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Smart cities provide fully integrated and networked connectivity between virtual/digital assets and physical building/infrastructure assets to form digital economies. However, industrial espionage, cyber-crime and deplorable politically driven cyber-interventions threaten to disrupt and/or physically damage the critical infrastructure that supports national wealth generation and preserves the health, safety and welfare of the populous. The purpose of this paper is to present a comprehensive review of cyber-threats confronting critical infrastructure asset management reliant upon a common data environment to augment building information modelling (BIM) implementation.

An interpretivist, methodological approach to reviewing pertinent literature (that contained elements of positivism) was adopted. The ensuing mixed methods analysis: reports upon case studies of cyber-physical attacks; reveals distinct categories of hackers; identifies and reports upon the various motivations for the perpetrators/actors; and explains the varied reconnaissance techniques adopted.

The paper concludes with direction for future research work and a recommendation to utilize innovative block chain technology as a potential risk mitigation measure for digital built environment vulnerabilities.

While cyber security and digitization of the built environment have been widely covered within the extant literature in isolation, scant research has hitherto conducted an holistic review of the perceived threats, deterrence applications and future developments in a digitized Architecture, Engineering, Construction and Operations (AECO) sector. This review presents concise and lucid reference guidance that will intellectually challenge, and better inform, both practitioners and researchers in the AECO field of enquiry.

The Pacific islands face the highest disaster risk globally in per capita terms. Countries in the region have been affected by several recent catastrophic events, as well as by frequent natural hazards of smaller magnitude. The purpose of this paper is to quantify total disaster risk faced by Pacific island countries (PICs).

The paper evaluates the three main sources of data for quantifying risk in the region—the International Emergency Database (EMDAT), DesInventar and the Pacific Catastrophe Risk Assessment and Financing Initiative, evaluating the information available on indirect disaster impacts and their likely impacts on poverty and well-being.

The analysis suggests that the three available data sets contain inconsistencies and underestimate disaster risk, especially for atoll nations. It also identifies four trends with respect to changes in natural hazards that result from climate change and are likely to have the greatest long-term impact on Pacific islands. Focusing on Tuvalu, the paper also quantifies the likely consequence of some of the possible interventions that aim to reduce those impacts.

The paper’s main conclusion is that improving the systematic collection of quantitative data on disaster events should be a basic first step in improving future policy decisions concerning resource allocation and efforts to insure losses from future disasters and climate change.

While a lot of research explored disaster risk in PICs, comparative analysis of quantitative information on disasters across the diverse countries of the region is limited.

Most recent developments in the Internet of Things (IoT) technologies can boost the efficacy of business process management (BPM) to improve process performance. The purpose of this paper is to describe a method for redesigning bank branch (BB) protection systems contributing to make BBs “smarter.”

Based upon a multiple case study approach, the paper deployed a four-step business process reengineering design from an information system development perspective. To overcome limitations of information scarcity required for modeling activities, a multimethod approach to data gathering and results validation was adopted. The approach was based on a comprehensive literature review and an in-depth qualitative survey involving a sample of six security managers of primary Italian banking groups.

The intelligent protection system resulting from the application of the methodology to the Italian BB sector was able to improve the security management process. Lead time and actors’ workload were reduced; running costs decreased; quality of information improved as well as the overall effectiveness of the protection system against criminal attacks.

The specific IoT technologies proposed are new. Additionally, to date, their application to BB security management has not been analyzed in the BPM literature. The value resides in the highly applicable results of the methodology to the BB network of a banking group both inside and outside of Italy.

Today, Big Data plays an imperative role in the creation, maintenance and loss of cyber assets of organisations. Research in connection to Big Data and cyber asset management is embryonic. Using evidence, the purpose of this paper is to argue that asset management in the context of Big Data is punctuated by a variety of vulnerabilities that can only be estimated when characteristics of such assets like being intangible are adequately accounted for.

Evidence for the study has been drawn from interviews of leaders of digital transformation projects in three organisations that are within the insurance industry, natural gas and oil, and manufacturing industries.

By examining the extant literature, the authors traced the type of influence that Big Data has over asset management within organisations. In a context defined by variability and volume of data, it is unlikely that the authors will be going back to restricting data flows. The focus now for asset managing organisations would be to improve semantic processors to deal with the vast array of data in variable formats.

Data used as evidence for the study are based on interviews, as well as desk research. The use of real-time data along with the use of quantitative analysis could lead to insights that have hitherto eluded the research community.

There is a serious dearth of the research in the context of innovative leadership in dealing with a threatened asset management space. Interpreting creative initiatives to deal with a variety of risks to data assets has clear value for a variety of audiences.

Dams are constructed for many purposes such as for power generation, irrigation, water supply and flood control. However, dams can also impose risks to the public, and the situation could be disastrous if dam failure occurred. The study area, Bertam Valley, is located downstream of hydroelectric dam known as Sultan Abu Bakar Dam, Cameron Highlands. The key objectives of the study are to determine the potential risk area at downstream and to assess the flooding impact on damage to buildings and infrastructures due to dam break event. ArcGIS application and output from two-dimensional flood modelling have been used as an integrated approach to analyse the impact due to dam break flood, by creating flood severity grid analysis. The result obtained shows that the estimated inundated area is about 0.28 km², and almost 197 buildings are potentially affected. Results from this study show that in the event of dam break, the huge volume of impounding water will pound to the downstream areas, threatening the populations, and environment along its path. The finding is useful to assist the local authorities and emergency responders in formulating an emergency procedure to save the people during an emergency.

