning model for repairable spare parts while considering a modified formulation of demand uncertainty to minimize costs. The model determines the optimal stock level, lateral transshipment, assignment of spare part orders to suppliers, equipment to repair centers, and the number of intervals over the planning horizon used in demand estimation. This research contributes to the literature by integrating recent decisions, using demand approximation by piecewise linearization, and considering backorder in warehouses evaluated by queuing models. A hybrid approach, including heuristic and genetic algorithms, is used to optimize the model using data from an oil company. The results show that using piecewise linearization and integrated repair and supply planning decisions optimizes costs and improves performance. Also, the availability is affected by the demand estimation, which necessitates precision prediction.
{"title":"A planning model for repairable spare part supply chain considering stochastic demand and backorder: an empirical investigation","authors":"Vahid B abaveisi, E. Teimoury, M. Gholamian","doi":"10.5267/j.dsl.2023.2.001","DOIUrl":"https://doi.org/10.5267/j.dsl.2023.2.001","url":null,"abstract":"Today, improving machine availability is vital for industries to compete in the global market. Spare parts play an essential role in the maintenance and repair of equipment, but planning an extensive network in strategic industries with various spare parts can be very challenging due to the existence of different decision factors. The spare parts supply chain deals with inventory management issues, which necessitates considering the related decisions such as determining the stock level and order quantity. Moreover, demand uncertainty and long supply time make decision-making more complex. This paper presents a repair and supply planning model for repairable spare parts while considering a modified formulation of demand uncertainty to minimize costs. The model determines the optimal stock level, lateral transshipment, assignment of spare part orders to suppliers, equipment to repair centers, and the number of intervals over the planning horizon used in demand estimation. This research contributes to the literature by integrating recent decisions, using demand approximation by piecewise linearization, and considering backorder in warehouses evaluated by queuing models. A hybrid approach, including heuristic and genetic algorithms, is used to optimize the model using data from an oil company. The results show that using piecewise linearization and integrated repair and supply planning decisions optimizes costs and improves performance. Also, the availability is affected by the demand estimation, which necessitates precision prediction.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"18 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90939975","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 : 2023-01-01DOI: 10.5267/j.dsl.2022.12.001
Lia Sheyla Quispe-Adauto, Sheyla Vilcas-Mamani, W. Vicente-Ramos
The objective of this research was to evaluate the effects of public debt sustainability on economic growth in the period 2000-2021 and establish a new optimal debt level that does not affect Peru's economic growth. The general method used to determine this effect was the hypothetical deductive method with a non-experimental and longitudinal trend design, because the data to be analyzed are variations that have occurred over time; the VAR (vector autoregressive) model was used as a specific method, because the evidence was insufficient to consider the simultaneity between the reactions of the variables to propose an SVAR model. Data were collected from economic portals such as the Ministry of Economy and Finance (MEF), as well as the Central Reserve Bank of Peru (BCRP). The estimated sample size was 88 observations representing all quarters from 2000 to 2021. As a result of the econometric regression, the impact of the level of public debt on economic growth is positive, since a one-unit increase in the percentage of public debt will increase the variation of GDP by almost 1.1%. Regarding the debt level forecast and according to the projection made, it was determined that the new debt level that does not affect the sustainability of public finances or the long-term economic growth of the Peruvian economy should be 38% of GDP.
{"title":"Sustainability of the Peruvian public debt and its effect on economic growth in the period 2000-2021","authors":"Lia Sheyla Quispe-Adauto, Sheyla Vilcas-Mamani, W. Vicente-Ramos","doi":"10.5267/j.dsl.2022.12.001","DOIUrl":"https://doi.org/10.5267/j.dsl.2022.12.001","url":null,"abstract":"The objective of this research was to evaluate the effects of public debt sustainability on economic growth in the period 2000-2021 and establish a new optimal debt level that does not affect Peru's economic growth. The general method used to determine this effect was the hypothetical deductive method with a non-experimental and longitudinal trend design, because the data to be analyzed are variations that have occurred over time; the VAR (vector autoregressive) model was used as a specific method, because the evidence was insufficient to consider the simultaneity between the reactions of the variables to propose an SVAR model. Data were collected from economic portals such as the Ministry of Economy and Finance (MEF), as well as the Central Reserve Bank of Peru (BCRP). The estimated sample size was 88 observations representing all quarters from 2000 to 2021. As a result of the econometric regression, the impact of the level of public debt on economic growth is positive, since a one-unit increase in the percentage of public debt will increase the variation of GDP by almost 1.1%. Regarding the debt level forecast and according to the projection made, it was determined that the new debt level that does not affect the sustainability of public finances or the long-term economic growth of the Peruvian economy should be 38% of GDP.","PeriodicalId":38141,"journal":{"name":"Decision Science Letters","volume":"24 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81823086","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 : 2023-01-01DOI: 10.5267/j.dsl.2022.10.002
S. Suripto
This study aims to determine an accurate forecasting model, especially an error rate of around 0, and to examine how the automatic rejection system reacts to stock price as a result of the pandemic. The statistical clustering method is used for the dataset in form of daily observations, while the sample covers the period of cases before and after COVID-19 pandemic from 02 January 2019 to 20 June 2020 at the Trinitan Minerals and Metal Company. Furthermore, the data used in the estimation are the opening and closing price of returns, which are later processed using SAS analysis tools. It is shown that the most appropriate decision-making processes are those proven to be most effective. Therefore, predicting future events based on a suitable time series model will help policymakers and strategists make decisions and develop appropriate strategic plans regarding the stock market. Meanwhile, 98% of the ARIMA (1,1,1) is a forecasting model which can be applied to predict stock prices. The new approach of this study is an integrated autoregressive moving average used as an attempt to accurately predict stock prices during a pandemic.
本研究旨在确定一个准确的预测模型，特别是错误率在0左右，并研究自动拒绝系统对大流行导致的股票价格的反应。数据集采用统计聚类方法，以日常观测数据的形式进行，样本涵盖2019年1月2日至2020年6月20日在Trinitan Minerals and Metal Company发生的2019冠状病毒病大流行前后的病例。此外，估计中使用的数据是收益的开盘价和收盘价，随后使用SAS分析工具对其进行处理。研究表明，最适当的决策过程是那些被证明是最有效的决策过程。因此，基于合适的时间序列模型预测未来事件将有助于决策者和战略家对股票市场做出决策并制定适当的战略计划。同时，98%的ARIMA(1,1,1)是一个预测模型，可以应用于预测股票价格。本研究的新方法是一种综合自回归移动平均线，用于在大流行期间准确预测股票价格。
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