Maintaining the judiciary's power requires a high level of budgetary expenditure, but the specifics of this relationship have yet to be fully explored. Although several studies have analyzed the impact of spending in the judiciary through productivity and performance-related measures, none have employed machine learning techniques. This study examines the productivity of the judiciary based on spending and other variables using machine learning techniques, including clustering and neural networks. The final neural network model supports the results of Pearson's parametric correlation test, which found no significant correlation between expenditure and productivity. This study's findings demonstrate the importance of understanding that increased public budgetary expenditure alone is insufficient for improving the judiciary's efficiency. Instead, other administrative and technical measures are necessary to meet the demands of the Brazilian judiciary and improve service delivery rates. These findings offer important theoretical and managerial contributions to the field.

This paper analyzes the relationship between corporate social responsibility (CSR) and social impact within the oil industry in an emerging market (Peru). Following the emerging literature on the social impact field, and using the case study methodology, the findings show that the expected positive relationship is diverse depending on several factors. Specifically, the results reveal that companies must focus on community and environmental responsibility, together with stakeholders' involvement to achieve social impact. However, when companies are weak in any of the previous factors, then the social impact is only partially accepted or even withdrawn.

Crisis environments, which are becoming systemic, pose significant challenges to smart government strategies. The paper aims to contribute to academic debate by proposing an analytical framework for examining the institutional capacities of smart government systems in addressing local crises. The paper focuses on the recent approach of robust governance and highlights a set of variables that promote effective smart government: contingency planning capacity, analytical capacity, organizational management capacity, and collaborative capacity. The study presents an analytical model for evaluating the robustness and effectiveness of local smart government systems in crises. One of the significant findings of this study has been the identification of critical indicators that inform institutional capacities of smart government systems. By analyzing these indicators, the proposed analytical framework provides a comprehensive approach to assess the preparedness of smart government systems in dealing with crises. Moreover, it can be used to benchmark the performance of local smart government systems in similar contexts and identify best practices for improving crisis management.

Major emergencies can have a devastating impact on society, becoming a catalyst for social disorder and unrest and a trigger for social or political change. In today's world of frequent emergencies, the emergency management capacity of local governments is key to promoting safe operations and maintaining stability in cities and towns. Aiming to explore the direction and focus of local government emergency management capacity building, this paper establishes a local government emergency capacity evaluation system based on the emergency management process and combines Gray-Dematel, a gray decision laboratory analysis method, and AISM, an adversarial explanatory agency model, to derive the importance and intrinsic relationship among emergency capacity indicators. The algorithm describes the importance degree of each indicator in the system and also helps better understand the intrinsic relationship among the indicators. The outcomes of this research can be used to outline directional suggestions for the development of local government emergency response capacity and provide a new theoretical basis for more effective construction of local government emergency response capacity.

Communication and effective interactions are inevitable necessities in every organizational setting. In this era of information and communication technology, where limitations and difficulties in proper communication and interactions between different entities of various organizations have been reduced maximally, the government, stakeholders, and citizens of the different nations should also utilize these available tools in a way to improve the maximum performance in governance through interactions and e-participation between the citizens, stakeholders, and the government parastatals. This research focuses on examining the available and most preferred applications or platforms which encourage the best level of communication and interaction through E-participation among the citizens, stakeholders, and government from the local government lev-el taking Nigeria as a case study

The COVID-19 pandemic has not only affected public health but has also significantly impacted the economy. Bandung, a bustling city in Indonesia serving as a satellite to the capital, has been hit hard due to its high population density, mobility, and reliance on the tourism, trade, and transportation sectors. Using a Computable General Equilibrium (CGE) model developed at the inter-regional level of Indonesia, this study investigates the microeconomic indicators of several economic activities in Bandung to assess the impact of the pandemic. Additionally, the study examines the role of private sector actors in contributing to the sustainable recovery efforts toward achieving Sustainable Development Goals (SDGs) amidst the pandemic. The findings reveal that Bandung's transportation, accommodation, food and beverage, water supply, and trade sectors experienced a significant decline in economic activity. However, there was a gradual recovery with increased economic activity between 2019 and 2021. Private sector actors and the health sector were the main drivers of economic recovery, with other sectors also contributing to the efforts.

