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The purpose of this paper is to assess the risk of a population in a given territory being harmed by climate change by distinguishing between: natural factors, which are associated with inherent vulnerability; and man‐made or policy‐induced factors, which are associated with adaptation. It is argued that this distinction is useful as a methodological approach and for policy making.

The approach utilises indices of vulnerability and adaptation, and juxtaposes them to arrive at an assessment of risk.

The major findings of this paper are that the “lowest‐risk” or “managed‐risk” category of territories are mostly port cities in high‐income countries, whereas the “mismanaged‐risk” and “highest‐risk” category of territories are vulnerable port cities located in low‐income countries.

The originality of the paper is that it highlights the distinction between natural and man‐made risks in arriving at a total assessment of risk – a distinction of utmost importance for policy making. An important, although obvious, conclusion is that adaptation does not reduce the inherent vulnerability of the territories concerned, but it serves to enable humans to withstand, bounce back from or absorb the effects of vulnerability to climate change.

Information technology is associated with psychological and physical risks such as high stress levels and antisocial behavior. The purpose of this paper is to understand why people engage in technology risk behavior, despite the negative consequences that might follow. Focusing on online games, this study identifies factors that affect individuals' intention to play online games and investigate whether the effects of these factors differ across different risk levels.

Experimental design was used as the research methodology. Subjects were randomly assigned to a single treatment with two conditions: high and low risk scenarios. A total of 597 responses were analyzed to test the research hypotheses.

The research findings reveal that subjective norms, curiosity and playfulness have a positive effect on the intention to play online games, while critical mass has no effect on the intention decisions. Further, among the three significant constructs, playfulness turned out to be the only factor that is affected by risk levels.

This study extends prior literature on technology adoption by examining the effect of different risk levels on adoption intention decisions. It further extends prior literature on online games by identifying the factors that drive individuals to play games while accounting for the risks associated with playing these games.

The research study identifies factors that should be taken into consideration when promoting the adoption of technologies, including online games.

This study offers a new understanding of technology adoption decisions that takes into account the different levels of risk associated with technology use. It shows that an individual's curiosity and the pressure emanating from one's social network are powerful behavior drivers that persist regardless of the level of risk. Further, this research study is among the first to apply categorical least squares methodology combined with a procedure for a moderated structural equation model to test a structural equation model with categorical multiplicative terms in LISREL.

The purpose of this paper is to develop a nuanced framework for evaluating a channel partner’s performance in distribution channel relationships. Given a channel partner’s task environment characteristics (high/low munificence, dynamism and complexity), the study examines which performance metrics (output, activity or capability) are most relevant for evaluating its performance levels effectively.

The study adopts self-administered cross-sectional survey-based research design. Matched data were collected from 252 channel partners – manager relationship dyads. The latent change score (LCS) model within SEM framework provides mean paired-differences of the relevance ratings for each metrics. This was used to assess the empirical validity of the hypothesized relationships.

The study demonstrates the importance of calibrating performance evaluation metrics to a channel partner’s task environment state, made possible by its holistic approach to performance evaluation. Based on an extensive analysis, it shows that no single metric is relevant within all environmental states; rather, it could be dysfunctional, a result that differs from vast majority of the literature.

Investigates individual linkages between task environment dimensions and performance metrics to provide a fuller understanding of these relationships. Also provides a theoretical framework to support further research on the topic.

The study provides managerial guidelines (and extensive graphical analysis) for nuanced and dynamic evaluation of channel partners’ performance that can enable firms to identify and promote their most valuable channel partners and prevent the deterioration of others.

First one to develop and empirically validate a nuanced framework for evaluating performance of exchange partners that operate under diverse task environment states.

The purpose of this paper is to extract the user behaviour and transform it into a unique signature that can be used as implicit authentication technique. Smart devices are equipped with multiple authentication techniques and still remain prone to attacks because all of these techniques require explicit intervention of the user. Entering a pin code, a password or even having a biometric print can be easily hacked by an adversary.

