An Optimization‐Based Framework for the Identification of Vulnerabilities in Electric Power Grids Exposed to Natural Hazards

This article proposes a novel mathematical optimization framework for the identification of the vulnerabilities of electric power infrastructure systems (which is a paramount example of critical infrastructure) due to natural hazards. In this framework, the potential impacts of a specific natural hazard on an infrastructure are first evaluated in terms of failure and recovery probabilities of system components. Then, these are fed into a bi‐level attacker–defender interdiction model to determine the critical components whose failures lead to the largest system functionality loss. The proposed framework bridges the gap between the difficulties of accurately predicting the hazard information in classical probability‐based analyses and the over conservatism of the pure attacker–defender interdiction models. Mathematically, the proposed model configures a bi‐level max‐min mixed integer linear programming (MILP) that is challenging to solve. For its solution, the problem is casted into an equivalent one‐level MILP that can be solved by efficient global solvers. The approach is applied to a case study concerning the vulnerability identification of the georeferenced RTS24 test system under simulated wind storms. The numerical results demonstrate the effectiveness of the proposed framework for identifying critical locations under multiple hazard events and, thus, for providing a useful tool to help decisionmakers in making more‐informed prehazard preparation decisions.     

Media Exposure to Terrorism and Perception of Immigrants as a Threat: The Role of Emotional Intelligence and Psychophysiological Self-Regulation

To better understand how media exposure to terrorism-related images can lead to perceiving immigrants as more threatening, in the present study we manipulated participants’ exposure to media coverage of terrorist attacks and investigated how this may influence people's perception of Arab immigrants. Considering the important role of regulatory abilities when facing stressful events like terrorist attacks, we measured individual differences in both trait emotional intelligence and resting heart rate variability (HRV). Results showed that participants perceived Arab immigrants as more threatening in the media exposure condition than in the control condition. Importantly, there were moderating effects of both trait emotional intelligence and HRV. People with lower trait emotional intelligence or lower HRV at rest felt more threatened in the media exposure condition compared to the control condition, whereas this effect was not observed among participants with higher trait emotional intelligence or higher resting HRV. The present study highlights some of the complexities related to how media exposure to terrorism-related images influences people's reactions to, and evaluations of, an outgroup that is related to the perpetrators of the attacks.     

When the main job tasks are perceived to be ‘irrelevant’ in the workplace: the internal uselessness of corporate social responsibility work in Japan

ABSTRACT

Despite a symbolic shift toward ‘emotional taint’ in dirty work literature, the role of the workplace has not been studied in relation to socially admired professions, such as corporate social responsibility (CSR) work. This article carries out an in-depth, critical examination of CSR as an emotionally tainted occupation in Japan. Its findings, substantiated by an analysis of 34 CSR workers’ rhetoric, help conceptualise ‘internal uselessness’. This emerges when workers feel their organisations publicly foster an image of their work that is decoupled from its internal reality, assigning them chief tasks they consider irrelevant. This leads to negative consequences that damage their workplace social relationships, professional aspirations and emotional well-being. The findings ultimately show that these CSR workers in Japan attempt to counterbalance internal uselessness through a social quest with peers outside their workplace, but also manage their emotions by rationalising their job status as inescapable, influenced by situated commitment norms.     

The Effect of Cultural Capital on High School Dropout: An Investigation in the Italian Provinces

This article studies at a detailed geographical level the relation between cultural capital and high school dropout. Bronfenbrenner’s systemic theory and Heckman’s perspective on cognitive/non-cognitive skills are considered as theoretical framework. We analyzed data from 103 Italian provinces employing Covariance Structure Analysis and spatial indices of autocorrelation. We found a consistent protective effect of cultural capital on dropout, independently of economic performance, in Central and Southern provinces, but not in Northern provinces. Spatial analyses showed very heterogeneous patterns of autocorrelation for dropout (especially across Southern provinces) even between neighboring areas, in spite of a more compact clustering when considering cultural and economic indicators. These results indicate that living in an environment with animated cultural life might enhance students’ non-cognitive skills, thus fostering their involvement in formative activities and the development of their human capital.     

The MIMIC–CUB Model for the Prediction of the Economic Public Opinions in Europe

Social Indicators Research - To study the Europeans’ perception on the economic conditions, a model that combine Multiple Indicators Multiple Causes (MIMIC) and Combination of Uniform and...     

Assessing the Performance of a Classification‐Based Vulnerability Analysis Model

In this article, a classification model based on the majority rule sorting (MR‐Sort) method is employed to evaluate the vulnerability of safety‐critical systems with respect to malevolent intentional acts. The model is built on the basis of a (limited‐size) set of data representing (a priori known) vulnerability classification examples. The empirical construction of the classification model introduces a source of uncertainty into the vulnerability analysis process: a quantitative assessment of the performance of the classification model (in terms of accuracy and confidence in the assignments) is thus in order. Three different app oaches are here considered to this aim: (i) a model–retrieval‐based approach, (ii) the bootstrap method, and (iii) the leave‐one‐out cross‐validation technique. The analyses are presented with reference to an exemplificative case study involving the vulnerability assessment of nuclear power plants.     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.     

The Construction of a Synthetic Index Comparing Multidimensional Well-Being in the European Union

For many years, the quantification and measurement of level of well-being in a society has become an object of study by researchers, economists, international organizations and institutions. The purpose of these researches and applications is mainly the collection of data as accurate and complete as possible, dictating the paths of economic and social development policies, in order to help the economic problem of allocating scarce resources within a community, where not all individual needs can be fully met. The present work is intended as a part of that field. It will undertake the construction of a composite index of multidimensional well-being, through an aggregation of data, able to balance the trade-off between immediacy and completeness of information and to trespass the limits that characterize the commonly used income related measures. The method of factor analysis, which aims at detecting a statistically sufficient number of variables, is used to represent most of the explained variance of the phenomenon. Results are tested with different aggregative processes. This analysis is applied to the reality of the European Union, characterized by deep transformation and cultural, economic and social inequalities.     

Asymptotic relative efficiency of wald tests in measurement error models

In this paper, asymptotic relative efficiency (ARE) of Wald tests for the Tweedie class of models with log-linear mean, is considered when the aux¬iliary variable is measured with error. Wald test statistics based on the naive maximum likelihood estimator and on a consistent estimator which is obtained by using Nakarnura's (1990) corrected score function approach are defined. As shown analytically, the Wald statistics based on the naive and corrected score function estimators are asymptotically equivalents in terms of ARE. On the other hand, the asymptotic relative efficiency of the naive and corrected Wald statistic with respect to the Wald statistic based on the true covariate equals to the square of the correlation between the unobserved and the observed co-variate. A small scale numerical Monte Carlo study and an example illustrate the small sample size situation.     

Exploring the relationship between product-service system and profitability

Journal of Management and Governance - Over the last few decades there has been a significant change in the economic output worldwide, and services have become more and more important....