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1 – 10 of over 1000Harkunti Pertiwi Rahayu, Louise K. Comfort, Richard Haigh, Dilanthi Amaratunga and Devina Khoirunnisa
This study aims to identify the gaps in current policy and propose a viable framework for policy improvement regarding people-centered tsunami early warning chain in Padang City…
Abstract
Purpose
This study aims to identify the gaps in current policy and propose a viable framework for policy improvement regarding people-centered tsunami early warning chain in Padang City. The objectives are: to describe the gaps and flaws in the current policy regarding local tsunami early warning chain, to identify potential actors to be involved in the tsunami early warning chain and to assess the roles and capacity of actors, and their potential for involvement in early warning.
Design/methodology/approach
This study is an exploratory study using social network analysis (SNA) on regulations and other legal documents, and primary data sources from a focus group discussion and semi-structured interviews.
Findings
The study found that the existed regulation lacks extension nodes to relay warnings to the populations at risk, often referred to as “the last mile.” Moreover, receiving warning information from both formal and informal sources is important to mobilize people evacuation more effectively during an emergency. The study found that mosque communities and disaster preparedness leaders are the potential actors who should be involved in the local early warning chain.
Practical implications
The research findings were presented as a recommendation to Padang City Government and have been legalized as the new tsunami early warning chain procedure in the Padang City Mayor Regulation 19/2018.
Originality/value
This research investigated local tsunami early warning dissemination in Padang City using SNA. The study demonstrates a close collaboration between researchers, practitioners and the community.
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Grace W.Y. Wang, Zhisen Yang, Di Zhang, Anqiang Huang and Zaili Yang
This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.
Abstract
Purpose
This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.
Design/methodology/approach
This paper proposes a bankruptcy prediction model by applying the hybrid of logistic regression and Bayesian probabilistic networks.
Findings
The proposed model shows its potential of contributing to a powerful tool to predict financial bankruptcy of shipping operators, and provides important insights to the maritime community as to what performance measures should be taken to ensure the shipping companies’ financial soundness under dynamic environments.
Research limitations/implications
The model and its associated variables can be expanded to include more factors for an in-depth analysis in future when the detailed information at firm level becomes available.
Practical implications
The results of this study can be implemented to oil tanker shipping firms as a prediction tool for bankruptcy rate.
Originality/value
Incorporating quantitative statistical measurement, the application of BN in financial risk management provides advantages to develop a powerful early warning system in shipping, which has unique characteristics such as capital intensive and mobile assets, possibly leading to catastrophic consequences.
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Xueyan Yang, Changxi Ma, Changfeng Zhu, Bo Qi, Fuquan Pan and Chengming Zhu
For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the…
Abstract
Purpose
For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.
Design/methodology/approach
The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.
Findings
By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.
Originality/value
Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
Propósito
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.
Diseño/metodología/enfoque
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.
Hallazgos
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%.
Originalidad/valor
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.
Palabras clave
Curva ROC, Evaluación de riesgos, Riesgo de incumplimiento, Sector bancario, Algoritmo clasificador bayesiano.
Tipo de artículo
Artículo de investigación
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Clement Moyo and Pierre Le Roux
The impact of financial reforms and financial development on an economy has received considerable attention over the recent past. This paper aims to investigate whether financial…
Abstract
Purpose
The impact of financial reforms and financial development on an economy has received considerable attention over the recent past. This paper aims to investigate whether financial liberalisation and financial development increase the likelihood financial crises in Southern African development community (SADC) countries.
Design/methodology/approach
Due to the binary nature of the dependent variable, the logit model is used for the analysis using data for the period 1990 to 2015.
Findings
The results showed that financial liberalisation captured by real interest rates reduces the likelihood of financial crises. Furthermore, regulatory quality strengthens this reductive effect of financial liberalisation on the probability of financial crises. On the other hand, financial development represented by bank credit increases the incidence of financial crises. The results also suggest that financial liberalisation may increase the likelihood of financial crises indirectly through financial development.
Research limitations/implications
The study recommends that a sound regulatory and supervisory framework be established as well as institutional quality raised to curb the effect of financial development on the incidence of financial crises.
Originality/value
There is scant evidence on the role that financial liberalisation and financial development play in the incidence of financial crises in the SADC. This study incorporates the effect of institutional quality in the analysis which has been neglected by most studies on financial reforms in SADC countries. A number of recent studies in SADC countries conclude that financial development resulting from financial reforms, may hinder economic growth. Therefore, this study sheds light on this negative relationship.
