Search results

1 – 10 of over 2000
Article
Publication date: 23 September 2022

Miaomiao Chen, Lu An, Gang Li and Chuanming Yu

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public…

Abstract

Purpose

The purpose of the study is to evaluate the severity of public events in real time from the perspective of social media and to construct the early warning mechanism of public events.

Design/methodology/approach

This study constructed the severity assessment system of public events from the dimensions of the netizens' role, the Internet media's role, the spread of public events and the attitudes and feelings of netizens. The method of analyzing the influence tendency of the public event severity indicators was proposed. A total of 1,107,308 microblogging entries regarding four public events were investigated. The severity of public events was divided into four levels.

Findings

It is found that serious public events have higher indicator values than medium level events on the microblogging platform. A quantitative severity classification standard for public events was established and the early warning mechanism of public events was built.

Research limitations/implications

Microblogging and other social media platforms provide rich clues for the real-time study and judgment of public events. This study only investigated the Weibo platform as the data source. Other social media platforms can also be considered in future.

Originality/value

Different from the ex-post evaluation method of judging the severity of public events based on their physical loss, this study constructed a quantitative method to dynamically determine the severity of public events according to the clues reflected by social media. The results can help the emergency management departments judge the severity of public events objectively and reduce the subjective negligence and misjudgment.

Details

Information Technology & People, vol. 36 no. 6
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 4 January 2022

Indrajit Pal, Subhajit Ghosh, Itesh Dash and Anirban Mukhopadhyay

This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic…

Abstract

Purpose

This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region.

Design/methodology/approach

Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience.

Findings

The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures.

Originality/value

The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

Details

International Journal of Disaster Resilience in the Built Environment, vol. 14 no. 5
Type: Research Article
ISSN: 1759-5908

Keywords

Article
Publication date: 16 February 2022

Zeeshan Aziz, Ebrahim Alzaabi and Mohamad Syazli Fathi

This paper aims to develop a crisis readiness framework for road traffic crisis response for law enforcement agencies in the United Arab Emirates (UAE).

Abstract

Purpose

This paper aims to develop a crisis readiness framework for road traffic crisis response for law enforcement agencies in the United Arab Emirates (UAE).

Design/methodology/approach

A Delphi method was used that combined questionnaire-based survey and the analytical hierarchy process to collect quantitative and qualitative data from an expert panel of crisis readiness professionals on how they prioritise and weigh the different strategic criteria, sub-criteria and performance indicators in the context of law enforcement agencies’ traffic response.

Findings

The findings of this paper resulted in the identification, ranking and validation of ten key dimensions of crisis readiness clustered into three distinct sets of priority rankings: response planning, resources, training and coordination; information management and communication and risk and hazard assessment; and early warning, legal and institutional frameworks, recovery initiation and property protection. The results additionally established the relative priority of sub-criteria for each criterion and validated a broad set of key performance indicators (KPIs) for the top six ranked criteria.

Research limitations/implications

The findings are based on a single case study focused on a specific area of operation within crisis response and one group of organisations of the UAE police sector. This potentially places a constraint on the wider generalisation of the findings to different operational areas and agencies, as they may have different priorities or organisational conditions that have implications for the framework application and the relative importance of certain criteria and sub-criteria.

Practical implications

This paper provides strategic guidance in the form of a prioritised list of criteria, sub-criteria and KPIs that can direct efforts to optimise different dimensions of crisis readiness at a strategic and operational level.

Originality/value

This paper makes an original contribution in identifying the key criteria and performance indicators of crisis readiness for road traffic situations. The findings contribute a comprehensive strategic readiness framework that supports planning and decision-making for the development of organisational capacities that can enhance response times of police to road traffic crises. This framework ranks dimensions of crisis readiness and key sub-criteria in order of priority and validates the key components of crisis readiness that can support practitioners to structure, standardise and benchmark key processes and elements of crisis response.

Details

Journal of Financial Management of Property and Construction , vol. 28 no. 2
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 19 March 2024

Thao-Trang Huynh-Cam, Long-Sheng Chen and Tzu-Chuen Lu

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct…

Abstract

Purpose

This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability.

Design/methodology/approach

The real-world samples comprised the enrolled records of 2,412 first-year students of a private university (UNI) in Taiwan. This work utilized decision trees (DT), multilayer perceptron (MLP) and logistic regression (LR) algorithms for constructing EPMs; under-sampling, random oversampling and synthetic minority over sampling technique (SMOTE) methods for solving data imbalance problems; accuracy, precision, recall, F1-score, receiver operator characteristic (ROC) curve and area under ROC curve (AUC) for evaluating constructed EPMs.

Findings

DT outperformed MLP and LR with accuracy (97.59%), precision (98%), recall (97%), F1_score (97%), and ROC-AUC (98%). The top-ranking factors comprised “student loan,” “dad occupations,” “mom educational level,” “department,” “mom occupations,” “admission type,” “school fee waiver” and “main sources of living.”

