Shape optimal design criterion in linear models

Within the framework of classical linear regression model optimal design criteria of stochastic nature are considered. The particular attention is paid to the shape criterion. Also its limit behaviour is established which generalizes that of the distance stochastic optimality criterion. Examples of the limit maximin criterion are considered and optimal designs for the line fit model are found.     

Lessons from Sweden’s first large-scale implementation of Six Sigma in healthcare

The Skaraborg Hospital Group (SkaS) has implemented a variety of quality management initiatives in the last 20 years in accordance with its strategy of excelling at quality development to fulfill the needs and expectations of its patients. One such initiative is Six Sigma, which has contributed to more than 40 completed improvement projects. Using an action research approach, this article describes the lessons that were learned from the first 22 Six Sigma projects, completed between 2006 and 2008 and having a success rate of 75%. We further describe how these insights have contributed to other ongoing quality improvement activities at SkaS. In particular, the paper presents some key points not earlier described in other Six Sigma healthcare applications.     

What Drives Fraud in a Credence Goods Market? – Evidence from a Field Study

This paper investigates the impact of competition on an expert firm's incentive to defraud its customers in a credence goods market. Controlling for the competence of car repair shops, their financial situation, and reputational concerns, we use and complement the data set from a nationwide field study conducted by the German Automobile Association that regularly checks the reliability of garages in Germany. We find that more intense competition lowers a firm's incentive to defraud its customers.     

Steering the Sales Force for New Product Selling: Why Is it Different,and How Can Firms Motivate Different Sales Reps?

This study investigates how to direct and assemble the sales force for new product selling. In a first step, the authors draw on self‐determination theory to explore and empirically test a threefold conceptualization of motivation. Results provide insights into why sales force steering works differently in the new product selling context. Specifically, results show that for new products’ financial performance, internalized new product selling motivation is more important than intrinsic and controlled motivation. In a second step, the authors show how firms can motivate different sales reps to achieve higher financial performance of new products. In doing so, they examine the interaction effects of sales reps’ predispositions and widespread firm‐steering instruments on new products’ financial performance. Results reveal that the new product sales orientation of the bonus strengthens the positive relationship between sales reps’ performance predisposition and new product financial performance but weakens the relationship between sales reps’ learning predisposition and financial new product performance. Moreover, results reveal that the new product sales orientation of the periodic review strengthens the positive relationship between sales reps’ learning predisposition and financial new product performance. A post hoc analysis shows that a differentiated steering approach that matches appropriate steering instruments with sales reps’ varying predispositions substantially enhances reps’ financial new product performance.     

Consistency of elementwise-weighted total least squares estimator in a multivariate errors-in-variables model <Emphasis Type="Bold">AX=B</Emphasis>

A multivariate measurement error model AXB is considered. The errors in [A,B] are rowwise independent, but within each row the errors may be correlated. Some of the columns are observed without errors, and in addition the error covariance matrices may differ from row to row. The total covariance structure of the errors is supposed to be known up to a scalar factor. The fully weighted total least squares estimator of X is studied, which in the case of normal errors coincides with the maximum likelihood estimator. We give mild conditions for weak and strong consistency of the estimator, when the number of rows in A increases. The results generalize the conditions of Gallo given for a univariate homoscedastic model (where B is a vector), and extend the conditions of Gleser given for the multivariate homoscedastic model. We derive the objective function for the estimator and propose an iteratively reweighted numerical procedure.Acknowledgements.A. Kukush is supported by a postdoctoral research fellowship of the Belgian office for Scientific, Technical and Cultural Affairs, promoting Scientific and Technical Collaboration with Central and Eastern Europe. S. Van Huffel is a full professor with the Katholieke Universiteit Leuven. This paper presents research results of the Belgian Programme on Interuniversity Poles of Attraction (IUAP Phase V-22), initiated by the Belgian State, Prime Ministers Office-Federal Office for Scientific, Technical and Cultural Affairs, of the Concerted Research Action (GOA) projects of the Flemish Government MEFISTO-666 (Mathematical Engineering for Information and Communication Systems Technology), of the IDO/99/03 project (K.U. Leuven) Predictive computer models for medical classification problems using patient data and expert knowledge, of the FWO projects G.0200.00, G.0078.01 and G.0270.02. The scientific responsibility is assumed by its authors. The authors would like to thank Maria Luisa Rastello and Amedeo Premoli for bringing the EW-TLS problem to their attention. The authors are grateful to two anonymous referees for the valuable comments.