In rural spaces, new activities are developed to add to the traditional ones in the context of multifunctionality, considering the protection and enhancement of natural and cultural heritage, as in Nature Parks. They incorporate new recreational and tourist functions, understood as an instrument for local development. This research aims to study the relationships between tourism and local development in three Natural Parks (Sierra de Aracena and Picos de Aroche, Sierra Norte de Sevilla and Sierra de Hornachuelos) in Andalusia (Spain). The research uses a mixed methodology consisting of, on the one hand, selective interviews with stakeholders focused on tourism and local development processes and, on the other, secondary data to analyze the repercussions on local development. The results show that (1) prevalence among the informants of the economic dimension in local development above the environmental and socio-cultural dimensions; (2) influence of declarations of protection and implementation of development policies on the growth of the tourist offer; (3) uneven tourism development in the different municipalities and Natural Parks; and (4) limited effects of tourism on local development.

Introduction: This study explores exposure to misinformation, COVID-19 risk perception, and confidence towards the government as predictors to negative attitudes toward the COVID-19 vaccine. Methods: A cross-sectional survey was carried out from 30 June to 30 August 2021 involving 775 respondents. The survey instrument for the questionnaire is an adaptation from various different studies consisting of five main variables: 1) misinformation about vaccination; 2) risk perception toward COVID-19; 3) attitudes toward the vaccination programme; 4) intention to get vaccinated; and 5) public confidence in the government in executing the vaccination programme. Results: The results of this study indicate that higher exposure to misinformation led to higher levels of negative attitudes toward the COVID-19 vaccine. When the perceived risk of COVID-19 infection was high, mistrust of vaccine benefits was low but there were also higher worries about the future effects of the vaccine. Confidence in government was associated with lower negative attitudes toward the COVID-19 vaccine. Conclusion: The results of this study may help develop an understanding of negative attitudes toward vaccinations in Malaysia and its contributing factors.

The COVID-19 pandemic has highlighted the adverse consequences created by an infodemic specifically on compliance with public health guidance and vaccine uptake. COVID-19 vaccine hesitancy is a complex construct that is related to health beliefs, misinformation exposure, and perceptions of governmental institutions. This study draws on theoretical models and current data on the COVID-19 infodemic to explore the association between perceived risk of COVID-19, levels of misinformation endorsement, and opinions about the government response on vaccine uptake. We surveyed a sample of 2,697 respondents from the US, Canada, and Italy using a mobile platform between 21-28 May, 2021. Using multivariate regression, we found that country of residence, risk perception of contracting and spreading COVID-19, perception of government response and transparency, and misinformation endorsement was associated with the odds of vaccine hesitancy. Higher perceived risk was associated with lower odds of hesitancy, while lower perceptions of government response, and higher misinformation endorsement were associated with higher hesitancy.

Poverty is one of the indexes that can see how a country succeeds in development. In Indonesia, the poverty rate is high as the impact of the Covid-19 pandemic increases over time. Therefore, a solution is embraced in the form of government policies in tackling poverty in Indonesia. The purpose of this study is to analyze the poverty caused by the Covid-19 pandemic.What is the current state of poverty caused by the Covid-19 pandemic in Indonesia? and what are the previous government policies that have succeeded in reducing poverty in Indonesia? The method used in this study is the literature review method based on the results of critical analysis of journal articles that are relevant to the topic of discussion. The results showed that three government policies have succeeded in lowering the poverty level in Indonesia, namely the PKH program policy, the zakat policy as an indicator of poverty reduction, and the Bank Wakaf Mikro policy. Therefore, this study focuses on the policy as a study for government policy in lowering poverty levels due to the Covid-19 Pandemic.

