The global tourism industry has already suffered an enormous loss due to COVID-19 (Coronavirus Disease 2019) in 2020. Crisis management, including disaster management and risk management, has been becoming a hot topic for organisations in the hospitality and tourism industry. This study aims to investigate relevant research domains in the hospitality and tourism industry context. To understand how crisis management practices have been adopted in the industry, the authors reviewed 512 articles including 79 papers on COVID-19, spanning 36 years, between 1985 and 2020. The findings showed that the research focus of crisis management, crisis impact and recovery, as well as risk management, risk perception and disaster management dominated mainstream crisis management research. Look back the past decade (2010 to present), health-related crisis (including COVID-19), social media, political disturbances and terrorism themes are the biggest trends. This paper proposed a new conceptual framework for future research agenda of crisis management in the hospitality and tourism industry. Besides, ten possible further research areas were also suggested in a TCM (theory-context-method) model: the theories of crisis prevention and preparedness, risk communication, crisis management education and training, risk assessment, and crisis events in the contexts of COVID-19, data privacy in hospitality and tourism, political-related crisis events, digital media, and alternative analytical methods and approaches. In addition, specific research questions in these future research areas were also presented in this paper.
In the Yangtze River Economic Belt, climate variability significantly affects sectors such as agriculture, energy, and related industries, making accurate temperature forecasting essential. This study develops and compares Seasonal Autoregressive Integrated Moving Average (SARIMA) and Ornstein-Uhlenbeck (O-U) models using temperature data from 11 provincial-level regions spanning 2004–2023. After model evaluation, the more accurate forecasting model was selected to support the design of temperature-indexed weather derivatives via option pricing theory. Our findings reveal: (1) temperature series become stationary after first-order differencing, validating their suitability for time series modeling; (2) both SARIMA and O-U models produce predictions closely aligned with observed data; (3) SARIMA exhibits lower forecasting errors for cumulative cooling degree days (CDDs), confirmed through Monte Carlo simulations; and (4) option pricing results show that increased climate volatility raises derivative premiums, reflecting heightened climate risk.This research demonstrates the potential of weather derivatives as a risk mitigation tool in the Yangtze River Economic Belt, contributing to climate-resilient economic development.
Jaber B. Al Jaberi, Badr Bageri, Salaheldin Elkatatny
Abstract In high-density water-based drilling fluids, optimizing filtration behavior, filter cake characteristics, and rheological properties is essential for efficient and safe drilling operations. This study investigates the impact of perlite addition on these critical properties using three mud formulations with varying densities. Filtration tests were conducted using filter paper and ceramic disks, while rheological properties were evaluated using industry-standard models. Results revealed that increasing mud density leads to higher filtration volumes and thicker filter cakes, which potentially compromises wellbore stability and increasing the risk of pipe sticking. However, the incorporation of perlite significantly enhanced performance by reducing both filtration volume and filter cake thickness across all densities. Rheological models’ assessments illustrated that the perlite had minimal impact on plastic viscosity (PV) and yield point (YP), but a notable improvement in gel strength behavior, indicating better management of cuttings and entrapped air in drilling operations. Among the tested rheological models, the Herschel-Bulkley models offered the closest fluid behavior to the experimental data without and with the perlite addition. These findings highlight perlite’s potential as a valuable additive for enhancing water-based drilling fluids, enhancing operational efficiency and minimizing drilling complications. This study demonstrates perlite effectiveness as a primary additive in Micromax-weighted fluids, extending the operational density range and offering a practical, low-cost solution for HPHT conditions.
Construction contracts contain critical risk-related information that requires in-depth examination, yet tight schedules for bidding limit the possibility of comprehensive review of extensive documents manually. This research aims to develop models for automating the review of construction contracts to extract information on risk and responsibility that will provide inputs for risk management plans. Models were trained on 2268 sentences from International Federation of Consulting Engineers templates and tested on an actual construction project contract containing 1217 sentences. A taxonomy classified sentences into Heading, Definition, Obliga-tion, Risk, and Right categories with related parties of Contractor, Employer, and Shared. Twelve models employing diverse Natural Language Processing vectorization techniques and Machine Learning algorithms were implemented and benchmarked based on accuracy and F1 score. Binary classification of sentence types and an ensemble method integrating top models were further applied to improve performance. The best model achieved 89 % accuracy for sentence types and 83 % for related parties, demonstrating the capabilities of automated contract review for identification of risk and responsibilities. Adopting the proposed approach can significantly expedite contract reviews to support risk management activities, bid preparation processes and prevent disputes caused by overlooking risks and responsibilities.
