Economic and economic statistical designs for three-level control charts

In some situations, an appropriate quality measure uses three or more discrete levels to classify a product characteristic. For these situations, some control charts have been developed based on statistical criteria regardless of economic considerations. In this paper, we develop economic and economic statistical designs (ESD) for 3-level control charts. We apply the cost model proposed by Costa and Rahim.[Economic design of X charts with variable parameters: the Markov chain approach, J Appl Stat 28 (2001), 875–885] Furthermore, we assume that the length of time that the process remains in control is exponentially distributed which allows us to apply the Markov chain approach for developing the cost model. We apply a genetic algorithm to determine the optimal values of model parameters by minimizing the cost function. A numerical example is provided to illustrate the performance of the proposed models and to compare the cost of the pure economic and ESD for three-level control charts. A sensitivity analysis is also conducted in this numerical example.     

A Hellinger distance approach to MCMC diagnostics

Bayesian analysis often requires the researcher to employ Markov Chain Monte Carlo (MCMC) techniques to draw samples from a posterior distribution which in turn is used to make inferences. Currently, several approaches to determine convergence of the chain as well as sensitivities of the resulting inferences have been developed. This work develops a Hellinger distance approach to MCMC diagnostics. An approximation to the Hellinger distance between two distributions f and g based on sampling is introduced. This approximation is studied via simulation to determine the accuracy. A criterion for using this Hellinger distance for determining chain convergence is proposed as well as a criterion for sensitivity studies. These criteria are illustrated using a dataset concerning the Anguilla australis, an eel native to New Zealand.     

Green supply chain management: the case of the construction sector in the United Arab Emirates (UAE)

Restraining the negative environmental impacts of the construction sector constitutes one of the major challenges of the twenty-first century. However, efforts to address it have been largely fragmented. With environmental consequences of a construction project typically dispersed across its life cycle, i.e. from design through to end-of-life, greening this sector requires a supply chain wide focus inclusive of all key stages and stakeholders; also, all relevant aspects such as the nature of green practices implemented and associated drivers, barriers and performance implications need to be considered. This forms the focus of the present study where a comprehensive, green supply chain management oriented understanding of the construction sector is developed through the context of the UAE construction sector, and incorporating inputs from all key stakeholders, i.e. Developers, Architects/Consultants, Contractors and (material) Suppliers. The study contributes to improving the efficiency and effectiveness of greening of the construction sector.     

Reversible jump Markov chain Monte Carlo algorithms for Bayesian variable selection in logistic mixed models

In this article, to reduce computational load in performing Bayesian variable selection, we used a variant of reversible jump Markov chain Monte Carlo methods, and the Holmes and Held (HH) algorithm, to sample model index variables in logistic mixed models involving a large number of explanatory variables. Furthermore, we proposed a simple proposal distribution for model index variables, and used a simulation study and real example to compare the performance of the HH algorithm with our proposed and existing proposal distributions. The results show that the HH algorithm with our proposed proposal distribution is a computationally efficient and reliable selection method.     

Comparing policy advisory systems beyond the OECD: models,dynamics and the second-generation research agenda

ABSTRACT

The concept of “policy advisory systems” was introduced by Halligan in 1995 as a way to characterize and analyze the multiple sources of policy advice utilized by governments in policy-making processes. The concept has proved useful and has influenced thinking about both the nature of policy work in different advisory venues as well as how these systems change over time. However, to date this work has examined mainly cases of developed countries and its application to developing and transitional countries is less certain. This paper sets out existing models of policy advisory systems based on Halligan’s original thinking on the subject and assesses the findings of many existing studies into OECD countries that advisory systems have been changing as a result of the dual effects of increased use of external consultants and others sources of advice – “externalization” – and the increased use of partisan advice inside government itself – “politicization”. Determining whether or not such changes have also characterized the situations found in developing and transitional countries and at the international-domestic and state-sub-state levels is the subject of the papers in this Special Issue.     

The competing risks analysis for parallel and series systems using Type-II progressive censoring

Abstract

Recently, the study of the lifetime of systems in reliability and survival analysis in the presence of several causes of failure (competing risks) has attracted attention in the literature. In this paper, series and parallel systems with exponential lifetime for each item of the system are considered. Several causes of failure independently affect lifetime distributions and observations of failure times of the systems are considered under progressive Type-II censored scheme. For series systems, the maximum likelihood estimates of parameters are computed and confidence intervals for parameters of the model are obtained using Fisher information matrix. For parallel systems, the generalized EM algorithm which uses the Newton-Raphson algorithm inside the EM algorithm is used to compute the maximum likelihood estimates of parameters. Also, the standard errors of the maximum likelihood estimates are computed by using the supplemented EM algorithm. The simulation study confirms the good performance of the introduced approach.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

三种运营模式下O2O外卖服务供应链质量努力策略研究

O2O外卖作为"互联网+"时代下的新型餐饮模式，日益受到人们的关注。本文研究的O2O外卖服务供应链由一个O2O外卖平台、一个餐饮商家和一个配送骑手构成。O2O外卖平台决策平台的服务质量努力和服务费用，餐饮商家决策产品价格，骑手决策配送服务质量努力程度，同时会受到来自平台或商家的服务质量激励。通过分析商家配送、平台配送和商家自建平台+配送三种运营模式，分别构建O2O外卖服务供应链成员的利润函数，运用博弈理论，优化得到不同模式下O2O外卖服务供应链成员的最优质量控制策略和最优利润。利用公式推导和对比分析，分别探讨了骑手激励金额上限和市场规模对服务供应链最优策略和最优利润的影响。通过数值仿真，可得结论：服务供应链各成员利润均随着市场规模的增大而增大，随着骑手激励金额上限的增加而先增大后减少。当市场规模较小时，平台配送模式下商家最优利润最大。而当市场规模较大时，商家自建平台+配送模式下商家最优利润最大。     

The (non-)application of blockchain technology in the Greek shipping industry

The implementation of blockchain technology (BCT) is gaining traction in supply chain networks, revolutionising the operation of contemporary supply chains and reshaping the potential of business relationships. Empirical studies on blockchain adoption are scant because implementation across networks is in fairly early phase of development, yet evidence from empirical studies is highly desirable. This is one of the first studies of blockchain adoption in the Greek shipping industry, which has not so far been examined by the literature, in direct comparison to early adopters in other European countries such as Norway. The research examined eight Greek shipping companies using workshops with experienced supply chain personnel. Qualitative analysis identified the current position of these organisations in terms of blockchain adoption, by considering possible benefits and inhibitors to implementation. Despite benefits of automated processes and reduced paperwork as a result of smart contracts, findings show a reluctance to adopt BCT. That is, enterprise resource planning (ERP) transformations have left organisations fatigued and disinclined towards further systems development and resistant to subsequent change. Also, the exposure of shared information in the shipping nexus is considered to cause a threat to competitive survival.