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This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Sustainable construction re-engineers the conventional project lifecycle to integrate sustainability solutions. The additional sustainability requirements introduce new layers of complexity, challenges and risks that if unaddressed, can derail the gains in sustainable construction projects. This study developed a multidimensional risk assessment model for sustainable construction projects in the United Arab Emirates (UAE).

The research activities a comprised comprehensive literature review to shortlist relevant risks, an analysis of the probability – impact rating of the shortlisted risks – and the development of a risk assessment model for SC projects in the UAE. The model is developed based on the multicriteria framework and mathematical formulation of the fuzzy synthetic evaluation approach.

The developed model quantified the overall risk level in sustainable construction projects to be 3.71 on a 5-point Likert scale, indicating that investment in SC projects in the UAE is risky and should be carefully managed. The developed model further revealed that each of the risk groups, comprising management (3.82), technical (3.78), stakeholder (3.68), regulatory (3.66), material (3.53) and economic risks (3.502), presents a significant threat to realizing outcomes typical of SC projects.

This study developed a multidimensional risk assessment model capable of objectively quantifying the overall risk level and provides decision support to project teams to improve risk management in sustainable construction projects.

Public-private partnership (PPP) power projects are associated with varying risk factors. This paper aims to develop a fuzzy quantitative risk allocation model (QRAM) to guide decision-making on risk allocation in PPP power projects in Ghana.

A total of 67 risk factors and 9 risk allocation criteria were established from literature and ranked in a two-round Delphi survey using questionnaires. The fuzzy synthetic evaluation method was used in developing the risk allocation model.

The model’s output variable is the risk allocation proportions between the public body and private body based on their capability to manage the risk factors. Out of the 37 critical risk factors, the public sector was allocated 12 risk factors with proportions = 50%, while the private sector was allocated 25 risk factors with proportions = 50%.

To the best of the authors’ knowledge, this research presents the first attempt in Ghana at endeavouring to develop a QRAM for PPP power projects. There is confidence in the model to efficiently allocate risks emanating from PPP power projects.

Businesses are increasingly vulnerable and exposed to physical climate change risks, which can cascade through local, national and international supply chains. Currently, few methodologies can capture how physical risks impact businesses via the supply chains, yet outside the business literature, methodologies such as sustainability assessments can assess cascading impacts.

Adopting a scoping review framework by Arksey and O'Malley (2005) and the PRISMA extension for scoping reviews (PRISMA-ScR), this paper reviews 27 articles that assess climate risk in supply chains.

The literature on supply chain risks of climate change using quantitative techniques is limited. Our review confirms that no research adopts sustainability assessment methods to assess climate risk at a business-level.

Alongside the need to quantify physical risks to businesses is the growing awareness that climate change impacts traverse global supply chains. We review the state of the literature on methodological approaches and identify the opportunities for researchers to use sustainability assessment methods to assess climate risk in the supply chains of an individual business.

This study examines the value implications of oil price uncertainty for investors in diversified firms using a sample of 922 USA firms from 2001 to 2019.

Our study employs a panel dataset to examine the value implications of oil price uncertainty for diversified firm investors. We consider several alternative specifications to account for unobserved factors and measurement errors that could potentially bias our results. In particular, we use alternative measures of the excess value of diversified firms and oil price uncertainty, additional control variables, fixed-effects models, the Oster test, impact threshold for confounding variable (ITCV) analysis, two-stage least square instrumental variable (2SLS-IV) analysis and the system-GMM model.

We find that the excess value of diversified firms, relative to a benchmark portfolio of single-segment firms, increases with high oil price uncertainty. The impact of oil price uncertainty is asymmetric, as corporate diversification is value-increasing for diversified firm investors only when the volatility is due to positive oil price changes and amidst supply-driven oil price shocks. The excess value increases irrespective of diversified firms’ financial constraints and oil usage. Diversified firms become conservative in their internal capital allocations with high oil price uncertainty. Such conservatism is value-increasing for diversified firm investors, as it supports higher performance in response to oil price uncertainty.

Our study has three important implications: first, they are relevant to investors in understanding the portfolio value implications of oil price uncertainty. Second, they are helpful for firm managers while comprehending the value-relevant implications of internal capital allocations. Finally, our findings are policy relevant in the context of the future of diversified firms in developed markets.

This study aimed at exploring the differential effects of different corporate governance (CG) indicators on risk management practices in Islamic financial institutions (IFIs) and conventional financial institutions (CFIs) of Pakistan. It also investigated the moderating role of institutional quality (IQ) in shaping the effects of CG practices on financial institutions of Pakistan.

