Pub Date : 2023-07-12DOI: 10.28991/esj-2023-07-04-09
Muhamet Hajdari, Fidan Qerimi, Arbëresha Qerimi
Objectives: This research aims to measure the impact of continuing education on employee productivity and that of the latter on the financial performance of commercial banks in Kosovo. Methods: A quantitative approach was employed to achieve the research objectives and questions. The statistical population comprised 3636 employees working at commercial banks operating in Kosovo. We obtained data from the Central Bank of Kosovo (CBK). A sample of 360 employees was then determined using Slovin's formula to include the representative sample. Findings: The Ordinary Least-Squares (OLS) model demonstrated that continuing education affects employee productivity, and the latter affects the financial performance of commercial banks in Kosovo. The findings indicated that 40.2% of employee productivity is explained by continuing education, while 20.4% of financial performance is explained by employee productivity. Novelty/improvement:This research showed that commercial banks could receive feedback on the importance of employees’ continuing education in increasing their productivity and, subsequently, the bank's financial performance. This can improve effectiveness and productivity at work and the organization's financial results, especially cost optimization and income generation. Doi: 10.28991/ESJ-2023-07-04-09 Full Text: PDF
{"title":"Impact of Continuing Education on Employee Productivity and Financial Performance of Banks","authors":"Muhamet Hajdari, Fidan Qerimi, Arbëresha Qerimi","doi":"10.28991/esj-2023-07-04-09","DOIUrl":"https://doi.org/10.28991/esj-2023-07-04-09","url":null,"abstract":"Objectives: This research aims to measure the impact of continuing education on employee productivity and that of the latter on the financial performance of commercial banks in Kosovo. Methods: A quantitative approach was employed to achieve the research objectives and questions. The statistical population comprised 3636 employees working at commercial banks operating in Kosovo. We obtained data from the Central Bank of Kosovo (CBK). A sample of 360 employees was then determined using Slovin's formula to include the representative sample. Findings: The Ordinary Least-Squares (OLS) model demonstrated that continuing education affects employee productivity, and the latter affects the financial performance of commercial banks in Kosovo. The findings indicated that 40.2% of employee productivity is explained by continuing education, while 20.4% of financial performance is explained by employee productivity. Novelty/improvement:This research showed that commercial banks could receive feedback on the importance of employees’ continuing education in increasing their productivity and, subsequently, the bank's financial performance. This can improve effectiveness and productivity at work and the organization's financial results, especially cost optimization and income generation. Doi: 10.28991/ESJ-2023-07-04-09 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42239740","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 : 2023-07-12DOI: 10.28991/esj-2023-07-04-02
Afshin Balal, Yaser Pakzad Jafarabadi, A. Demir, Morris Igene, M. Giesselmann, Stephen B. Bayne
Solar energy is a widely accessible, clean, and sustainable energy source. Solar power harvesting in order to generate electricity on smart grids is essential in light of the present global energy crisis. However, the highly variable nature of solar radiation poses unique challenges for accurately predicting solar photovoltaic (PV) power generation. Factors such as cloud cover, atmospheric conditions, and seasonal variations significantly impact the amount of solar energy available for conversion into electricity. Therefore, it is essential to precisely estimate the output of solar power in order to assess the potential of smart grids. This paper presents a study that utilizes various machine learning models to predict solar photovoltaic (PV) power generation in Lubbock, Texas. Mean Squared Error (MSE) and R² metrics are utilized to demonstrate the performance of each model. The results show that the Random Forest Regression (RFR) and Long Short-Term Memory (LSTM) models outperformed the other models, with a MSE of 2.06% and 2.23% and R² values of 0.977 and 0.975, respectively. In addition, RFR and LSTM demonstrate their capability to capture the intricate patterns and complex relationships inherent in solar power generation data. The developed machine learning models can aid solar PV investors in streamlining their processes and improving their planning for the production of solar energy. Doi: 10.28991/ESJ-2023-07-04-02 Full Text: PDF
