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��ࡱ�>�� u �r�zbjbj�n�n2z��a��ar ��""��8�d]��olyyyyy��{o}o}o}o}o}o}o$hq�t<�o��o��yy4�o��y�y{o��{o��y��@ �x��go�o0�o�zt�jzt��1zt�lp��o�o)��o��zt��"qs: risk analysis volume 44, issue 7, july 2024 1. title: machines meet humans on the social road: risk implications authors: peng liu abstract: human drivers and machine drivers (i.e., automated vehicles or avs) will share roads and interact with each other, creating mixed traffic. in this perspective, we develop two mental models about them and their social interactions, aiming to understand the risk implications of avs and mixed traffic. based on mental model i (i.e., machine drivers are superior drivers without human weaknesses), many simulation-based safety assessments, which often overlook or oversimplify human-av social interactions, have predicted significant safety benefits when machine drivers interact with or replace human drivers. in contrast, mental model ii considers human and machine drivers as heterogeneous and incompatible, suggesting that their interactions may lead to unexpected and occasionally negative outcomes, particularly in imminent mixed traffic. this perspective gains support from recent comparative empirical studies that employ various methods such as survey experiments, driving simulators, test-tracks, on-road observations, and av accident analysis. these studies provide initial evidence of emerging traffic risks arising from human-av social interactions, including human drivers� aggression and road rage toward avs, human drivers exploiting avs, avs exerting negative peer influences on human drivers, and their incompatibility increasing human drivers� challenges in joining mixed traffic and thus risky behaviors. we propose specific suggestions to mitigate problematic human-av social interactions and the associated emerging risks. 2. title: complexity for complexity�how advanced modeling may limit its applicability for decision-makers authors: ben j. m. ale, david h. slater abstract: as today's engineering systems have become increasingly sophisticated, assessing the efficacy of their safety-critical systems has become much more challenging. the more classical methods of �failure� analysis by decomposition into components related by logic trees, such as fault and event trees, root cause analysis, and failure mode and effects analysis lead to models that do not necessarily behave like the real systems they are meant to represent. these models need to display similar emergent and unpredictable behaviors to sociotechnical systems in the real world. the question then arises as to whether a return to a simpler whole system model is necessary to understand better the behavior of real systems and to build confidence in the results. this question is more prescient when one considers that the causal chain in many serious accidents is not as deep-rooted as is sometimes claimed. if these more obvious causes are not taken away, why would the more intricate scenarios that emanate from more sophisticated models be acted upon. the paper highlights the advantages of modeling and analyzing these �normal� deviations from ideality, so called weak signals, versus just system failures and near misses as well as catastrophes. in this paper we explore this question. 3. title: security screening metrics for information-sharing partnerships authors: wendy yu, zachary a. collier, shital thekdi abstract: recent history has shown both the benefits and risks of information sharing among firms. information is shared to facilitate mutual business objectives. however, information sharing can also introduce security-related concerns that could expose the firm to a breach of privacy, with significant economic, reputational, and safety implications. it is imperative for organizations to leverage available information to evaluate security related to information sharing when evaluating current and potential information-sharing partnerships. the �fine print� or privacy policies of firms can provide a signal of security across a wide variety of firms being considered for new and continued information-sharing partnerships. in this article, we develop a methodology to gauge and benchmark information security policies in the partner-selection process that can help direct risk-based investments in information sharing security. we develop a methodology to collect and interpret firm privacy policies, evaluate characteristics of those policies by leveraging natural language processing metrics and developing benchmarking metrics, and understand how those characteristics relate to one another in information-sharing partnership situations. we demonstrate the methodology on 500 high-revenue firms. the methodology and managerial insights will be of interest to risk managers, information security professionals, and individuals forming information sharing agreements across industries. 