Estimation for an inverted exponentiated Rayleigh distribution under type II progressive censoring

In this paper, we consider estimation of unknown parameters of an inverted exponentiated Rayleigh distribution under type II progressive censored samples. Estimation of reliability and hazard functions is also considered. Maximum likelihood estimators are obtained using the Expectation–Maximization (EM) algorithm. Further, we obtain expected Fisher information matrix using the missing value principle. Bayes estimators are derived under squared error and linex loss functions. We have used Lindley, and Tiernery and Kadane methods to compute these estimates. In addition, Bayes estimators are computed using importance sampling scheme as well. Samples generated from this scheme are further utilized for constructing highest posterior density intervals for unknown parameters. For comparison purposes asymptotic intervals are also obtained. A numerical comparison is made between proposed estimators using simulations and observations are given. A real-life data set is analyzed for illustrative purposes.     

Measurement Equivalence Using Generalizability Theory: An Examination of Manufacturing Flexibility Dimensions

As the field of decision sciences in general and operations management in particular has matured from theory building to theory testing over the past two decades, it has witnessed an explosion in empirical research. Much of this work is anchored in survey‐based methodologies in which data are collected from the field in the form of scale items that are then analyzed to measure latent unobservable constructs. It is important to assess the invariance of scales across groups in order to reach valid, scientifically sound conclusions. Because studies have often been conducted in the field of decision sciences with small sample sizes, it further exacerbates the problem of reaching incorrect conclusions. Generalizability theory can more effectively test for measurement equivalence in the presence of small sample sizes than the confirmatory factor analysis (CFA) tests that have been conventionally used for assessing measurement equivalency across groups. Consequently, we introduce and explain the generalizability theory (G‐theory) in this article to examine measurement equivalence of 24 manufacturing flexibility dimension scales that have been published in prior literature and also compare and contrast G‐theory with CFA. We show that all the manufacturing flexibility scales tested in this study were invariant across the three industry SIC groups from which data were collected. We strongly recommend that G‐theory should always be used for determining measurement equivalence in empirical survey‐based studies. In addition, because using G‐theory alone does not always reveal the complete picture, CFA techniques for establishing measurement equivalence should also be invoked when sample sizes are large enough to do so. Implications of G‐theory for practice and its future use in operations management and decision sciences research are also presented.     

Concomitants of k-record values arising from Morgenstern family of distributions and their applications in parameter estimation

In this paper, we have obtained the marginal and joint distributions of concomitants of k-record values for the Morgenstern family of distributions (MFD) and hence obtained the moments and product moments of concomitants of k-record values. Applying this results we have derived the best linear unbiased estimators of some parameters involved in Morgenstern type bivariate logistic distribution which belongs to MFD based on concomitants of k-record values.     

Estimation using hybrid censored data from a generalized inverted exponential distribution

ABSTRACT

We consider point and interval estimation of the unknown parameters of a generalized inverted exponential distribution in the presence of hybrid censoring. The maximum likelihood estimates are obtained using EM algorithm. We then compute Fisher information matrix using the missing value principle. Bayes estimates are derived under squared error and general entropy loss functions. Furthermore, approximate Bayes estimates are obtained using Tierney and Kadane method as well as using importance sampling approach. Asymptotic and highest posterior density intervals are also constructed. Proposed estimates are compared numerically using Monte Carlo simulations and a real data set is analyzed for illustrative purposes.     

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firm’s decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers’ performances meet the industry and environment standards with effective human resource.     

HIV prevention and sex workers: an international lesson in empowerment

This article examines the impact and influence of advocacy on HIV prevention efforts among sex workers in India. A novel project initiated in Songachi, a red-light district in Calcutta, was instrumental in reducing the rate of new infections among sex workers and increasing the use of condoms to significant levels. The Songachi Project utilised methods and techniques that empowered this stigmatised, exploited and disenfranchised segment of the population. The impact of this World Bank-aided project was far-reaching; a key benefit is that it can be duplicated in developing countries around the world. Social workers involved in harm reduction initiatives and HIV/AIDS prevention efforts with at-risk groups like sex workers can develop their own prevention programmes utilising this model as presented here.     

