Reconsidering the exploration of power distance: an active case study approach

In this paper, we present what we call an “active case study” and we theorize specifically on the relevance hereof for an exploration of power distance (as conceptualized by Hofstede (Culture's Consequences: International Differences in Work-Related Values, Sage, Beverley Hills, CA, 1980)). As Hofstede conceives it, the notion of “power distance” enables an understanding of the predominant ideas about inequality prevalent in a (national) culture, which in turn infuse work relationships. An active case study approach—as we elucidate in the paper—implies an acknowledgement on the part of those organizing the research of the manner in which their intervention might affect the way “respondents” experience their work relationships. We suggest that our proposed active case study approach offers novel possibilities for exploring power distance and should be added to the repertoire of approaches used to examine this in organizational life. We develop our argument in this regard by offering a detailed account of the application of this approach to a Taiwanese organization (the Kaohsiung Harbor Bureau in Taiwan).     

Single-machine batch delivery scheduling with an assignable common due window

This paper addresses a batch delivery single-machine scheduling problem in which jobs have an assignable common due window. Each job will incur an early (tardy) penalty if it is early (tardy) with respect to the common due window under a given schedule. There is no capacity limit on each delivery batch, and the cost per batch delivery is fixed and independent of the number of jobs in the batch. The objective is to find the optimal size and location of the window, the optimal dispatch date for each job, as well as an optimal job sequence to minimize a cost function based on earliness, tardiness, holding time, window location, window size, and batch delivery. We show that the problem can be optimally solved in O(n⁸)$O(n^8)$ time by a dynamic programming algorithm under a reasonable assumption on the relationships among the cost parameters. A computational experiment is also conducted to evaluate the performance of the proposed algorithm. We also show that some special cases of the problem can be optimally solved by lower order algorithms.     

A class of weighted dependence measures for bivariate failure time data

This paper considers a class of summary measures of the dependence between a pair of failure time variables over a finite follow-up region. The class consists of measures that are weighted averages of local dependence measures, and includes the cross-ratio-measure and finite region version of Kendall's τ; recently proposed by the authors. Two new special cases are identified that can avoid the need to estimate the bivariate survivor function and that admit explicit variance estimators. Nonparametric estimators of such dependence measures are proposed and are shown to be consistent and asymptotically normal with variances that can be consistently estimated. Properties of selected estimators are evaluated in a simulation study, and the method is illustrated through an analysis of Australian Twin Study data.     

Boris Raux,olfactory narcissism,and environmental risk

This article develops the concept of “olfactory narcissism” through an analysis of Boris Raux’s multi-media artworks. Approaching narcissism through the sense of smell, Raux frames the self in insistently material, trans-corporeal terms. His olfactory projects thus explore questions about the porous self and the ethical and environmental stakes of “deodorization” and olfactory self-fashioning. The paper explores how olfactory aesthetics can contribute to a deeper understanding of modernity’s atmospheric practices as well as their implications for subject formation, social relations, and environmental health.     

Joint analysis of longitudinal data and competing terminal events in the presence of dependent observation times with application to chronic kidney disease

In many prospective clinical and biomedical studies, longitudinal biomarkers are repeatedly measured as health indicators to evaluate disease progression when patients are followed up over a period of time. Patient visiting times can be referred to as informative observation times if they are assumed to carry information in addition to that of the longitudinal biomarker measures alone. Irregular visiting times may reflect compliance with physician instruction, disease progression and symptom severity. When the follow-up time may be stopped by competing terminal events, it is possible that patient observation times may correlate with the competing terminal events themselves, thus making the observation times difficult to assess. To explicitly account for the impact of competing terminal events and dependent observation times on the longitudinal data analysis in the context of such complex data, we propose a joint model using latent random effects to describe the association among them. A likelihood-based approach is derived for statistical inference. Extensive simulation studies reveal that the proposed approach performs well for practical situations, and an analysis of patients with chronic kidney disease in a cohort study is presented to illustrate the proposed method.     

The efficiency of government spending on health: Evidence from Europe and Central Asia

This paper uses data envelopment analysis (DEA) to evaluate health expenditures to demonstrate how productivity has changed over time for 46 selected countries in Europe and Central Asia. Our results show that countries could have increased output by 1.2% given the existing level of inputs. The patterns of efficiency change for the observed countries are further analyzed using the Malmquist productivity index (MPI). Decreased productivity growth is related to technical change. Finally, we regress efficiency scores on a set of environmental variables using a Tobit model. The positive influence of hospital beds and primary schooling on efficiency scores demonstrates that countries with better medical environments and a greater number of educational years may enjoy increased efficiency. In addition, there exists a regional effect between Europe and Central Asia.     

销售价格影响需求的易变质产品动态定价模型

在需求率线性依赖于销售价格的情形下,研究有限销售周期内一次订购模式下单一易变质产品在连续时间上的最优动态定价决策问题.针对给定初始库存水平和初始库存水平待定两种情形,利用最优控制理论分别建立了易变质产品的动态定价模型,目标是最大化产品销售周期内总的销售利润.通过分析,可将问题分别转化为有控制变量约束的拉格郎日问题和波尔扎问题.利用Pontryagin极大值原理求解上述两类问题,均得到系统最优定价决策.对上述第一类问题分别进行了数值仿真,仿真结果表明:不同参数取值情形下,产品最优动态定价决策会在三种情形中变动.     

Pseudo-full likelihood estimation for prospective survival analysis with a general semiparametric shared frailty model: Asymptotic theory

In this work we present a simple estimation procedure for a general frailty model for analysis of prospective correlated failure times. Earlier work showed this method to perform well in a simulation study. Here we provide rigorous large-sample theory for the proposed estimators of both the regression coefficient vector and the dependence parameter, including consistent variance estimators.