Sustainable Risk Research Articles

From policy to progress: do female parliamentarians influence energy justice?

ABSTRACT Women parliamentarians have been playing an increasingly important role in shaping climate policy and advocating for energy justice in recent years. As lawmakers, they have a unique opportunity to influence policy decisions and prioritize sustainable practices that can mitigate the effects of climate change. Additionally, women parliamentarians bring a unique perspective to the table, often championing issues that directly impact women, children, and marginalized communities who are disproportionately affected by climate change and energy injustices. As the composition of parliamentarians becomes more diversified with the increasing representation of women, it is crucial to investigate whether female parliamentarians influence energy justice. Based on the theory of ecofeminism, which suggests that women are relatively more concerned with environmental sustainability and environmental risks than men, this study tests the hypothesis that women parliamentarians are more likely to take action in favour of energy justice. Specifically, this paper aims to examine the causal effect of female parliamentarians in promoting energy justice in a panel of 62 countries. The study proposes three sub-indicators of energy justice namely distributive justice, procedural justice, and restorative justice. Using the two-stage instrumental variable approach, we isolate the effect of female parliamentarians and find that it is a driver of energy justice. The results of a mediation analysis highlight the role of democracy and human capital as transmission channels, explaining the indirect effect of female parliamentarians on energy justice. The study's conclusions therefore highlight the importance of supporting and empowering women parliamentarians in their efforts to combat climate change and energy injustice.

DMI fungicide resistance in Zymoseptoria tritici is unlinked to geographical origin and genetic background: a case study in Europe.

The hemibiotrophic fungus Zymoseptoria tritici causing Septoria tritici blotch (STB), is a devastating foliar pathogen of wheat worldwide. A common group of fungicides used to control STB are the demethylation inhibitors (DMIs). DMI fungicides restrict fungal growth by inhibiting the sterol 14-α-demethylase, a protein encoded by CYP51 gene and essential for maintaining fungal cell permeability. However, the adaptation of Z. tritici populations in response to intensive and prolonged DMI usage has resulted in a gradual shift towards reduced sensitivity to this group of fungicides. In this study, 311 isolates were collected pre-treatment from nine wheat-growing regions in Europe in 2019. These isolates were analysed by high-throughput amplicon-based sequencing of nine housekeeping genes and the CYP51 gene. Analyses based on housekeeping genes and the CYP51 gene revealed a lack of population structure in Z. tritici samples irrespective of geographical origin. Minimum spanning network (MSN) analysis showed clustering of multilocus genotypes (MLGs) based on CYP51 haplotypes, indicating an effect of selection due to DMI fungicide use. The majority of the haplotypes identified in this study have been reported previously. The diversity and frequencies of mutations varied across regions. Using a high-throughput amplicon-sequencing approach, we found several mutations in the CYP51 gene combined in different haplotypes that are likely to cause fungicide resistance. These mutations occurred irrespective of genetic background or geographical origin. Overall, these results contribute to the development of effective and sustainable risk monitoring for DMI fungicide resistance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Navigating Urban Risks for Sustainability: A Comprehensive Evaluation of Urban Vulnerability Based on a Pressure–Sensitivity–Resilience Framework

Cities are important symbols of civilization in human society. The vulnerability to cities caused by human activities and natural disasters has become increasingly evident. How to reduce the vulnerability of cities is an important topic in the research of urban public safety and sustainable development. In this study, a comprehensive evaluation of urban vulnerability is conducted on the basis of the pressure–sensitivity–resilience framework from a complex systems perspective, integrating three subsystems—the resource–environment, economic, and social subsystems. On the basis of data from 18 cities in Sichuan Province, China, from 2006 to 2021, this study analyzes vulnerability in terms of its scores, spatial and temporal evolution, and obstacles. The results reveal that the overall vulnerability of the Sichuan Basin has shown a fluctuating downward trend over the past sixteen years, and the spatial distribution has evolved into a large “low-vulnerability” agglomeration. The obstacles affecting urban vulnerability are also changing dynamically and include factors such as the harmless treatment rate of household waste and industrial smoke dust emissions. Drawing from these insights, this study enables the identification and diagnosis of urban vulnerability and, further, provides city managers with tailored recommendations for crafting policies that aim to mitigate risks and promote sustainable development.