4. title: sensitivity analysis for a participatory approach to enhance the climate resilience of venice, italy authors: beatrice sambo, marcello sano, anna sperotto, marco zanetti, silvia torresan, james h. lambert, igor linkov, andrea critto abstract: increases in the magnitudes and frequencies of climate-related extreme events are redistributing risk across coastal systems, including their environmental, economic, and social components. consequently, stakeholders (shs) are faced with long-term challenges and complex information when managing assets, services, and uses of the coast. in this context, sh engagement is a key step for risk management and in the preparation of resilience plans to respond and adapt to climate change. this paper develops a participatory method to identify and prioritize a set of risk measures, combining multi-criteria analysis with sensitivity analysis. the process involved local and regional authorities of the veneto region testing the method, including national, regional, and local government, catchment officers, research organizations, natural parks managers and non-governmental organizations (ngos). shs identified and ranked a range of adaptation measures to increase climate resilience, with a focus on coastal risk in the venice lagoon. results demonstrate that the sensitivity analysis provides useful information on how different sectors of expertise can influence the ranking of the identified risk management measures, highlighting the value of investigating the preferences or priorities of different sh groups within the definition of adaptation plans. 5. title: exploring sustainable energy consumption and social conflict risks in turkey: insights from a novel multiresolution ardl approach authors: hassen mohamed, foued sa�daoui abstract: nonrenewable energy sources have been shown to be a cause of conflict and terrorism, highlighting the global conflict aspect, but little is known about the causal relationship between the energy system and terrorism in turkey. this study aims to fill this gap by examining the causal links among renewable energy consumption, fossil fuels, terrorist attacks, education, trade opening, and geopolitical risks in turkey from 1980 to 2016. using the autoregressive distributed lag (ardl) approach and granger causality tests, the study analyzes the short and long-term relationships between the variables. additionally, robustness tests are conducted using a powerful multiresolution ardl approach to ensure the stability of the statistical findings. the results reveal the existence of long-term relationships between all the variables, particularly among terrorism, renewable energy, and education. in the short term, a one-way relationship exists between terrorism and education to renewable energies and from trade openness to terrorism. the study demonstrates that nonrenewable energy increases terrorism in the long term, whereas renewable energy and trade openness reduce terrorism, highlighting the potential impact of global conflicts on turkey's sustainable development. therefore, renewable energy is a powerful tool to fight against terrorism, and turkey has encouraged its use and deployment of diplomatic efforts to resolve political and military conflicts, particularly in the middle east. this study provides insights into the complex relationship among sustainable energy consumption, terrorism, education, and trade opening, contributing to the understanding of the geopolitical risks and economics in turkey. it has implications for policymakers in the region, highlighting the importance of renewable energy and trade openness as tools for conflict resolution and sustainable development in the face of global conflicts. 6. title: a global study of screening intensity and economic status on epidemic control performance during various epidemic periods of covid-19 mutant strains authors: chao-chin chang, chia-lin chang abstract: this study analyzed global data on epidemic control measures and economic conditions in different countries during different mutant strain epidemic periods, including the alpha, delta, and omicron strains. the study estimated the elasticity coefficient through a log-log model, which represents the percent change of the confirmed case number with respect to a percent change in the total number of screening tests in a country for epidemic control. the 7-day rolling data of screening tests and confirmed cases from the our world in data database for the pandemic periods of alpha strain in 2020, delta strain in 2021, and omicron strain in 2022, suggest that the magnitude of the elasticity was associated with the economic condition of a country. compared with the results during either alpha or delta pandemic period, the omicron pandemic has a much higher estimated elasticity coefficient of 1.317 (alpha: 0.827 and delta: 0.885). further examining economic conditions categorized by quartile ranges, the results indicate that the elasticity is statistically significantly lower in countries with gross domestic product (gdp) per capita between $11,354 and $26,651, and in countries with gdp per capita above $26,651 than in countries with gdp per capita below $3,335. these results suggest that countries should consider not only epidemiological measures but also economic conditions when formulating epidemic control strategies. this study highlights the importance of assessing the appropriateness of epidemic control strategies within a country and provides valuable insights into the effectiveness of such strategies, particularly in the context of community screening. 