Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

A KNOWLEDGE-BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS

A knowledge-based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause-effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation-tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.     

Geometric sample size determination in Bayesian analysis

The problem of sample size determination in the context of Bayesian analysis is considered. For the familiar and practically important parameter of a geometric distribution with a beta prior, three different Bayesian approaches based on the highest posterior density intervals are discussed. A computer program handles all computational complexities and is available upon request.     

Internet Poker Websites and Pathological Gambling Prevention Policy

Despite the widespread increase in online poker playing and the risk related to excessive poker playing, research on online poker websites is still lacking with regard to pathological gambling prevention strategies offered by the websites. The aim of the present study was to assess the pathological gambling-related prevention strategies of online poker websites. Two keywords (“poker” and “poker help”) were entered into two popular World Wide Web search engines. The first 20 links related to French and English online poker websites were assessed. Seventy-four websites were assessed with a standardized tool designed to rate sites on the basis of accountability, interactivity, prevention strategies, marketing, and messages related to poker strategies. Prevention strategies appeared to be lacking. Whereas a substantial proportion of the websites offered incitation to gambling such as betting “tips,” few sites offered strategies to prevent or address problem gambling. Furthermore, strategies related to poker, such as probability estimation, were mostly reported without acknowledging their limitations. Results of this study suggest that more adequate prevention strategies for risky gambling should be developed for online poker.     

A Preliminary Investigation of Factors Associated With Job Loss Grief

This study investigated relationships among factors hypothesized as related to job loss grief. A summary grief score correlated positively with time since job loss and number of dependents, and negatively with length of notice. Perceived reemployment prospects and income loss related positively to some grief index subscales, as did the condition of living on one's own. Job duration correlated negatively with some grief responses. Implications for counseling and avenues for future research are discussed.     

Behavioural criteria of managerial and leadership effectiveness within Egyptian and British public sector hospitals: an empirical case study and multi-case/cross-nation comparative analysis

This paper reports the results of a study of managerial and leadership effectiveness carried out within an Egyptian public sector hospital in which concrete examples of ‘effective’ and ‘least effective/ineffective’ manager and managerial leader behaviour, as observed by superiors, peers and subordinates, were collected using the critical incident technique. These critical incidents were then content analyzed to identify a smaller number of discrete behavioural statements and criteria of effectiveness. The paper also reports the results of a subsequent comparative analysis of these Egyptian findings against equivalent behavioural criteria that emerged from studies in two different British NHS Trust hospitals. This latter multi-case/cross-nation study revealed high degrees of overlap, commonality, and relative generalization across all three organizations. The results lend strong empirical support to those who believe in ‘generic’ and ‘universalistic’ explanations of the nature of managerial and leadership effectiveness.     

A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards

The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non–English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.     

Alpha power Weibull distribution: Properties and applications

In this paper, a new lifetime distribution is defined and studied. We refer to the new distribution as alpha power Weibull distribution. The importance of the new distribution comes from its ability to model monotone and non monotone failure rate functions, which are quite common in reliability studies. Various properties of the proposed distribution are obtained including moments, quantiles, entropy, order statistics, mean residual life function, and stress-strength parameter. The maximum likelihood estimation method is used to estimate the parameters. Two real data sets are used to illustrate the importance of the proposed distribution.     

On Bayesian sample size determination

Three Bayesian methods are considered for the determination of sample sizes for sampling from the Laplace distribution – the distribution of time between rare events – with a normal prior. These methods are applied to the sizing of aircraft mid-air collisions in a navigation system or large flight path deviations of aircraft in air traffic management scenarios. A computer program handles all computations and gives a good insight about the best suggested method.     

Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

Given the ubiquitous nature of infrastructure networks in today's society, there is a global need to understand, quantify, and plan for the resilience of these networks to disruptions. This work defines network resilience along dimensions of reliability, vulnerability, survivability, and recoverability, and quantifies network resilience as a function of component and network performance. The treatment of vulnerability and recoverability as random variables leads to stochastic measures of resilience, including time to total system restoration, time to full system service resilience, and time to a specific α% resilience. Ultimately, a means to optimize network resilience strategies is discussed, primarily through an adaption of the Copeland Score for nonparametric stochastic ranking. The measures of resilience and optimization techniques are applied to inland waterway networks, an important mode in the larger multimodal transportation network upon which we rely for the flow of commodities. We provide a case study analyzing and planning for the resilience of commodity flows along the Mississippi River Navigation System to illustrate the usefulness of the proposed metrics.