In this paper, the authors introduce a novel authentication model to be used as complementary to the existing authentication models. Particularly, the duration of usage of each application and the occurrence time were examined and modelled into a user signature. During the learning phase, a cubic spline function is used to extract the user signature based on his/her behavioural pattern.

Preliminary field experiments show a 70 per cent accuracy rate in determining the rightful owner of the device.

The main contribution of this paper is a framework that extracts the user behaviour and transforms it into a unique signature that can be used to implicitly authenticate the user.

Using a phenomenon known as the bullwhip effect, the authors explore why additional uncertainty in the marketplace can create severe disruptions in global supply chains (GSCs). The purpose of this paper is to analyze related risks in regional vs GSCs during low and high levels of uncertainty. The authors propose and discuss a number of potential implications alongside some tactics that may help mitigate disruptions in some cases before they become terminal problems for the supply chain sustainability.

Monte Carlo simulation is used to generate the conditions of uncertainty and various scenarios that may emerge to challenge GSCs. Vensim software is utilized as a tool for simulation purposes. The authors considered scenarios applicable to manufacturing and retail sectors specifically because of storability property of goods.

Regional supply chains, as opposed to global ones, are more stable and reliable (less risk of disruption) during low and high levels of uncertainty. During uncertain times, upstream suppliers are at greater risk in GSCs. Firms must make strategic decisions that will secure its supply chain functionality and assess the likelihood of such events since many firms entered emerging markets.

Building on internalization theory, it shows that risk and survival are components of decision making that are further complicated by supply chains now operating globally in emerging markets. The paper demonstrates with simulation that GSCs are riskier than regional supply chains in low and high levels of uncertainty, particular as it relates to the bullwhip effect. It also provides recommendations about supply chain restructure and investments in communication improvements to reduce the bullwhip effect in the supply chain.

It would take billions of miles’ field road testing to demonstrate that the safety of automated vehicle is statistically significantly higher than the safety of human driving because that the accident of vehicle is rare event.

This paper proposes an accelerated testing method for automated vehicles safety evaluation based on improved importance sampling (IS) techniques. Taking the typical cut-in scenario as example, the proposed method extracts the critical variables of the scenario. Then, the distributions of critical variables are statistically fitted. The genetic algorithm is used to calculate the optimal IS parameters by solving an optimization problem. Considering the error of distribution fitting, the result is modified so that it can accurately reveal the safety benefits of automated vehicles in the real world.

Based on the naturalistic driving data in Shanghai, the proposed method is validated by simulation. The result shows that compared with the existing methods, the proposed method improves the test efficiency by 35 per cent, and the accuracy of accelerated test result is increased by 23 per cent.

This paper has three contributions. First, the genetic algorithm is used to calculate IS parameters, which improves the efficiency of test. Second, the result of test is modified by the error correction parameter, which improves the accuracy of test result. Third, typical high-risk cut-in scenarios in China are analyzed, and the proposed method is validated by simulation.

Section 404 of the Sarbanes–Oxley Act (SOX) altered the relationship between auditors and their clients by requiring an external audit of companies’ internal controls. Regulatory guidance is interpreted and applied by external auditors to comply with SOX. The purpose of this paper is to apply service operations management theories and techniques to the internal control audit process to better understand the role regulatory guidance plays in audit services. We discuss service operations management theories that apply to the production of audit services and employ the operations management technique of simulation to examine the effects of a historical relationship between the client and the auditor, information sharing between the client and the auditor, and the auditor’s perceived risk of the client on the internal control audit process. The application of service operations management theories and the simulation results illustrate that risk and information sharing are key factors for the audit process. The results suggest the updated Public Company Accounting Oversight Board guidance from Auditing Standard 2 to Auditing Standard 5 appropriately increased audit effectiveness by encouraging risk-based judgments and information sharing. This paper merges accounting and service operations management research to examine the effects of regulatory guidance on the internal control audit process. The paper uses simulation to illustrate the importance of interpreting regulatory guidance and the specific effects of risk and information sharing on the internal control audit process.