Practical implications

This work only used enrollment information to identify dropout students and crucial factors associated with dropout probability as soon as students enter universities. The extracted rules could be utilized to enhance student retention.

Originality/value

Although first-year student dropouts have gained non-stop attention from researchers in educational practices and theories worldwide, diverse previous studies utilized while-and/or post-semester factors, and/or questionnaires for predicting. These methods failed to offer universities early warning systems (EWS) and/or assist them in providing in-time assistance to dropouts, who face economic difficulties. This work provided universities with an EWS and extracted rules for early dropout prevention and intervention.

Details

Journal of Applied Research in Higher Education, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-7003

Keywords

Article
Publication date: 10 October 2023

Guangping Liu, Kexin Zhou and Xiangzheng Sun

The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of…

Abstract

Purpose

The aim of this study is to analyze the influence mechanism of real estate enterprises' status on debt default risk and explore the heterogeneity effect of the characteristics of enterprises.

Design/methodology/approach

Against the background of the “three red lines” regulation of the financing of real estate enterprises and the COVID-19 pandemic, the authors select 123 real estate enterprises listed on China's Shanghai and Shenzhen A-shares markets from the first quarter of 2021 to the second quarter of 2022 as a research sample. The social network analysis method and Z-score financial risk early warning model are used to measure real estate enterprises' status and debt default risk. The authors construct a panel regression model to analyze how the status of real estate enterprises influences their debt default risk.

Findings

The results show that the status of real estate enterprises negatively and significantly affects their debt default risk. Economic policy uncertainty and financing constraints play negative moderating and mediating roles, respectively. Further research has found that the effect of real estate enterprises' status on debt default risk is characterized by heterogeneity in equity characteristics, i.e. it is significant in the sample of nonstate-owned enterprises but not in the sample of state-owned enterprises.

Practical implications

It is helpful for real estate enterprises to attach importance to the value of social networks, and the authors provide policy suggestions for real estate enterprises to constantly improve their risk management systems.

Originality/value

Using economic policy uncertainty as the moderating variable and financing constraints as the mediating variable, the authors analyze how the status of real estate enterprises influences debt default risk, which contributes to a better understanding of the formation of the debt default risk of real estate enterprises.

Details

Journal of Property Investment & Finance, vol. 42 no. 1
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 23 November 2023

Sirine Ben Yaala and Jamel Eddine Henchiri

This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events…

28

Abstract

Purpose

This study aims to predict stock market crashes identified by the CMAX approach (current index level relative to historical maximum) during periods of global and local events, namely the subprime crisis of 2008, the political and social instability of 2011 and the COVID-19 pandemic.

Design/methodology/approach

Over the period 2004–2020, a log-periodic power law model (LPPL) has been employed which describes the price dynamics preceding the beginning dates of the crisis. In order to adjust the LPPL model, the Global Search algorithm was developed using the “fmincon” function.

Findings

By minimizing the sum of square errors between the observed logarithmic indices and the LPPL predicted values, the authors find that the estimated parameters satisfy all the constraints imposed in the literature. Moreover, the adjustment line of the LPPL models to the logarithms of the indices closely corresponds to the observed trend of the logarithms of the indices, which was overall bullish before the crashes. The most predicted dates correspond to the start dates of the stock market crashes identified by the CMAX approach. Therefore, the forecasted stock market crashes are the results of the bursting of speculative bubbles and, consequently, of the price deviation from their fundamental values.

Practical implications

The adoption of the LPPL model might be very beneficial for financial market participants in reducing their financial crash risk exposure and managing their equity portfolio risk.

Originality/value

This study differs from previous research in several ways. First of all, to the best of the authors' knowledge, the authors' paper is among the first to show stock market crises detection and prediction, specifically in African countries, since they generate recessionary economic and social dynamics on a large extent and on multiple regional and global scales. Second, in this manuscript, the authors employ the LPPL model, which can expect the most probable day of the beginning of the crash by analyzing excessive stock price volatility.

Details

African Journal of Economic and Management Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-0705

Keywords

Article
Publication date: 18 January 2022

Runhui Lin, Lun Wang, Biting Li, Yanhong Lu, Zhiqiang Qi and Linyu Xie

Blockchain is a technical solution integrating multiple technologies, with the potential to overcome the drawbacks of organizational governance. Given the emergence and prevalence…

Abstract

Purpose

Blockchain is a technical solution integrating multiple technologies, with the potential to overcome the drawbacks of organizational governance. Given the emergence and prevalence of blockchain, its importance for organizational governance has progressively increased. Therefore, this study aims to analyze how blockchain restructure organizational governance.

