In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.
{"title":"The impact of intellectual capital efficiency on value creation in video game industry—An evidence from Taiwan","authors":"Hsing-Hua Hsiung, Chia-Yen Lin, Guan-Yu Zhu","doi":"10.24294/jipd.v7i3.2340","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2340","url":null,"abstract":"In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"5 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135406069","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}
This research paper aims to assess the sustainable competitiveness of Balkan countries. Sustainable competitiveness was measured based on the indicators in The Sustainable Competitiveness Report from 2022, published by Solability. According to this report, sustainable competitiveness is evaluated using six grouped criteria. In this paper, the competitiveness of the Balkan countries was assessed through the application of the multicriteria analysis methods Entropy and MARCOS (Measurement Alternatives and Ranking according to the Compromise Solution). The weight of each criterion was determined using the Entropy method. The results highlighted that the most significant criteria were Natural Capital and Resource Efficiency & Intensity, which carried the highest weight, whereas the Social Cohesion criterion was of lesser importance, represented by the lowest weight. Using the MARCOS method, the Balkan countries were ranked, with Greece securing the top position, closely followed by Albania, while North Macedonia exhibited the weakest performance. Sensitivity analysis further substantiated these findings. The outcomes of this study significantly contribute to the academic understanding of sustainable competitiveness and provide valuable practical insights for policymakers and stakeholders interested in advancing sustainable development efforts in the Balkan region.
本研究旨在评估巴尔干国家的可持续竞争力。可持续竞争力是根据Solability发布的《2022年可持续竞争力报告》中的指标来衡量的。根据这份报告，可持续竞争力是用六组标准来评估的。本文运用多准则分析方法熵和MARCOS (Measurement Alternatives and Ranking according the Compromise Solution)对巴尔干国家的竞争力进行了评估。采用熵值法确定各指标的权重。结果表明，最重要的标准是自然资本和资源效率;强度，其权重最高，而社会凝聚力标准的重要性较低，权重最低。使用MARCOS方法，巴尔干国家排名，希腊位居榜首，阿尔巴尼亚紧随其后，而北马其顿表现最差。敏感性分析进一步证实了这些发现。本研究的结果极大地促进了对可持续竞争力的学术理解，并为有意推动巴尔干地区可持续发展努力的政策制定者和利益相关者提供了宝贵的实践见解。
{"title":"Assessing the role of institutional reform in enhancing Balkan sustainable competitiveness: An Entropy-MARCOS perspective","authors":"Anđelka Štilić, Adis Puška, Darko Božanić, Duško Tešić","doi":"10.24294/jipd.v7i3.2167","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2167","url":null,"abstract":"This research paper aims to assess the sustainable competitiveness of Balkan countries. Sustainable competitiveness was measured based on the indicators in The Sustainable Competitiveness Report from 2022, published by Solability. According to this report, sustainable competitiveness is evaluated using six grouped criteria. In this paper, the competitiveness of the Balkan countries was assessed through the application of the multicriteria analysis methods Entropy and MARCOS (Measurement Alternatives and Ranking according to the Compromise Solution). The weight of each criterion was determined using the Entropy method. The results highlighted that the most significant criteria were Natural Capital and Resource Efficiency & Intensity, which carried the highest weight, whereas the Social Cohesion criterion was of lesser importance, represented by the lowest weight. Using the MARCOS method, the Balkan countries were ranked, with Greece securing the top position, closely followed by Albania, while North Macedonia exhibited the weakest performance. Sensitivity analysis further substantiated these findings. The outcomes of this study significantly contribute to the academic understanding of sustainable competitiveness and provide valuable practical insights for policymakers and stakeholders interested in advancing sustainable development efforts in the Balkan region.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135667054","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}
The crypto space offers numerous opportunities for users to grow their wealth through trading, lending, and borrowing activities. However, these opportunities come with inherent risks that need to be carefully managed to protect your assets and maximize returns. By understanding the risks associated with wallets and depository services, trading, lending, and borrowing, users can make informed decisions and enjoy the benefits of the rapidly evolving world of cryptocurrencies. This review paper analyses 43 papers for the period of 2019–2023 and proposes recommendations for policy makers. The results confirm that international regulators expect national authorities to implement a regulatory framework for digital assets comparable to those that already exist for traditional finance. For national authorities, this means having and using the powers, tools and resources to regulate and oversee a growing market. Authorities should cooperate and coordinate with each other, at the national and international levels, to encourage consistency and knowledge sharing. Market operators (exchanges), service providers, exchanges and wallets, create effective risk management structures, as well as reliable mechanisms for collecting, storing, protecting and reporting data.