{"title":"Forecasting Solar Power Generation Utilizing Machine Learning Models in Lubbock","authors":"Afshin Balal, Yaser Pakzad Jafarabadi, A. Demir, Morris Igene, M. Giesselmann, Stephen B. Bayne","doi":"10.28991/esj-2023-07-04-02","DOIUrl":"https://doi.org/10.28991/esj-2023-07-04-02","url":null,"abstract":"Solar energy is a widely accessible, clean, and sustainable energy source. Solar power harvesting in order to generate electricity on smart grids is essential in light of the present global energy crisis. However, the highly variable nature of solar radiation poses unique challenges for accurately predicting solar photovoltaic (PV) power generation. Factors such as cloud cover, atmospheric conditions, and seasonal variations significantly impact the amount of solar energy available for conversion into electricity. Therefore, it is essential to precisely estimate the output of solar power in order to assess the potential of smart grids. This paper presents a study that utilizes various machine learning models to predict solar photovoltaic (PV) power generation in Lubbock, Texas. Mean Squared Error (MSE) and R² metrics are utilized to demonstrate the performance of each model. The results show that the Random Forest Regression (RFR) and Long Short-Term Memory (LSTM) models outperformed the other models, with a MSE of 2.06% and 2.23% and R² values of 0.977 and 0.975, respectively. In addition, RFR and LSTM demonstrate their capability to capture the intricate patterns and complex relationships inherent in solar power generation data. The developed machine learning models can aid solar PV investors in streamlining their processes and improving their planning for the production of solar energy. Doi: 10.28991/ESJ-2023-07-04-02 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45149315","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 : 2023-07-12DOI: 10.28991/esj-2023-07-04-018
S. Muthaiyah, V. Singh, Thein Oak Kyaw Zaw, K. Anbananthen, Byeonghwa Park, Myung Joon Kim
The objective of this study is to explore effective and innovative machine learning techniques that can assist medical professionals in developing more accurate prognoses that can enhance the survivability of osteosarcoma patients by investigating potential prognostic factors and identifying novel therapeutic approaches. A comprehensive analysis was conducted using a dataset of 128 osteosarcoma patients between 1997 to 2011. The dataset included 52 attributes in total that covered a wide range of demographics, together with information on clinical records, treatment protocols, and survival outcomes. Data was obtained from NOCERAL (National Orthopaedic Centre of Excellence in Research and Learning), Kuala Lumpur. Three distinct binary classification methods (i.e., random forest, support vector machine (SVM), and artificial neural network (ANN)) were employed to identify the prognostic factors that are associated with improved survival efficacy measures. The results of this study revealed that both SVM and ANN outperformed random forests in predicting survivability for both the 2-year and 5-year time frames. These findings indicate the potential of SVM and ANN as effective tools for predicting osteosarcoma survivability. The study signifies a significant step towards integrating machine learning techniques into the existing toolkit available to medical practitioners. This study contributes to the medical field by providing a comparative analysis of three prominent machine learning techniques for predicting osteosarcoma survivability. The superior performance of SVM and ANN over random forests highlights the potential of these methods in generating more accurate survivability predictions. Further development and refinement of these machine learning techniques hold promise for enhancing their effectiveness and instilling greater confidence among medical professionals and patients in the predictive capabilities of machine learning and artificial intelligence models for osteosarcoma survivability. Doi: 10.28991/ESJ-2023-07-04-018 Full Text: PDF
{"title":"A Binary Survivability Prediction Classification Model towards Understanding of Osteosarcoma Prognosis","authors":"S. Muthaiyah, V. Singh, Thein Oak Kyaw Zaw, K. Anbananthen, Byeonghwa Park, Myung Joon Kim","doi":"10.28991/esj-2023-07-04-018","DOIUrl":"https://doi.org/10.28991/esj-2023-07-04-018","url":null,"abstract":"The objective of this study is to explore effective and innovative machine learning techniques that can assist medical professionals in developing more accurate prognoses that can enhance the survivability of osteosarcoma patients by investigating potential prognostic factors and identifying novel therapeutic approaches. A comprehensive analysis was conducted using a dataset of 128 osteosarcoma patients between 1997 to 2011. The