The Economic Cybernetics Analysis and the Effects of the Occurrence of COVID-19 in Romania

From the perspectives of early warning and identification of risk, risk quantification and analysis, also as risk management, we propose recommendation, which includes analysis of citizen behavior in panic, cooperation of the institutions in Romania. The whole analysis will be performed from a perspective of the field of economic cybernetics. The 2019-nCoV coronavirus epidemic started in China's Wuhan city, which has spread throughout the country and subsequently, in a very short period of time, in several states, being viewed as a global contagion effect that causes great concern. As the virus gets closer to Romania, it becomes worrying and citizens are already panicking. Therefore, in this article we will analyze, according to public data, what is the current situation and how well Romania is prepared to manage the risks arising from the confirmation of COVID-19 in the country and how the behavior of citizens in a state of panic is influenced. In addition, we analysed the medical system from Romania from the point of view of the analysis of the management of the viable system, in the situation of pandemic crisis the medical system being one of the sensitive points of any system

Financial contagion and identifying speculative frenzies: Unraveling price bubbles in cryptocurrency markets

This research investigates the occurrence of financial bubbles in the cryptocurrency market and highlights the factors that may influence the formation of these bubbles. Three cryptocurrencies were analyzed: Bitcoin, Ethereum, and Cardano, and our findings showed that these cryptocurrencies exhibited potential bubbles during the three-year period under study, from 2020 to 2023. To detect financial bubbles, the Exponential Curve Fitting Model (EXCF) model was used. Events such as the Covid-19 pandemic and the Russia-Ukraine conflict were examined from the perspective of their potential impact on the cryptocurrency market and investor behavior. The study also illustrated how investors’ behavior, whether rational or influenced by external factors, as well as internal factors such as panic levels and knowledge in the financial-economic domain, were analyzed

Cybernetics Approach Using Agent-Based Modeling in the Process of Evacuating Educational Institutions in Case of Disasters

In the context of an emergency, evacuating people from a location in the shortest possible time is essential, as is the high degree of safety that people should expect when evacuating. Lately, in Romania there have been more and more fire events generated by different causes. This article will use agent-based modeling to simulate an emergency evacuation model in NetLogo. The model has been used to perform and analyze various scenarios. With the help of NetLogo, we managed to perform 400 simulations with the evacuation of 180 people (students, teachers, and non-teaching staff) based on which we developed several recommendations to streamline the evacuation process in order to reduce the possibility of death. The present research will help to identify the evacuation times from a school, but it will also highlight certain aspects that may occur during the evacuation. The model that was used in this research took into account the individual particularities of the people taking part in the evacuation, emphasizing the effects that form in a crowd of people when evacuating; effects such as the funnel effect, which is caused by the formation of bottlenecks around narrow areas. All these things are part of the analysis of the measurement of entropy of the exhaust system, a problem that has captured all of the specialists’ attention. Finally, solutions have been proposed to improve evacuation time in case of disasters

Mathematical Patterns in Fuzzy Logic and Artificial Intelligence for Financial Analysis: A Bibliometric Study

In this study, we explored the dynamic field of fuzzy logic and artificial intelligence (AI) in financial analysis from 1990 to 2023. Utilizing the bibliometrix package in RStudio and data from the Web of Science, we focused on identifying mathematical models and the evolving role of fuzzy information granulation in this domain. The research addresses the urgent need to understand the development and impact of fuzzy logic and AI within the broader scope of evolving technological and analytical methodologies, particularly concentrating on their application in financial and banking contexts. The bibliometric analysis involved an extensive review of the literature published during this period. We examined key metrics such as the annual growth rate, international collaboration, and average citations per document, which highlighted the field’s expansion and collaborative nature. The results revealed a significant annual growth rate of 19.54%, international collaboration of 21.16%, and an average citation per document of 25.52. Major journals such as IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, the Journal of Intelligent & Fuzzy Systems, and Information Sciences emerged as significant contributors, aligning with Bradford’s Law’s Zone 1. Notably, post-2020, IEEE Transactions on Fuzzy Systems showed a substantial increase in publications. A significant finding was the high citation rate of seminal research on fuzzy information granulation, emphasizing its mathematical importance and practical relevance in financial analysis. Keywords like “design”, “model”, “algorithm”, “optimization”, “stabilization”, and terms such as “fuzzy logic controller”, “adaptive fuzzy controller”, and “fuzzy logic approach” were prevalent. The Countries’ Collaboration World Map indicated a strong pattern of global interconnections, suggesting a robust framework of international collaboration. Our study highlights the escalating influence of fuzzy logic and AI in financial analysis, marked by a growth in research outputs and global collaborations. It underscores the crucial role of fuzzy information granulation as a mathematical model and sets the stage for further investigation into how fuzzy logic and AI-driven models are transforming financial and banking analysis practices worldwide

Toward Sustainable Development: Assessing the Effects of Financial Contagion on Human Well-Being in Romania

