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The study aims to assess the effectiveness of prevailing methods for quantifying physical climate risks. Its goal is to evaluate their utility in guiding financial decision-making within the real estate industry. Whilst climate risk has become a pivotal consideration in transaction and regulatory compliance, the existing tools for risk quantification frequently encounter criticism for their perceived lack of transparency and comparability.

We utilise a sequential exploratory mixed-methods analysis to integrate qualitative aspects of underlying tool characteristics with quantitative result divergence. In our qualitative analysis, we conduct interviews with companies providing risk quantification tools. We task these providers with quantifying the physical risk of a fictive pan-European real estate portfolio. Our approach involves an in-depth comparative analysis, hypothesis tests and regression to discern patterns in the variability of the results.

We observe significant variations in the quantification of physical risk for the pan-European portfolio, indicating limited utility for decision-making. The results highlight that variability is influenced by both the location of assets and the hazard. Identified reasons for discrepancies include differences in regional databases and models, variations in downscaling and corresponding scope, disparities in the definition of scores and systematic uncertainties.

The study assists market participants in comprehending both the quantification process and the implications associated with using tools for financial decision-making.

To our knowledge, this study presents the initial robust empirical evidence of variability in quantification outputs for physical risk within the real estate industry, coupled with an exploration of their underlying reasons.

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

The purpose of this study is to examine how companies integrate cyber risk into their enterprise risk management practices. Data breaches have become commonplace, with thousands occurring each year, and some costing hundreds of millions of dollars. Consequently, cyber risk has become one of the gravest risks facing organizations, and has attracted boardroom-level attention. On the other hand, companies already manage many kinds of difficult and growing risks, and that firms lose less than 1% of annual revenues as a result of cyber incidents. Therefore, how should firms appropriately address cyber risk? Is it indeed a materially different kind of risk area, or is it simply just one more risk that can seamlessly be integrated into existing enterprise risk management (ERM) practices?

The authors performed thematic analysis based on semi-structured interviews, with non-probabilistic, purposive sampling, to answer two main questions. First, how do firms manage enterprise risks, generally? And second, how are they integrating cyber risk into these existing processes?

The authors find that there is considerable variation in the approach and sophistication in ERM practices, such as whether they are driven more like an auditing function, or as a risk champion. The authors also find that despite the novelty of cyber risk, it can be integrated like other enterprise risks, and that cyber risk is most often seen as an operational risk (similar to workplace accidents or fraud), rather than a strategic risk, emerging from, for example, technology innovation and R&D.

The generalization of the results is limited by the sample size and variation of firms interviewed. While the authors attempted to interview enterprise risk managers across a wide variation of firms, there were clear limitations in the scope. That being said, the authors were fortunate to be able to examine ERM and cyber risk practices across small and large, private and publicly traded companies, from a variety of business sectors.

The authors believe these finding are important because they present evidence that while cyber risk may be new, it does not require specialized handling or processes to track it at the enterprise level. While some firms may choose to provide special accommodations or attention because of their data collection or business practices, this approach is neither necessary nor required of all firms in all situations.

This research is one of the only papers that, to the best of the authors’ knowledge, examines how cyber risk is integrated at an enterprise level.

The increasing prevalence of enterprise risk coupled with global competition requires a strategic link to the way forward through measured outcomes determined in a collaborative and visual manner.

The model was conceptualized and validated through strategic management deficiencies encountered in venture ownership, management consulting and teaching practice and was augmented with extensive stakeholder input and existing scholarly research.

Managing risk is a complex and somewhat dark task that can happen everywhere or nowhere within a firm and requires mitigating strategies developed with stakeholder consensus. In practice with three distinct audiences of entrepreneurs, senior managers and capstone student strategists, the model does facilitate linked risk and opportunity identification as well as the quantification and/or qualification of variables. The process is as impactful as the outcomes when individual risk “appetites” and a collective risk culture emerge.

Innovative organizations must regularly scan their external environment and assess internal resources and capabilities in a structured and actionable manner while understanding their risk culture. Valuable outcomes emerge from facilitating strategic risk management discussions, particularly in growing and informal organizations. Risk communications with stakeholders are complex and increasingly important.