An Integrated Logistic Model for Predictable Disasters

In the aftermath of a disaster, the relief items are transported from temporary warehouses (Staging Areas, SAs) to the Points of Distribution (PODs). Reducing the response time to provide relief items to disaster victims and cost minimization are two important objectives of this study. We propose an integrated optimization model for simultaneously determining (1) locations of staging areas, (2) inventory assignments to these SAs, (3) selecting sizes and numbers of trucks, and (4) routing of trucks from SAs to PODs. We also introduce another variable, a value function, which forces the model to reduce the logistics response time. We study the interactions among these variables through extensive sensitivity analysis. The time horizon for supply of relief items to disaster areas is usually limited to six days after the disaster occurs. Therefore, we use the proposed optimization model in a rolling‐horizon manner, one day at a time. This reduces daily demand uncertainty. We analyze three disaster scenarios: (1) a low impact disaster, (2) a medium impact disaster, and (3) a high impact disaster. We conduct 720 experiments with different parameter values, and provide answers to the following questions that are useful for the logistic managers: (i) What are the right sizes (in terms of storage capacities) of SAs closer to the PODs? (ii) How should the budget be allocated in a disaster scenario? (iii) What mix of different types (in terms of sizes) of trucks should be selected in a given scenario? The most important managerial insights include: (i) operational budget beyond a limit does not improve the operational efficiency, (ii) when the budget is very low, it is essential to select smaller SAs close to the PODs in order to carry out operations in a feasible manner, (iii) when the impact of disaster is high, it is always beneficial to select larger SAs close to the PODs (as long as the budget is not very low), (iv) when the budget is high and the impact of disaster is not very high, the emergency management administrators need to select SAs prudently based on the tradeoff between the operational cost and the humanitarian value, and (v) the cost of operations is higher when all the trucks are of the same type compared to the case when there is a mix of different types of trucks. Also, we find that the optimal selection of SAs is not impacted by different combinations of the types of trucks. The focus of this study is on disasters that can be forecasted in advance and provide some lead time for preparations, for example, hurricanes. In order to understand the disaster management process of such disasters and develop our model, we (i) interviewed several emergency management administrators, and (ii) studied the disaster management processes available in documents released by various government agencies.     

Class of dual to ratio estimators for double sampling

The paper proposes a class of dual to ratio estimators for estimating the mean of finite population, for double sampling.     

Integrated approach for optimizing quality control in international manufacturing networks

Abstract

This article aims at providing an integrated approach for optimizing quality control in International Manufacturing Networks (IMN) which can be characterized by consisting of numerous plants acting autonomously according to an individual target system. A key challenge is to ensure the overall process quality despite distributed value creation processes and differing target systems in dynamic environments. Hence, the developed approach allows for identifying potentials in the quality control strategy using a value stream-based method to visualize quality characteristics and procedures in the production process chain. Furthermore, the approach contains a framework for identifying possible improvement measures and a simulation-based evaluation concept to evaluate the effects of different measures with respect to individual target systems. The simulation combines elements of a discrete-event simulation in order to depict the value stream with agent-based modelling for realizing different target systems by considering distinctive plant roles. The article concludes with a case study of a globally operating automotive supplier to apply the approach. A forward research agenda is proposed that evaluates the approach in multiple cases, deriving patters across companies or industries.     

Chain-type ratio estimator in successive sampling using multi-auxiliary information

ABSTRACT

The present work is an attempt to make use of several auxiliary variables at both the occasions for improving the precision of estimates at the current occasion on two occasions of successive sampling. Chain-type ratio estimator has been proposed for estimating the population mean at current occasion in two occasions rotation (successive) sampling. Theoretical properties of the proposed estimator have been investigated. The proposed estimator has been compared with simple mean estimator when there is no matching and with the ratio estimator in successive sampling when information is available on one auxiliary variable on both the occasions. Optimum replacement strategy has also been discussed. Theoretical results have been justified through empirical investigation.