FORMATION OF STRATEGIC DIRECTIONS FOR THE USE OF ARTIFICIAL INTELLIGENCE IN THE ENTERPRISE TO ACHIEVE THE GOALS OF SUSTAINABLE DEVELOPMENT

Rapid artificial intelligence (AI) development opens new opportunities for enterprises to achieve sustainable development goals. This article summarizes the research results of applying AI to optimize production processes, reduce environmental impact, increase productivity, and strengthen social responsibility. The article aims to highlight the potential of AI for achieving enterprises' sustainable development goals and identify effective strategies for its application to increase economic efficiency, social responsibility, and environmental sustainability. A qualitative analysis of statistical data, official regulatory documents, books, and articles from accredited journals was used to achieve the goal. The obtained results showed that AI could be used to analyze production processes and forecast the demand for raw materials, optimize supply chains and reduce energy consumption, identify potential sustainability risks and develop strategies to prevent them, identify defects in production and control product quality in real-time, create personalized services and products for customers. The study highlights the importance of AI's ethical and safe use to ensure its positive impact on society and the environment. The practical value of the article lies in the systematic review of studies on the effects of AI on the sustainable development of enterprises. The obtained results can be used to improve production processes, increase enterprises' competitiveness, and promote sustainable development.

Can ESG Disclosure Stimulate Corporations’ Sustainable Green Innovation Efforts? Evidence from China

The Environmental, Social, and Governance (ESG) Composite Rating denotes corporations’ capability for supporting sustainable development activities, social responsibility, and transparent and ethical governance. It aims to inform investors and stakeholders about the company’s sustainability and social responsibility risks. ESG has increasingly become an informal yet significant driving force in promoting sustainable green innovation within the diversified co-governance environmental management system. This paper examines the dynamic relationship between ESG performance and sustainable green innovation practices in Chinese A-share listed companies from 2011 to 2022. The results show a positive correlation between ESG performance and the level of corporate sustainable green innovation. They also validate the moderating roles of informal external pressure and internal development demands. While the moderating effect of public environmental concern (PEC) is not significant, corporate digital transformation (CDT) significantly and positively moderates the relationship between ESG performance and sustainable green innovation. These findings offer policymakers and corporations a means to formulate a framework to shape the conduct of corporations to meet the market’s green development needs and to establish instruments that promote green innovation.

Tracking Workplace Violence over 20 Years

Introduction. Violence against healthcare workers (HCWs) is a widespread, underreported, and inadequately prevented problem. Only a few companies have efficient systems for assessing the extent of the phenomenon. Methods. In 2005, the health surveillance service of a public health company introduced a system that monitored violence experienced by HCWs by means of three items from the Violent Incident Form (VIF) integrated with departmental in-depth analyses using the participatory ergonomics group technique. Results. In 2005, the annual rate of physical assaults was 8.2%, that of threats was 12.0%, and the harassment rate was 19.6%. Over the past twenty years of observation (2005–2024), the percentage of workers who reported experiencing a physical attack in the previous year at their periodic medical examination has fluctuated between 5.8% and 11.1%, except for the years 2020 and 2021 when, during the COVID-19 pandemic, the rate was 3.9% and 3.2%, respectively. During the same pandemic period, the annual threat rate, which ranged from 9.4% to 20.1%, dropped to 7.7%, while the prevalence of harassment, which was between 13.5 and 19.6, fell to 7.2%. HCWs believe that (i) limiting visitor access, (ii) a better balance of the demand for services, and (iii) a better attitude towards HCWs were the causes of the reduced rate of violence during the pandemic. Conclusions. Recording the violence experienced during health surveillance is an economical, reliable, and sustainable risk assessment method.

