A new aging concept derived from the increasing convex ordering

In this paper, a comparison between the life distribution of a new unit with that of a used unit in the increasing convex order is made leading to a new class of life distributions which we call “new better than used in convex ordering of second order”. This class includes as subclasses the NBU and the NBUC and is a subclass of the NBUCA class. Preservation properties under convolution, random maxima, mixing and formation of coherent structures are established. Stochastic comparisons of the excess lifetime when the inter-arrival times belong to the NBUC(2) class are developed. Some applications of Poisson shock models and a test of exponentiality against NBUC(2) alternative are presented.     

Multiple facility location on a network with linear reliability order of edges

We study the problem of locating facilities on the nodes of a network to maximize the expected demand serviced. The edges of the input graph are subject to random failure due to a disruptive event. We consider a special type of failure correlation. The edge dependency model assumes that the failure of a more reliable edge implies the failure of all less reliable ones. Under this dependency model called Linear Reliability Order (LRO) we give two polynomial time exact algorithms. When two distinct LRO’s exist, we prove the total unimodularity of a linear programming formulation. In addition, we show that minimizing the sum of facility opening costs and expected cost of unserviced demand under two orderings reduces to a matching problem. We prove NP-hardness of the three orderings case and show that the problem with an arbitrary number of orderings generalizes the deterministic maximum coverage problem. When a demand point can be covered only if a facility exists within a distance limit, we show that the problem is NP-hard even for a single ordering.     

Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams

Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system. To this end, we model the performance of Gilroy, CA, a moderate‐size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures. The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.     

Personal sacrifice and corporate cultures: career progression for disabled staff in higher education

Disabled people are under-represented in higher education (HE), especially in senior posts. This article reports research on the perspectives of career progression into leadership held by disabled staff in one post-1992 university. Findings indicated that some participants were already engaged in leadership or aspired to such roles, and reported positive experiences. However, participants also experienced barriers to progression, including a lack of awareness of equality and diversity among managers and colleagues, inadequate professional development opportunities and the competitive organisational culture of management that could impact on their health and work–life balance. We conclude that disabled staff in HE do not yet have equal opportunities for progression into leadership roles compared with their non-disabled peers. There is a need for realignment of the culture of leadership and management to make it more compatible with the full inclusion of disabled staff in HE such that their unique contributions are valued.     

Making Sense of Neoliberal Subjectivity: A Discourse Analysis of Media Language on Self-development

The influence of neoliberalism on culture and subjectivity is well documented. This paper contributes to understanding of how neoliberal ideology enters into the production of subjectivity. While subject formation takes place in multiple and contradictory ways and across multiple social sites, we focus on the increasingly popular media discourse of self-development, and examine it as a technology of neoliberal subjectification. Drawing on Foucauldian understandings, we analyze data from two different newspapers from two different national contexts, both of which are heavily influenced by neoliberalism. Based on our analysis, we detail four interrelated discourses—rationality, autonomy and responsibility, entrepreneurship, and positivity and self-confidence—demonstrating how these discourses constitute the neoliberal subject in ways consonant with neoliberal governmentality. There is no observable resistance to subject positions offered within these discourses. Self-development discourse instills stronger individualism in society, while constraining collective identity, and thus provides social control and contributes to preserving status quo of neoliberal societies.     

An empirical investigation of managerial achievement,job statisfaction and values: An informational perspective

Provision of appropriate information and feedback to managers is crucial for the success of an organization. This study examines the availability and desirability of various informational feedback mechanisms to a group of managers in Saudi Arabia. Study results highlight some interesting differences among managers with varying value orientations and satisfaction profiles in terms of their informational needs. Implications of the findings are discussed.     

Optimal design of the adaptive exponentially weighted moving average control chart over a range of mean shifts

The adaptive exponentially weighted moving average (AEWMA) control chart is a smooth combination of the Shewhart and exponentially weighted moving average (EWMA) control charts. This chart was proposed by Cappizzi and Masarotto (2003) to achieve a reasonable performance for both small and large shifts. Cappizzi and Masarotto (2003) used a pair of shifts in designing their control chart. In this study, however, the process mean shift is considered as a random variable with a certain probability distribution and the AEWMA control chart is optimized for a wide range of mean shifts according to that probability distribution and not just for a pair of shifts. Using the Markov chain technique, the results show that the new optimization design can improve the performance of the AEWMA control chart from an overall point of view relative to the various designs presented by Cappizzi and Masarotto (2003). Optimal design parameters that achieve the desired in-control average run length (ARL) are computed in several cases and formulas used to find approximately their values are given. Using these formulas, the practitioner can compute the optimal design parameters corresponding to any desired in-control ARL without the need to apply the optimization procedure. The results obtained by these formulas are very promising and would particularly facilitate the design of the AEWMA control chart for any in-control ARL value.     

Fortune d’une catégorie : la souffrance au travail chez les médecins du travail

For about 10 years now in France, doctors in occupational medicine have been using the category “suffering at work” to refer to what they consider to be new pathologies at the workplace. This category's diffusion in industrial medicine reveals the influence of a current in psychology (the “psychodynamics of work”) on these doctors. A qualitative study carried out with workplace doctors shows how a large percentage of them have appropriated this category. An active — and activist — fraction has wielded it to defend a new conception of industrial medicine's role, which centered around clinical practices, should pay more attention to workers’ subjective sense of suffering. In a context where the institutional prospects of industrial medicine are a cause of concern and where feelings of a lack of esteem have been revived in a profession that, since its origins, has been looking for legitimacy, the category of work-related suffering enables these doctors to win new territory and breathing room by transforming their line of work.     

A Comparison of the Performance of Phase II Simple Linear Profile Control Charts when Parameters are Estimated

The standard deviation of the average run length (SDARL) is an important performance metric in studying the performance of control charts with estimated in-control parameters. Only a few studies in the literature, however, have considered this measure when evaluating control chart performance. The current study aims at comparing the in-control performance of three phase II simple linear profile monitoring approaches; namely, those of Kang and Albin (2000), Kim et al. (2003), and Mahmoud et al. (2010). The comparison is performed under the assumption of estimated parameters using the SDARL metric. In general, the simulation results of the current study show that the method of Kim et al. (2003) has better overall statistical performance than the competing methods in terms of SDARL values. Some of the recommended approaches based solely on the usual average run length properties can have poor SDARL performance.     

The Effect of Methods for Handling Missing Values on the Performance of the MEWMA Control Chart

This article is concerned with the effect of the methods for handling missing values in multivariate control charts. We discuss the complete case, mean substitution, regression, stochastic regression, and the expectation–maximization algorithm methods for handling missing values. Estimates of mean vector and variance–covariance matrix from the treated data set are used to build the multivariate exponentially weighted moving average (MEWMA) control chart. Based on a Monte Carlo simulation study, the performance of each of the five methods is investigated in terms of its ability to obtain the nominal in-control and out-of-control average run length (ARL). We consider three sample sizes, five levels of the percentage of missing values, and three types of variable numbers. Our simulation results show that imputation methods produce better performance than case deletion methods. The regression-based imputation methods have the best overall performance among all the competing methods.