dataset included 52 attributes in total that covered a wide range of demographics, together with information on clinical records, treatment protocols, and survival outcomes. Data was obtained from NOCERAL (National Orthopaedic Centre of Excellence in Research and Learning), Kuala Lumpur. Three distinct binary classification methods (i.e., random forest, support vector machine (SVM), and artificial neural network (ANN)) were employed to identify the prognostic factors that are associated with improved survival efficacy measures. The results of this study revealed that both SVM and ANN outperformed random forests in predicting survivability for both the 2-year and 5-year time frames. These findings indicate the potential of SVM and ANN as effective tools for predicting osteosarcoma survivability. The study signifies a significant step towards integrating machine learning techniques into the existing toolkit available to medical practitioners. This study contributes to the medical field by providing a comparative analysis of three prominent machine learning techniques for predicting osteosarcoma survivability. The superior performance of SVM and ANN over random forests highlights the potential of these methods in generating more accurate survivability predictions. Further development and refinement of these machine learning techniques hold promise for enhancing their effectiveness and instilling greater confidence among medical professionals and patients in the predictive capabilities of machine learning and artificial intelligence models for osteosarcoma survivability. Doi: 10.28991/ESJ-2023-07-04-018 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69322328","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}
COVID-19 pandemic lockdown measures reasonably limited the social contacts of people in many countries. It is crucial to understand the effect of such policies on people’s social ties and the possible need for evidence-based public policy amendments. Therefore, this study examines 1) the prevalence of loneliness in the population aged 15+ in Lithuania in late 2021 and 2) the self-rated effect of the COVID crisis on loneliness in population groups with different levels of loneliness. It also focuses on the socio-demographic characteristics of these population groups. Data from a representative cross-sectional quantitative survey (N = 1067), carried out in November–December 2021, was used. Based on the 6-item De Jong Gierveld Loneliness Scale, descriptive statistics analysis revealed the high prevalence (51% of a medium level of loneliness) in the Lithuanian population. One in three people (36%) declared low-level loneliness, and each seventh or eighth (13%) reported high-level loneliness. The feelings of respondents who reported a high level of loneliness were also less stable; they more often stated that their feelings of loneliness increased during the pandemic. These research findings make contributions to studies of loneliness within the context of sudden crises. They emphasise the importance of policymakers focusing on additional measures when preparing for future emergencies and providing special attention to residents who experience the highest levels of loneliness. Doi: 10.28991/ESJ-2023-SPER-020 Full Text: PDF
在许多国家，COVID-19大流行的封锁措施合理地限制了人们的社会接触。了解这些政策对人们社会关系的影响以及可能需要以证据为基础的公共政策修订是至关重要的。因此，本研究旨在研究1)2021年末立陶宛15岁以上人群的孤独感患病率，以及2)新冠肺炎危机对不同孤独感水平人群孤独感的自评影响。它还侧重于这些人口群体的社会人口特征。使用的数据来自于2021年11月至12月进行的代表性横断面定量调查(N = 1067)。基于6项De Jong Gierveld孤独量表，描述性统计分析显示立陶宛人口的高患病率(中等孤独水平的51%)。三分之一(36%)的人表示自己的孤独程度较低，七分之一或八分之一(13%)的人表示自己的孤独程度较高。报告高度孤独的受访者的情绪也不太稳定;他们更多地表示，在大流行期间，他们的孤独感增加了。这些研究结果对突发危机背景下的孤独研究做出了贡献。他们强调了政策制定者在为未来的紧急情况做准备时关注额外措施的重要性，并特别关注那些经历最高程度孤独的居民。Doi: 10.28991/ESJ-2023-SPER-020
{"title":"Perceived Effects of the COVID-19 Pandemic on Loneliness: The Most Vulnerable Population Groups","authors":"Margarita Gedvilaitė-Kordušienė, Sarmitė Mikulionienė","doi":"10.28991/esj-2023-sper-020","DOIUrl":"https://doi.org/10.28991/esj-2023-sper-020","url":null,"abstract":"COVID-19 pandemic lockdown measures reasonably limited the social contacts of people in many countries. It is crucial to understand the effect of such policies on people’s social ties and the possible need for evidence-based public policy amendments. Therefore, this study examines 1) the prevalence of loneliness in the population aged 15+ in Lithuania in late 2021 and 2) the self-rated effect of the COVID crisis on loneliness in population groups with different levels of loneliness. It also focuses on the socio-demographic characteristics of these population groups. Data from a representative cross-sectional quantitative survey (N = 1067), carried out in November–December 2021, was used. Based on the 6-item De Jong Gierveld Loneliness