Measuring The Pulse of Sustainable Investment: A Systematic Review & Bibliometric Perspective

In recent times, increasing regulatory pressure and changes in investor preferences have led to an increase in the importance of sustainable investment at both academic and practitioner levels, with the field still occupying the formative stage. Therefore, the objectives of this study are to explore the intellectual underpinnings of and suggest future research avenues in the discipline of sustainable investment, as well as to conduct a systematic review and bibliometric analysis. In total 1,222 articles were selected from the Scopus database for the period 2013-2023. The study follows the SPAR-4-SLR protocol, involving performance analysis and science mapping using VOSviewer and the R-package. Network analysis revealed eight major clusters primarily focusing on firms’ financial performance, stock returns, contributions to climate change, economic growth, sustainable development goals, risk assessment, and corporate social responsibility. Additionally, the study developed a unified taxonomy model based on a causal framework that includes the foremost independent, mediating, moderating, and dependent variables, studied in the field of sustainable investment.

Management accounting practices going sustainable: the move toward sustainable risk management in ASEAN developing economies

Purpose The purpose of this study will be to provide a comprehensive perspective on sustainable risk management (SRM) with internal components within enterprises. Particularly, this study aims to explore how sustainable management accounting practices mediate the influence of both risk-taking tendency (RTT) and sustainable core values on SRM. Additionally, it also examines the moderating influence of the RTT on the link between sustainable management accounting practices and SRM, as a mediated moderating model. Design/methodology/approach The study hypotheses have been appraised using partial least squares structural equation modeling with observed information from 495 sizeable listed enterprises in ASEAN developing economies, comprising Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam. Findings The findings have been as follows: (1) The RTT favorably influences sustainable management accounting practices (SMAPs), which, in turn, affects SRM; (2) Sustainable core values favorably affect SMAPs, which, in turn, affect SRM; (3) It can be specified that SMAPs mediate the influence of both RTT and sustainable core values on SRM; (4) When the RTT is strong, the influence of SMAPs on SRM has been enlarged. Originality/value The findings of this study demonstrate how the interaction between RTT and SMAPs can benefit to the success of large enterprises that use risk management systems in emerging economics. Furthermore, the present paper interprets the mechanism by which SMAPs influence SRM.

Exploring Expert Insights on Early Years Risk and Protective Factors for Long-term Marital Sustainability

Exploring Expert Insights on Early Years Risk and Protective Factors for Long-term Marital Sustainability

Social network, sustainable livelihood capital and risk response: an empirical analysis of rural China

ABSTRACT In rural China, farmers who have been “lifted out of poverty” still at risk of returning to poverty. The sustainable livelihood and risk coping ability of farmers are of great significance for rural development, and social networks have a distinctive effect on livelihood and risk coping ability of farmers. Based on full-coverage survey in a village, this paper adopts the entropy weight method, Social Network Analysis, and aims to build a social network model and reveal the impact of social networks on farmer’s livelihood and risk coping ability. The results show that the farmers’ livelihood capital based on social network has a significant amplification. Furthermore, social relationships can directly affect farmers’ ability to cope with livelihood risks. And, for farmers with higher social, information, human and financial capital, the effectiveness of social networks in enhancing their risk coping capacity is more significant. Overall, it is suggested that more attention should be paid to the positive role of social networks on the livelihood in the future. For rural development, social relationship networks should be continuously enriched and to strengthen its multiplier effect on farmers’ livelihood. And for farmer development, it should take measures to improve the mobilising capacity of social relations. And to amplify the effectiveness of various types of livelihood capital in risk response.

Community-Based Disaster Insurance for Sustainable Economic Loss Risk Mitigation: A Systematic Literature Review

This systematic literature review (SLR) explores the role of community-based catastrophe insurance (CBCI) as a tool for sustainable economic loss risk mitigation. Utilizing bibliometric analysis and a literature review, this study aims to reveal the methods employed in CBCI schemes from a novel perspective, highlighting their effectiveness in mitigating catastrophe risks. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was employed to systematically collect and analyze articles sourced from the Scopus, ScienceDirect, and Dimensions databases. The findings provide a comprehensive summary of the CBCI implementation, including various considerations such as risk-sharing mechanisms, premium determination, and policy frameworks. This research offers a fresh perspective on CBCI as a sustainable approach to catastrophe risk mitigation, contributing valuable insights to policymakers, practitioners, and researchers interested in community resilience and disaster risk management.

