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To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

This study aims to improve the reliability of emergency safety barriers by using the subjective safety analysis based on evidential reasoning theory in order to develop on a framework for optimizing the reliability of emergency safety barriers.

The emergency event tree analysis is combined with an interval type-2 fuzzy-set and analytic hierarchy process (AHP) method. In order to the quantitative data is not available, this study based on interval type2 fuzzy set theory, trapezoidal fuzzy numbers describe the expert's imprecise uncertainty about the fuzzy failure probability of emergency safety barriers related to the liquefied petroleum gas storage prevent. Fuzzy fault tree analysis and fuzzy ordered weighted average aggregation are used to address uncertainties in emergency safety barrier reliability assessment. In addition, a critical analysis and some corrective actions are suggested to identify weak points in emergency safety barriers. Therefore, a framework decisions are proposed to optimize and improve safety barrier reliability. Decision-making in this framework uses evidential reasoning theory to identify corrective actions that can optimize reliability based on subjective safety analysis.

A real case study of a liquefied petroleum gas storage in Algeria is presented to demonstrate the effectiveness of the proposed methodology. The results show that the proposed methodology provides the possibility to evaluate the values of the fuzzy failure probability of emergency safety barriers. In addition, the fuzzy failure probabilities using the fuzzy type-2 AHP method are the most reliable and accurate. As a result, the improved fault tree analysis can estimate uncertain expert opinion weights, identify and evaluate failure probability values for critical basic event. Therefore, suggestions for corrective measures to reduce the failure probability of the fire-fighting system are provided. The obtained results show that of the ten proposed corrective actions, the corrective action “use of periodic maintenance tests” prioritizes reliability, optimization and improvement of safety procedures.

This study helps to determine the safest and most reliable corrective measures to improve the reliability of safety barriers. In addition, it also helps to protect people inside and outside the company from all kinds of major industrial accidents. Among the limitations of this study is that the cost of corrective actions is not taken into account.

Our contribution is to propose an integrated approach that uses interval type-2 fuzzy sets and AHP method and emergency event tree analysis to handle uncertainty in the failure probability assessment of emergency safety barriers. In addition, the integration of fault tree analysis and fuzzy ordered averaging aggregation helps to improve the reliability of the fire-fighting system and optimize the corrective actions that can improve the safety practices in liquefied petroleum gas storage tanks.

In 2009, the Third Circuit decided Hydrogen Peroxide, which announced a more rigorous standard under Federal Rule of Civil Procedure 23(b)(3) for assessing whether a putative class could establish antitrust injury. Earlier this year, the Supreme Court decided Comcast v. Behrend, a case that carries potentially broad implications for both antitrust cases and Rule 23(b)(3) class actions generally. A review of the case law starting with Hydrogen Peroxide and continuing through Comcast and its progeny reveals the new rigor in antitrust class action decisions and suggests what the future may hold, including the type of arguments that may provide defendants the most likely chance of defeating class certification. After Comcast, rigor under 23(b)(3) can no longer be avoided in assessing all class actions questions, and courts should now apply Daubert fully in the class setting concerning both impact and damages. Courts should also closely evaluate plaintiffs’ proposed methodologies for proving impact to determine if they apply to each class member. Finally, courts will inevitably have to determine how rigorously to scrutinize experts’ damages methodologies and whether Comcast requires or suggests more scrutiny in assessing common evidence for measuring damages.

The purpose of this paper is to present a multi‐expert system that can provide designers with suggestions for improvement. The multi‐expert system can analyse a design and provide designers with ideas for changes to designs at an early stage in order to improve assembly later in the manufacturing process.

The whole system consists of four expert systems: computer‐aided design (CAD) expert, automated assembly expert, manual assembly expert and design analysis expert. The design analysis expert includes a sub‐system to collate the information from the assembly experts and to provide costs and advice.

The paper finds that the approach and the systems can reduce manufacturing costs and lead times.

A knowledge‐based reckoning approach to design‐for‐assembly automation is used. The approach and systems can reduce manufacturing costs and lead times. The system can estimate assembly time and cost for manual or automatic assembly and select suitable assembly techniques.

The system can estimate assembly time and cost for manual or automatic assembly and select a suitable assembly technique.

The new system models assembly, product and process design using a natural approach for capturing intelligence. The new approach categorised automated assembly and manual assembly into separate individual experts. Intelligence and knowledge from each is captured and embedded within the individual expert that represented the process. This approach enabled greater flexibility and made the sub‐systems easier to modify, upgrade, extend and reuse.

This paper includes three analyses concerning: expert support in the selection of impact variables for scientific models relevant to environmental planning, the quality of students’ individual estimates of corresponding impacts before and after a group discussion, and the accuracy of artificially‐aggregated judgments of independent groups. Participants were students of environmental sciences at ETH Zurich. The first analysis revealed that during participation in an environmental case study, students’ individual estimates of impacts of variables which have been suggested by experts increased, as compared to the estimates of impacts of additional variables, which have been selected by the students. The remaining analyses consider group discussions on the strength of particular environmental impacts. The quality of the estimates was analyzed referring to expert estimates of the impacts.

Civil engineering structures are regularly confronted with failures that can lead to catastrophic consequences. It is important, after a failure, to be able to identify the origin and the sequence of factors that led to it. This failure analysis by experts, called forensic engineering investigation, generally leads to the drafting of an expert report. These reports do not inform on the processes that guided the experts to a conclusion and the uncertainties involved. This paper aims to propose a new methodological approach to formalize the opinions of experts in forensic engineering.