The purpose of this paper is to introduce the zero‐modified distributions in the calculation of operational value‐at‐risk.

This kind of distributions is preferred when excess of zeroes is observed. In operational risk, this phenomenon may be due to the scarcity of data, the existence of extreme values and/or the threshold from which banks start to collect losses. In this article, the paper focuses on the analysis of damage to physical assets.

The results show that basic Poisson distribution underestimates the dispersion, and then leads to the underestimation of the capital charge. However, zero‐modified Poisson distributions perform well the frequency. In addition, basic negative binomial and its related zero‐modified distributions, in their turn, offer a good prediction of count events. To choose the distribution that suits better the frequency, the paper uses the Vuong's test. Its results indicate that zero‐modified Poisson distributions, basic negative binomial and its related zero‐modified distributions are equivalent. This conclusion is confirmed by the capital charge calculated since the differences between the six aggregations are not significant except that of basic Poisson distribution.

Recently, the zero‐modified formulations are widely used in many fields because of the low frequency of the events. This article aims to describe the frequency of operational risk using zero‐modified distributions.

The authors investigate whether firm-specific vulnerability to climate change influences foreign exchange hedging, using a novel text-based measure of firm-level climate change exposure generated by state-of-the-art machine-learning algorithms.

The authors' empirical analysis includes firm-fixed effects, random-effects regressions, propensity score matching (PSM), entropy balancing, an instrumental-variable analysis and using an exogenous shock as a quasi-natural experiment.

The authors' findings suggest that greater climate change exposure brings about a significant reduction in exchange rate hedging. Companies more exposed to climate change may invest significant resources to address climate change risk, such that they have fewer resources available for currency risk management. Additionally, firms seriously coping with climate change risk may view exchange rate risk as relatively less important in comparison to the risk posed by climate change. Notably, the authors also find that the negative effect of climate change exposure on currency hedging can be specifically attributed to the regulatory aspect of climate change risk rather than the physical dimension, suggesting that companies view the regulatory dimension of climate change as more critical.

Recent studies have demonstrated that climatic fluctuations represent one of the most recent sources of unpredictability, thereby impacting the economy and financial markets (Barnett et al., 2020; Bolton and Kacperczyk, 2020; Engle et al., 2020). The authors' study advances this field of research by revealing that company-specific exposure to climate change serves as a significant determinant of corporate currency hedging, thus expanding the existing knowledge base.

The 1988 Basel Accord and the proposed revisions to the Accord represent some of the most significant international regulations impacting the financial decisions of firms, in this case, financial services firms, in recent years. The revisions to the Accord incorporate operational risk into the capital, supervisory and market requirements. In our review of the issues in this area, we provide insight into the workings of an important international regulation. We also present suggestions for further research in this area that will become feasible when data on the impact of the new regulations become available after the proposed implementation in 2006.

This study aims to investigate hazards in theater venues on the performance day by combining operational risk theory with a service blueprint method.

Interviews and Delphi method are applied to find the hazards, then a survey and ANOVA are followed. The study explores a profile of hazards using data from theater venues in Taiwan and examines whether employee characteristics (i.e. professional tasks, experience and working location) affect risk perception.

The study suggests a new framework represented by a 5 (types of loss events) × 6 (service systems) matrix to check operational risks. The analyses indicate two types of hazards: risk perception about performance and operations by performers and crew (RPPOPC) and audience behaviors and safety (RPABS). RPPOPC is related to the core show, but not all employees possess high RPPOPC. Seniors have relatively low RPPOPC, and frontend house employees possess insufficient RPABS. Further, front house employees, seniors and those working in municipal cities show relatively high RPPOPC in high-loss situations.

Managers can use the analytic framework to effectively identify operational risks in the core show operations and audience service offerings. They can promote risk perception considering employee differences and loss severity. However, the framework does not discuss the cause-and-effect relationship. Incorporating a large amount of loss experience into a risk information system would help clarify this complex relationship.

This study contributes to hazard mitigation in the performing arts sector, both in the peripheral services for customers and in the core show services.

This paper aims to investigate the multi-faceted impact of host country risks on the success of private participation in infrastructure projects. The authors make a distinction between exogenous and endogenous risks, differentiating those that are completely beyond the control of the firm from those in which firms might exert some degree of influence to reduce the negative repercussions.

Drawing on logistic regression analyses, the authors analyze a sample of 10,350 private participation in infrastructure projects in 126 countries from 1997 to 2014.

The authors find that higher levels of exogenous risk are associated with a lower probability of project success, whereas they find no significant effect for endogenous risk.

By pointing to this differential effect, this study makes a contribution to the current debate in the literature on private participation projects.