SUPPLY CHAIN RISK MANAGEMENT: STRATEGIC SOLUTIONS FOR REDUCING TRANSPORTATION AND LOGISTICS RISKS

This study investigates strategic approaches to mitigating risks in transportation and logistics within global supply chains, focusing on the integration of advanced technologies, flexibility, collaboration, and sustainability. By employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the study systematically reviews 37 key articles to provide a comprehensive understanding of modern risk management practices. The findings reveal the increasing reliance on technologies such as predictive analytics, the Internet of Things (IoT), and blockchain for enhancing visibility, monitoring, and decision-making. Flexibility in logistics networks, including alternative sourcing and diversified transportation routes, emerged as crucial for mitigating disruptions, while collaboration among supply chain partners, particularly through real-time information sharing, significantly reduces risk exposure. Additionally, the study highlights the growing integration of sustainability into risk management, addressing climate change and environmental risks. This research underscores the need for proactive, adaptable, and sustainable risk management strategies to maintain supply chain resilience in the face of evolving global challenges.

Utilising machine learning for corporate social responsibility (CSR) and environmental, social, and governance (ESG) evaluation: Transitioning from committees to climate

Transparency and accountability are critical components of corporate sustainability. This study uses machine learning and empirical analysis to examine the influence of corporate social responsibility (CSR) committees and environmental, social, and governance (ESG) initiatives on corporate sustainability. Using 2017–2021 Bloomberg Terminal data, we investigated the environmental footprints, disclosure practices, risk profiles, and ESG fund commitments of Fortune 500 companies. Key findings indicate that CSR committees positively impact environmental performance, with an increase in environmental responsibility over time. Policy implications highlight the necessity for collaboration to prioritize environmental sustainability and address climate risk disclosure auditing within the audit profession.

A Novel Framework to Evaluate the Effect of Strategic Systems Thinking on Sustainable Supply Chain Risks, LARG Capabilities and Performance

Supply chain (SC) disruptions created due to sustainable, social, economic, environmental and technical risks are mitigated by lean, agile, resilient and green (LARG) capabilities across the SC node. This study aims at the assessment and alignment of SC risks and capabilities for a strategic fit of appropriate practices resulting in performance, efficiency and continuity of operations. The novelty of this research work is the investigation of the direct and mediating effects of strategic system thinking (SST) between SC risks, capabilities and performance. A survey comprising of 78 items was administered to 255 managers of Pakistan automotive SC industries. The exploratory factor analysis and confirmatory factor analysis were executed to identify the valid constructs along with their reliability and validity. The structural equation modeling (SEM) was used to test the conceptual model by establishing the second order constructs. SEM results indicated only technical risks having negative significant effect with performance. In terms of capabilities, the general, efficiency, integration as well as the redundant resources were found to have significant association with SC performance. The SST approach was found to be significantly associated with technical risks and capabilities such as general, recovery and redundancy. The hypothesis of SST as a mediating variable across all factors was not observed to be valid in this research. This study can help in the policy and decision-making as well as strategic assessment, planning, development, positioning and alignment of resources across the sustainable SC. The operations can be influenced positively through system integration and conservation of resources for a sustainable performance. The green, environmental and social risks had higher SC impact and need to be focused upon in Pakistan automotive SC for higher performance and sustainability.