In a globally interconnected economy marked by volatility, this study employs the Autoregressive Distributed Lag (ARDL) model to examine financial contagion’s impact on Romania’s financial stability. It investigates both conventional and unconventional channels through which financial contagion is transmitted, emphasizing its sensitivity to factors such as geopolitical events and investor sentiment. The study also assesses the influence of unemployment, market capitalization, and financial freedom on Romania’s Human Development Index (HDI) from 2000 to 2022. Using HDI, which encompasses health and education alongside economic aspects, the research provides a holistic view of well-being and quality of life. In addition to the ARDL model’s insights, this study expands its scope by conducting a multilinear regression analysis, with GDP as the dependent variable. We have incorporated independent variables such as HDI, transaction volume, and the BET-FI index to comprehensively assess their relationships and potential impact on Romania’s economic growth. This analytical approach unveils intricate connections between key economic and financial indicators, paving the way for a deeper understanding of how these variables interact. Furthermore, to shed light on the financial dynamics within Romania, a supplementary analysis in the Altreva Adaptive Modeler was undertaken, focusing on the BET-FI index. This software-based exploration provides a nuanced perspective on the index’s behavior and its interactions with other economic and social indicators. This additional dimension contributes to our holistic understanding of the effects of financial contagion and the implications for sustainable human development in Romania. By combining traditional econometric methodologies with cutting-edge modeling techniques, this study strives to offer a robust framework for comprehending the multifaceted nature of financial contagion and its implications for both the national economy and well-being. These findings have the potential to guide policymakers and financial institutions in implementing more effective risk management strategies, driving economic development, and ultimately enhancing the overall quality of life in Romania

Quantitative Modeling of Financial Contagion: Unraveling Market Dynamics and Bubble Detection Mechanisms

This study explored the complex interplay and potential risk of financial contagion across major financial indices, focusing on the Bucharest Exchange Trading Investment Funds Index (BET-FI), along with global indices like the S&P 500, Nasdaq Composite (IXIC), and Dow Jones Industrial Average (DJIA). Our analysis covered an extensive period from 2012 to 2023, with a particular emphasis on Romania’s financial market. We employed Autoregressive Distributed Lag (ARDL) modeling to examine the interrelations among these indices, treating the BET-FI index as our primary variable. Our research also integrated Exponential Curve Fitting (EXCF) and Generalized Supremum Augmented Dickey–Fuller (GSADF) models to identify and scrutinize potential price bubbles in these indices. We analyzed moments of high volatility and deviations from typical market trends, influenced by diverse factors like government policies, presidential elections, tech sector performance, the COVID-19 pandemic, and geopolitical tensions, specifically the Russia–Ukraine conflict. The ARDL model revealed a stable long-term relationship among the variables, indicating their interconnectedness. Our study also highlights the significance of short-term market shifts leading to long-term equilibrium, as shown in the Error Correction Model (ECM). This suggests the existence of contagion effects, where small, short-term incidents can trigger long-term, domino-like impacts on the financial markets. Furthermore, our variance decomposition examined the evolving contributions of different factors over time, shedding light on their changing interactions and impact. The Cholesky factors demonstrated the interdependence between indices, essential for understanding financial contagion effects. Our research thus uncovered the nuanced dynamics of financial contagion, offering insights into market variations, the effectiveness of our models, and strategies for detecting financial bubbles. This study contributes valuable knowledge to the academic field and offers practical insights for investors in turbulent financial environments

From Data to Insights: A Bibliometric Assessment of Agent-Based Modeling Applications in Transportation

This paper presents a bibliometric analysis within the research domain dedicated to the utilization of agent-based modeling (ABM) in the field of transportation. By employing specific keywords related to both agent-based modeling and transportation, we have identified and extracted 1016 scholarly papers from the ISI Web of Science database, spanning the period from 2002 to 2023. Through the application of bibliometric methods, we have systematically examined key contributors, affiliations of academic institutions, influential publications, and renowned journals within this domain. Our analysis reveals a consistent and robust growth in scholarly interest pertaining to agent-based modeling in the field of transportation throughout the considered period. Notably, within approximately four decades of ABM’s application in transportation, a distinct upward trajectory began in 2008, culminating in the year 2021. The entire considered period witnessed a remarkable surge in paper production, characterized by an annual growth rate of 21.67%. Furthermore, employing an n-gram analysis, we have delineated and discussed the principal areas within transportation that have progressively benefited from the advancements in agent-based modeling. Prominently, the domains of air transport and road transport have exhibited substantial development over time, while the implications of climate change have emerged as a persistent concern throughout the entire study period

A Two-Door Airplane Boarding Approach When Using Apron Buses

Boarding is one of the major processes of airplane turnaround time, with a direct influence on the airline companies’ costs. From a sustainable point of view, a faster completion of the boarding process has impact not only on the airline company’s long-term performance, but also on customers’ satisfaction and on the airport’s possibility of offering more services without additional investments in new infrastructure. Considering the airplane boarding strategies literature, it can be observed that the latest papers are dealing with developing faster boarding strategies, most of them considering boarding using just one-door of the aircraft. Even though boarding on one-door might be feasible for the airports having the needed infrastructure and sufficient jet-bridges, the situation is different in European airports, as the use of apron buses is fairly common. Moreover, some of the airline companies have adapted their boarding pass in order to reflect which door one should board once they get down from the bus. While using these buses, the boarding strategies developed in the literature are hard to find their applicability. Thus, a new method for boarding on two-door airplanes when apron buses are used is proposed and tested against the actual boarding method. A model is created in NetLogo 6.0.4, taking advantages of the agent-based modeling and used for simulations. The results show a boarding time reduction of 8.91%