Waste identification diagrams

Value Stream Mapping (VSM) is a very popular tool in lean environments to represent production flows, mapping value stream of a product or family of products, and helps to identify some types of waste. Although very popular, this tool has some limitations as already described in many publications, especially in terms of restrictions in showing most types of waste as well as in its inability to represent various production routes. The purpose of this study is to introduce the waste identification diagram (WID), a new tool to represent production units with its different forms of waste, which overcomes some VSM limitations. The originality of WID comes from the use of its symbols’ dimensions to convey, in a visual and immediate way, relevant information about a production unit. In this paper, WID is applied on a production unit of a lift manufacturer, for testing its performance and comparing it to VSM. The main findings are that WID is in general more effective than VSM in terms of representation of complex production units and in terms of identification of more forms of waste. WID must however overcome some of its limitations such as the lack of information-flow representation and the links to suppliers and clients.     

Markov Chains and De-initializing Processes

We define a notion of de-initializing Markov chains. We prove that to analyse convergence of Markov chains to stationarity, it suffices to analyse convergence of a de-initializing chain. Applications are given to Markov chain Monte Carlo algorithms and to convergence diagnostics.     

SYMBOLIC POLITICS IN THE INFORMATION AGE: THE 1996 REPUBLICAN PRESIDENTIAL CAMPAIGNS IN CYBERSPACE

This paper traces the use of the World Wide Web as a medium of political communication during the 1996 American presidential campaigns. Beginning with the Republican campaigns' use of the medium during the primary election season, a typology of uses of the web is outlined. While all campaigns felt it necessary to participate in the World Wide Web, different candidates used the medium differently. Furthermore, no campaign made full use of the much-publicized interactive capacity of the web; they used it more as a new means of transmitting traditional mass-media literature (video, graphics, etc.) and as a way of providing access to large volumes of campaign information (voting records, speeches, position papers, etc.).     

Teachers,Schools, and Academic Achievement

This paper disentangles the impact of schools and teachers in influencing achievement with special attention given to the potential problems of omitted or mismeasured variables and of student and school selection. Unique matched panel data from the UTD Texas Schools Project permit the identification of teacher quality based on student performance along with the impact of specific, measured components of teachers and schools. Semiparametric lower bound estimates of the variance in teacher quality based entirely on within‐school heterogeneity indicate that teachers have powerful effects on reading and mathematics achievement, though little of the variation in teacher quality is explained by observable characteristics such as education or experience. The results suggest that the effects of a costly ten student reduction in class size are smaller than the benefit of moving one standard deviation up the teacher quality distribution, highlighting the importance of teacher effectiveness in the determination of school quality.     

Preparing for Elite Political Participation Simulations and the Political Socialization of Adolescents

Objective. We ask: How do socialization experiences shape adolescent perceptions of and the performance of gender in political leadership roles? We examine a political simulation, Model United Nations, which attracts academically motivated students aspiring to elite roles in politics and government. Methods. Using observational and survey data, we explore adolescent behavior in the simulation as both a learning experience and as a reflection of students' perceptions of leadership behavior. Results. Three critical observations emerge. First, the Model United Nations is a domain in which young women do not play an equal part. Female delegates take far fewer speaking turns. However, contextual factors, including membership on a committee that deals with less masculine issues and on a committee with a female chair, increase the likelihood of female turn‐taking. Second, though participants come to the event with very similar motivations, young women leave less satisfied with their personal effectiveness than do young men. Finally, female delegates are judged less favorably by themselves and others and thus as less successful in the simulation. Conclusions. These findings have normative implications for the recruitment of young women to politics.     

The FastHCS algorithm for robust PCA

Principal component analysis (PCA) is widely used to analyze high-dimensional data, but it is very sensitive to outliers. Robust PCA methods seek fits that are unaffected by the outliers and can therefore be trusted to reveal them. FastHCS (high-dimensional congruent subsets) is a robust PCA algorithm suitable for high-dimensional applications, including cases where the number of variables exceeds the number of observations. After detailing the FastHCS algorithm, we carry out an extensive simulation study and three real data applications, the results of which show that FastHCS is systematically more robust to outliers than state-of-the-art methods.     

k-POD: A Method for k-Means Clustering of Missing Data

The k-means algorithm is often used in clustering applications but its usage requires a complete data matrix. Missing data, however, are common in many applications. Mainstream approaches to clustering missing data reduce the missing data problem to a complete data formulation through either deletion or imputation but these solutions may incur significant costs. Our k-POD method presents a simple extension of k-means clustering for missing data that works even when the missingness mechanism is unknown, when external information is unavailable, and when there is significant missingness in the data.

[Received November 2014. Revised August 2015.]