Design/methodology/approach

This study presents a structured systematic literature review of blockchain-enabled applications across diverse organizational governance models and several case studies to illustrate them. Based on the above analysis, governance mechanisms, transaction upgrading and challenges are proposed.

Findings

Based on the literature review and typical applications, the authors summarize the advances in the research on the theoretical and practical applications of blockchain in organizational governance. We also identify the influence mechanisms of organizational governance and investigate transaction upgrading based on blockchain. Finally, the authors discuss three types of challenges (i.e. administrative, technical and environmental) to the relationship between blockchain and organizational governance. Along with the development of blockchain applications, the impact of blockchain on organizational governance has progressed in both theory and practice. Therefore, these findings will have significant implications for both academics and practitioners.

Originality/value

This paper makes three key theoretical contributions: we review the literature on the impact of blockchain on organizational governance and present typical cases to illustrate it; propose four governance mechanisms for the application of blockchain in organizational governance; and propose an innovating-and-matching-oriented model of transaction upgrading based on blockchain.

Details

Nankai Business Review International, vol. 14 no. 2
Type: Research Article
ISSN: 2040-8749

Keywords

Article
Publication date: 12 September 2023

Norfaizah Othman, Mariani Abdul-Majid and Aisyah Abdul-Rahman

This paper aims to determine the effect of equity financing on bank stability during normal and crisis periods.

Abstract

Purpose

This paper aims to determine the effect of equity financing on bank stability during normal and crisis periods.

Design/methodology/approach

This study uses a static panel regression that includes pooled ordinary least square, random effect and fixed effect model to examine the influence of equity financing on bank stability. In estimating bank stability during a financial crisis, the authors predict the occurrence of a crisis using the early warning system (EWS). The authors then used z-score to measure Islamic banks’ stability.

Findings

Islamic banks that offer equity financing structure are more stable compared to Islamic banks without such structure. Islamic banks with medium equity financing have highest stability relative to Islamic banks with high or low equity financing. During crises, the Islamic banks with equity financing structure remain relatively stable compared to other Islamic banks.

Research limitations/implications

The sampling coverage could have included a larger number of countries and banks.

Practical implications

The authorities need to strengthen the banking framework to support the Islamic financial products by encouraging a wider use of risk-sharing instruments. Besides using a debt-like financing structure, Islamic banks should also place emphasis on equity financing in instilling the banking sector stability. In monitoring banks with equity financing, the authorities may need to look into the level of equity financing.

Social implications

Besides avoiding riba and gharar in financing, equity financing encourages cooperation and participation among society as they share the risks.

Originality/value

This paper analyses the effect of equity financing on the Islamic banks stability during normal and crisis periods. This paper further examines the intensity of the equity financing and its influence on bank stability.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. 16 no. 6
Type: Research Article
ISSN: 1753-8394

Keywords

Article
Publication date: 10 July 2023

Yuzhen Long, Chunli Yang, Xiangchun Li, Weidong Lu, Qi Zhang and Jiaxing Gao

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to…

Abstract

Purpose

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

Design/methodology/approach

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

Findings

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

Originality/value

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

Details

International Journal of Energy Sector Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 25 December 2023

Isaac Akomea-Frimpong, Jacinta Rejoice Ama Delali Dzagli, Kenneth Eluerkeh, Franklina Boakyewaa Bonsu, Sabastina Opoku-Brafi, Samuel Gyimah, Nana Ama Sika Asuming, David Wireko Atibila and Augustine Senanu Kukah

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of…

Abstract

Purpose

Recent United Nations Climate Change Conferences recognise extreme climate change of heatwaves, floods and droughts as threatening risks to the resilience and success of public–private partnership (PPP) infrastructure projects. Such conferences together with available project reports and empirical studies recommend project managers and practitioners to adopt smart technologies and develop robust measures to tackle climate risk exposure. Comparatively, artificial intelligence (AI) risk management tools are better to mitigate climate risk, but it has been inadequately explored in the PPP sector. Thus, this study aims to explore the tools and roles of AI in climate risk management of PPP infrastructure projects.

Design/methodology/approach

Systematically, this study compiles and analyses 36 peer-reviewed journal articles sourced from Scopus, Web of Science, Google Scholar and PubMed.

Findings

The results demonstrate deep learning, building information modelling, robotic automations, remote sensors and fuzzy logic as major key AI-based risk models (tools) for PPP infrastructures. The roles of AI in climate risk management of PPPs include risk detection, analysis, controls and prediction.

Research limitations/implications

For researchers, the findings provide relevant guide for further investigations into AI and climate risks within the PPP research domain.

Practical implications

This article highlights the AI tools in mitigating climate crisis in PPP infrastructure management.

Originality/value

This article provides strong arguments for the utilisation of AI in understanding and managing numerous challenges related to climate change in PPP infrastructure projects.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

1 – 10 of over 2000