Though the share of the world population living in extreme poverty declined to 10 percent in 2015, from 16 percent in 2010 and 36 percent in 1990, data shows that the world is not on track in achieving the target of less than 3 percent of people living in extreme poverty by 2030. Hence the study sought to investigate the influence of AI on poverty reduction. Using content analysis one of the unobtrusive research techniques, the study found out that, the availability of relevant data is making AI be able to deliver value to humanity and AI has a strong influence on poverty in areas of relevant data collection through poverty maps, its ability to revolutionize agriculture, education, and the financial sector through digital financial inclusion. The study also discovered that many countries especially developing nations are not collecting as much data to identify the number of poor people and the regions where these people are located. However, the existence of AI is assisting to change this, or instance the study discovered that the research team at Stanford University is using satellite images to provide an alternative to map poverty, to identify the regions where poverty is more concentrated. Also, various robotics and AI programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab, are coming forth with AI programs in agriculture which are doing a lot to improve farming, through the identification of diseases, prediction of crop yields, and location of areas prone to a scarcity among several other notable signs of progress in education. Therefore, the study recommends that governments, development institutions and other organizations that are striving to fight poverty to invest more in AI as well as adopting and scaling up its use as it presents benefits in the quest to ensure that poverty is reduced.

Since the first coronavirus patient was identified in Bangladesh on March 8, the most controversial issue is about the exact level of the infection in Bangladesh. Conformity with the population density the number of COVID-19 tests is inadequate. As the number of tests increases, so does the number of infections, making it difficult to predict the spread of COVID-19 in Bangladesh. In this case, the unplanned initiatives are particularly responsible in other for unplanned measures, lack of public awareness, and lack of proper knowledge. In this case, the Ministry of Health has made three major mistakes, three important features of the medical system in Bangladesh have been mentioned. It is more effective to prevent COVID-19 by isolating the infected person by further testing COVID-19 until effective treatment is available and to provide adequate and effective masks and personal protective equipment (PPE). In this case, the COVID-19 testing kit invention has received a good response in many countries of the world. This study focuses on the comprehensive data verification, selection, and evaluation of COVID-19 in Bangladesh and its implications for the future, what to do to address and prevent the COVID-19 challenge, and effective treatment against the coronavirus (COVID-19). It is hopeful that the discussion of the material mentioned in this research paper will help to strike a balance between the government, citizens, and experts which will be feasible in improving the current situation in COVID-19 Bangladesh and reducing its severity.

Green development ensures the socioeconomic development that incorporates environmental issues while remaining economically viable for owners and tenants. Government as the authority of the state should provide favorable incentives, policy and regulatory pressure for green development. The present study aims to investigate the government policies and regulations for green development in Bangladesh and make a critical discussion of the initiatives. The study is descriptive in nature and collects secondary information. Evidence suggests that environmental degradation and climate change related risks and vulnerabilities have intensified in Bangladesh. The government of Bangladesh (GOB) is concerned about green development and formulates various Acts, regulations and policy initiatives since 2010. Major green development initiatives observed in the financial institutions due to the mandatory requirements by Bangladesh Bank but green bond and green insurance in capital market are yet to be developed. The GOB required taking proper policy initiatives for the garments and leather industries to ensure pollution free production system which ensures green trade initiatives. The environmental taxes and ecological compensation mechanisms should be revised. Urban green space and Government green procurement are still less concerning matter. The GOB should make effective collaboration with all related stakeholders to ensure the green development.

Decisions affecting the COVID-19 pandemic, by the individual and those with highest authority, are being made on the basis of unreliable data. Data about cases and deaths are collected daily but represent only a sample of reality. Statistics convert sample data into more reliable estimates. However, statistics have no magical powers; reliability requires dependable data. It is futile to rail against this darkness; COVID-19 is not a scientific experiment. However, we must do better both with data collection and data analysis. In this review, I focus on one element of the data, the asymptomatic case of COVID-19. Without reliable information about this number, decision makers are significantly blinded. By its nature, the asymptomatic case is hidden but contaminating to understanding COVID-19. The true case rate and death rate per case are unknowable without knowing the fraction of cases that are asymptomatic. The best estimate of asymptomatic cases is in the CDC document: COVID-19 Pandemic Planning Scenarios. For four different scenarios the estimates range from 10% to 70%, with the best estimate of 40% for asymptomatic cases. However, even the definition of the asymptomatic case is problematic. In simplest terms, two elements are required: an infection and no symptoms. How is “no symptoms” to be usefully defined? It appears to be analogous to pontificating about black swans from studying only white swans. It implies infection, but how is infection defined? Is it presence of the virus, replication of the virus, or presence of antibodies? Is asymptomatic disease an oxymoron? Without extensive, purposeful screening for specifically defined, essential symptoms and appropriate virus and antibody testing over time, the class of asymptomatic cases remains unknown. Current estimates range from <20% to ˃80%. If low, it can be ignored; if high, it dramatically and proportionately lowers the case rate and the death rate per case. Consequentially, the asymptomatic rate dramatically affects our societal and political responses. In this focused review, we assess the limitations of the published estimates, bring attention to the importance of obtaining accurate data, and exhort that high priority be given in the scientific community to understanding the issue, asymptomatic COVID-19 cases.

