The economic sociology of markets,industries, and firms

Theory and Society -     

NONPARAMETRIC REGRESSION ON FUNCTIONAL DATA: INFERENCE AND PRACTICAL ASPECTS

We consider the problem of predicting a real random variable from a functional explanatory variable. The problem is tackled using a nonparametric kernel approach, which has been recently adapted to this functional context. We derive theoretical results from a deep asymptotic analysis of the behaviour of the estimate, including mean squared convergence (with rates and precise evaluation of the constant terms) as well as asymptotic distribution. Practical use of these results relies on the ability to estimate these constants. Some perspectives in this direction are discussed. In particular, a functional version of wild bootstrapping ideas is proposed and used both on simulated and real functional datasets.     

A Bayesian compartmental model for the evaluation of 1,3-butadiene metabolism

Summary. We propose a Bayesian model for physiologically based pharmacokinetics of 1,3-butadiene (BD). BD is classified as a suspected human carcinogen and exposure to it is common, especially through cigarette smoke as well as in urban settings. The main aim of the methodology and analysis that are presented here is to quantify variability in the rates of BD metabolism by human subjects. A three-compartmental model is described, together with informative prior distributions for the population parameters, all of which represent real physiological variables. The model is described in detail along with the meanings and interpretations of the associated parameters. A four-compartment model is also given for comparison. Markov chain Monte Carlo methods are described for fitting the model proposed. The model is fitted to toxicokinetic data obtained from 133 healthy subjects (males and females) from the four major racial groups in the USA, with ages ranging from 19 to 62 years. Subjects were exposed to 2 parts per million of BD for 20 min through a face mask by using a computer-controlled exposure and respiratory monitoring system. Stratification by ethnic group results in major changes in the physiological parameters. Sex and age were also tested but not found to have a significant effect.     

What Does it Take for a Canadian Political Scientist to be Cited?*

Objectives. The article examines the factors that influence the frequency whereby scholarly articles published by Canadian political scientists are cited. Method. We collected data on 1,860 journal articles published between 1985 and 2005 by 758 Canadian political scientists and listed in the Social Science Citation Index. Using these data, we performed OLS and tobit estimations to identify factors influencing citation frequency. Results. The regressions show that the reputation of the journal in which the article is published, though important, does not explain everything. The gender of the author(s), the number of authors, the geographical focus of the article, the field, and the methodology also matter. Conclusion. An article is more likely to be widely cited if it is published in a prestigious journal, if it is written by several authors, if it applies quantitative methods, if it compares countries, and if it deals with administration and public policy or elections and political parties. Faculty members who belong to larger departments and those who are women are more cited.     

Ordinal models and generalized estimating equations to evaluate disease severity

Many assays have been carried out in Capsicum spp. in order to evaluate its resistance to Phytophthora capsici , which causes blight and considerable yield loss. An assay aiming at the selection of resistant pepper and bell pepper genotypes to P. capsici was jointly performed in the laboratory of the Phytopathological Clinic of Entomology, Phytopathology and Agricultural Zoology and in the experimental area of the Plant Production Department, both located at ESALQ, University of São Paulo, Brazil. The data set for this assay comes from ordinal categorized random variables, whose analysis does not generally take into account the ordinal nature of the responses, but instead, builds indexes, among other measures, in order to evaluate the resistance of the studied genotypes. This work presents ordinal generalized linear fits in order to evaluate blight severity as well as to identify and select new resources to the pathogen. It also analyses the estimating equations proposed by Liang & Zeger (1986a, b) in order to obtain an infection pattern for the disease. From the fit of the cumulative logit models, valuable genotypes are identified for genetic breeding programs.     

Bounds for the Expected Time to Extinction and the Probability of Extinction in the Galton-Watson Process

Upper bounds for the expected time to extinction in the Galton-Watson process are obtained. We also found upper and lower bounds for the probability of extinction of this process. These bounds improve some bounds previously obtained by other authors.     

A heterarchical generic discrete manufacturing simulation model and its application in a world class manufacturing environment

Current factory design and evaluation is very primitive. Factory components are designed in many cases independently. Product and process design are not well integrated. An encompassing framework is needed for iterating through a series of total factory designs, searching for optimal performance. In addition, a vehicle is needed for predicting the performance of a proposed advanced manufacturing system, so that engineers may have a sound means for evaluating such proposals. A heterarchical discrete manufacturing SIMNET II simulation model (SIMCELLS) was developed as a comprehensive methodology for designing and evaluating discrete manufacturing systems. SIMCELLS allows manufacturing systems engineers to experiment with alternative system structures and control strategies while seeking that combination of design features that will produce the desired overall system performance. The model in combination with a modernization programme is enabling a firm to successfully manufacture and sell trucks meeting international standards. The SIMNET II model     

Optimizing lot size and setup time in a JIT environment: a multiple objective application

The just-in-time (JIT) system has been studied extensively and implemented by a number of US firms as an ell'ective production system. The core of JIT involves determination of lot size and setup time reduction so as to increase manufacturing flexibility while minimizing the inventory level. This decision problem usually involves multiple conflicting objectives and mixed-model production. In this paper, goal programming (GP) is applied to a real-world JIT problem involving fabrication of different automotive and industrial rubber composite belts. The model results provide new insights concerning the conflicting nature of several goals, especially between meeting demand and reducing setup or idle time. Also, the GP solution is superior to the current JIT practice of the company.