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Ivan Soukal, Jan Mačí, Gabriela Trnková, Libuse Svobodova, Martina Hedvičáková, Eva Hamplova, Petra Maresova and Frank Lefley
The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest…
Abstract
Purpose
The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.
Design/methodology/approach
The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.
Findings
This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.
Research limitations/implications
The authors identify several gaps in the literature which this research does not address but could be the focus of future research.
Practical implications
The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.
Social implications
Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.
Originality/value
To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.
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Abderahman Rejeb, Karim Rejeb, Andrea Appolloni and Stefan Seuring
The literature on public procurement (PP) has increased significantly in recent years, and, to date, several reviews have been conducted to study this relevant subject…
Abstract
Purpose
The literature on public procurement (PP) has increased significantly in recent years, and, to date, several reviews have been conducted to study this relevant subject. Nevertheless, a bibliometric analysis of the PP knowledge domain is still missing. To fill this knowledge gap, a bibliometric review is carried out to investigate the current state of PP research.
Design/methodology/approach
A total of 640 journal articles are selected from the Scopus database for the final analysis. The performance indicators of the literature are identified and explained through bibliometric analysis. Furthermore, the conceptual and intellectual structures are studied through a keyword co-occurrence network and bibliographic coupling.
Findings
The results of the review indicate that PP research has increased significantly in recent years. The top ten most productive journals, countries, authors and academic institutions are identified. The findings from the keyword co-occurrence network reveal six main research themes including innovation, corruption and green public procurement (GPP). By applying bibliographic coupling, the focus of PP research revolves around seven thematic areas: GPP, corruption, the role of small and medium-sized enterprises (SMEs) in PP, electronic PP, innovation, labour standards and service acquisition. The research potential of each thematic area is evaluated using a model based on maturity and recent attention (RA).
Originality/value
To the best of the authors' knowledge, this is the first study to successfully organise, synthesise and quantitatively analyse the development of the PP domain amongst a large number of publications on a large time scale.
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With increasing marine resource development, the rapid development of the marine economy, and the continuous decline of the marine natural resource system, the contradiction…
Abstract
Purpose
With increasing marine resource development, the rapid development of the marine economy, and the continuous decline of the marine natural resource system, the contradiction between marine resources and economic development is becoming increasingly acute. The study of marine resources and economic development has become a hot and challenging issue in marine resource economics research in recent years. The purpose of this study is to analyze the current situation of marine resources and to realize the sustainable use of marine resources.
Design/methodology/approach
This study systematically reviews and analyzes the current status of research on marine resources and economic development issues in four main aspects: marine resource management, marine resources and economic growth, marine resources and economic security, and marine resource accounting in the field of marine resource economics.
Findings
It is found that compared to the current status of research on land-based resources and economic development, there is a significant lag in both theoretical construction and methodological innovation in marine resources and economic development.
Originality/value
The purpose of this study is to systematically grasp the current status of marine resources research, promote the coordinated development of marine resources and economic growth, and then realize the safe and sustainable development and utilization of marine resources.
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Gayatri Panda, Manoj Kumar Dash, Ashutosh Samadhiya, Anil Kumar and Eyob Mulat-weldemeskel
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore…
Abstract
Purpose
Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.
Design/methodology/approach
The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.
Findings
The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.
Research limitations/implications
The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.
Originality/value
The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.
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Jessica Paule-Vianez, Milagros Gutiérrez-Fernández and José Luis Coca-Pérez
The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.
Abstract
Purpose
The purpose of this study is to construct the first short-term financial distress prediction model for the Spanish banking sector.
Design/methodology/approach
The concept of financial distress covers a range of different types of financial problems, in addition to bankruptcy, which is not common in the sector. The methodology used to predict financial problems was artificial neural networks using traditional financial variables according to the capital, assets, management, earnings, liquidity and sensibility system, as well as a series of macroeconomic variables, the impact of which has been proven in a number of studies.
Findings
The results obtained show that artificial neural networks are a highly suitable method for studying financial distress in Spanish credit institutions and for predicting all cases in which an entity has short-term financial problems.
Originality/value
This is the first work that tries to build a model of artificial neural networks to predict the financial distress in the Spanish banking system, grouping under the concept of financial distress, apart from bankruptcy, other financial problems that affect the viability of these entities.
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