The research consists in combining abstract argumentation with the theory of imprecise probabilities to take into account epistemic and stochastic uncertainties to support forensic engineering investigation.

A model and a tool to support forensic analysis are presented. An application on the collapse of the Brumadinho dam highlights the interest of the chosen approach.

This work is the first use of the abstract argument framework in civil engineering, and so in forensic engineering. Furthermore, it provides an innovative model based on imprecise probability for AAF.

International construction joint ventures (ICJVs) are an effective strategy for construction companies worldwide for delivering large and complex projects. Despite numerous ICJVs studies, there is a lack of comprehensive empirical examination of what drives ICJVs implementation. This study aims to investigate the key drivers for implementing ICJVs through an international survey.

Grounded on a comprehensive literature review and structured questionnaire survey, 123 ICJV experts' responses from 24 different countries/jurisdictions were analyzed using inferential and descriptive statistics. Mann–Whitney U test was used to determine any divergence of ranking of the drivers by the experts. Factor analysis (FA) was used to identify the clusters underlying the key drivers. Rank agreement analysis was later used to investigate the consensus between experts from developing and developed countries/jurisdictions on their ranking of the clusters.

Out of 34 factors, 26 factors greatly drive the implementation of ICJVs. Mann–Whitney U test results prove the absence of significant disparity among the experts in the ranking of the drivers. Six clusters were obtained through factor analysis (FA), namely, market-penetration and innovation-driven drivers, legal and market-driven drivers, fiscal incentives and market expansion drivers, personal branding drivers, sustainable advantage/power drivers and industrial and organizational promotion drivers. Rank agreement analysis exhibited varied levels of concurrence between professionals from developed and developing countries/jurisdictions.

The appreciation of the factors motivating ICJVs is beneficial to the successful implementation of ICJV strategies. A clear understanding of the drivers can help practitioners and policymakers to customize their ICJVs to reap the expected benefits.

The study has generated valuable insights into the factors that are greatly driving the implementation of ICJVs worldwide. While the findings of this study provide a profound contribution to theory and practice, it contributes to sustainable growth in different perspectives.

The purpose of this paper is to compare various linear opinion pooling models for aggregating probability judgments and to determine whether Cooke's performance weighting model can sift out better calibrated experts and produce better aggregated distribution.

The leave‐one‐out cross‐validation technique is adopted to perform an out‐of‐sample comparison of Cooke's classical model, the equal weight linear pooling method, and the best expert approach.

Both aggregation models significantly outperform the best expert approach, indicating the need for inputs from multiple experts. The performance score for Cooke's classical model drops considerably in out‐of‐sample analysis, indicating that Cooke's performance weight approach might have been slightly overrated before, and the performance weight aggregation method no longer dominantly outperforms the equal weight linear opinion pool.

The results show that using seed questions to sift out better calibrated experts may still be a feasible approach. However, because the superiority of Cooke's model as discussed in previous studies can no longer be claimed, whether the cost of extra efforts used in generating and evaluating seed questions is justifiable remains a question.

Understanding the performance of various models for aggregating experts' probability judgments is critical for decision and risk analysis. Furthermore, the leave‐one‐out cross‐validation technique used in this study achieves more objective evaluations than previous studies.

This study aims to detect the most appropriate delay analysis method in mega airport projects.

First, the criteria affecting the selection of delay analysis methods were detected through an in-depth literature review and an expert panel, which was conducted with 12 experts who have experience in delay analysis domain in mega airport projects. Later, fuzzy VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) approach was conducted by considering the detected selection criteria and the most common delay analysis methods.

Windows Analysis method was detected as the best option for mega airport projects. It was followed by Time Impact Analysis (TIA), collapsed as-built analysis, as-planned vs as-built method and impacted as-planned method, respectively.

Each project has its own characteristics and thus requires specific management techniques; therefore, selecting a delay analysis method without considering the project types and size may cause conflicts between the contracting parties. On the one hand, numerous fruitful studies concerning delay analysis methods have been conducted in the literature, but on the other hand, none of them has considered project characteristics in terms of project size and type while selecting the most appropriate delay analysis method. Moreover, the larger the size of a project is, the more vulnerable it is to encounter with delays. Mega airport construction projects are complex in their nature in that they are large size and involve multi-disciplinary processes; thus, they need special attention in the process of resolving delays. This study intended to fill this gap in the literature by focusing on selection of the most appropriate delay analysis method for mega airport projects, and it is clear that considering the project type and size in the selection of delay analysis methods will provide more reliable outcomes.

Modern societies are imbued with a fundamental tension of expertise, as expert status is both a source of authority and channel of wider public trust. Scholars of expertise have shown, though, that the public often lacks trust in experts, something which often occurs alongside politicized social problems. I argue that there are contexts in which expert–public interactions may facilitate trust-building processes even amidst the politicization of problems in which experts are attempting to manage. I refer to this as “negotiated expertise,” when communities with divergent sensibilities of problems (re)construct the rules and norms of expertise in ways that build trust and facilitate cooperative and collective action. This builds on an interactionist understanding of trust and expertise, focusing on the ways in which communities negotiate the meanings, rules, and norms of expert settings. Through a qualitative analysis of Miami's Sea Level Rise Committee, I identify two key factors that facilitate trust-building in expert–public interactions: an emergent socioenvironmental problem and “advocacy-experts.” I suggest that these contexts and factors enabled Miamians to work toward reciprocal practices and understandings, unexpectantly building trust in a politicized setting.