A family of efficient estimators of the finite population mean in simple random sampling

In this paper an estimator of the finite population mean using auxiliary information in sample surveys has been proposed. The bias and mean squared error are obtained under large sample approximation. It has been shown that the proposed estimator performs better than some recently published estimators.     

An efficient nonparametric test for bivariate two-sample location problem

We propose a new test for the two-sample bivariate location problem. The proposed test statistic has a U-statistic representation with a degenerate kernel. The limiting distribution is found for the proposed test statistic. The power of the test is compared using Monte Carlo simulation to the tests of Blumen [I. Blumen, A new bivariate sign-test for location, Journal of the American Statistical Association 53 (1958) 448–456], Mardia [K.V. Mardia, A non-parametric test for the bivariate two-sample location problem, Journal of the Royal Statistical Society, Series B 29 (1967) 320–342], Peters and Randles [D. Peters, R.H. Randles, A bivariate signed-rank test for the two-sample location problem, Journal of the Royal Statistical Society, Series B 53 (1991) 493–504], LaRocque, Tardif and van Eeden [D. LaRocque, S. Tardif, C. van Eeden, An affine-invariant generalization of the Wilcoxon signed-rank test for the bivariate location problem, Australian and New Zealand Journal of Statistics 45 (2003) 153–165], and Baringhaus and Franz [L. Baringhaus, C. Franz, On a new multivariate two-sample test, Journal of Multivariate Analysis 88 (2004) 190–206]. Under the bivariate normal and bivariate t distributions the proposed test was more powerful than the competitors for almost every change in location. Under the other distributions the proposed test reached the desired power of one at a faster rate than the other tests in the simulation study. Application of the test is presented using bivariate data from a synthetic and a real-life data set.     

Why do Emerging Market Firms Engage in Voluntary Environmental Management Practices? A Strategic Choice Perspective

In this paper, we investigate firms’ decisions to engage in voluntary environmental management (VEM) practices within an emerging market context. Drawing on the strategic choice and the resource‐based view perspectives, we report results from a survey of VEM practices – a specific form of self‐governance – drawing on a sample of 519 Turkish firms from various industries to identify important strategic antecedents of firms’ decisions to engage in such practices. We find that as firms become more customer focused, more inclined to pursue a differentiation strategy and subject to a higher level of strategy‐oriented stakeholder focus, they tend to implement higher levels of VEM practices, with important implications for research, policy and practice for both emerging and developed markets.     

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Abstract

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective. It will help industries to develop strategies for managing the SC effectively and ensuring improvement in performance continuously. To achieve this, this work proposes to use a two-phase research methodology. First, 36 SC performance improvement indicators are recognised from a literature survey and from field and industrial expert’s inputs. Secondly, a structural model is proposed using the fuzzy analytical hierarchy process (AHP) to prioritise the indicators strategically to improve the SC performance. The fuzzy AHP method helps determine the priority of concerns of the identified indicators under fuzzy surroundings. Inputs in this research are taken from four ancillary Indian plastic manufacturing firms. Research findings indicate that collaborations and information exchange dimension indicators obtained the highest priority in improving SC performance. The model proposed is considered very useful for the SC managers/practitioners/decision-makers to understand better and distinguish the essential SC performance improvement indicators and to take systematic decisions specifically to improve the performance of business in a SC context. Sensitivity analysis was conducted to examine the priority ranking of the indicators.     

The Effect of Lead Time Uncertainty on Safety Stocks

The pressure to reduce inventory investments in supply chains has increased as competition expands and product variety grows. Managers are looking for areas they can improve to reduce inventories without hurting the level of service provided. Two areas that managers focus on are the reduction of the replenishment lead time from suppliers and the variability of this lead time. The normal approximation of lead time demand distribution indicates that both actions reduce inventories for cycle service levels above 50%. The normal approximation also indicates that reducing lead time variability tends to have a greater impact than reducing lead times, especially when lead time variability is large. We build on the work of Eppen and Martin (1988) to show that the conclusions from the normal approximation are flawed, especially in the range of service levels where most companies operate. We show the existence of a service‐level threshold greater than 50% below which reorder points increase with a decrease in lead time variability. Thus, for a firm operating just below this threshold, reducing lead times decreases reorder points, whereas reducing lead time variability increases reorder points. For firms operating at these service levels, decreasing lead time is the right lever if they want to cut inventories, not reducing lead time variability.     

Performance Impacts of Strategy,Information Technology Applications,and Business Process Outsourcing in U.S. Manufacturing Plants

This paper develops a conceptual model to study the role of outsourcing strategies and plant‐level information technology (IT) application infrastructure in the outsourcing of production and support business processes, as well as their subsequent impact on overall plant performance. We validate this model empirically using cross‐sectional survey data from U.S. manufacturing plants. We find that some IT applications are more effective at enabling the outsourcing of business processes than others. For example, the implementation of enterprise management systems is associated with the outsourcing of both production and support processes, whereas operations management systems are not associated with the outsourcing of plant processes. Plants with a low‐cost outsourcing strategy are more likely to outsource support processes than plants with a competency‐focused outsourcing strategy. However, both cost‐ and competency‐based strategies have a positive and similar impact on the outsourcing of production processes. In terms of implications for plant performance, our findings indicate that the outsourcing of production and support processes is associated with higher gross margins. Although plant IT infrastructure is positively associated with favorable on‐time delivery rates, there is no positive association between the incidence of plant outsourcing and on‐time delivery rates. These results have implications for crafting plant‐level outsourcing strategies and for investments in IT systems to facilitate the outsourcing of business processes for enhanced plant performance.     

Threshold Incentives and Sales Variance

In this paper, we analyze the impact of two forms of commonly used threshold‐based incentive schemes on the observed sales variability. The first form of the incentive comprises an additional marginal payment on crossing a specified sales threshold and the second form of the incentive scheme comprises a lumpsum bonus payment on crossing the predetermined sales threshold. We model the effect of such incentives under two specific scenarios: an exclusive dealership selling a single product and a non‐exclusive dealer selling two competing products. For an exclusive dealer, we show that a bonus contract not only increases the expected sales, but, more importantly, decreases the sales (order) variance. Consequently, the bonus‐based scheme allows the manufacturer to regulate sales variance better. With a non‐exclusive dealer, the sales variance increases substantially with an additional marginal payment contract. However, our analysis suggests that the bonus contract continues to perform better in this case, too, if the threshold level is set appropriately using the underlying demand distribution.     

Asymptotic properties of a quast-maximum likelihood estimator in truncated regression model with serial correlation

Robinson (1982a) presented a general approach to serial correlation in limited dependent variable models and proved the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) for the Tobit model with serial correlation, obtained under the assumption of independent errors. This paper proves the strong consistency and asymptotic normality of the QMLE based on independent errors for the truncated regression model with serial correlation and gives consistent estimators for the limiting covariance matrix of the QMLE.     

Estimation of mean in presence of non-response using two phase sampling scheme

This paper considers the problem of estimating the population mean using information on an auxiliary variable in presence of non-response. Some modified ratio, product and regression estimators in double sampling have been suggested and their properties are studied. It is shown that to the first degree of approximation, estimators based on estimated optimum values have the same variance as that of the optimum estimators. An empirical study is carried to judge the merits of the suggested estimators over conventional unbiased estimator and other known estimators. Both theoretical and empirical study results present the soundness and usefulness of the suggested estimators in practice.