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��ࡱ�>�� r��bjbj�.�.2��d�g�d�g(b ��66��8|��cr��q�q�q�q�q�q�q$it��vf�q]��q��4r��q��q��@�h'��q3r0cr�ew�xew��t1ew�np��q�qtn��cr��ew��6b�: risk analysis volume 44, issue 6, june 2024 1. title: unpacking the modeling process for energy policy making authors: samuele lo piano, m�t� j�nos lqrincz, arnald puy, steve pye, andrea saltelli, stef�n thor smith, jeroen van der sluijs abstract: this article explores how the modeling of energy systems may lead to an undue closure of alternatives by generating an excess of certainty around some of the possible policy options. we retrospectively exemplify the problem with the case of the international institute for applied systems analysis (iiasa) global modeling in the 1980s. we discuss different methodologies for quality assessment that may help mitigate this issue, which include numeral unit spread assessment pedigree (nusap), diagnostic diagrams, and sensitivity auditing (saud). we illustrate the potential of these reflexive modeling practices in energy policy-making with three additional cases: (i) the case of the energy system modeling environment (esme) for the creation of uk energy policy; (ii) the negative emission technologies (nets) uptake in integrated assessment models (iams); and (iii) the ecological footprint indicator. we encourage modelers to adopt these approaches to achieve more robust, defensible, and inclusive modeling activities in the field of energy research. 2. title: time for a paradigm change: problems with the financial industry's approach to operational risk authors: tom butler, robert brooks abstract: organizational and risk cultures in the financial industry are argued to be the root cause of banking problems. it is concerning that financial regulators and practitioners still consider the industry to be seriously fragile in several respects, particularly to operational risks and risks associated with digital transformation and innovation�not that the risks of organizational misconduct have disappeared. the rescue of credit suisse in 2023 confirms this. this paper employs extant theories of organizational culture, learning, and action to critically evaluate the existing risk paradigm in banking and to highlight its deficiencies, which practitioners can only address by questioning the flawed assumptions and dysfunctional values and behaviors found to be endemic in banks. however, business and risk practitioners are also married to institutional approaches that focus on assessing risk and measuring historical losses to allocate regulatory capital, rather than forward-looking approaches to measure and manage risk. this requires a paradigm change. this paper presents a novel risk measurement and accounting methodology, risk accounting, to help underpin such change. risk accounting measures risk exposure in quantitative and qualitative terms and can be implemented using an ai-enabled digital architecture that could solve endemic problems with risk data aggregation and analysis. significantly, risk accounting enables a financial value to be placed on risk exposures at a granular level. this level of transparency provides an incentive to change behaviors in banks and support cultural change while providing a basis for a paradigm change in the way operational risk is managed. 3. title: revealing the energy paradox: assessing the asymmetric impact of pandemic uncertainty on consumption of renewable and nonrenewable energy authors: tsung-xian lin, tsung-te lin, sajid ali, raima nazar, muhammad khalid anser abstract: uncertainties have grown around the world during the last few decades. pandemic uncertainty has a substantial impact on economic activities, which may have a big influence on energy consumption. the goal of this investigation is to appraise the asymmetric influence of pandemic uncertainty on nonrenewable and renewable energy consumption in the top 10 energy consumer economies of the european union (germany, poland, spain, netherlands, france, italy, belgium, sweden, czech republic, and finland). previously, panel data approaches were utilized to obtain reliable outcomes on the pandemic-energy consumption nexus, regardless of the fact that various nations did not autonomously exhibit similar relationship. this investigation, on the other hand, implements a special technique �quantile-on-quantile� that supports us to appraise time-series interdependence in each economy by providing international yet nation-specific perceptions of the connection among the variables. estimates show that pandemic uncertainty reduces both nonrenewable and renewable energy consumption in most selected nations at stated quantiles of the data distribution. nonrenewable energy consumption is much more influenced by pandemic uncertainty than renewable energy consumption. furthermore, the rank of asymmetries across our variables differentiates by the economy, emphasizing the need for decisionmakers to pay much attention to pandemics-related uncertainty and the energy sector. 