A sample of 57 financial institutions including commercial banks, insurance companies and Modarba companies over the period 2006–2017 is used to carry out the empirical analysis. The authors applied the robust two-step system-generalized method of moments estimator, which is also called the dynamic panel data estimator. They also built the PCA-based composite index of CG and IQ by using different indicators to investigate the moderating role of IQ. They used three proxies for risk taking, five for CG and one for Shari’ah governance. To test the validity of the instruments, they applied the Arellano and Bond’s (1991) AR (1) and AR (2) tests and the J-statistic of Hansen (1982).

The results provided strong evidence that several individual characteristics of CG and the composite index are significantly related to the operational risk, the liquidity risk and the Z-score (a proxy for solvency risk). The results also revealed that IQ significantly and substantially contributes in reducing the level of risks. Finally, the estimation results indicated that the effects of CG on risk management are significantly different at IFIs and CFIs. This differential impact is mainly attributed to the fundamental differences in business models, operational strategies and contractual obligations of both types of institutions.

The findings of this study are important for enhancing our understanding of how CG relates to risk taking in Islamic and conventional financial services industries and how good quality institutions are important for formulating the governance effects on the risk-taking behavior of financial institutions. The findings suggest that a suitable size of board should be chosen to manage the risk effectively. As the findings show that the risk-taking behavior of IFIs differs from that of CFIs, the regulators and international standard setting bodies should tailor the regulatory frameworks accordingly.

This paper is different from the existing studies in four aspects. First, to the best of the authors’ knowledge, this is the first empirical investigation in Pakistan, which does the comparison of IFIs and CFIs while examining the impacts of CG on risk management. Second, the paper constructs the composite index of CG by considering several different indicators of governance and examines the combined effect of governance indicators on risk management process. Third, this paper adds to the growing literature on the role of IQ by investigating whether it acts as a moderator between CG structures and risk management and if yes, then whether this moderating role is different for IFIs and CFIs. Finally, the paper builds upon the existing research work on the CG effects for different types of financial institutions by proposing a single regression based analytical framework for comparing the effects across two different types of institutions, harvesting the benefits of higher degrees of freedom and avoiding/minimizing the measurement error.

This study aims to investigate the effect of mandatory international financial reporting standards (IFRS) adoption on the risk disclosure quality by listed European insurers.

The study used a content analysis of the annual reports and consolidated accounts of 13 insurance companies listed in the European market between 2002 and 2007 based on two regulatory frameworks, Solvency and IFRS.

The results showed a significant effect of the mandatory adoption of IFRS and a clear improvement in the quality of risk disclosure. Moreover, risk disclosure is positively associated with the size of the company.

The authors can consider the relatively limited size of the sample as a limitation of this study. Moreover, the manual content analysis used to be considered subjective.

The findings of this study provide useful insights to professional and regulatory bodies about the consequences of IFRS adoption to enhance transparency and particularly risk disclosure.

The research contributes to the existing literature. First, the authors have shown that companies are improving in the quality of risk disclosure even before 2005. Second, the authors have shown that the year 2005 is distinguished by a marked improvement in disclosure trends, with companies aligning themselves with coercive and mimetic regulatory forces. Third, the authors highlight the significant effect of mandatory IFRS adoption even in highly regulated industries, such as the insurance industry.

The increasing globalization and technological advancements have increased the information spillover on stock markets from various variables. However, there is a dearth of a comprehensive review of how stock market volatility is influenced by macro and firm-level factors. Therefore, this study aims to fill this gap by systematically reviewing the major factors impacting stock market volatility.

This study uses a combination of bibliometric and systematic literature review techniques. A data set of 54 articles published in quality journals from the Australian Business Deans Council (ABDC) list is gathered from the Scopus database. This data set is used to determine the leading contributors and contributions. The content analysis of these articles sheds light on the factors influencing market volatility and the potential research directions in this subject area.

The findings show that researchers in this sector are becoming more interested in studying the association of stock markets with “cryptocurrencies” and “bitcoin” during “COVID-19.” The outcomes of this study indicate that most studies found oil prices, policy uncertainty and investor sentiments have a significant impact on market volatility. However, there were mixed results on the impact of institutional flows and algorithmic trading on stock volatility, and a consensus cannot be established. This study also identifies the gaps and paves the way for future research in this subject area.

This paper fills the gap in the existing literature by comprehensively reviewing the articles on major factors impacting stock market volatility highlighting the theoretical relationship and empirical results.