Scale, descriptive statistics analysis revealed the high prevalence (51% of a medium level of loneliness) in the Lithuanian population. One in three people (36%) declared low-level loneliness, and each seventh or eighth (13%) reported high-level loneliness. The feelings of respondents who reported a high level of loneliness were also less stable; they more often stated that their feelings of loneliness increased during the pandemic. These research findings make contributions to studies of loneliness within the context of sudden crises. They emphasise the importance of policymakers focusing on additional measures when preparing for future emergencies and providing special attention to residents who experience the highest levels of loneliness. Doi: 10.28991/ESJ-2023-SPER-020 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136356048","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 : 2023-06-21DOI: 10.28991/esj-2023-sper-019
Y. J. Amuda
A plethora number of literature advocates for economic diversification in Nigeria in order to address its socio-economic challenges. The advent of the COVID-19 pandemic has exemplified this viewpoint even further, as it has had a severe impact on many parts of the Nigerian economy while the federal government scrambles for revenue to fulfill national expenses. However, observation reveals that little attention is paid to the influence of COVID-19 on the oil and gas sector, despite the necessity to diversify economic resources for human capital development. The purpose of this research is to investigate the influence of COVID-19 on the Nigerian oil and gas sector. Problems are recognized and solutions are proposed through the textual analysis of literature. According to the research, COVID-19 has a negative influence on the oil and gas business in Nigeria due to Nigeria's overreliance on oil resources as a key source of national revenue, among other issues. As a result, the study emphasized the need for and importance of diversifying the nation's economic resources by focusing more attention on sectors such as SMEs that are aided with protection and promotion, as well as the agricultural sector, which incorporates technology and scientific input as a driving force for improvement. If adopted, diversification will address numerous difficulties such as poverty, which affects the majority of inhabitants, unemployment, mounting foreign debt, and the massive importation of products and services into the country due to a lack of economic diversification. According to the report, the Nigerian government should invest extensively in small and medium-sized firms (SMEs) and agricultural investment in order to overcome the economic challenges caused by COVID-19's detrimental influence on the economy. Doi: 10.28991/ESJ-2023-SPER-019 Full Text: PDF
{"title":"Impact of COVID-19 on Oil and Gas Sector in Nigeria: A Condition for Diversification of Economic Resources","authors":"Y. J. Amuda","doi":"10.28991/esj-2023-sper-019","DOIUrl":"https://doi.org/10.28991/esj-2023-sper-019","url":null,"abstract":"A plethora number of literature advocates for economic diversification in Nigeria in order to address its socio-economic challenges. The advent of the COVID-19 pandemic has exemplified this viewpoint even further, as it has had a severe impact on many parts of the Nigerian economy while the federal government scrambles for revenue to fulfill national expenses. However, observation reveals that little attention is paid to the influence of COVID-19 on the oil and gas sector, despite the necessity to diversify economic resources for human capital development. The purpose of this research is to investigate the influence of COVID-19 on the Nigerian oil and gas sector. Problems are recognized and solutions are proposed through the textual analysis of literature. According to the research, COVID-19 has a negative influence on the oil and gas business in Nigeria due to Nigeria's overreliance on oil resources as a key source of national revenue, among other issues. As a result, the study emphasized the need for and importance of diversifying the nation's economic resources by focusing more attention on sectors such as SMEs that are aided with protection and promotion, as well as the agricultural sector, which incorporates technology and scientific input as a driving force for improvement. If adopted, diversification will address numerous difficulties such as poverty, which affects the majority of inhabitants, unemployment, mounting foreign debt, and the massive importation of products and services into the country due to a lack of economic diversification. According to the report, the Nigerian government should invest extensively in small and medium-sized firms (SMEs) and agricultural investment in order to overcome the economic challenges caused by COVID-19's detrimental influence on the economy. Doi: 10.28991/ESJ-2023-SPER-019 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41903459","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 : 2023-05-20DOI: 10.28991/esj-2023-sper-017