The Landslide–Transport Interaction Corridor describes areas where road development and usage affect slope stability and are susceptible to disruption by landslide activity. Roads and highways traversing unstable slopes are not only vulnerable to damage, but also contribute to slope destabilization through built-up structures, surface runoff, excavation, and vibration. In the Nilgiris, the climatic and geological conditions of the Western Ghats predispose slopes to failure, while vehicle-induced vibrations and improper road construction further aggravate this risk. This study focuses on assessing ground conditions using a Multichannel Analysis of Surface Waves (MASW) and quantifying vehicle-induced vibrations through a vibration monitoring system. The results indicate the presence of substantial disintegrated materials as overburden covers in the region, making slopes more susceptible to saturation and allowing vibrations to propagate without attenuation. The findings from this study serve as an important factor in highlighting that prolonged vehicle-induced vibrations on landslide susceptible slopes can accelerate instability over time.
The construction industry has a significantly contribute to the economy of Sri Lanka. However, in recent years, its overall share of the national output has declined, primarily due to the impacts of the COVID-19 pandemic, political instability, and ongoing economic challenges. Many construction firms halted projects and laid off employees, highlighting the critical need for effective risk management during crises to predict and mitigate risks. This study explores emerging risk factors in Sri Lanka's construction sector post-crisis. Using a three-phase linear decision-making model, the research combines a literature review, a survey of 290 construction professionals, and structural equation modelling (SEM) to identify major risk factors across four phases of risk management. Key risks out of 23 include general factors like health and safety issues, material costs, regulations, political interference, corruption, and labor shortages, while phase-specific risks involve delays, budget overruns, payment delays, and cancellations. The study revises the risk registers to improve risk management strategies. While the findings are context-specific to Sri Lanka, they may offer indicative insights for other developing countries facing similar crisis-driven disruptions. The practical implications extend to multinational and local companies, supported by data from 22 countries, offering a comprehensive framework for addressing construction industry challenges in volatile environments. The novelty of this study lies in its use of theoretical triangulation to align Classical Risk Management theory with real-world operational risk factors, revealing critical overlaps, behavioral influences, and contextual gaps in traditional frameworks.
History of scholarship and learning. The humanities, Social sciences (General)
This study examines the variations in Land Surface Temperature (LST) and its correlation with urban, water, vegetation, and surface indices in the Siliguri Urban Agglomeration area in the Himalayan foothill region. The rapid urbanization of Siliguri, characterized by its diverse landscape and escalating economic activities, presents an opportunity to investigate the impacts of urban expansion on local climatic conditions. Utilizing remote sensing data and GIS technology, the study analyzes LST changes and correlates them with the Normalized Difference Built-up Index (NDBI), Normalized Difference Water Index (NDWI), and Normalized Difference Vegetation Index (NDVI). The findings reveal a significant increase in LST over the past decades, closely tied to the expansion of urban areas and the reduction in vegetation and water bodies. The study highlights a strong correlation between LST and NDBI, indicating the pronounced effect of urbanization on local temperature regimes. The inverse relationship between LST and NDVI/NDWI underscores the cooling influence of vegetative and aquatic surfaces. These insights are pivotal for urban planning and sustainable development in the Himalayan foothills, offering methodologies applicable to similar urbanizing regions. The research emphasizes integrating natural elements in urban landscapes to mitigate the urban heat island effect and adapt to climate change challenges.