4. title: on the interconnected nature of risk and responsibility in the research and development of new and emerging technologies authors: yuwan malakar, justine lacey abstract: risk analysis of new and emerging technologies requires innovative approaches that are agile, exploratory, and can accommodate broad stakeholder engagement and perspectives. existing theories of risk governance and responsible innovation suggest that operationalizing guiding principles for engagement such as inclusion and reflection may provide a useful approach to the risk analysis of these technologies. yet, methodologies to systematically assess how we might operationalize such guiding principles in risk analysis are limited in existing risk research. we contribute to filling this gap by demonstrating a practical methodology for examining and documenting how research and development (r&d) professionals operationalize inclusion and reflection in risk analysis and what value this provides to risk analysis in the r&d context. we use the australian nanotechnology r&d sector as our case study, interviewing 28 experts to examine how r&d professionals have operationalized inclusion and reflection into their risk analysis practices, generating three findings. first, we describe how our research design enables the successful translation of theory into a methodology that supports an empirical assessment of the integration of these guiding principles into risk analysis practice. second, we argue that successfully and systematically integrating inclusion and reflection in risk analysis fosters a wider understanding and identification of risk through the activation of multi-actor and multi-institutional stakeholder engagement processes. third, we outline how this research depicts the outward-facing and introspective nature of risk analysis. 5. title: individual characteristics associated with perceptions of control over mortality risk and determinants of health effort authors: richard brown, elizabeth sillence, gillian pepper abstract: people who believe they have greater control over health and longevity are typically more likely to invest in their long-term health. investigating individual differences in perceived control over risk and exploring different determinants of health effort may help to tailor health promotion programs to more effectively encourage healthy behaviors. from a sample of 1500 adults, we measured perceived control over 20 causes of death, overall perceived uncontrollable mortality risk (pumr), state-level optimism, self-reported health effort, and the accuracy of estimations of avoidable deaths. we found individual differences in perceptions of control over specific causes of death based on age, gender, and income. pumr was predicted by socioeconomic variables expected to influence exposure to risk and resource availability. higher levels of pumr, not perceptions of control over specific causes of death, predicted self-reported health effort. the strength of relationship between pumr and lower health effort was not moderated by state-level optimism. age and education both positively predicted greater accuracy in assessing the prevalence of avoidable deaths. we suggest that pumr may capture people's �general sense� of mortality risk, influenced by both exposure to hazards and the availability of resources to avoid threats. conversely, perceived control over specific risks may involve more deliberate, considered appraisals of risk. this general sense of risk is thought to play a more notable role in determining health behaviors than specific assessments of control over risk. further study is needed to investigate the degree to which pumr accurately reflects objective measures of individual risk. 6. title: when increasing risk perception does not work. using behavioral psychology to increase smoke alarm ownership authors: patty jansen, chris snijders, martijn c. willemsen abstract: the central question of our study is which determinants drive smoke alarm ownership and intention to purchase one, and whether we can increase smoke alarm ownership by addressing these determinants in a communication-based intervention. we first made an inventory of possible determinants for smoke alarm prevention by consulting prominent prevention behavior theories protection motivation theory and health belief model and other relevant literature. we expanded this list of determinants based on interviews (n = 15) and used survey data representative for the netherlands to decide to focus on smoke alarm ownership (rather than installation or maintenance). we then tested the determinants of smoke alarm ownership and buying intention in a survey (n = 622). based on these results, we ran an a/b test (n = 310) of two messages to stimulate smoke alarm ownership: one emphasized the determinants we found to be strong predictors in the survey (know-how, social norm, annoyance) and one emphasized typical determinants that are often addressed in campaigns but were poor predictors in the survey (vulnerability, severity, benefits). results showed that the message based on the strong determinants resulted in a significant increase in smoke alarm ownership (9.1%) compared to the control group (0.9%; p = 0.027), while the message using the typical determinants did not lead to significant effects. taken together, our results give a promising direction for interventions to increase smoke alarm ownership, and above all, show that a comprehensive problem analysis for a specific target behavior is a necessary step to induce behavioral change. 