Nga Phan Thi Hang, M. Nguyen, Thi Thuy Hang Le
Vietnam's economy faces many difficulties and complicated developments. To create an environment with favorable conditions for sustainable development, it is necessary to have innovative business solutions that not only bring profits for businesses but also solve environmental and social problems. In addition, small and medium enterprises (SMEs) have made many positive contributions to economic restructuring, creating stable jobs for hundreds of thousands of employees and ensuring social security. Besides, SMEs in Vietnam have faced many difficulties and challenges during the COVID-19 pandemic. Thus, the papers' objectives explored critical factors affecting the sustainable development of SMEs in Vietnam. The authors applied two methods, such as qualitative and quantitative, with data obtained from 400 managers of small and medium enterprises and used structural equation modeling and SPSS 20.0, Amos software. The article's findings have the digital transformation factor's most substantial impact on sustainable development. The article's novelty is determined by five factors: market trends, state support policy, social responsibility, quality of human resources, and digital transformation. Finally, the authors recommended guidelines to help businesses be more cohesive in removing difficulties and solving issues related to credit relations to put capital into modern technology investment to ensure business effectiveness and sustainable development for SMEs. Doi: 10.28991/ESJ-2023-SPER-017 Full Text: PDF
{"title":"Digital Transformation Affecting Sustainable Development: A Case of Small and Medium Enterprises during the Covid-19 Pandemic","authors":"Nga Phan Thi Hang, M. Nguyen, Thi Thuy Hang Le","doi":"10.28991/esj-2023-sper-017","DOIUrl":"https://doi.org/10.28991/esj-2023-sper-017","url":null,"abstract":"Vietnam's economy faces many difficulties and complicated developments. To create an environment with favorable conditions for sustainable development, it is necessary to have innovative business solutions that not only bring profits for businesses but also solve environmental and social problems. In addition, small and medium enterprises (SMEs) have made many positive contributions to economic restructuring, creating stable jobs for hundreds of thousands of employees and ensuring social security. Besides, SMEs in Vietnam have faced many difficulties and challenges during the COVID-19 pandemic. Thus, the papers' objectives explored critical factors affecting the sustainable development of SMEs in Vietnam. The authors applied two methods, such as qualitative and quantitative, with data obtained from 400 managers of small and medium enterprises and used structural equation modeling and SPSS 20.0, Amos software. The article's findings have the digital transformation factor's most substantial impact on sustainable development. The article's novelty is determined by five factors: market trends, state support policy, social responsibility, quality of human resources, and digital transformation. Finally, the authors recommended guidelines to help businesses be more cohesive in removing difficulties and solving issues related to credit relations to put capital into modern technology investment to ensure business effectiveness and sustainable development for SMEs. Doi: 10.28991/ESJ-2023-SPER-017 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49062340","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 : 2023-05-20DOI: 10.28991/esj-2023-sper-018
G. N. Achmad, Rizky Yudaruddin, P. W. Budiman, Eka Nor Santi, .. Suharsono, A. H. Purnomo, Noor Wahyuningsih
Objectives: All businesses worldwide, especially small and medium-sized organizations, are now concerned about environmental degradation. Eco-innovation and environmental collaboration are expected to be the driving forces for saving the environment and the performance of companies. Therefore, this study aimed to ascertain how eco-innovation and environmental cooperation affect the financial, social, and environmental performance of SMEs. This study also explored environmental collaboration as a moderating variable for the effect of eco-innovation on the performance of SMEs. Methods/Analysis: Data from 300 small and medium-sized enterprises of Creative Home Décor were analyzed using structural equation modeling. Findings: Eco-innovation is necessary to improve the performance of Indonesia's SMEs. Environmental collaboration has a beneficial