Investigating the Human Reliability in the Healthcare Sector Using the Fuzzy Analytic Network Process and the Success Likelihood Index Method.

Background: We aimed to identify the factors contributing to human error in hospital emergency departments using scientific methods. Methods: We used the Fuzzy Analytical Network Process (FANP) and Success Likelihood Index Method (SLIM) to investigate human reliability in 54 hospital emergency departments in 15 provinces of Iran from 2021 to 2022. Results: The study classified 17 general factors affecting human errors in hospital emergency departments. Organizational (0.349), occupational (0.330), and personal factors (0.320) had the most significant impact on human error. Based on a matrix of paired comparisons for nine emergency tasks using the probability of success index method, "checking test results and diagnosis" had the highest probability of error when referring patients to intensive care or discharge. Although the study prioritized patients, there was still a cumulative probability of human error before disease diagnosis at 0.01332, highlighting the need for further training to minimize these risks. Conclusion: The FANP and SLIM were effective in identifying the factors contributing to human error in hospital emergency departments. Doctors and nurses working in these departments require more knowledge, experience, and responsibility to avoid errors. By identifying factors influencing the occurrence of human error and finding solutions to reduce risks, hospitals can improve the quality of their care and prevent errors.

How does corporate organizational identity, environmental project complexity and environmental project effort matter for project success?

The challenge of achieving success in environmental projects persists for many organizations, and the reasons behind it are unclear. This study is aimed at investigating such reasons by testing the impact of corporate environmental identity, project complexity, and environmental intensity on environmental project success. The study seeks to provide practical recommendations to organizations to enhance their efforts to reduce environmental pollution. The study obtained data from sixteen experts of environmental project managers and applied the fuzzy AHP, fuzzy hierarchical models, and fuzzy TOPSIS techniques for empirical findings. The findings show that organizational identity for the environment and environment project complexity are the key triggers for the success of the environment in the Chinese context. Moreover, it is discovered that team functional diversity is critical to team absorptive capability. This research identified links that offer managers information on prospective selection and project improvement models, with enhanced capacity in leadership dimensions leading to increased project management success. The study also suggested several implications for environmental project success and developing pro-environmental behavior among project managers.

COVID-19 in Europe: from outbreak to vaccination.

BACKGROUND: COVID-19 is a pandemic of unprecedented proportions in recent human history. To date, the world has paid a high toll in terms of human lives lost, and on economic, financial, and social repercussions. In Europe, countries tried to mobilize all resources available to contain the COVID-19 effects, but the outcomes are diverse across countries. There have also been massive efforts geared towards finding safe and effective vaccines and to distribute them massively to the population. The main objective of this paper is to describe the COVID-19 prevalence in Europe. Secondly, it aims to identify epidemiological typologies allowing to distinguish the countries in terms of their response to the pandemic, and finally assess the effect of vaccination on pandemic control. METHODS: The study covers 30 European countries: EU 27 in addition to Norway, Switzerland, and United Kingdom. Four epidemiological variables are analyzed at two distinct moments, at the end of 2020 and at the beginning of 2022: total number of cases per million, total number of deaths per million, total number of tests per thousand, and case fatality rate. In a second step, it uses a fuzzy approach, namely archetypal analysis, to identify epidemiological typologies, and positions countries by their response to the pandemic. Finally, it assesses how vaccination, stringency measures, booster doses and population age affect the case fatality rate, using a multiple regression model. RESULTS: The outcomes unveil four epidemiological typologies for both periods. The clearest sign of change in the two periods concerns the case fatality rate that is found to be low in a single typology in 2020 but occurs in three typologies in 2022, although to different degrees. There is also statistical evidence of the positive impact of the primary vaccination on mortality reduction; however, the same does not hold for the booster dose and stringency measures. CONCLUSIONS: The study shows that primary vaccination is the most effective measure to reduce mortality by COVID-19 suggesting that vaccination provides hope for an end to the pandemic. However, a worldwide access to vaccination is needed to make this happen.

Non-oil economic transition for economic and environmental sustainability in Saudi Arabia: a multi-factor analysis under fuzzy environment.

In this study, an analysis of Saudi Arabia's economic diversification, particularly non-oil transition, is conducted. Initially, key success factors and sub-factors that provide basis for the analysis are identified through literature survey. Three key factors (economic, labor, and market), twenty-one sub-factors (seven under each factor) are identified. To obtain the relative importance of factors and sub-factors, fuzzy analytical hierarchy process (FAHP) has been used. The economic criterion obtained the highest weight followed respectively by fiscal and labor criteria. The "proportion of Saudis in the workforce" sub-criterion received the highest weight under labor criterion, the "investment-intensive business models" sub-criterion obtained the highest weight under economic criterion, and the "increase non-oil revenue" sub-criterion got the highest weight under fiscal criterion. Overall, increase non-oil revenue sub-criterion (under fiscal criterion) received the highest weight. Later, eight major non-oil sectors are prioritized with respect to criteria and sub-criteria using fuzzy technique for order preference by similarity to the ideal solution. Petrochemicals sector ranked topped in the contribution to achieving non-oil transition. The findings of the study shall enable the government and policymakers to specifically design policies for respective sectors knowing their importance in the transition and subsequently bring a new cycle of prosperity to the Kingdom of Saudi Arabia.

