Search results

The purpose of this rapid scoping review was to map existing literature on risk communication strategies implemented by authorities and aimed at vulnerable immigrants in the context of pandemics.

Existing literature on the topic was charted in terms of its nature and volume by summarizing evidence regarding the communication strategies. Literature searches were conducted in Academic Search Premier and CINAHL, databases were searched from 2011 to present on March 31, 2021.

Five articles met the criteria and were included in this review, pointing at limited research in this area. The findings indicated that a close interaction between communication authorities and immigrants is important. Community education, building trust in communication sources, clear risk communication and inclusive decision-making among all were found to be important when communicating health risks to immigrants.

The primary limitation of this rapid scoping review is that the literature searches were conducted in only two databases, namely, Academic Search Premier and CINAHL. A wider search across several other databases could have given more profound results. Furthermore, some studies where immigrants were conceptualized as, for instance, “disadvantaged groups” might be overseen due to a choice of the search strategy used in this study. There are also certain limitations related to the studies included in this review.

Identifying efficient ways of conveying recommendations may further assist authorities and scientists in developing more effective health-related risk communication.

This study covered health-related risk communication in the context of pandemics, addressing the need to investigate different groups of immigrants and the challenges related to communicating risks to these groups.

This study examines the mediating role of motivation on outdoor recreation on the attitude–behavior and social marketing–behavior linkages. The paper scrutinizes the moderating impact of coronavirus disease 2019 (COVID-19) risk perception in transforming individual motivation on nature-based outdoor recreation into environmentally responsible behavior.

Data were collected and conducted in Vietnamese National Parks. The dataset consists of 900 valid responses by domestic travelers. The research was operationalized using empirical data and employed structural equation modeling (SEM) and SPSS PROCESS analysis.

First, this study confirms that outdoor recreation activities and business's marketing on social networks tend to transform into support for individual behavior in terms of protecting environment and having responsibility for environment. Second, the current paper also represents the academic efforts to contribute to outdoor recreation literature by explaining the current global problem that has caused serious upheaval in global society as well as individual life. The findings not only confirmed the mediating role of nature-based outdoor recreation motivation between attitude and behavior, but also examined the moderating effect of COVID-19 risk perception in the relationship between motivation and behavior.

The findings indicate the significant association of social marketing, environment attitudes, outdoor recreation motivation and environmentally responsible behavior. The findings not only confirmed the mediating role of nature-based outdoor recreation motivation between attitude and behavior, but also examined the moderating effect of COVID-19 risk perception in the relationship between motivation and behavior. These results provide key insights about examining visitors' behavior for environment protection during future infectious disease outbreaks.

The purpose of this study is to understand how neuroscientific tools are used and discussed in ongoing research on strategy in organizations.

The authors used a bibliometric study of bibliographic pairing to answer the research question. They collected data from the Web of Science and Scopus databases using the keywords “neuroscience*,” “neurostrategy*” and “neuroscientific*.”

This study presents a framework that relates fundamental aspects discussed in current research using neuroscientific tools: Neuroscience and its research tools in organizations; emotions and information processing; interdisciplinary application of neuroscientific tools; and moral and ethical influences in the leaders' decision-making process.

The inclusion of neuroscientific tools in Strategic Management research is still under development. There are criticisms and challenges related to the limitations and potential to support future research.

Despite recognizing the potential of neuroscientific tools in the mind and brain relationship, this study suggests that at this stage, because of criticisms and challenges, they should be used as support and in addition to other traditional research techniques to assess constructs and mechanisms related to strategic decisions and choices in organizations.

Neuroscientific methods in organizational studies can provide insights into individual reactions to ethical issues and raise challenging normative questions about the nature of moral responsibility, autonomy, intention and free will, offering multiple perspectives in the field of business ethics.

In addition to presenting the potential and challenges of using scientific tools in strategic management studies, this study helps create methodological paths for studies in strategic management.

Studying tourist behavior provides the privilege of diverging in the competition between destinations to attract tourists. Previous studies have explored the effects of tourist behavior on brand satisfaction, attachment and loyalty. However, there is a lack of studies that investigated the intuition behind shaping tourist behavior. To address this issue, this study aims to contribute to providing a viewpoint to apply locus of control (LOC) theory in the tourism context. LOC studies how individuals believe in controlling their feelings and judgment toward events.

Loan default risk or credit risk evaluation is important to financial institutions which provide loans to businesses and individuals. Loans carry the risk of being defaulted. To understand the risk levels of credit users (corporations and individuals), credit providers (bankers) normally collect vast amounts of information on borrowers. Statistical predictive analytic techniques can be used to analyse or to determine the risk levels involved in loans. This paper aims to address the question of default prediction of short-term loans for a Tunisian commercial bank.

The authors have used a database of 924 files of credits granted to industrial Tunisian companies by a commercial bank in the years 2003, 2004, 2005 and 2006. The naive Bayesian classifier algorithm was used, and the results show that the good classification rate is of the order of 63.85 per cent. The default probability is explained by the variables measuring working capital, leverage, solvency, profitability and cash flow indicators.

The results of the validation test show that the good classification rate is of the order of 58.66 per cent; nevertheless, the error types I and II remain relatively high at 42.42 and 40.47 per cent, respectively. A receiver operating characteristic curve is plotted to evaluate the performance of the model. The result shows that the area under the curve criterion is of the order of 69 per cent.

The paper highlights the fact that the Tunisian central bank obliged all commercial banks to conduct a survey study to collect qualitative data for better credit notation of the borrowers.

El riesgo de incumplimiento de préstamos o la evaluación del riesgo de crédito es importante para las instituciones financieras que otorgan préstamos a empresas e individuos. Existe el riesgo de que el pago de préstamos no se cumpla. Para entender los niveles de riesgo de los usuarios de crédito (corporaciones e individuos), los proveedores de crédito (banqueros) normalmente recogen gran cantidad de información sobre los prestatarios. Las técnicas analíticas predictivas estadísticas pueden utilizarse para analizar o determinar los niveles de riesgo involucrados en los préstamos. En este artículo abordamos la cuestión de la predicción por defecto de los préstamos a corto plazo para un banco comercial tunecino.

Utilizamos una base de datos de 924 archivos de créditos concedidos a empresas industriales tunecinas por un banco comercial en 2003, 2004, 2005 y 2006. El algoritmo bayesiano de clasificadores se llevó a cabo y los resultados muestran que la tasa de clasificación buena es del orden del 63.85%. La probabilidad de incumplimiento se explica por las variables que miden el capital de trabajo, el apalancamiento, la solvencia, la rentabilidad y los indicadores de flujo de efectivo.

Los resultados de la prueba de validación muestran que la buena tasa de clasificación es del orden de 58.66% ; sin embargo, los errores tipo I y II permanecen relativamente altos, siendo de 42.42% y 40.47%, respectivamente. Se traza una curva ROC para evaluar el rendimiento del modelo. El resultado muestra que el criterio de área bajo curva (AUC, por sus siglas en inglés) es del orden del 69%.

El documento destaca el hecho de que el Banco Central tunecino obligó a todas las entidades del sector llevar a cabo un estudio de encuesta para recopilar datos cualitativos para un mejor registro de crédito de los prestatarios.

Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.

Artículo de investigación