Abstract Effective risk management is crucial in the construction industry, which has a substantial economic impact but is vulnerable to high financial risks due to volatile material costs and complex project-based financial structures. This study presents a new hybrid model to improve the prediction of financial distress for Taiwanese-listed construction companies. The research compares four boosting-based ensemble learning models, advanced deep learning models, and improved ensemble models that incorporate a novel approach using the Multi-Criteria Decision-Making (MCDM) technique, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to enhance feature selection. Experimental results show that while TOPSIS-eXtreme Gradient Boosting (TOPSIS-XGBoost) is highly effective at managing imbalanced financial datasets, Light Gradient Boosting Machine (LightGBM) performs better in balanced environments. Both models exhibit substantial performance gains when integrated with the Forensic-Based Investigation (FBI) optimization algorithm, resulting in the optimized hybrids—FBI-TOPSIS-XGBoost and FBI-LightGBM—which achieve marked improvements in predictive accuracy. These optimized models consistently outperform benchmark approaches, including the Altman Z-score, Zmijewski X-score, Logistic Regression, and Random Forest, across multiple evaluation metrics. To enhance transparency and interpretability, a global SHapley Additive exPlanations (SHAP) analysis was conducted, revealing that profitability and per-share index indicators are the primary determinants driving model predictions. Additionally, an expert system interface has been developed to enhance the practical usability of these models. These findings strengthen the methodological foundation for predicting financial distress and provide stakeholders with valuable tools for mitigating risk in Taiwan’s construction industry.
Computer engineering. Computer hardware, Information technology
As one of the modern enterprise management systems, the Occupational Health and Safety Management System (OHSMS) has garnered increasing attention. The OHSMS has undergone continuous refinement and expansion across various fields, emerging as a pivotal indicator of enterprise competitiveness. Currently, both the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) International and the China National Accreditation Service for Conformity Assessment (CNAS) require for establishing occupational health management related to laboratory animal work. However, within the domestic laboratory animal industry, development of OHSMS is relatively lagging behind due to unfamiliarity with laws and regulations and a lack of experienced management personnel. Consequently, the OHSMS in laboratory animal institutions is still in its early stage. Drawing on the authors' practical experience in establishing OHSMS in laboratory animal institutions, this article first outlines domestic and international occupational health laws, regulations, and safety management systems for laboratory animals, as well as common occupational diseases and their associated risk factors in China. Subsequently, this article highlights key elements for the construction of OHSMS in laboratory animal institutions in areas such as establishing occupational health and safety regulations, conducting training, performing occupational health examinations for staff, monitoring on-site occupational hazard factors, implementing the "three simultaneous" system for occupational disease prevention facilities in construction projects, creating and maintaining occupational health records, developing a notification management system for occupational hazards, and formulating emergency response plans for occupational disease hazard accidents. These points are intended as a reference for professionals in the industry.
Oluwaseun Adeola Bakare, Onoriode Reginald Aziza, Ngozi Samuel Uzougbo
et al.
The oil and gas industry operates in a complex and highly regulated environment where ethical considerations and legal compliance are paramount. This paper proposes an Ethical and Legal Project Management Framework specifically designed for the oil and gas sector, aiming to enhance project execution while ensuring adherence to ethical standards and legal requirements. The framework integrates ethical principles with legal obligations, fostering a culture of integrity and accountability within organizations. At its core, the framework emphasizes the identification and assessment of ethical risks throughout the project lifecycle. By incorporating ethical risk management into project planning and execution, organizations can proactively address potential ethical dilemmas, thus minimizing the risk of legal issues and reputational damage. Key components include stakeholder analysis, transparency in decision-making, and mechanisms for reporting unethical behavior. Legal compliance is another critical element of the framework. The oil and gas industry is subject to a myriad of local, national, and international regulations. The framework outlines best practices for ensuring compliance with environmental laws, labor regulations, and health and safety standards. This involves regular legal audits, staff training, and the establishment of compliance protocols to keep pace with evolving legal requirements. Furthermore, the framework highlights the importance of stakeholder engagement in promoting ethical and legal practices. Engaging with local communities, regulatory bodies, and internal stakeholders ensures that diverse perspectives are considered, enhancing decision-making processes and fostering trust. In addition, the integration of technology and data analytics plays a crucial role in supporting ethical and legal project management. By utilizing advanced tools for monitoring compliance and ethical conduct, organizations can enhance transparency and accountability. In conclusion, the Ethical and Legal Project Management Framework serves as a comprehensive guide for oil and gas companies striving to balance project efficiency with ethical integrity and legal compliance. By embedding these principles into their project management practices, organizations can achieve sustainable success in a challenging industry landscape. Keywords: Ethical Framework, Legal Compliance, Project Management, Oil and Gas Industry, Stakeholder Engagement, Risk Management.