7. title: general science-technology orientation, specific benefit�risk assessment frame, and public acceptance of gene drive biotechnology authors: xinsheng liu, carol l. goldsmith, ki eun kang, arnold vedlitz, zach n. adelman, leah w. buchman, elizabeth heitman, raul f. medina abstract: with limited understanding of most new biotechnologies, how do citizens form their opinion and what factors influence their attitudes about these innovations? in this study, we use gene drive biotechnology in agricultural pest management as an example and theoretically propose that given low levels of knowledge and awareness, citizens� acceptance of, or opposition to, gene drive is significantly shaped by two predisposition factors: individuals� general orientation toward science and technology, and their specific benefit-risk assessment frame. empirically, we employ data collected from a recent us nationally representative public opinion survey (n = 1220) and conduct statistical analyses to test the hypotheses derived from our theoretical expectations. our statistical analyses, based on various model specifications and controlling for individual-level covariates and state-fixed effects, show that citizens with a more favorable general orientation toward science and technology are more likely to accept gene drive. our data analyses also demonstrate that citizens� specific gene drive assessment frame�consisting of a potential benefit dimension and a potential risk dimension, significantly shapes their attitudes as well�specifically, people emphasizing more on the benefit dimension are more likely to accept gene drive, whereas those who place more importance on the risk dimension tend to oppose it. we discuss contributions of our study and make suggestions for future research in the conclusion. 8. title: a covid-19 cluster analysis in an office: assessing the long-range aerosol and fomite transmissions with infection control measures authors: atsushi mizukoshi, jiro okumura, kenichi azuma abstract: simulated exposure to severe acute respiratory syndrome coronavirus 2 in the environment was demonstrated based on the actual coronavirus disease 2019 cluster occurrence in an office, with a projected risk considering the likely transmission pathways via aerosols and fomites. a total of 35/85 occupants were infected, with the attack rate in the first stage as 0.30. it was inferred that the aerosol transmission at long-range produced the cluster at virus concentration in the saliva of the infected cases on the basis of the simulation, more than 108 pfu ml"1. additionally, all wearing masks effectiveness was estimated to be 61%�81% and 88%�95% reduction in risk for long-range aerosol transmission in the normal and fit state of the masks, respectively, and a 99.8% or above decline in risk of fomite transmission. the ventilation effectiveness for long-range aerosol transmission was also calculated to be 12%�29% and 36%�66% reductions with increases from one air change per hour (ach) to two ach and six ach, respectively. furthermore, the virus concentration reduction in the saliva to 1/3 corresponded to the risk reduction for long-range aerosol transmission by 60%�64% and 40%�51% with and without masks, respectively. 9. title: risk assessment for conventional diesel exhaust (before 1990) and lung cancer in a cohort of miners authors: robert m park abstract: diesel exhaust in the latter half of the 20th century has been found to be a lung carcinogen. conventional diesel emissions continue in the transportation, mining, construction, and farming industries. from the diesel exhaust in miners study, a public-use dataset was used to calculate the excess lifetime risk of lung cancer associated with diesel exposure (1947�1997). excess rates of lung cancer mortality associated with respirable elemental carbon (rec) and possible other mining exposures (e.g., oil mists, explosives emissions) were investigated using poisson regression methods. lung cancer mortality declined with increasing employment duration while increasing with cumulative rec and non-diesel exposures, suggesting a strong worker survivor effect. attenuation of the rec effect was observed with increasing cumulative exposure. after adjustment for employment duration, the excess rate ratio for lung cancer mortality was 0.67 (95% ci = 0.35 0.99) for a 10-year lagged exposure to 200 �g/m3 rec, a typical below-ground exposure in the study mines. at exposures of 200, 10, and 1 �g/m3 rec, the estimated excess lifetime risks, respectively, were 119, 43, and 8.7 per thousand. analysis of an inception cohort hired after dieselization commenced produced smaller and less certain estimates of lifetime risk. from exposures to conventional diesel engine exhaust common in occupational groups in the past, the excess lifetime risk of lung cancer was more than 5%. ambient rec exposures in the general population were estimated to