Coronavirus disease (COVID-19) has caused mankind serious confusion, economic havoc and psychological distress. This study evaluated the level of knowledge, attitude and perception about COVID-19 pandemic, infection control and impact among veterinarians in Nigeria. A cross-sectional online survey was used to collect data from consenting respondents during implementation of lockdown in the country (April 23 - May 31, 2020). Purposive and chain referral sampling techniques were used to recruit 368 respondents from various sectors of the profession. The proportion of respondents surveyed 197/368 (53.5 %) were from the public sector, 35.3 % from private sector, 1.1 % were unemployed and 0.8 % retired. Majority of the respondents were males (72.8 %), within 30 – 39 years (39.7 %) and had 1 – 10 years work experience. Respondents displayed good level of knowledge about COVID-19 (72.4 % ± 9.9 %, range 44.1-91.2 %), with information mostly derived from TV/Radio (81.5%) and social media (81.0 %). The overall attitude level was poor and various determinants for good attitude among respondents were if they were above 60 years (p = 0.013), possessed postgraduate qualification ( p = 0.031), worked over 30 years post DVM (p = 0.001), had household members between 5 and 10 (p = 0.012), and were resident in states on total lockdown (p = 0.024). There was no correlation between the knowledge level score and respondents’ attitude towards the pandemic (p = 0.12). With increasing rate of COVID-19 transmission, research data are needed to develop evidence-driven strategies, policies and effective risk mitigations to reduce the pandemic’s adverse impacts.

The 1783-1784 Laki eruption was one of the most severe natural catastrophes to occur in Iceland in historical times (since 1140 years). Vegetation damage by sulphate aerosol and fluorine poisoning caused a massive decimation of livestock. The impact of fluorine poisoning and sulphate aerosol on human mortality is uncertain, but the loss of animals caused a famine which took many lives. The vulnerability of the Icelandic society to famine is discussed. 18th Century Iceland was a Danish dependency and, despite the abundance of fish in the surrounding waters, a subsistence farming community and thus highly dependent on livestock. On the other hand, the farming community possessed coping strategies which mitigated the impact of livestock loss. During the famine, the Danish government was in principle willing to provide relief. However, local authorities in Iceland were slow to ask for help, and did not dare to exploit the means at their disposal (e.g. the right to ban the export of Icelandic foodstuff) without consent from Copenhagen. The Danish officials in turn were unwilling to act decisively upon incomplete information. These two factors prevented timely measures. While 4.4 × 10^5kg of grain were provided for famine relief in summer 1784, the merchants exported 1.2 × 10^6kg of fish, which greatly aggravated the hunger in the second winter. The effects of this ‘natural’ catastrophe could therefore have been significantly reduced by efficient government.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.

The 1783-1784 Lakagígar eruption was probably the most severe natural catastrophe to occur in Iceland. While contemporary records suggest that no or few human lives were lost directly due to the eruption, vegetation damage by acid rain and fluorine poisoning caused a massive decimation of livestock, which led to a famine lasting 1.5 years. Contagious diseases also took many lives, but may be an indirect result of hunger. 18th Century Iceland was a Danish dependency and a subsistence farming community highly vulnerable to famine. Development of the fisheries could have improved the situation, but this did not occur. Instead, Iceland remained trapped in a vicious circle of conservatism, poverty, and lack of technological means (seaworthy fishing boats) sustained by artificially low fish prices decreed by the Danish king. During the famine, the Danish government was in principle willing to provide relief. However, local authorities in Iceland were slow to ask for help, and did not dare to exploit the means at their disposal (e.g. the right to ban the export of Icelandic foodstuff) without consent from Copenhagen. The Danish officials in turn were unwilling to act decisively upon incomplete information. These two factors prevented timely measures. While 440,000kg of grain were provided for famine relief in summer 1784, the merchants exported 1,200,000kg of fish, which greatly aggravated the hunger in the second winter. The effects of this `natural' catastrophe could therefore have been significantly reduced by efficient government.