Matej Vojtek, Soheyl Moradi, Davide Luciano De Luca
et al.
In this study, we aimed to assess the fluvial and pluvial flood hazard by a combination of basin and municipal scale assessment using an indicator-based approach, hydrologic-hydraulic modeling, and geographic information systems (GIS). The study area is represented by the Gidra River Basin and 12 municipalities. To calculate a composite flood hazard index (CFHI), we used two components: pluvial flood potential index (PFPI) and fluvial flood hazard index (FFHI). Altogether, five physical-geographical indicators and land use/land cover were used to calculate the PFPI. For determining the FFHI, we calculated three hydraulically modeled indicators for Q100: flood extent, average flow depth, and average flow velocity in each municipality. The most endangered municipalities in terms of the FFHI are located in the central and upper part of the basin while in case of the PFPI, the highest values were obtained by the municipalities located in the lower and central part of the basin. The highest values of CFHI were recorded in municipalities of Cífer, Budmerice, and Jablonec, which are in central part of the studied basin. Reliability of the calculated PFPI and FFHI was proven by the occurrence of past floods in the studied municipalities during the years 1996–2024.
Evaluating the resilience of the innovation ecosystem to maintain its performance, in the sense of resistance to disruption and recovery after it, has recently received more attention. Several studies have been conducted to model different ecosystems and evaluate their resilience. However, modeling the innovation ecosystem from a holistic perspective and performing a quantitative assessment of its resilience have received less attention. This paper models the innovation ecosystem holistically and evaluates its resilience index using a quantitative approach through five main steps. In the first step, a case study related to the innovation ecosystem of Iran's Ministry of Energy, called the Power Innovation Ecosystem, is modeled by combining system dynamics and agent-based modeling. Upon validating the model in the second step, the disruption of the loss of experts is investigated in the third step, and all possible actions to recover each actor are analyzed. In the fourth step, the performance of the ecosystem is simulated before and after the disruption using the data gathered in the previous steps. Finally, resilience is calculated in two different ways in the fifth step. Several improvement solutions are also suggested when considering that the resilience index of the innovation ecosystem is at a medium level. This research may assist policymakers in observing the resilience level of the innovation ecosystem based on the proposed model. By applying strategic changes to this model, they can determine the effects of their policies and make the most appropriate decisions to increase the resilience of the innovation ecosystem.
Herawati Herawati, Maria Kanan, Anwar Mallongi
et al.
Background: Water is a very important material for the life of creatures in nature and its function for life cannot be replaced by other compounds. Groundwater is an important resource for humans, especially in rural areas that depend on Groundwaters as the main source of clean water. However, the quality of groundwater in many areas has decreased due to pollution from human activities, such as agriculture and industry.
Method: This study aims to analyse the level of pollution risk of groundwaters in rural areas of Masama District, Banggai Regency using descriptive quantitative methods. Spatial analysis of pollution risk was conducted on 516 Groundwaters selected as samples. Spatial data is collected by recording the location of each well using GPS, which is then used to create a spatial map. The pollution risk analysis is based on the Sanitation Inspection results, using 11 key indicators.
Result: The results showed that 4 Groundwaters (0.78%) were in the very high pollution risk category, 115 Groundwaters (22.29%) were in the high-risk category, 204 Groundwaters (39.53%) were classified as medium risk, and 193 Groundwaters (37.40%) had low pollution risk. The results indicate that most Groundwaters in the study area are at moderate to high risk. Groundwaters with high and very high risk are dominated by Groundwaters located in Minang Andala, Purwo Agung and Kembang Merta villages, which are agricultural areas with sufficient area and most of the people have livestock around their homes which could potentially be a source of contaminants.
Conclusion: This study shows that the majority of Groundwaters in the study area have a moderate to high risk of pollution, with high and very high-risk categories found in villages that have agricultural and livestock activities. This emphasises the need for more intensive groundwater management and protection measures.