confer lifetime risks of 0.14 to 14 per thousand, depending on assumptions made. 10. title: interdependent security games in a unidirectional network authors: edward c. rosenthal, christian trudeau abstract: we consider directed tree networks with a single source, where there exists a positive probability of a disruptive event at any node. such networks model security considerations in pipelines as well as in unidirectional digital networks. if a disruptive event occurs at a certain node, that node and its downstream nodes incur economic losses. users thus have an incentive to invest in upstream locations as well as their own sites to reduce the probability of a disruptive event. the initial model we develop to reduce the expected investment plus disruption costs is a multiplicative model for which closed-form solutions cannot be obtained in general. we overcome this problem with an additive model that we show closely approximates the initial formulation. this model reduces the security problem to a public goods setting where we minimize the total expected cost at each node. the users then need to share these costs in an equitable fashion, which gives rise to a set of cooperative games. for the case where disutilities to all users are identical, the shapley value can be computed efficiently, along the lines of an airport game. we also treat the case where risk reduction and disutility vary across the network. finally, we prove that the cooperative game is concave in this general case, which guarantees that the core of the game is nonempty and that the shapley value is an element of the core. 11. title: risk aggregation considering probabilistic and consequential interactions: a general formulation with computational cost handling authors: chunbing bao, meng cai, jianping li, qinyue zheng, dengsheng wu, qingchun meng abstract: complicated interaction between risk events is the critical obstacle preventing accurate risk aggregation, which is an important issue in risk management. recent research integrates interaction into risk aggregation with different perspectives and lacks a comprehensive discussion of this issue, making the risk aggregation process not universal for diverse cases, especially in subjective risk assessment contexts. therefore, this article proposes a theoretically convincing risk aggregation method embedding different types of interaction to support decision analysis more effectively. the main contributions of this article are as follows: (a) more in-depth and stricter definitions, measures, and graphical descriptions of different types of interaction are developed to ensure the accuracy of risk aggregation; (b) a formal risk aggregation approach that could apply in both objective and subjective risk assessment contexts while elegantly embedding risk interactions is proposed; (c) the additivity of risks and risk sets in the risk aggregation process is discussed in detail and the conditions for additivity are clarified; (d) the quasi-two/three-additive measures, which approximately obtain the aggregate risk value within sufficient reliability, are proposed to greatly reduce the computational cost. to examine the applicability of the proposed general risk aggregation method, a case study is finally presented to show the complete risk aggregation process and its application in the decision-making stage. 12. title: a machine learning�based generalized approach for predicting unauthorized immigration flow considering dynamic border security nexus authors: ridwan al aziz, tanvir ahmed, jun zhuang abstract: unauthorized immigration has been a long-standing and contentious challenge for developed and developing countries. numerous continually evolving push and pull factors across international borders, such as economy, employment, population density, unrest, corruption, and climate have driven this migration. large-scale pandemics such as covid-19, causing further instability in countries' financial well-being, can initiate or alter emigration flow from different countries. in light of such a complex confluence of factors, climate change, and demographic shifts in migrant communities, it is high time to shift toward machine learning�reinforced generalized approaches from the traditional parametric approaches based on migrant community�specific localized surveys. to our best knowledge, no literature has explored the nonparametric approach and developed a comprehensive database independent of localized surveys to analyze unauthorized migration. this article fills this gap by deploying nine nonparametric machine learning algorithms for predicting unauthorized immigration flow considering the dynamic border security nexus. this framework considers the seasonal autoregressive integrated moving average model as the null model. the proposed novel framework removes the dependency on localized survey-based studies and provides a more cost-effective, faster, and big data�friendly approach. this study finds the bayesian additive regression tree model as the best predictive model. 