and substantial effect on the performance of the environment and society. Regarding environmental collaboration as a moderating variable, this study identified a positive and statistically significant coefficient regulating the relationship between financial performance and eco-innovation. Novelty /Improvement. The novelty of this research lies in its focus on the impact of eco-innovation and environmental collaboration on the performance of SMEs, particularly in developing countries such as Indonesia, during the COVID-19 pandemic. The study also contributed to the theoretical and empirical understanding of eco-innovation in developing countries and highlighted the importance of environmental collaboration in enhancing the social and environmental performance of SMEs. Additionally, this paper provided empirical and theoretical contributions on the role of environmental collaboration as a moderating variable that is particularly improving the performance of Indonesia's SMEs in Creative Home Décor during the COVID-19 pandemic.JEL Classifications: M12, L68, L25, L53, Q56 Doi: 10.28991/ESJ-2023-SPER-018 Full Text: PDF
{"title":"Eco-Innovation and SME Performance in Time of Covid-19 Pandemic: Moderating Role of Environmental Collaboration","authors":"G. N. Achmad, Rizky Yudaruddin, P. W. Budiman, Eka Nor Santi, .. Suharsono, A. H. Purnomo, Noor Wahyuningsih","doi":"10.28991/esj-2023-sper-018","DOIUrl":"https://doi.org/10.28991/esj-2023-sper-018","url":null,"abstract":"Objectives: All businesses worldwide, especially small and medium-sized organizations, are now concerned about environmental degradation. Eco-innovation and environmental collaboration are expected to be the driving forces for saving the environment and the performance of companies. Therefore, this study aimed to ascertain how eco-innovation and environmental cooperation affect the financial, social, and environmental performance of SMEs. This study also explored environmental collaboration as a moderating variable for the effect of eco-innovation on the performance of SMEs. Methods/Analysis: Data from 300 small and medium-sized enterprises of Creative Home Décor were analyzed using structural equation modeling. Findings: Eco-innovation is necessary to improve the performance of Indonesia's SMEs. Environmental collaboration has a beneficial and substantial effect on the performance of the environment and society. Regarding environmental collaboration as a moderating variable, this study identified a positive and statistically significant coefficient regulating the relationship between financial performance and eco-innovation. Novelty /Improvement. The novelty of this research lies in its focus on the impact of eco-innovation and environmental collaboration on the performance of SMEs, particularly in developing countries such as Indonesia, during the COVID-19 pandemic. The study also contributed to the theoretical and empirical understanding of eco-innovation in developing countries and highlighted the importance of environmental collaboration in enhancing the social and environmental performance of SMEs. Additionally, this paper provided empirical and theoretical contributions on the role of environmental collaboration as a moderating variable that is particularly improving the performance of Indonesia's SMEs in Creative Home Décor during the COVID-19 pandemic.JEL Classifications: M12, L68, L25, L53, Q56 Doi: 10.28991/ESJ-2023-SPER-018 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46239759","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 : 2023-05-20DOI: 10.28991/esj-2023-sper-016
Wachiraporn Poungjinda, S. Pathak, Ivan Bimbilovski
The concept of legal principles for intellectual property (IP) protection is related to the adequate marketing of drug patents to protect patent rights. The objective of this research is to understand and analyze the factors affecting the market concerning international law, treaties, acts, and declarations, leading to encouraging creativity, production, increased investment, especially amidst the COVID-19 pandemic. The qualitative methodology provided for an in-depth understanding and analysis of primary and secondary research data gathered from key informant interviews and published literature. The collected data were analyzed with Strength, Weakness, Opportunity, and Threats (SWOT), a Delphi panel, and Correct, Adapt, Maintain, and Explore (CAME) analysis. The results found legal problems concerning the lack of rules to protect the rights and freedoms damaged by the monopoly on drug patents, complexities in the process of importing medicinal compounds, and how to access information with limited accessibility during COVID-19. Therefore, it is advisable to amend the law to curtail monopolies and to enact a law that prescribes rules for importing medicinal compounds to produce generic drugs in the country, including identifying the status of the patent holders. The research further paves the way for utilizing micro level research to be conducted in the development of intellectual property rights. Doi: 10.28991/ESJ-2023-SPER-016 Full Text: PDF
