Information-Processing Alternatives for Coping with Manufacturing Environment Complexity

Investment in information systems and technology is often justified as a necessary strategy for coping with the increased complexity and information needs of today/s manufacturing environments. However, the world class manufacturing paradigm suggests that increased complexity is not always necessary to meet the needs of markets and customers. Galbraith/s (1973, 1977) seminal information-processing model is applied to a manufacturing environment, supported by the world class manufacturing paradigm, to test the role of various information-processing alternatives for coping with increased environmental complexity. Moderated regression and multiple discriminant analysis are used to test hypotheses in a sample of 164 manufacturing plants. Environmental complexity was found to be related to manufacturing performance for each of the five dependent variables. This relationship was moderated by at least one information-processing alternative for each dependent variable, including self-contained tasks, lateral relations, and environmental management strategies for reducing manufacturing, supplier, and goal diversity. Investments in information systems and reduction of labor and customer diversity did not moderate this relationship. Practices that were found to be particularly effective in moderating this relationship included the use of multifunctional employees, communication of manufacturing strategy, coordination of decision making, product design simplicity, reduction of parts counts, supervisory interaction facilitation, recruiting and selection for flexible employees, JIT practices, blanket purchase orders, and strong customer relationships.     

The Role of Organizational and Information Technology Antecedents in Reengineering Initiation Behavior*

Business Process Reengineering (BPR) has been a major catalyst of the pervasive organizational change we have witnessed over the past decade. Although one can speculate on the reasons for the popularity of this phenomenon, it is important that we carefully examine its underlying antecedents for initiation, implementation, and ultimately success, if we are to add value to practitioners of this concept. This study empirically examines the importance of facets of the organizational structure, IT knowledge resources and infrastructure, and the IS function in the initiation of BPR. Data from 313 corporations were gathered using a carefully validated survey, and initiators were compared with noninitiators. The results strongly suggest that client-server architectures, the strategic integration of IS, and cross departmental interaction are among the more important factors facilitating initiation and can be important inputs in a BPR decision-making process. The study attempts to build a contingent theory for BPR, and the more sustainable notion of fundamental process change.     

Female athletic participation and income: evidence from a latent class model

This paper introduces and applies an EM algorithm for the maximum-likelihood estimation of a latent class version of the grouped-data regression model. This new model is applied to examine the effects of college athletic participation of females on incomes. No evidence for an “athlete” effect in the case of females has been found in the previous work by Long and Caudill [12], Henderson et al. [10], and Caudill and Long [5]. Our study is the first to find evidence of a lower wage for female athletes. This effect is present in a regime characterizing 42% of the sample. Further analysis indicates that female athletes in many otherwise low-paying jobs actually get paid less than non-athletes.     

Statistical approaches for conducting network meta-analysis in drug development

We introduce health technology assessment and evidence synthesis briefly, and then concentrate on the statistical approaches used for conducting network meta-analysis (NMA) in the development and approval of new health technologies. NMA is an extension of standard meta-analysis where indirect as well as direct information is combined and can be seen as similar to the analysis of incomplete-block designs. We illustrate it with an example involving three treatments, using fixed-effects and random-effects models, and using frequentist and Bayesian approaches. As most statisticians in the pharmaceutical industry are familiar with SAS? software for analyzing clinical trials, we provide example code for each of the methods we illustrate. One issue that has been overlooked in the literature is the choice of constraints applied to random effects, and we show how this affects the estimates and standard errors and propose a symmetric set of constraints that is equivalent to most current practice. Finally, we discuss the role of statisticians in planning and carrying out NMAs and the strategy for dealing with important issues such as heterogeneity.     

Proposed best practice for statisticians in the reporting and publication of pharmaceutical industry‐sponsored clinical trials

In this paper we set out what we consider to be a set of best practices for statisticians in the reporting of pharmaceutical industry‐sponsored clinical trials. We make eight recommendations covering: author responsibilities and recognition; publication timing; conflicts of interest; freedom to act; full author access to data; trial registration and independent review. These recommendations are made in the context of the prominent role played by statisticians in the design, conduct, analysis and reporting of pharmaceutical sponsored trials and the perception of the reporting of these trials in the wider community. Copyright © 2010 John Wiley & Sons, Ltd.     

ESTIMATION OF MULTIVARIATE SHANNON ENTROPY USING MOMENTS

Three new entropy estimators of multivariate distributions are introduced. The two cases considered here concern when the distribution is supported by a unit sphere and by a unit cube. In the former case, the consistency and the upper bound of the absolute error for the proposed entropy estimator are established. In the latter one, under the assumption that only the moments of the underlying distribution are available, a non‐traditional estimator of the entropy is suggested. We also study the practical performances of the constructed estimators through simulation studies and compare the estimators based on the moment‐recovered approaches with their counterparts derived by using the histogram and k th nearest neighbour constructions. In addition, one worked example is briefly discussed.