Fuzzy analysis of students' perception of traffic safety in school environments: the case of a small Brazilian city.

Thousands of lives are lost every year due to traffic accidents worldwide, and youths are the most affected. The goal of this paper is to analyze the differences in young students' perceptions about traffic safety in school surroundings in order to help in the formulation of public policies and the development of infrastructure to make school travels safer. A questionnaire was used to obtain the perception of high school students from institutions with different urban characteristics. Data modelling with fuzzy logic and statistical analysis of variance indicated that students' perceptions are influenced by the different realities these youths are exposed to daily, such as school socioeconomic category, transport mode, urban environment and gender. Traffic engineering measures, public policies and road safety education action, inciting active mobility, can be validated and supported by these results. This road safety analysis may also be a participative alternative for locations with low data access.

Fuzzy controller based E-nose classification of Sitophilus oryzae infestation in stored rice grain.

Fuzzy controller artmap based algorithms via E-nose selective metal oxides sensor (MOS) data was applied for classification of S. oryzae infestation in rice grains. The screened defuzzified data of selective sensors was further applied to detect S. oryzae infested rice with PCA and MLR techniques. Reliability of data was cross validated with reference methods of protein and uric acid content. Out of 18 MOS, 6 sensors namely P30/2, P30/1, T30/1, P40/2, T70/2 and PA/2 showed maximum resistivity change. Defuzzified score of 62.17 for P30/2 and 59.33 for P30/1 MOS further confirmed validity studies of E-nose sensor response with reference methods. The PCA plots were able to classify up to 84.75% of rice with variable degree of S. oryzae infestation. The MLR values of predicted versus reference values of protein and uric acid content were found to be fitting with R2 of 0.972, 0.997 and RMSE values of 2.08, 1.05.

IPTU: avaliação de potencial e utilização sob a ótica da teoria dos conjuntos fuzzy / IPTU: evaluación de potencial y el uso bajo la óptica de la teoría de conjuntos fuzzy / Assessment of potential and use of the IPTU tax, based on the fuzzy set theory

Resumo A fim de identificar os determinantes do potencial de arrecadação do imposto sobre propriedade predial e territorial urbana (IPTU) no Brasil, bem como a utilização dessa capacidade, este artigo propõe uma análise comparativa dos municípios brasileiros aplicando a teoria dos conjuntos fuzzy. A aplicação dessa metodologia na área das finanças públicas é pioneira no Brasil, o que proporcionou resultados inéditos em matéria de tributação da propriedade. Os resultados confirmaram o que analistas e até mesmo dirigentes municipais já apontaram há tempos: a maioria dos municípios brasileiros não utiliza todo o seu potencial de arrecadação do IPTU - fato que tende a ser mais crítico nas cidades de menor porte e que dependem mais de recursos de outras esferas de governo. O artigo inova ao mensurar esse potencial a partir de uma análise comparativa entre cidades com semelhantes características.

Resumen Con el fin de identificar los determinantes del potencial de la colección de impuesto sobre bienes inmuebles y territorial urbano en Brasil, así como la exploración de tal capacidad, este artículo propone un análisis comparativo de los municipios brasileños mediante la aplicación de la teoría de conjuntos fuzzy. La aplicación de esta metodología en el área de las finanzas públicas es pionera en Brasil, e ha dado resultados sin precedentes sobre los impuestos de propiedad. Los resultados confirmaron lo que los analistas y líderes municipales incluso han señalado hace algún tiempo: la mayoría de los municipios brasileños no utiliza todo su potencial para recaudar IPTU - hecho que tiende a ser más crítico en ciudades más pequeñas y que dependen de fondos desde otras esferas del gobierno. Este artículo innova para medir este potencial basado en un análisis comparativo de las ciudades con características similares.

Abstract This article proposes a comparative analysis among Brazilian municipalities in order to identify the determinants of the potential and of the ability to collect urban property tax (IPTU) in Brazil. The analysis applied the fuzzy set theory, a pioneer methodological choice in the field of public finances in Brazil, which has provided unprecedented results in terms of property taxation. The results confirmed what analysts and municipal leaders have pointed out for a long time: the majority of Brazilian municipalities do not use their full potential to collect the IPTU — a fact that tends to be more critical in smaller cities, which depend on funding from other spheres of Government. The article breaks new ground in assessing this potential based on a comparative analysis of cities with similar characteristics.