{"title":"Legal Protection against Patent and Intellectual Property Rights Violations Amidst COVID-19","authors":"Wachiraporn Poungjinda, S. Pathak, Ivan Bimbilovski","doi":"10.28991/esj-2023-sper-016","DOIUrl":"https://doi.org/10.28991/esj-2023-sper-016","url":null,"abstract":"The concept of legal principles for intellectual property (IP) protection is related to the adequate marketing of drug patents to protect patent rights. The objective of this research is to understand and analyze the factors affecting the market concerning international law, treaties, acts, and declarations, leading to encouraging creativity, production, increased investment, especially amidst the COVID-19 pandemic. The qualitative methodology provided for an in-depth understanding and analysis of primary and secondary research data gathered from key informant interviews and published literature. The collected data were analyzed with Strength, Weakness, Opportunity, and Threats (SWOT), a Delphi panel, and Correct, Adapt, Maintain, and Explore (CAME) analysis. The results found legal problems concerning the lack of rules to protect the rights and freedoms damaged by the monopoly on drug patents, complexities in the process of importing medicinal compounds, and how to access information with limited accessibility during COVID-19. Therefore, it is advisable to amend the law to curtail monopolies and to enact a law that prescribes rules for importing medicinal compounds to produce generic drugs in the country, including identifying the status of the patent holders. The research further paves the way for utilizing micro level research to be conducted in the development of intellectual property rights. Doi: 10.28991/ESJ-2023-SPER-016 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47377109","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 : 2023-05-17DOI: 10.28991/esj-2023-sied2-08
P. Nguyen, D. Le
This paper aims to investigate the impact of organizational justice components on job satisfaction, organizational commitment, and organizational citizenship behaviours (OCB) of employees in the higher education sector of Vietnam. Although many research studies have been conducted in organizations on the topics of organizational justice, as well as organizational commitment, and organizational citizenship behaviour, there is a shortage of these topics in higher education institutions as well as in Asian context. Therefore, this article attempts to fill this literature gap. A total of 317 employees from various universities in Vietnam participated in this study, and a self-administered survey was conducted, which was modified based on suggestions from the universities' management team following interviews. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) technique. The results showed that procedural justice and interactional justice had a significant impact on both job satisfaction and organizational commitment, while distributive justice only affected job satisfaction. Furthermore, the study found that job satisfaction and organizational commitment significantly affected OCB. However, this study had a limitation in terms of the narrow sample size, which only included participants from universities. Future studies should broaden the sample size to include participants from vocational colleges. On paper, the study shows the effects of organizational justice on OCB through the mediating roles of individual work outputs, which received inadequate attention in previous studies. Doi: 10.28991/ESJ-2023-SIED2-08 Full Text: PDF
{"title":"Understanding Organizational Citizenship Behaviour through Organizational Justice and its Consequences among Vietnamese’s Universities Employees","authors":"P. Nguyen, D. Le","doi":"10.28991/esj-2023-sied2-08","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-08","url":null,"abstract":"This paper aims to investigate the impact of organizational justice components on job satisfaction, organizational commitment, and organizational citizenship behaviours (OCB) of employees in the higher education sector of Vietnam. Although many research studies have been conducted in organizations on the topics of organizational justice, as well as organizational commitment, and organizational citizenship behaviour, there is a shortage of these topics in higher education institutions as well as in Asian context. Therefore, this article attempts to fill this literature gap. A total of 317 