Optimal design and maintenance of a repairable multi-state system with standby components

The configuration of a repairable system directly influences its performance measures, such as mean time between failures and steady state availability. Additionally, maintenance strategies such as corrective, preventive, and condition-based can affect the performance of the system. The objective of this work is to investigate the trade-offs between the configuration of a repairable multi-state system with binary components and its maintenance strategy. The corresponding stochastic process for the proposed model is formulated using the continuous-time Markov process and important performance measures of such a multi-state system are derived. An optimization model is introduced for the cost-effective design of this repairable multi-state system. The results are demonstrated using a numerical example for a power generation system.     

A Feasibility Study of Implementing the Policies on Increasing Birth Rate with an Emphasis on Socio-economic Status: A Case Study of Kermanshah Metropolis,Western Iran

Population and development have a mutual relationship, and more to the point, lack of sufficient knowledge on population development and fertility can lead to the presentation of inappropriate population plans in such a way that they may turn out to be useless and ineffective even in the event of implementation. So, the present study aimed to delve into the feasibility of implementing the new governmental policies on increasing birth rate with an emphasis on the socioeconomic status in Kermanshah Metropolis, Iran. To evaluate poverty and fertility in Kermanshah Metropolis, the present cross-sectional study used the latest statistics obtained from the Statistical Center of Iran (2011), and as for the data analysis, such tests in Arc/GIS and SPSS 20 software. The results of the present study showed that the spatial patterns of poverty and fertility were formed in clusters across the city, and the results of variance analysis of the relationship between the variables of fertility and poverty demonstrated that there was a significant difference between the selected neighborhoods in terms of the variables of poverty and total fertility (P < 0.001). Furthermore, the spatial autocorrelations of fertility and poverty in Kermanshah were positive and showed that the spatial means and standard distances of poverty and fertility were overlapping. Not all districts and urban neighborhoods were equal in the total fertility rate. So, given the societal classes’ different socioeconomic and cultural status across different neighborhoods, the government’s new approaches to increasing birthrate cannot be applied to all classes throughout Kermanshah Metropolis.

     

Comparison of different estimation methods in growth curve models for categorical data: A simulation study

This simulation study aims at investigating the performance of maximum likelihood and weighted least-square estimation approaches in growth curve models with categorical data. The goodness-of-fit indices were compared with a number of scenarios (different trajectories, sample sizes, replications, and number of categories). The results show that when the number of categories and replications are small, using weighted least-square estimating methods leads to better goodness-of-fit indices. However, when the number of categories and replications are large, both maximum likelihood and weighted least squares in estimating methods will result in similar fit indices.     

Simultaneous arrival of customers to two different queues and modeling dependence via copula approach

ABSTRACT

In classical queueing systems, a customer is allowed to wait only in one queue to receive the service. In practice, when there exist a number of queues rendering the same service, some customers may tend to simultaneously take turn in more than one queue with the aim to receive the service sooner and thus reduce their waiting time. In this article, we introduce such a model and put forward a methodology to deal with the situation. In this regard, we consider two queues and assume that if a customer, who has turn in both queues, receives the service from one of the queues, the other turn is automatically withdrawn. This circumstance for the model brings about some abandonment in each queue as some customers receive the service from the other one. We study the customer’s waiting time in the mentioned model, which is defined as the minimum of waiting times in both queues and obtain probability density function of this random variable. Our approach to obtain probability density function of each of the waiting time random variables is to rely on the existing results for the abandonment case. We examine the situation for the cases of independence and dependence of the waiting time random variables. The latter is treated via a copula approach.     