7. title: why did us urban homicide spike in 2020? a cross-sectional data analysis for the largest american cities authors: mohammad m. fazel-zarandi, arnold barnett abstract: working with data about homicide victims and perpetrators from 50 of america's largest cities, we investigate the explanatory power of some familiar explanations for why murder in those cities rose sharply in 2020. the analysis reveals that the distribution of risk by race was essentially the same in 2020 as in 2019. that empirical finding challenges some theories of how racial tensions after the death of george floyd may have driven homicide increases. similarly, homicide growth was not concentrated in those cities with the greatest availability in 2020 of new and older guns, or among the cities that suffered the most from the covid-19 pandemic. at a minimum, the cross-city outcomes should reduce confidence that some combination of �race, guns, and covid-19� explains all of the most important aspects of what happened in 2020. 8. title: game-theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment authors: alireza rangrazjeddi, andr�s d. gonz�lez, kash barker abstract: having reliable interdependent infrastructure networks is vital for well-being of a safe and productive society. systems are vulnerable to failure or performance loss due to their interdependence among various networks, as each failure can propagate through the whole system. although the conventional view has concentrated on optimizing the restoration of critical interdependent infrastructure networks using a centralized approach, having a lone actor as a decision-maker in the system is substantially different from the actual restoration decision environment, wherein infrastructure utilities make their own decisions about how to restore their network service. in a decentralized environment, the definition of whole system optimality does not apply as each decision-maker's interest may not converge with the others. subsequently, this results in each decision-maker developing its own reward functions. therefore, in this study, we address the concern of having multiple decision-makers with various payoff functions in interdependent networks by proposing a decentralized game theory algorithm for finding nash equilibria solutions for network restoration in postdisaster situations. 9. title: understanding the implications of low knowledge and high uncertainty in risk studies authors: shital thekdi, terje aven abstract: risk analysis has existed for thousands of years and will continue to grow in importance across professions and industries. of special importance is the need to understand and manage risk when there is low knowledge and high uncertainties. even with pristine and high-quality risk analysis in these situations, integrity and credibility can be questioned, and risk events can happen. although these issues do not prove some shortcoming in risk analysis and risk management, they can directly impact the risk analyst and decision-makers. the risk literature has addressed the issues of defining and promoting integrity and credibility for risk studies, but there is little existing guidance for the analyst when handling the commonly encountered low knowledge and high uncertainty contexts. in this article, we explore the implications of low knowledge and high uncertainty in risk studies to understand how the risk analyst can acknowledge those features in a risk study, with recognition that those features may be questioned later. the topic of this article will be of interest to risk managers, professionals, and analysts in general who are tasked with analyzing and communicating with studies. 10. title: risk perception and interpersonal discussion on risk: a systematic literature review authors: sara perlstein abstract: risk perception research has long been attentive to the fact that risk is a social construction. nevertheless, this fact has not been integrated into empirical research in any systematic manner. empirical studies that do focus on the social construction of risk often do so from very different positions and with different objectives in mind. interpersonal discussion, while considered an important medium of social construction, is rarely given consideration. this systematic literature review aims to provide a coherent foundation for empirical studies of interpersonal discussion on risk. specifically, it summarizes existing research into the reciprocal relationship between interpersonal discussion on risk and individual-level risk perception. the systematic literature review adheres to the preferred reporting items for systematic reviews (prisma) guidelines. a total of 843 unique articles were identified, of which 60 are included in the review. a majority of the articles in the corpus found a positive association between interpersonal discussion on risk and risk perception. this association, however, lacks robustness, especially in terms of the direction of causality. three theoretical interpretations of the relationship are found in the corpus: (1) interpersonal discussion as a conduit for risk information, (2) risk perception as shared social schemata, and (3) interpersonal discussion on risk as a facilitator of similarity between network members. implications for future research are discussed. this literature review concludes with six guiding principles for future research into the interpersonal discussion�risk perception relationship. 