{"title":"Understanding the risks associated with wallets, depository services, trading, lending, and borrowing in the crypto space","authors":"Alexey Mikhaylov","doi":"10.24294/jipd.v7i3.2223","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2223","url":null,"abstract":"The crypto space offers numerous opportunities for users to grow their wealth through trading, lending, and borrowing activities. However, these opportunities come with inherent risks that need to be carefully managed to protect your assets and maximize returns. By understanding the risks associated with wallets and depository services, trading, lending, and borrowing, users can make informed decisions and enjoy the benefits of the rapidly evolving world of cryptocurrencies. This review paper analyses 43 papers for the period of 2019–2023 and proposes recommendations for policy makers. The results confirm that international regulators expect national authorities to implement a regulatory framework for digital assets comparable to those that already exist for traditional finance. For national authorities, this means having and using the powers, tools and resources to regulate and oversee a growing market. Authorities should cooperate and coordinate with each other, at the national and international levels, to encourage consistency and knowledge sharing. Market operators (exchanges), service providers, exchanges and wallets, create effective risk management structures, as well as reliable mechanisms for collecting, storing, protecting and reporting data.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"87 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135823844","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}
Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.
{"title":"Developing a model of work duration under the influence of risk events in the implementation of life cycle contracts for large energy construction projects","authors":"Valery Bezpalov, Liudmila Goncharenko, Dmitry Fedyunin, Sergey Lochan, Svetlana Avtonomova","doi":"10.24294/jipd.v7i3.1946","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.1946","url":null,"abstract":"Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885140","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}
Leilei Jiang, Walton Wider, Jem Cloyd M. Tanucan, Jonna Karla C. Bien
The COVID-19 pandemic has led to a reevaluation of global health capabilities, highlighting the importance of prioritizing the welfare of frontline healthcare workers. These individuals encountered difficult circumstances on a global scale, including longer work hours, heightened risk of virus exposure, and substantial strain on their mental and physical well-being. Healthcare professionals in China faced similar challenges. This article discusses systemic issues that have been exacerbated by the pandemic and argues for a sustained emphasis on the well-being of healthcare workers, rather than solely addressing it as a crisis response. Given the increasing likelihood of future global pandemics, it is crucial to emphasize the establishment of a durable support system that can enhance resilience and crisis management capabilities. This study examines the systemic challenges of the Chinese healthcare system, with a particular focus on the difficulties encountered during the pandemic. We advocate for a paradigm shift that acknowledges healthcare workers as essential stakeholders within healthcare systems. The objective is to encourage a worldwide conversation for implementing initiatives that transcend national boundaries, with the goal of consistently incorporating a culture of compassion and assistance into healthcare systems. We propose the implementation of a comprehensive support system that encompasses all facets of healthcare, going beyond the mere management of crises. Our vision is for health systems to prioritize the well-being of healthcare workers and the communities they serve, with a focus on resilience.
{"title":"Reforming China’s healthcare management in the wake of COVID-19: A psychological well-being perspective","authors":"Leilei Jiang, Walton Wider, Jem Cloyd M. Tanucan, Jonna Karla C. Bien","doi":"10.24294/jipd.v7i3.2680","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2680","url":null,"abstract":"The COVID-19 pandemic has led to a reevaluation of global health capabilities, highlighting the importance of prioritizing the welfare of frontline healthcare workers. These individuals encountered difficult circumstances on a global scale, including longer work hours, heightened risk of virus exposure, and substantial strain on their mental and physical well-being. Healthcare professionals in China faced similar challenges. This article discusses systemic issues that have been exacerbated by the pandemic and argues for a sustained emphasis on the well-being of healthcare workers, rather than solely addressing it as a crisis response. Given the increasing likelihood of future global pandemics, it is crucial to emphasize the establishment of a durable support system that can enhance resilience and crisis management capabilities. This study examines the systemic challenges of the Chinese healthcare system, with a particular focus on the difficulties encountered during the pandemic. We advocate for a paradigm shift that acknowledges healthcare workers as essential stakeholders within healthcare systems. The objective is to encourage a worldwide conversation for implementing initiatives that transcend national boundaries, with the goal of consistently incorporating a culture of compassion and assistance into healthcare systems. We propose the implementation of a comprehensive support system that encompasses all facets of healthcare, going beyond the mere management of crises. Our vision is for health systems to prioritize the well-being of healthcare workers and the communities they serve, with a focus on resilience.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885015","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}
H. I. Tillekaratne, P. Wickramagamage, Induka Werellagama, Upaka Rathnayake, Chandana Siriwardana, Asela Bandara, C. M. Madduma-Bandara, T. W. M. T. W. Bandara, Amila Abeynayaka
During and after any disaster, a situation report (SITREP) is prepared, based on the Daily Incident Updates (DIU), as an initial decision support information base. It is observed that the decision support system and best practices are not optimized through the available formal reporting on disaster incidents. The rapidly evolving situation, misunderstood terms, inaccurate data and delivery delays of DIU are challenges to the daily SITREP. Multiple stakeholders stipulated with different tasks should be properly understood for the SITREP to initiate relevant response tasks. To fill this research gap, this paper identifies the weaknesses of the current practice and discusses the upgrading of the incident-reporting process using a freely available software tool, enabling further visualization, and producing a comprehensive timely output to share among the stakeholders. In this case, “Power-BI” (a data visualization software) is used as a 360-degree view of useful metrics—in a single place, with real-time updates while being available on all devices for operational decision-making. When a dataset is transformed into several analytical reports and dashboards, it can be easily shared with the target users and action groups. This article analyzed two sources of data, namely the Disaster Management Center (DMC) and the National Disaster Relief Service Center (NDRSC) of Sri Lanka. Senior managers of disaster emergencies were interviewed and explored social media to develop a scheme of best practices for disaster reporting, starting from just before the occurrence, and following the unfolding sequence of the disasters. Using a variety of remotely acquired imageries, rapid mapping, grading, and delineating impacts of natural disasters, were made available to concerned users.
