A slacks-based inefficiency measure for a two-stage system with bad outputs

We model the performance of DMUs (decision-making units) using a two-stage network model. In the first stage of production DMUs use inputs to produce an intermediate output that becomes an input to a second stage where final outputs are produced. Previous black box DEA models allowed for non-radial scaling of outputs and inputs and accounted for slacks in the constraints that define the technology. We extend these models and build a performance measure that accounts for a network structure of production. We use our method to estimate the performance of Japanese banks, which use labor, physical capital, and financial equity capital in a first stage to produce an intermediate output of deposits. In the second stage, those deposits become an input in the production of loans and securities investments. The network estimates reveal greater bank inefficiency than do the estimates that treat the bank production process as a black box with all production taking place in a single stage.     

Asymptotic results in canonical discriminant analysis when the dimension is large compared to the sample size

This paper deals with the distributions of test statistics for the number of useful discriminant functions and the characteristic roots in canonical discriminant analysis. These asymptotic distributions have been extensively studied when the number p   of variables is fixed, the number q+1$q+1$ of groups is fixed, and the sample size N tends to infinity. However, these approximations become increasingly inaccurate as the value of p increases for a fixed value of N. On the other hand, we encounter to analyze high-dimensional data such that p is large compared to n. The purpose of the present paper is to derive asymptotic distributions of these statistics in a high-dimensional framework such that q   is fixed, p→∞$p\to \infty$, m=n-p+q→∞$m=n-p+q\to \infty$, and p/n→c∈(0,1)$p/n\to c\in (0,1)$, where n=N-q-1$n=N-q-1$. Numerical simulation revealed that our new asymptotic approximations are more accurate than the classical asymptotic approximations in a considerably wide range of (n,p,q)$(n,p,q)$.     

FLEXIBILITY,ADAPTABILITY, AND EFFICIENCY IN MANUFACTURING SYSTEMS

There are many different approaches and conceptualizations of flexibility in the present literature. This lends itself to a lack of clarity and can result in confusion on the central concept. Here we identify shortcomings in the existing literature. To clarify some of the important concepts, we distinguish between flexibility (ability to change states), adaptability (ability to change within a state), and efficiency (resources utilized). To illustrate such distinctions, we present a capacity expansion model that takes flexibility and adaptability into consideration. Numerical examples show how the concepts of flexibility and adaptability can be used in manufacturing.     

Assessing the prediction accuracy of cure in the Cox proportional hazards cure model: an application to breast cancer data

A cure rate model is a survival model incorporating the cure rate with the assumption that the population contains both uncured and cured individuals. It is a powerful statistical tool for prognostic studies, especially in cancer. The cure rate is important for making treatment decisions in clinical practice. The proportional hazards (PH) cure model can predict the cure rate for each patient. This contains a logistic regression component for the cure rate and a Cox regression component to estimate the hazard for uncured patients. A measure for quantifying the predictive accuracy of the cure rate estimated by the Cox PH cure model is required, as there has been a lack of previous research in this area. We used the Cox PH cure model for the breast cancer data; however, the area under the receiver operating characteristic curve (AUC) could not be estimated because many patients were censored. In this study, we used imputation‐based AUCs to assess the predictive accuracy of the cure rate from the PH cure model. We examined the precision of these AUCs using simulation studies. The results demonstrated that the imputation‐based AUCs were estimable and their biases were negligibly small in many cases, although ordinary AUC could not be estimated. Additionally, we introduced the bias‐correction method of imputation‐based AUCs and found that the bias‐corrected estimate successfully compensated the overestimation in the simulation studies. We also illustrated the estimation of the imputation‐based AUCs using breast cancer data. Copyright © 2014 John Wiley & Sons, Ltd.     

Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking

This paper studies the performance of nineteen private commercial banks and two government-owned banks in Bangladesh during the period 2005–2008 using a slacks-based inefficiency measure and the directional technology distance function. Performance is measured assuming a black-box production structure and then the black-box is opened and examined using a two stage network production structure. Current period performance in maximizing desirable loans and securities investments and minimizing bad loans depends on how efficiently inputs at one stage of production are transformed into intermediate outputs which are used at a subsequent stage of production. In addition, current period production of the intermediate output is constrained by the amount of non-performing loans that were generated in an earlier period.     

Challenges to Successful Community-based Integrated Approach to Dementia: A Qualitative Study

The aim of this study is to identify key challenges to successful community-based integrated team approach to the management of older adults with dementia. A nationwide community-based qualitative research strategy was applied. We purposively recruited 24 health-care providers and 13 family caregivers from selected 8 prefectures among 47 prefectures. Face to face interviews were conducted from May to September 2017. Qualitative content analysis was used to analyze the qualitative data. Ten themes regarding the challenges were emerged: Ignored wishes, Family caregivers’ full responsibilities, Encouragement, Practical and easy-to-understand information, Essential skills of dementia diagnosis and assessment, Gratitude by helping others, Difference between being kind and overly-kind, Legal barrier against information sharing, Coordination between volunteers and clients, and Conflict avoidance in multidisciplinary collaboration. The findings highlight the need to provide practical and easy-to-understand information for family caregivers, educate physicians in dementia diagnosis and assessment, share personal dementia care information among health-care providers, promote platforms which aim to match dementia care volunteers with older adults with dementia and their families in need of help, and raise awareness of advance care planning among both older individuals and health-care providers.     

A management policy for sika deer based on sex-specific hunting

We consider here a management policy for a sika deer (Cervus nippon) population in the eastern part of Hokkaido. Deer populations are characterized by a large intrinsic rate of population increase, no significant density effects on population growth before population crash, and a relatively simple life history. Our goals of management for the deer population are (1) to avoid irruption with severe damage to agriculture and forestry, (2) to avoid the risk of extinction of the deer population, and (3) to maintain a sustainable yield of deer. To make a robust program on the basis of uncertain information about the deer population, we consider three levels of relative population size and four levels of hunting pressures. We also take into consideration a critical level for extinction, an optimal level, and an irruption level. The hunting pressure for females is set to increase with the population size. We also recommend catching males if the population size is between the critical and optimal levels and catching females and males if the population size is larger than the optimal level. We must avoid cases of irruption or threatened population under various sets of uncertain parameter values. The simulation results suggest that management based on sex-specific hunting is effective to diminish the annual variation in hunting yield. Received: April 8, 1998 / Accepted: December 25, 1998     

Simple Formula for Calculating Bias‐corrected AIC in Generalized Linear Models

In real‐data analysis, deciding the best subset of variables in regression models is an important problem. Akaike's information criterion (AIC) is often used in order to select variables in many fields. When the sample size is not so large, the AIC has a non‐negligible bias that will detrimentally affect variable selection. The present paper considers a bias correction of AIC for selecting variables in the generalized linear model (GLM). The GLM can express a number of statistical models by changing the distribution and the link function, such as the normal linear regression model, the logistic regression model, and the probit model, which are currently commonly used in a number of applied fields. In the present study, we obtain a simple expression for a bias‐corrected AIC (corrected AIC, or CAIC) in GLMs. Furthermore, we provide an ‘R’ code based on our formula. A numerical study reveals that the CAIC has better performance than the AIC for variable selection.