11. title: assessing key behavioural theories of drought risk adaptation: evidence from rural kenya authors: teun schrieks, w. j. wouter botzen, toon haer, oliver v. wasonga, jeroen c. j. h. aerts abstract: the horn of africa drylands are increasingly experiencing severe droughts, which impose a threat on traditional livelihood strategies. understanding adaptation behavior in rural communities is key to helping reduce the impact of these droughts. we investigate adaptation behavior by assessing four established economic and social psychological theories on decision making under risk: expected utility theory (eut), rank dependent utility theory (rdu), protection motivation theory (pmt), and theory of planned behavior (pmt). to measure adaptation behavior and the theory constructs, we conducted a household survey in kenya (n = 502). regression analysis shows that the economic theories (eut and rdu) have the best fit for our data. risk and time preferences are found to play an important role in adaptation decisions. an analysis of differences in decision making for distinct types of adaptation measures shows that risk averse (agro-)pastoralists are more likely to implement adaptation measures that are adjustments to their current livelihood practices, and less willing to invest in adaptation measures that require a shift to other livelihood activities. moreover, we find significant effects for elements of the social psychological theories (pmt and tpb). a person's belief in their own ability to implement an adaptation measure (perceived self-efficacy) and adaptation by family and friends are important factors in explaining adaptation decisions. finally, we find that the type of adaptation measures that people implement is influenced by, among others, gender, education level, access to financial resources, and access to government support or aid. our analysis gives insights into the drivers of individual adaptation decisions, which can enhance policies promoting adaptation of dryland communities. 12. title: communicating scientific uncertainty in the early stages of the covid-19 pandemic: a message experiment authors: dallin r. adams, chelsea l. ratcliff, manusheela pokharel, jakob d. jensen, yi liao abstract: the world health organization (who) officially declared covid-19 a pandemic on march 11, 2020. it was a time of significant uncertainty as experts were not yet certain whether social distancing behaviors were necessary to slow the spread of the virus. some public communicators opted to acknowledge uncertainty based on the limited evidence, whereas others downplayed uncertainty. this situation provided researchers with an opportunity to advance theory by explicating and testing cognitive responses to message uncertainty. immediately following the who declaration (march 13�19, 2020), u.s. adults (n = 1186) were randomly assigned to one of six conditions in a 2 (message uncertainty: low, high) � 3 (argument support: expert, threat, precedent) between-participants experiment. overall, perceived uncertainty negatively mediated the impact of message uncertainty on intentions. however, participant education was a key moderator. for those with more than a high school education, uncertain messages were related to higher intentions to social distance through increased critical reflection. for those with a high school education or less, uncertain messages were related to lower intentions through decreased message credibility. 13. title: integrating household survey with inoperability input�output model of critical infrastructure systems: a case study of hurricane sandy authors: joost santos, sisi meng, pallab mozumder abstract: critical infrastructures are ubiquitous and their interdependencies have become more complex leading to their uncertain behaviors in the aftermath of disasters. the article develops an integrated economic input�output model that incorporates household-level survey data from hurricane sandy, which made its landfall in 2012. in this survey, 427 respondents who were living in the state of new jersey during hurricane sandy were used in the study. the integration of their responses allowed us to show the probability and duration of various types of critical infrastructure failures due to a catastrophic hurricane event and estimate the economic losses across different sectors. the percentage of disruption and recovery period for various infrastructure systems were extracted from the survey, which were then utilized in the economic input�output model comprising of 71 economic sectors. sectors were then ranked according to: (i) inoperability, the percentage in which a sector is disrupted relative to its ideal level, and (ii) economic loss, the monetary worth of business interruption caused by the disaster. with the combined infrastructure disruptions in the state of new jersey, the model estimated an economic loss of $36 billion, which is consistent with published estimates. results from this article can provide insights for future disaster preparedness and resilience planning. 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