{"title":"Situation report (SITREP) visualization for effective management of disaster incidents in Sri Lanka","authors":"H. I. Tillekaratne, P. Wickramagamage, Induka Werellagama, Upaka Rathnayake, Chandana Siriwardana, Asela Bandara, C. M. Madduma-Bandara, T. W. M. T. W. Bandara, Amila Abeynayaka","doi":"10.24294/jipd.v7i3.2206","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2206","url":null,"abstract":"During and after any disaster, a situation report (SITREP) is prepared, based on the Daily Incident Updates (DIU), as an initial decision support information base. It is observed that the decision support system and best practices are not optimized through the available formal reporting on disaster incidents. The rapidly evolving situation, misunderstood terms, inaccurate data and delivery delays of DIU are challenges to the daily SITREP. Multiple stakeholders stipulated with different tasks should be properly understood for the SITREP to initiate relevant response tasks. To fill this research gap, this paper identifies the weaknesses of the current practice and discusses the upgrading of the incident-reporting process using a freely available software tool, enabling further visualization, and producing a comprehensive timely output to share among the stakeholders. In this case, “Power-BI” (a data visualization software) is used as a 360-degree view of useful metrics—in a single place, with real-time updates while being available on all devices for operational decision-making. When a dataset is transformed into several analytical reports and dashboards, it can be easily shared with the target users and action groups. This article analyzed two sources of data, namely the Disaster Management Center (DMC) and the National Disaster Relief Service Center (NDRSC) of Sri Lanka. Senior managers of disaster emergencies were interviewed and explored social media to develop a scheme of best practices for disaster reporting, starting from just before the occurrence, and following the unfolding sequence of the disasters. Using a variety of remotely acquired imageries, rapid mapping, grading, and delineating impacts of natural disasters, were made available to concerned users.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135884540","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}
[Objective]In order to explore the sustainable food security level in the Yangtze River Economic Belt, ensure food security and sustainable development of agricultural modernization, it is necessary to establish a scientific food security evaluation system to safeguard local food security.[Methods]This paper takes the food system of the Yangtze River Economic Belt in China as the research object, based on the food security research results at home and abroad, based on sustainable development thinking, combined with a new perspective of dynamic equilibrium research: Beginning with food normalcy, a comprehensive analysis of food production, food economy, social development, ecological security, and technical support for sustainable development is presented using the entropy-weighted TOPSIS model to build a food security evaluation system for sustainable development. [Conclusion]After systematic analysis, it is concluded that (1) the average value of food security score of the Yangtze River Economic Belt from 2008 to 2021 is 0.429, and the overall food in the Yangtze River Economic Belt is in general security level (0.400 ≤ Q1 ≤ 0.600), and the overall situation of food security is not optimistic, (2) from the segmentation of the Yangtze River Economic Belt, the high and low level of food security are divided into sections: midstream > downstream > upstream, and each province and city is slowly rising to different degrees. In this way, we propose general countermeasures to ensure local food security from the perspective of sustainable development.