This study aims to find a communication model of contingency plan for disaster risk management of Sinabung Volcano eruption, in North Sumatera. The object of the research is communication and coordination across the government, non-government organization, and community. This study used planning theory, the concept of communication planning, and types of disaster management plan as tools for analysing. Descriptive qualitative is used as the method. Data collection was obtained from the focus group discussion (FGD), in-depth interviews, observation, and study documentation. There are three stages in descriptive qualitative research that is data reduction, data presentation, and conclusion. An analysis was conducted qualitatively on the program and competence actors. The results found the communication model of disaster risk management through documents of contingency planning to overcome the threat of Mount Sinabung eruption. During the emergency response period a core model was used to reduce the impact of the Mount Sinabung eruption. The contingency plan becomes the Karo District Government’s document. This document were authorized by an authorized official and is ready to be applied to the Emergency Response Operation Plan. Plans for emergency response operations are carried out based on information regarding damage and the need to obtain results of a quick review. Contingency plans are submitted to the legislature for political commitment and support and budget allocation.

This paper seeks to explain the rapid growth of the Islamic State of Iraq & Syria (ISIS) and approach the question of “what is” the Islamic State? The paper offers several contributions. First is the proposal of a dynamic hypothesis that ISIS is an emerging-state actor and differs notably from traditional non-state actors and insurgencies. The theory consists of both a causal loop diagram and key propositions. A detailed system dynamics simulation (E-SAM) was constructed to test the theory. The propositions of emerging-state actor theory are constructed as synthetic experiments within the simulation and confirm evidence of emerging-state actor behavior. E-SAM’s novelty is its combination of combat simulation with endogenous geospatial feedback, ethnographic behavior in choosing sides in conflict, and details internal simulation of key actor mechanisms such as financing, recruiting and governance. E-SAM can be loaded with scenarios to simulate non-state actors in different geospatial domains: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.

This paper builds upon a theory of emerging-state actors using ISIS as a case study. This paper seeks to apply the theory in analyzing intervention & containment policies to use against emerging-state actors, using ISIS as the case study. Two baseline scenarios are used for evaluation – one replicating the historical foreign intervention against ISIS and a counter-factual where no foreign intervention occurred. Eleven contemporary military policies were tested against these baseline in isolation, combination, at different timing windows and under hypothetical “best case” conditions as well as operationally constrained. Insights of these tests include the influence of ethnographic envelopes, timing windows. Finally, a policy based on emerging-state actor theory is tested performing substantially better across primary measures than other policies or the historical baseline. This is compared against a falsified-policy designed to disprove that emerging-state actor theory contributed to the benefits. This paper’s contributions are a practical application of system dynamics simulations and systems-thinking to current problems, generate insights into the dynamics of emerging-state actors and intervention strategies, and demonstrate utility for future application of the underlying simulation in other scenarios involving non-state actor irregular conflict including terrorism, insurgents, or emerging-state actors.

This paper seeks to explain the rapid growth of the Islamic State of Iraq & Syria (ISIS) and approach the question of “what is” the Islamic State? The paper offers several contributions. First is the proposal of a dynamic hypothesis that ISIS is an emerging-state actor and differs notably from traditional non-state actors and insurgencies. The theory consists of both a causal loop diagram and key propositions. A detailed system dynamics simulation (E-SAM) was constructed to test the theory. The propositions of emerging-state actor theory are constructed as synthetic experiments within the simulation and confirm evidence of emerging-state actor behavior. E-SAM’s novelty is its combination of combat simulation with endogenous geospatial feedback, ethnographic behavior in choosing sides in conflict, and details internal simulation of key actor mechanisms such as financing, recruiting and governance. E-SAM can be loaded with scenarios to simulate non-state actors in different geospatial domains: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.