The Competitive Characteristics of U.S Manufacturers in the Machine Tool Industry

This paper examines the competitive characteristics of U.S. manufacturers in the machine tool (MT) industry. After several decades of decline, this industry has recently shown signs of a modest but sustained recovery. Empirical evidence from a national survey of 104 MT producers suggests that the revival of this sector has been driven by a combination of factors, including renewed export involvement, improved customer support, and better product design. Although most MT companies are small-to-medium-sized enterprises (SMEs), the survey data show that very small SMEs are poorly represented in the recovery thrust of the industry as a whole. Our principal conclusion is that the MT industry has been following an export-led path toward stabilization, but that certain types of small producers are unlikely to thrive for very long. The most serious problems facing small producers include shrinking local markets, import competition, shortages of skilled labor, and cyclical demand.     

WINDOW ON EASTERN EUROPE: Ethical Perceptions of Polish Business Students

An experienced educationalist comments on the views of top Polish business students on ethics in public life, government and business in modern Poland. The author is Wicklander Professor of Professional Ethics at DePaul University, Chicago, and also served recently as Visiting Fulbright Professor at the Adam Mickiewicz University in Poznan, Poland. He is currently President of the Society of Business Ethics in the USA.     

Preliminary test estimators of the parameters of simple linear model with measurement error

In this paper, we discuss the properties of preliminary test estimators (PTE) of the parameters of simple linear model with measurement error (ME model) when the slope of the linear model is suspected to be zero. Expressions of the bias, MSE and efficiencies are obtained under conditional as well as unconditional situations with known reliability coefficient. Conditional model results are compared to the standard model without measurement error. We also provide the unconditional model analysis in finite samples. Asymptotic theory under local alternatives is developed when the variance of measurement error or the ratio of the variance of the model error relative to the variance of the measurement error is known. Asymptotic expressions of bias and MSE of the estimators along with their efficiencies are obtained. In every case, it is shown that the measurement error tend to increase the variability of the estimators compared to the estimators without measurement error. Graphs and tables are provided to see these results and to determine optimum level of significance for minimum guaranteed efficiency. Received October 2001 RID="*" ID="*"  A. K. Md. E. Saleh is a Distinguished Research Professor and H. M. Kim is a Ph.D. candidate in the School of Mathematics and Statistics, Carleton University, Ottawa. Acknowledgment. The authors gratefully acknowledge the constructive suggestion of the referees to improve the paper. The research is supported by NSERC grant A3088.     

Progressive stress accelerated life tests under finite mixture models

In this paper, progressive stress accelerated life tests are considered when the lifetime of a product under use condition follows a finite mixture of distributions. The experiment is performed when each of the components in the mixture follows a general class of distributions which includes, among others, the Weibull, compound Weibull, power function, Gompertz and compound Gompertz distributions. It is assumed that the scale parameter of each component satisfies the inverse power low, the progressive stress is directly proportional to time and the cumulative exposure model for the effect of changing stress holds. Based on type-I censoring, the maximum likelihood estimates (MLEs) of the parameters under consideration are obtained. A special attention is paid to a mixture of two Rayleigh components. Simulation results are carried out to study the precision of the MLEs and to obtain confidence intervals for the parameters involved.