{"title":"Building a sustainable food security evaluation system for the Yangtze River Economic Belt: Analysis based on entropy weight TOPSIS model method","authors":"Xiaolong Chen, Cora Un.In Wong, Hongfeng Zhang","doi":"10.24294/jipd.v7i3.2547","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2547","url":null,"abstract":"[Objective]In order to explore the sustainable food security level in the Yangtze River Economic Belt, ensure food security and sustainable development of agricultural modernization, it is necessary to establish a scientific food security evaluation system to safeguard local food security.[Methods]This paper takes the food system of the Yangtze River Economic Belt in China as the research object, based on the food security research results at home and abroad, based on sustainable development thinking, combined with a new perspective of dynamic equilibrium research: Beginning with food normalcy, a comprehensive analysis of food production, food economy, social development, ecological security, and technical support for sustainable development is presented using the entropy-weighted TOPSIS model to build a food security evaluation system for sustainable development. [Conclusion]After systematic analysis, it is concluded that (1) the average value of food security score of the Yangtze River Economic Belt from 2008 to 2021 is 0.429, and the overall food in the Yangtze River Economic Belt is in general security level (0.400 ≤ Q1 ≤ 0.600), and the overall situation of food security is not optimistic, (2) from the segmentation of the Yangtze River Economic Belt, the high and low level of food security are divided into sections: midstream > downstream > upstream, and each province and city is slowly rising to different degrees. In this way, we propose general countermeasures to ensure local food security from the perspective of sustainable development.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135853800","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}
Kefas Bagastio, Raymond Sunardi Oetama, Arief Ramadhan
Stock investment in Indonesia has been steadily growing in the past five years, offering profit potential alongside the risk of loss. Stockholders must analyze the stocks they intend to purchase. Stockholders often analyze stocks by observing patterns that occurred in the previous days to predict future prices. Therefore, a method is needed to simplify the process of analyzing the stock pattern. Although there are already several websites that have the concept of predicting stock prices, these websites do not utilize deep learning algorithms. This research aims to develop a stock price prediction website using deep learning algorithms, specifically the Long Short-Term Memory (LSTM) algorithm to help users predict stock prices. This research focuses on five banks with the highest market capitalization in Indonesia, namely Bank Central Asia, Bank Rakyat Indonesia, Bank Mandiri, Bank Negara Indonesia, and Bank Syariah Indonesia. The website utilizes Flask framework and LSTM. Flask is used to apply LSTM model to the website, while the LSTM can capture long-term dependencies in high-complexity data. The result of this research is a stock price prediction website application, where the prediction results are displayed through the website. The LSTM model for each stock has a Mean Absolute Percentage Error (MAPE) of less than 10%, which indicates that the model is “Highly accurate” based on the MAPE accuracy scale judgment.
{"title":"Development of stock price prediction system using Flask framework and LSTM algorithm","authors":"Kefas Bagastio, Raymond Sunardi Oetama, Arief Ramadhan","doi":"10.24294/jipd.v7i3.2631","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2631","url":null,"abstract":"Stock investment in Indonesia has been steadily growing in the past five years, offering profit potential alongside the risk of loss. Stockholders must analyze the stocks they intend to purchase. Stockholders often analyze stocks by observing patterns that occurred in the previous days to predict future prices. Therefore, a method is needed to simplify the process of analyzing the stock pattern. Although there are already several websites that have the concept of predicting stock prices, these websites do not utilize deep learning algorithms. This research aims to develop a stock price prediction website using deep learning algorithms, specifically the Long Short-Term Memory (LSTM) algorithm to help users predict stock prices. This research focuses on five banks with the highest market capitalization in Indonesia, namely Bank Central Asia, Bank Rakyat Indonesia, Bank Mandiri, Bank Negara Indonesia, and Bank Syariah Indonesia. The website utilizes Flask framework and LSTM. Flask is used to apply LSTM model to the website, while the LSTM can capture long-term dependencies in high-complexity data. The result of this research is a stock price prediction website application, where the prediction results are displayed through the website. The LSTM model for each stock has a Mean Absolute Percentage Error (MAPE) of less than 10%, which indicates that the model is “Highly accurate” based on the MAPE accuracy scale judgment.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136209939","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}
Seema Rehman, Saif Ullah, Fahad Azim, Haroon Ur Rasheed Khan
Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.
{"title":"Impact of financial development, energy consumption and urbanization on CO2 emissions from buildings using quantile ARDL model","authors":"Seema Rehman, Saif Ullah, Fahad Azim, Haroon Ur Rasheed Khan","doi":"10.24294/jipd.v7i3.2166","DOIUrl":"https://doi.org/10.24294/jipd.v7i3.2166","url":null,"abstract":"Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.","PeriodicalId":41907,"journal":{"name":"Journal of Infrastructure Policy and Development","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210322","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}
João Fragoso Januário, Álvaro Costa, Carlos Oliveira Cruz, Joaquim Miranda Sarmento, Vítor Faria e Sousa
The relationship between transport infrastructure and accessibility has long stood as a central research area in regional and transport economics. Often invoked by governments to justify large public spending on infrastructure, the study of this relationship has led to conflicting arguments on the role that transport plays in productivity. This paper expands the existing body of knowledge by adopting a spatial analysis (with spillover effects) that considers the physical effects of investment in terms of accessibility (using distinct metrics). The authors have used the Portuguese experience at regional level over the last 30 years as a case study. The main conclusions are as follows: i) the choice of transport variables matters when explaining productivity, and more complex accessibility indicators are more correlated with; ii) it is important to account for spill-over effects; and iii) the evidence of granger causality is not widespread but depends on the regions.
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