Opportunity mapping offers a novel process to identify prioritized strategies that may be otherwise determined intuitively with limited input or absent altogether. The process facilitates actionable outcomes as a supplement to the known practice of risk assessment while contributing to a competitive advantage.

The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.

A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.

It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.

This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.

Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

Global and interconnected supply chains are increasingly exposed to systemic risks, whereby individual failures propagate across firms, sectors and borders. Systemic risks have emerged from the decisions of individual firms, e.g., outsourcing and buffer reduction, and are now beyond their control. This paper aims to identify appropriate approaches to mitigating those risks.

Systemic risks require analyzing supply chains beyond a dyadic perspective. This study approaches the problem through the lenses of complex systems and network theories. Drawing on the lessons learned from other systemic-risk-prone systems, e.g. energy and financial networks, both in research and practice, this study analyzes the adequate level of governance to monitor and manage systemic risks in supply chains.

The authors argue that governance institutions should be mandated to overview and reduce systemic risks in supply chains from the top down, as central bankers do for the financial system. Using firm-level data and tools from network analysis and system dynamics, they could quantify systemic risks, identify risk-prone interconnections in supply chains and design mitigating measures. This top-down approach would complement the bottom-up supply chain management approach and could help insurers design policies for contingent business interruptions.

Instead of looking at supply chains purely from the firms’ angle, the perspective of insurers and governments is brought in to reflect on the governance of risks.

Uncertainty management (UM) in projects has been a point of attention for researchers for many years. Research on UM has mainly been aimed at uncertainty analyses in the front-end and managing uncertainty in the construction phase. In contrast, UM components in the design phase have received less attention. This research aims to improve knowledge about the key components of UM in the design phase of large road projects.

This study adopted a literature review and case study. The literature review was used to identify relevant criteria for UM. These criteria helped to design the interview guide. Multiple case study research was conducted, and data were collected through document study and interviews with project stakeholders in two road projects. Each case's owners, contractors and consultants were interviewed individually.

The data analysis obtained helpful information on the involved parties, process and exploit tools and techniques during the design phase. Johansen's (2015) framework [(a) human and organisation, (b) process and (c) tools and techniques)] was completed and developed by identifying relevant criteria (such as risk averse or risk-taker, culture and documentation level) for each component. These criteria help to measure UM performance. The authors found that owners and contractors are major formal UM actors, not consultants. Empirical data showed the effectiveness of Web-based tools in UM.

The studied cases were Norwegian, and this study focussed on uncertainties in the project's design phase. Relevant criteria did not cover all the criteria for evaluating the performance of UM. Qualitative evaluation of criteria allows further quantitative analysis in the future.

This paper gave project owners and managers a better understanding of relevant criteria for measuring UM in the owners and managers' projects. The paper provides policy-makers with a deeper understanding of creating rigorous project criteria for UM during the design phase. This paper also provides a guideline for UM in road projects.

This research gives a holistic evaluation of UM by noticing relevant criteria and criteria's interconnection in the design phase.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.

The statistics show that older adults have been major fire victims in high-rise buildings. However, the fire safety building codes in most countries are not inclusive and do not reflect provisions for older adults. The research aims to develop a fire risk assessment index system for older adults living in high-rise residential buildings in India. The study further develops a fire rating system to improve fire safety provisions in high-rise buildings in India.

The paper employs Delphi, analytic hierarchy process (AHP) and fuzzy comprehensive risk evaluation techniques. It considers 18 in-depth interviews and group discussions with builders, developers, architects, policymakers, and fire safety experts and consultants to develop a fire risk assessment system for older occupants living in high-rise residential buildings in India.

The fire protection systems and fire management systems are not as per the needs of older adults. The egress system components need improvisation considering the challenges of older adults.

The study is limited to older adults living in high-rise residential buildings in the capital city of Gujarat, Ahmedabad.

This study will assist policymakers in developing fire safety standards that are targeted to the needs of older persons living in high-rise residential buildings during a fire evacuation.

While several approaches for measuring fire risk in high-rise residential buildings exist, no such system has been developed specifically for older adults in India.