employees from various universities in Vietnam participated in this study, and a self-administered survey was conducted, which was modified based on suggestions from the universities' management team following interviews. The collected data were analyzed using the partial least squares structural equation modeling (PLS-SEM) technique. The results showed that procedural justice and interactional justice had a significant impact on both job satisfaction and organizational commitment, while distributive justice only affected job satisfaction. Furthermore, the study found that job satisfaction and organizational commitment significantly affected OCB. However, this study had a limitation in terms of the narrow sample size, which only included participants from universities. Future studies should broaden the sample size to include participants from vocational colleges. On paper, the study shows the effects of organizational justice on OCB through the mediating roles of individual work outputs, which received inadequate attention in previous studies. Doi: 10.28991/ESJ-2023-SIED2-08 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46445932","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 : 2023-05-17DOI: 10.28991/esj-2023-sied2-07
C. Ramos-Galarza, V. Ramos, J. Cruz-Cárdenas, Mónica Bolaños-Pasquel
Introduction: Negative beliefs, fear, avoidance behaviors, and superficial attitudes surrounding the learning of statistics create significant problems for university students in Latin America. Objective: To analyze the impact of fearful behavior, superficial work, and avoidance displayed by university students when it comes to statistics. Method: In this article, we give details about a quantitative research project carried out by two independent studies. The first (N = 310) focused on the development of a scale to assess negative beliefs, fears, and avoidance behaviors towards statistics, in which goodness of fit was determined in a 3-factor model. In the second study (N = 250), it was hypothesized that undergraduates perform superficially due to negative beliefs and avoidance behaviors when learning statistics. Findings: The proposed model explained 42% of the variance. In addition, in the analysis of the proposed mediation model, an adequate adjustment was found. In the discussion of this research project, the need to intervene in the negative beliefs, fears, and avoidance behaviors displayed by university students towards statistics is highlighted. Novelty:This research project explains why college students dislike or avoid learning statistics in depth. The findings will allow for a modification in the way statistics is taught so that Latin American professionals achieve better performance in this field. Doi: 10.28991/ESJ-2023-SIED2-07 Full Text: PDF
{"title":"University Students’ Rejection to Learning Statistics: Research from a Latin American Standpoint","authors":"C. Ramos-Galarza, V. Ramos, J. Cruz-Cárdenas, Mónica Bolaños-Pasquel","doi":"10.28991/esj-2023-sied2-07","DOIUrl":"https://doi.org/10.28991/esj-2023-sied2-07","url":null,"abstract":"Introduction: Negative beliefs, fear, avoidance behaviors, and superficial attitudes surrounding the learning of statistics create significant problems for university students in Latin America. Objective: To analyze the impact of fearful behavior, superficial work, and avoidance displayed by university students when it comes to statistics. Method: In this article, we give details about a quantitative research project carried out by two independent studies. The first (N = 310) focused on the development of a scale to assess negative beliefs, fears, and avoidance behaviors towards statistics, in which goodness of fit was determined in a 3-factor model. In the second study (N = 250), it was hypothesized that undergraduates perform superficially due to negative beliefs and avoidance behaviors when learning statistics. Findings: The proposed model explained 42% of the variance. In addition, in the analysis of the proposed mediation model, an adequate adjustment was found. In the discussion of this research project, the need to intervene in the negative beliefs, fears, and avoidance behaviors displayed by university students towards statistics is highlighted. Novelty:This research project explains why college students dislike or avoid learning statistics in depth. The findings will allow for a modification in the way statistics is taught so that Latin American professionals achieve better performance in this field. Doi: 10.28991/ESJ-2023-SIED2-07 Full Text: PDF","PeriodicalId":11586,"journal":{"name":"Emerging Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46671436","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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