The purpose of this paper is to analyse the effects of the maturities of credit‐enhanced debt contracts on the value of an insurer's loan‐guarantee portfolios.

The paper proposes a contingent‐claims model and uses as measure of credit insurance risk, the market value of the private guarantee, which accounts for projects' and guarantor's specific risks, correlations as well as financial leverage.

The results indicate that in the case of insuring the debts of two parallel projects with different specific risks, one high‐risk and the other low‐risk, the tradeoff between maturities of the guarantees increases with the projects' expected losses, hence the maturity choice decision is crucial for portfolios subject to high expected losses. For a two sequential projects loan‐guarantee portfolio, the paper finds that, regardless of the order of execution of the projects, it is the maturity of the debt supporting the high‐risk project that drives the risk exposure of the portfolio.

Since the management of portfolios of guarantees is of significant importance to many organizations both domestically and internationally, this paper proposes a simple and tractable model to gauge the impact of maturity choices for loan‐guarantee portfolios.

This is a first attempt at modeling multiple maturities in the context of portfolios of vulnerable loan guarantees.

Supply chains need to balance competing objectives; in addition to efficiency, supply chains need to be resilient to adversarial and environmental interference and robust to uncertainties in long-term demand. Significant research has been conducted designing efficient supply chains and recent research has focused on resilient supply chain design. However, the integration of resilient and robust supply chain design is less well studied. The purpose of the paper is to include resilience and robustness into supply chain design.

The paper develops a method to include resilience and robustness into supply chain design. Using the region of West Africa, which is plagued with persisting logistical issues, the authors develop a regional risk assessment framework and then apply categorical risk to the countries of West Africa using publicly available data. A scenario reduction technique is used to focus on the highest risk scenarios for the model to be tractable. Next, the authors develop a mathematical model leveraging this framework to design a resilient supply network that minimizes cost while ensuring the network functions following a disruption. Finally, the authors examine the network's robustness to demand uncertainty via several plausible emergency scenarios.

The authors provide optimal sets of transshipment hubs with varying counts from 5 through 15 hubs. The authors determine there is no feasible solution that uses only five transshipment hubs. The authors' findings reinforce those seven transshipment hubs – the solution currently employed in West Africa – is the cheapest architecture to achieve resilience and robustness. Additionally, for each set of feasibility transshipment hubs, the authors provide connections between hubs and demand spokes.

While, at the time of this research, three other manuscripts incorporated both resilience and robustness of the authors' research unique solved the problem as a network flow instead of as a set covering problem. Additionally, the authors establish a novel risk framework to guide the required amount of redundancy, and finally the out research proposes a scenario reduction heuristic to allow tractable exploration of 512 possible demand scenarios.

Many modern firms strive to become sustainable. To this end, they are required to improve not only their own environmental and social performance but also the performance of their suppliers. Building on population ecology theory, we explore how buyers' exposure to supplier sustainability risk and their subsequent risk management strategies at the buyer–supplier dyad level can lead to adherence to sustainability by the supplier populations.

We rely on a bottom-up research design, in which the actions of buyers within buyer–supplier dyads lead to population-wide changes on the supplier side. Specifically, we use experimental data on managing sustainability risk to build an agent-based simulation model and assess the effect of evolutionary processes on the presence of sustainable/unsustainable business practices in the supplier population.

Our findings suggest that buyers' cumulative actions in managing sustainability risk do not necessarily result in effective population-wide improvements (i.e. at a high rate and to a high degree). For example, in high risk impact conditions, the buyer population is usually able to decrease the population level risk in a long run, but they would need both power and resources for quickly achieving such improved outcomes. Importantly, this positive change, in most cases, is due to the fact that the buyer population selects out the suppliers with high probability of misconduct (i.e. decreased supplier population density).

Drawing on the organizational population ecology theory, we explore when, to what degree and how quickly the buyers' cumulative efforts can lead to population-wide changes in the level of supplier sustainability risk, as well as the composition and density of supplier population. Methodologically, this paper is one of the first studies which use a combination of experimental data and agent-based modeling to offer more valuable insights on supply networks.