Coastal urban flood risk management: Challenges and opportunities − A systematic review

Generational mechanisms and spatio-temporal evolution patterns of Coastal urban flood risk involve complex interactions between climate change, sea level rise and human-induced factors, necessitating integrated adaptive flood management strategies to mitigate evolving vulnerabilities. This systematic review offers a thorough assessment of the challenges and strategic opportunities for sustainable adaptation in managing flood risk in Coastal urban areas. It integrates emerging innovative technologies and financial solutions to identify promising approaches to implement mitigation strategies and improve Coastal urban flood resilience. Enhancing governance and policy frameworks is crucial for the successful implementation of Coastal Urban Flood Risk Management (CUFRM) plans. An innovative participatory planning framework is developed to promote flood management practices which are socially inclusive and equitable. Funding for green infrastructure and nature-based solutions and the strategic use of public–private partnerships are effective methods for advancing sustainable flood risk management (FRM). The advancements in emerging technologies, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), social media and digital twin technologies, provide dynamic and collaborative platforms for simulating flood scenarios and have potential to significantly improve CUFRM practices. In the end, a cross-country comparison of current practices in Australia, China, Netherlands, the UK and the USA reveals a diverse range of approaches and valuable insights derived from regional experiences. The review provides a comprehensive analysis for researchers, policymakers and practitioners aiming to improve flood resilience in coastal metropolitan regions by learning from effective UFRM approaches that enhance governance structures, infrastructure resilience and funding mechanisms.

SUSTAINABLE FINANCE AND USE OF ARTIFICIAL INTELLIGENCE IN INVESTMENT DECISION MAKING

Artificial Intelligence (AI) is widely used across various industries to enhance efficiency, optimize decision-making, and create innovative solutions and it is now transforming the field of investment decision-making. As companies and investors place a greater emphasis on ethical and sustainable practices, sustainable finance-which incorporates environmental, social, and governance (ESG) factors into financial activities - is gaining global traction. Artificial Intelligence (AI) is becoming a vital instrument in the sustainable finance, because of its ability to analyse enormous volumes of data and spot patterns that are beyond human comprehension. This research paper examines the use of artificial intelligence (AI) tools like predictive analytics, machine learning, and natural language processing,in the financial decision-making. AI can quickly evaluate ESG aspects, predict long-term sustainability risks, and pinpoint high-impact investment opportunities that are in line with sustainability objectives by automating data gathering and analysis. Furthermore, AI-driven insights promote more ethical and knowledgeable financial decision-making by helping investors better manage risks related to social inequity, resource depletion, and climate change. Even though artificial intelligence (AI) has many benefits for sustainable finance, there are drawbacks as well, including data biases, opaque algorithms, and ethical issues. The article concludes that, artificial intelligence helps in creating more precise, effective, and socially conscious financial strategies.Artificial Intelligence (AI) is becoming increasingly important in sustainable finance decision-making due to its ability to handle complex, large-scale data, identify patterns, and optimize decision-making processes in ways that can advance sustainability goals. However, to fully realise AIs potential in forming a sustainable future for global finance, careful governance and ethical concerns are indispensable.

The Influence of Sustainable Risk Management on the Implementation of Risk-Based Internal Auditing

Risk management exerts a significant influence on the competitiveness of an organization and its operational processes. It presents opportunities for expansion, foresight, and the need to promote sustainability. Many organizations have executed comprehensive risk management processes. Moreover, internal audit has increasingly attracted managers’ attention, forming the basis of modern governance methods. The aim of this study is to examine, from the viewpoint of the agency, the impact of the role of internal auditors, training in risk management, and management support on risk management. Following this, the work examines risk management in terms of the risk-based auditing implementation that is performed by Saudi public organizations. This study encompassed 234 completed and therefore valid questionnaires from the manager and assistance of the internal audit department, internal auditors, accountants, and managers employed in Saudi public organizations. The data collected have been analyzed utilizing Smart Partial Least Squares (SmartPLS). This study’s findings confirmed that there is a significant association between the role of internal auditors in risk management, training in risk management, and between management support and risk management. There is also a significant association between risk management and the implementation of risk-based internal auditing. This study’s findings have significant ramifications for those in charge of public-sector organizations, and sustainability, aiming to enhance the dependability and trustworthiness of the internal audit process and other aspects of financial reports and audits in general. Currently, there is a dearth of published research on the factors that influence risk management and also on risk-based internal auditing. This study contributes to the emerging literature on this subject by examining Saudi public organizations; it also establishes empirical variables through a thorough review of relevant research. Conducted here is an empirical investigation that identifies the factors that affect risk management and then its influence on risk-based internal auditing implementation in the economic system of Saudi Arabia. By focusing on Saudi public organizations, this article highlights other countries that have similar systems of governance rules and procedures in their government-operated entities.