Determinants of voluntary CSR disclosure: empirical evidence from Germany

Currently, companies spend a great deal of effort on Corporate Social Responsibility (CSR) disclosures. CSR disclosure relates to the provision of information on companies’ environmental and social performance. From an economic perspective, companies might disclose this information to avoid or decrease potential political costs. We construct a CSR disclosure index based on the Global Reporting Initiative (GRI) guidelines. Using content analysis, we analyze 130 listed German companies’ CSR disclosures (470 firm-year observations) to investigate the determinants of these voluntary disclosure activities. Our results show that, consistent with the political cost theory, German companies’ disclosures of all CSR issues are affected by their visibility, shareholder structure, and relationship with their US stakeholders. In addition, higher profitability is associated with more environmental disclosures. Finally, size and industry membership affect the amount of CSR disclosure.     

An efficient Bayesian approach for Gaussian Bayesian network structure learning

This article proposes a Bayesian computing algorithm to infer Gaussian directed acyclic graphs (DAGs). It has the ability of escaping local modes and maintaining adequate computing speed compared to existing methods. Simulations demonstrated that the proposed algorithm has low false positives and false negatives in comparison to an algorithm applied to DAGs. We applied the algorithm to an epigenetic dataset to infer DAG's for smokers and nonsmokers.     

The Reverse Supply Chain Planning Matrix: A Classification Scheme for Planning Problems in Reverse Logistics

This paper presents a conceptual planning framework for reverse supply chain operations based on an extensive literature review and industry expertise. Such a holistic scheme for classification of planning tasks is necessary as the intensification of research on reverse logistics and closed‐loop supply chains in recent years has raised a number of planning problems that differ from those of solely forward‐oriented supply chains. Up to now, a common and comprehensive definition of relevant planning problems along the reverse chain has not existed. Thus, a thorough understanding of the interdependence between these elements is missing. This paper aims to systematically identify planning problems, which are assigned to different planning horizons and distinct process stages of product recovery. The result is a classification scheme, called a ‘Reverse Supply Chain Planning Matrix’ (RSCPM), which categorizes planning problems and shows their interrelation in recovery operations. It serves both academia and practitioners as a holistic overview for planning and decision tasks. Moreover, decision‐makers are supported in identifying the relevant variables in reverse supply chains and in revealing the consequences of one decision regarding other parameters of the system. To the best of the authors' knowledge, the RSCPM is the first attempt to comprehensively structure the field of reverse supply chain research by identifying, defining and interconnecting planning problems within an integrated framework, as is common in the forward case.     

Explaining the ending of Sweden's nuclear phase-out policy: a new approach by referring to the advocacy coalition framework theory

Sweden has been a role model for many European countries as regards the phasing-out of nuclear power. Nuclear power policy became a strong political issue in 1976, much earlier than in other countries. Sweden was the first country in the world to decide to phase out nuclear energy. A non-binding referendum on this subject was held in 1980. As a result, parliament decided to ban nuclear power after 2010. The main aim of the paper is to understand the complex process of policy change throughout various periods in the Swedish phase-out policy by applying the advocacy coalition framework (ACF) theory. The ACF was designed in 1988 by Sabatier and Jenkins Smith to explain, for example, coalition structure and behavior, belief and policy change in controversial/debatable policy subsystems. In February 2009, the Swedish center-right alliance announced a position paper regarding plans to overturn a 30-year ban on new atomic plants, as a part of a new impulse to increase energy security and fight global warming. Based on a decision taken in the Swedish Parliament in June 2010, when a small majority approved these two aims, Sweden reversed its nuclear power phase-out. This paper will analyze the most relevant factors that led to such a radical policy change.     

Perceived Marital Support and Incident Mental Illness: Evidence from the National Comorbidity Survey

Social support in marriage may be associated with reduced risk for mental illness. Past studies are limited by short follow up and a focus on depression. A two‐wave nationally representative survey in the United States (n = 2,503) is used to examine whether social support in marriage is associated with the onset of each of four clusters of disorders—internalizing, externalizing, phobic, and bipolar—10 years later. Results indicate that higher levels of perceived marital support were protective against internalizing, fear, and bipolar disorders, and against incident externalizing disorders for women. Protective effects of social support in marriage against mental illness are long‐lasting, and sometimes differ by gender. Findings suggest the importance of mental health assessment in clinical practice.