The MS6.8 earthquake occurred in Luding County, Ganzi Prefecture, Sichuan Province, China at 12:52 p.m. on Sept. 5, 2022, is preliminarily analyzed in terms of regional tectonics, historical earthquakes, sequence characteristics and focal mechanism solutions. The results show that: 1) The magnitude difference ΔM between the main shock and the maximum aftershock, the energy ratio ER of the main shock to the aftershocks, the p-value and the estimated Mmax-value indicate that the MS6.8 Luding earthquake sequence can be divided into the main shock-aftershock type (MAT). 2) The spatial distribution of the aftershocks, their corresponding b-value and expected maximum magnitude are obviously segmented, which reflect the complexity of the seismogenic tectonics. 3) According to the focal mechanisms obtained from the HASH program, the geometry distribution of the sequence, and the relationship between the sequence and the nearby faults, it can be inferred that the Moxi fault segment of the Xianshuihe fault zone is the seismogenic tectonics of the MS6.8 Luding earthquake sequence.
Engineering (General). Civil engineering (General), Risk in industry. Risk management
The pharmaceutical industry is the backbone of the healthcare system for any country. However, this industry faces various risks, which hamper its efficient working in providing life-saving medicines/services to the people. In this context, the purpose of the study is to improve the resilience and performance of the pharmaceutical industry (PI) with the identification, and assessment of supply chain (SC) risks. A case illustration has also been presented in the Indian context. The study utilizes an extensive literature survey and the Delphi method for identifying, finalizing, and classifying the risks into seven categories. The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) has been used to analyze and prioritize the risks to determine their criticality. The results show that the three most important risks are financial, supplier, and demand/customer/market. Within these risks, the three most critical sub-risks are found to be loss of customers, raw material (RM) issues, and bad reputation of the company, respectively. The study provides managers with an extensive list of PI risks for their consideration. The results also present the critical risks which need to be mitigated for enhanced performance and resilience of the industry. The study also emphasizes the importance of interconnection between various SC partners for better risk management.
The drivers of non-performing loans (NPL) and the possible effects of the institutional and business environments on the credit risk exposure of banks in the panel of BRICS countries and segregated models are analyzed in this paper. The purpose of the study is to identify the relationship between banking, macroeconomic and institutional factors of non-performing loans of banks at the BRICS level for the period 1996–2020. The panel ARDL approach is used for this purpose. The Panel Granger causality test is applied to verify the hypothesis of the relationship between economic development and NPLs. Panel co-integration tests examine the existence of a long-term link between the same two variables. The results of the study demonstrated that a decrease in the proportion of NPLs results from boosting performance metrics like the Z-score. Because the banking industry has more resources as a result of higher financial development and/or financial intermediation, the amount of NPLs is reduced. Finally, our study demonstrates how important the institutional environment is for raising the quality of bank credit. It was concluded that the low level of NPLs in BRICS countries was largely linked to more effective anti-corruption management, robust regulatory standards, increased application of the rule of law, freedom of speech and accountability.
In paper the empirical assessment of formation of innovative modes is presented to the industries. Relevance of research is caused by need of development of new tools of the analysis and stimulation of innovative development as industrial companies and national economy as a whole.Research objective – an assessment of the factors influencing innovative behavior of the company and allocation of innovative modes in the industry. Authors for the analysis of factors have used a method of the regression analysis of 627 Russian industrial companies given questioning, for allocation of innovative modes the clustering method is used with the help to – averages. In research factors are analysed: investments of the companies in researches and development, orientation to grocery and technological innovations, orientation to marketing innovations and creation of value, orientation to organizational and administrative innovations. Results of research show that in the Russian industrial sector it is possible to allocate innovative modes: “simulators”, “founders of valuable innovations”, “effective producers”, “technological innovators”, “radical innovators”. The “maturity levels” are developed for the allocated innovative modes depending on characteristics: opportunities the company independently to develop new products (services); improvement existing products, managements of researches and development, including coordination with external developers in network projects, strategic alliances, digital innovative platforms; generation and identification of new ideas; implementation of selection of ideas on the basis of the principles of compliance of strategy and their further development; identifications of new enterprise opportunities (studying of changes of environment and branch market, assessment of influence and identification of threats); providing a susceptibility to new technologies, a transfer of technologies; ensuring rationalization of system of production and management and commercial processes; improvement of operating technological processes; commercial use of objects of intellectual property. It is shown that the companies of higher level of an innovative mode make a bigger contribution to gross domestic product, create more workplaces and provide higher level of a salary, therefore development of the mechanism of stimulation of transition of the companies to more advanced level of an innovative mode is necessary.