Evaluation of risk strategies for supply chain sustainability with interval-valued neutrosophic fuzzy EDAS

Sustainability means the most effective and efficient use of existing resources to meet the needs of future and current generations. Nowadays, with the increase in global environmental problems as well as social and economic problems, sustainability in the supply chain of the automotive industry has become increasingly important. In our study, after conducting an extensive literature review in the automotive industry, consulting with experts, and identifying 35 different Sustainability Risks across 5 sustainability dimensions, we proposed a total of 40 risk strategies to mitigate these risks. Using the evaluations of automotive supply chain experts from one of Turkey's leading logistics companies, risk strategies were ranked using the Interval-Valued Neutrosophic Fuzzy Evaluation based on Distance from Average Solution (IVN Fuzzy EDAS) method, and the best strategies were determined. Accordingly, it has been determined that the optimal approach for companies is to establish and implement legal compliance procedures and programs while adhering to prevailing regulations and policies. It aims to make a useful contribution to the literature in terms of covering this subject for the first time with fuzzy EDAS method, adding new sustainability risk dimensions, and developing broad-level risk and risk prevention strategies on the subject. In this study, the interval-valued neutrosophic fuzzy EDAS method was applied for the first time to the issue of sustainability risks in the automotive industry. At the same time, this study aims to contribute to the literature by adding new dimensions to sustainability.

Social perspectives on the sustainability challenges within the desalination sector: a Q-method study

Desalination offers options to augment water supplies for growing urban and industrial demand. Yet these facilities and related infrastructure projects have significant impacts on environmental, economic, and social sustainability. However, few studies examine how key actors in the sector understand or incorporate sustainability ideas and practices into the design, construction, and operation of desalination facilities. This study fills this gap by examining stakeholder perspectives on sustainability in the desalination sector using Q-method. We identified three dominant social perspectives on these topics. Factor 1 views desalination as important for the long-term sustainability of water supply. Factor 2 sees the social and environmental impacts of desalination as too big of a sustainability risk when there are other water resources to consider. Factor 3 indicates that the parties pursuing desalination have the responsibility of addressing sustainability concerns through their proposals and project specifications. These perspectives reveal how desalination stakeholders understand sustainability, key challenges, and responsibility for ensuring sustainable desalination projects. The findings provide insight into how desalination stakeholders can improve sustainability processes and outcomes.

Sustainability risk in insurance companies: A machine learning analysis

AbstractSustainable development constitutes a global challenge today, and the sustainable development goals (Agenda 2030) will probably set the course for the coming decades. This paper discusses sustainability in insurance companies by combining two aspects: a social approach (the environmental impact) and a business approach (the prediction of claims due to climate change). Our objective is to analyse the impact of physical risk in a home insurance portfolio and to measure in economic terms the effect of climate change in the future, by applying machine learning methodologies. Two data sources are used: a Spanish insurance portfolio with 31,998 policies and claims from 2017 to 2022, and daily meteorological variables from 290 Spanish weather stations from 2000 to 2022. Two climate scenarios are considered: RCP 4.5 (medium impact) and RCP 8.5 (high impact). On average for the period 2023–2052, the results reveal that claims will increase by 105% for the 4.5 scenario and by 129% for the 8.5 scenario. Our paper makes a clear contribution to sustainability by analysing climate risks and their impact on an insurance portfolio. It shows the grave consequences of climate change for the insurance sector's solvency and the political implications for the financial system in general.