Multiobjective Stochastic Multivariate Stratified Sampling in Presence of Nonresponse

The case of nonresponse in multivariate stratified sampling survey was first introduced by Hansen and Hurwitz in 1946 considering the sampling variances and costs to be deterministic. However, in real life situations sampling variance and cost are often random (stochastic) and have probability distributions. In this article, we have formulated the multivariate stratified sampling in the presence of nonresponse with random sampling variances and costs as a multiobjective stochastic programming problem. Here, the sampling variance and costs are considered random and converted into a deterministic NLPP by using chance constraint and modified E-model. A solution procedure using three different approaches are adopted viz. goal programming, fuzzy programming, and D₁ distance method to obtain the compromise allocation for the formulated problem. An empirical study has also been provided to illustrate the computational details.     

A new sampling method for estimating the population mean

A double L ranked set sampling (DLRSS) method is suggested for estimating the population mean. The DLRSS is compared with the simple random sampling (SRS), ranked set sampling (RSS) and L ranked set sampling (LRSS) methods based on the same number of measured units. The conditions for which the suggested estimator performs better than the other estimators are derived. It is found that, the suggested DLRSS estimator is an unbiased of the population mean, and is more efficient than its counterparts using SRS, RSS, and LRSS methods. Real data sets are used for illustration.     

Estimation of inaccuracy measure for censored dependent data

In the present paper, we propose non parametric estimators for the inaccuracy measure for the lifetime distribution based on censored data. This measure plays important roles in reliability and survival analysis in connection with modeling and analysis of life time data. Asymptotic properties of the estimators are established under suitable regularity conditions. Monte Carlo simulation studies are carried out to compare the performance of the estimators using the mean-squared error. The methods are illustrated using a real data set.     

A new estimator of finite population mean based on the dual use of the auxiliary information

When a sufficient correlation between the study variable and the auxiliary variable exists, the ranks of the auxiliary variable are also correlated with the study variable, and thus, these ranks can be used as an effective tool in increasing the precision of an estimator. In this paper, we propose a new improved estimator of the finite population mean that incorporates the supplementary information in forms of: (i) the auxiliary variable and (ii) ranks of the auxiliary variable. Mathematical expressions for the bias and the mean-squared error of the proposed estimator are derived under the first order of approximation. The theoretical and empirical studies reveal that the proposed estimator always performs better than the usual mean, ratio, product, exponential-ratio and -product, classical regression estimators, and Rao (1991 Rao, T.J. (1991). On certail methods of improving ration and regression estimators. Commun. Stat. Theory Methods 20(10):3325–3340.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), Singh et al. (2009 Singh, R., Chauhan, P., Sawan, N., Smarandache, F. (2009). Improvement in estimating the population mean using exponential estimator in simple random sampling. Int. J. Stat. Econ. 3(A09):13–18. [Google Scholar]), Shabbir and Gupta (2010 Shabbir, J., Gupta, S. (2010). On estimating finite population mean in simple and stratified random sampling. Commun. Stat. Theory Methods 40(2):199–212.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), Grover and Kaur (2011 Grover, L.K., Kaur, P. (2011). An improved estimator of the finite population mean in simple random sampling. Model Assisted Stat. Appl. 6(1):47–55. [Google Scholar], 2014) estimators.     

ON EXTENSIONS OF PROBABILISTIC PROFIT BUDGETS: A COMMENT

Recognizing the potential importance of new uses of analysis, the author provides an alternative approach for constructing the confidence interval (C.I.) for the population coefficient of variation, V=α/μ. More specifically, the comment demonstrates the use of some of the existing percentage points of the sample coefficient of variation, v=s/x . The results of these approximations are then compared empirically with the results recently published by Hayya, Copeland and Chan [1, pp. 115–118]. The available approximations given by Iglewicz [2] and again by Iglewicz and Myers [3] of the practical range of V and of the sample size n are more accurate than those obtained using the method in [1].     

Evaluating barriers to implementing green supply chain management: An example from an emerging economy

Abstract

This study proposes a fuzzy-based VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) framework for evaluating barriers to implementing green supply chain management (GSCM) in the context of an emerging economy. The methodology uses a mix method approach combining literature review and opinions of some selected managers from the plastic industry of Bangladesh to identify four main-barriers and twenty-five sub-barriers relevant to GSCM implementation. Fuzzy-VIKOR approach was applied to aid in the analysis of the barriers in the plastic industry of Bangladesh. The findings of the study show the order/rank of intensity and severity of the main-barriers to implementing GSCM practices in the plastic industry of Bangladesh as follows: ‘inadequate knowledge and support’, ‘insufficient technology and infrastructure’, ‘financial constraints and unsupportive organizational’ and ‘operational policies’. The results also show the rankings of the sub-barriers under each main barriers. This research contributes to the literature in a number of ways. First, it identifies multi-levels of barriers to GSCM implementation. Secondly, it identifies and proposes alternative action plans (strategies) to help mitigate and implement GSCM practices. Though this study has significant contributions, a number of limitations do exist. The barriers in this study were identified using the extant literature review and industrial managers’ opinions. A more scientific approach and empirical validation is required, especially in the plastic manufacturing industry of Bangladesh to identify more new challenging barriers. However, this study can provide managers with a better understanding of the barriers to implementing GSCM practices and motivate the researchers to further extend the investigation on the insights for developing strategic plans for implementing GSCM practices in the plastic industry of Bangladesh.     

GIS and development control system for a local authority in Malaysia

The process of development control involves a technique for the systematic compilation of expert quantitative analysis and qualitative assessment of project land use and property development viability, including its effect on the surrounding area, and the presentation of results in a way that enables the importance of the predicted results, and the scope of modifying or mitigating them to be properly evaluated by the relevant decision making body before a planning permission is rendered. Taking the local authorities in Malaysia as an example, this paper will discuss and demonstrate the development of a GIS database and its integration and application for development and building control. The first part of the paper examines the functions of local authorities particularly in the context of development control. In this study, the procedure involved in granting a planning permission as well as enforcement becomes the main focus because it determines the bulk of the system design. The study identifies seven sub-systems namely planning permission, building control, planning enforcement, geospatial database, information kiosk, document processing and presentation sub-systems. The system is developed using a combination of office automation, CAD, GIS, multimedia and other software packages. This paper will focus on the development of the GIS for the purpose of development control. The components of the GIS database include land information, buildings, existing developments, planning information, development plans, utilities, community facilities, transportation, environment and the socio-economy database. The GIS database will be used at every stage of development control, for example, in initial discussions, registration, invitation of objections, the development control process, the consideration by Technical Committee and the consideration by Planning Committee. It is anticipated that the GIS database could be used by many parties involved in the process as a reference point in evaluating a planning submission. Having access to the database will provide flexibility in assessing a proposed development and deciding on the overall urban growth management programme in the most cost-effective manner. The system will also provide transparency and consistency in the development control procedure.