Abstract

A partially neighbor balanced design is a design in which for any fixed treatment, other treatments occur as neighbor λ i times. This paper generates infinite series of one-dimensional partially neighbor balanced designs for v = n treatments. The blocks used in these designs are considered circular. Designs given here are partially balanced in terms of nearest neighbors and not necessarily in terms of variance. Binary and non-binary concepts have been used for the construction of designs. Theorem 1 generates binary generalized 2-neighbor designs and theorem 2 generates non-binary generalized 3-neighbor designs. These theorems generate designs for v = n treatments i.e., for odd and even number of treatments simultaneously. This concept remains relatively under-explored in the literature. The objective is to decrease error variance due to neighbor effect and reduce computational cost.

This study shows the link between the working capital management and profitability with the indirect effect of management policies effectiveness under the context of Pakistan textile industry for which data have been taken from period 2006-2012. This study solve the problem related market share of textile firms' of Pakistan in the global market while the demand for textile products are increasing day by day. The convenience sampling technique is used for the selection of sample of our study which consists of 9 textile firms. For data analysis we have adopted the methodology of Hayajneh and Yassine (2011) which they have used to determine the WC performance of Jordanian manufacturing firms and devise the similar model for profitability. The result shows that the WCM and Profitability has a negative relationship with each other. While, the effective management policies have positive impact on the relationship between WCM and Profitability. This study is useful for financial managers for getting the better economic position and for attaining the short term miles stones of a firm as well as long term goals of business.

No abstract

This paper is an extension of Hanif, Hamad and Shahbaz estimator [1] for two-phase sampling. The aim of this paper is to develop a regression type estimator with two auxiliary variables for two-phase sampling when we don’t have any type of information about auxiliary variables at population level. To avoid multi-collinearity, it is assumed that both auxiliary variables have minimum correlation. Mean square error and bias of proposed estimator in two-phase sampling is derived. Mean square error of proposed estimator shows an improvement over other well known estimators under the same case.