13. title: risk coupling analysis under accident scenario evolution: a methodological construct and application authors: jianting yao, boling zhang, dongdong wang, dachen lei, ruipeng tong abstract: dynamic processes in various fields exhibit risk coupling phenomena, but existing risk analysis studies tend to ignore the risk coupling effects of dynamic scenarios. considering the principles of digitization, objective quantification, and the full process that should be adopted in the risk coupling analysis, an integrated risk coupling analysis framework is proposed. specifically, the weighted eclat algorithm is used to mine the risk association rules, then the key risk factors are extracted by social network analysis, and the stochastic petri net is used to complete the construction, simulation, and evolution of accident scenarios. this universal framework can analyze the risk phenomena of accident scenario evolution in a process-oriented manner and decouple risks based on key risk factors and disconnect the chain of the accident scenario evolution process. finally, the proposed framework is applied to the coupled analysis of fire risk in chinese urban communities to verify its feasibility and scientific validity. 14. title: trust and trustworthy artificial intelligence: a research agenda for ai in the environmental sciences authors: ann bostrom, julie l. demuth, christopher d. wirz, mariana g. cains, andrea schumacher, �miranda white, john k. williams abstract: demands to manage the risks of artificial intelligence (ai) are growing. these demands and the government standards arising from them both call for trustworthy ai. in response, we adopt a convergent approach to review, evaluate, and synthesize research on the trust and trustworthiness of ai in the environmental sciences and propose a research agenda. evidential and conceptual histories of research on trust and trustworthiness reveal persisting ambiguities and measurement shortcomings related to inconsistent attention to the contextual and social dependencies and dynamics of trust. potentially underappreciated in the development of trustworthy ai for environmental sciences is the importance of engaging ai users and other stakeholders, which human�ai teaming perspectives on ai development similarly underscore. co-development strategies may also help reconcile efforts to develop performance-based trustworthiness standards with dynamic and contextual notions of trust. we illustrate the importance of these themes with applied examples and show how insights from research on trust and the communication of risk and uncertainty can help advance the understanding of trust and trustworthiness of ai in the environmental sciences. 15. title: spatiotemporal multi-graph convolutional network-based provincial-day-level terrorism risk prediction authors: lanjun luo, boxiao li, chao qi abstract: predicting terrorism risk is crucial for formulating detailed counter-strategies. however, this task is challenging mainly because the risk of the concerned potential victim is not isolated. terrorism risk has a spatiotemporal interprovincial contagious characteristic. the risk diffusion mechanism comes from three possibilities: cross-provincial terrorist attacks, internal and external echoes, and internal self-excitation. this study proposed a novel spatiotemporal graph convolutional network (stgcn)-based extension method to capture the complex and multidimensional non-euclidean relationships between different provinces and forecast the daily risks. specifically, three graph structures were constructed to represent the contagious process between provinces: *.>@dlrtvxz\^p��ʸʸʸ��wobbtf9tthj�5�ojqj^jo(h��h��5�ojqj^jh�"�hu<�5�ojqj^jh�ud5�ojqj^jo(h�"�h�"�o(&h�"�h�"�5�cjojqj^jajo(ht6o5�cjojqj^jajh@ t5�cjojqj^jajh 2e5�cjojqj^jaj#h: !h: !5�cjojqj^jaj#h�"�h�"�5�cjojqj^jaj h$-�5�cjojqj^jajo(#h��h��5�cjojqj^jajxz\�� vw�@ ��8#9#�#�#�*�*��gd�psgd)w�gd$?�gdto�gd�l$gd%j,gdu<�gd�"�$a$gdt4�� > p v l � � � � � � � �� $%��˽��|�n^||�nn^|hvi�h�l$5�ojqj^jo(h�^�h�^�5�ojqj^jh�l$h�l$5�ojqj^jh�l$5�ojqj^jo(hj�5�ojqjo(hiht4ojqj^jo(h��h��ojqj^jhihj�ojqj^jo(h�"�hu<�5�ojqj^jht45�ojqj^jo(h��h��5�ojqj^jhicy5�ojqj^j!��uvwxyz`a��*?@ij�� 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and the self-excited graph. the long short-term memory and self-attention layers were extended to stgcn for capturing context-dependent temporal characters. at the same time, the one-dimensional convolutional neural network kernel with the gated linear unit inside the classical stgcn can model single-node-dependent temporal features, and the spectral graph convolution modules can capture spatial features. the experimental results on afghanistan terrorist attack data from 2005 to 2020 demonstrate the effectiveness of the proposed extended stgcn method compared to other machine learning prediction models. furthermore, the results illustrate the crucial of capturing comprehensive spatiotemporal correlation characters among provinces. based on this, this article provides counter-terrorism management insights on addressing the long-term root causes of terrorism risk and performing short-term situational prevention. 01�82p��. ��a!�"�#��$��%��s��x2�� 0@p`p��2(�� 0@p`p�� 0@p`p�� 0@p`p�� 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