Investigating the failure to best respond in experimental games

Experimental Economics - We examine strategic sophistication using eight two-person 3?×?3 one-shot games. To facilitate strategic thinking, we design a ‘structured’...     

Note on the existence and modulus of continuity of the {\textit{SLE}}_8 curve

We review one method for estimating the modulus of continuity of a Schramm–Loewner evolution (SLE) curve in terms of the inverse Loewner map. Then we prove estimates about the distribution of the inverse Loewner map, which underpin the difficulty in bounding the modulus of continuity of SLE for $\kappa =8$ . The main idea in the proof of these estimates is applying the Girsanov theorem to reduce the problem to estimates about one-dimensional Brownian motion.     

Do parents,teachers and children use the SDQ in a similar fashion?

Few studies have investigated whether parents’, teachers’ and children’s responses to the strengths and difficulties questionnaire (SDQ) have equivalence. In this study, data from 854 matched questionnaires collected in Malaysia were subjected to tau equivalence confirmatory factor analysis, to assess if all three groups responded to the same target (the child) similarly. We first fitted Goodman’s (Journal of Child Psychology and Psychiatry, 38, 581–586, (1997a); Journal of Child Psychology and Psychiatry, 40, 791–801, 1997b) five factor model, but found that this did not fit the model despite attempts to improve and rectify model fit. We thereafter attempted to fit Dickey and Blumberg (Journal of the American Academy of Child Adolescent Psychiatry, 43, 1159–1167, 2004) three factor model, but similarly found a lack of fit. We then undertook an exploratory model with a random half of the data, obtaining a three factor solution, and tested this in a confirmatory tau equivalence model. The Unconstrained Model provided a fit to the data, revealing a similar structure across the three informant groups. As this fit was for the Unconstrained Model, it reveals that groups differ in the value they place on each of the variables but overall that held a similar underlying factor structure. The findings are discussed in relation to the possible cultural issues involved and the use of the SDQ.     

Exploring supply management status,internal collaboration and operating performance

An important internal link in the supply chain is between supply managers and their internal customers. These individuals must collaborate to determine purchase specifications, develop sourcing strategies, ensure supplier performance, and maintain effective supplier relationships. Using power and social networking as the theoretical lenses, we develop and test a conceptual model examining the supply management function’s status, supply manager’s networking behavior, collaboration with the internal customer, and operating performance (lower cost, better quality, faster delivery, and consistent delivery). We also examine the mediating effect of collaboration and networking behavior on the positive effect of status and operating performance. Data gathered in an online survey of supply management professionals are examined using path analysis. Results show that without including the mediators, supply management status is directly related to all four operating performance measures. It is also positively related to collaboration with the internal customer and networking behavior. Contrary to expectations, the supply manager’s networking behavior is not related to collaboration with the internal customer. Collaboration is positively related to all four operating performance measures. However, the supply manager’s networking behavior is only related to one operating performance measure, better quality. Mediation analysis shows that supply management status has a direct effect on faster delivery performance beyond what is explained by collaboration and the supply manager’s networking behavior. The findings suggest that organizations should look for ways to elevate the status of the supply management function to improve internal collaboration and operating performance.     

Reasoning under uncertainty and multi-criteria decision making in data privacy

By means of an integration of decision theory and probabilistic models, we explore and develop methods for improving data privacy. Our work encompasses disclosure control tools in statistical databases and privacy requirements prioritization; in particular we propose a Bayesian approach for the on-line auditing in Statistical Databases and Pairwise Comparison Matrices for privacy requirements prioritization. The first approach is illustrated by means of examples in the context of statistical analysis on the census and medical data, where no salary (resp. no medical information), that could be related to a specific employee (resp. patient), must be released; the second approach is illustrated by means of examples, such as an e-voting system and an e-banking service that have to satisfy privacy requirements in addition to functional and security ones. Several fields in the social sciences, economics and engineering will benefit from the advances in this research area: e-voting, e-government, e-commerce, e-banking, e-health, cloud computing and risk management are a few examples of applications for the findings of this research.     

Testing for the bivariate Poisson distribution

This paper studies goodness-of-fit tests for the bivariate Poisson distribution. Specifically, we propose and study several Cramér–von Mises type tests based on the empirical probability generating function. They are consistent against fixed alternatives for adequate choices of the weight function involved in their definition. They are also able to detect local alternatives converging to the null at a certain rate. The bootstrap can be used to consistently estimate the null distribution of the test statistics. A simulation study investigates the goodness of the bootstrap approximation and compares their powers for finite sample sizes. Extensions for testing goodness-of-fit for the multivariate Poisson distribution are also discussed.     

The dimensional assessment of personality in drug addicts: a mixed-effects Rasch model approach

Drug abuse results from a series of different factors, such as social and family issues. Subjects more vulnerable to develop an addiction are, for instance, people living in high-stress environments who may resort to addiction in order to cope with their circumstances, such as demanding jobs, family crisis or other situations or people living in low-income households where violence occurs, who may be triggered into addiction as a way to escape negative emotions or ignore any underlying problems or issues. Psychometric research in the field of drug dependence has focused on identifying certain personality characteristics. It is now generally agreed that personality may influence, precipitate or perpetuate substance abuse. The aim of this paper is to perform a dimensional assessment of personality in a sample of drug addicts. To better understand the complexity of addictive behaviours of substance-using individuals, the Cloninger’s temperament and character inventory test is employed while the item response data analysis is performed by mixed-effects Rasch models. These models combine the advantages both of Rasch measurement framework for latent variables and of models with hierarchical data. To evaluate the differences in dimensions of temperament and character inventory test in subjects with drug addiction, we fit and compare a sequence of mixed-effects Rasch models. Results from models fitting are compared and discussed for a data set of 84 participants.     

A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies

This paper uses Bayesian stochastic frontier methods to measure the productivity gap between Poland and Western countries that existed before the beginning of the main Polish economic reform. Using data for 20 Western economies, Poland and Yugoslavia (1980–1990) we estimate a translog stochastic frontier and make inference about individual efficiencies. Following the methodology proposed in our earlier work, we also decompose output growth into technical, efficiency and input changes and examine patterns of growth in the period under consideration. This revised version was published online in July 2006 with corrections to the Cover Date.     

BP: developing excellence in the global enterprise

World-class supply management organizations like Honda of America, John Deere, Chrysler, Hewlett Packard, and Motorola all understand the power of continuous improvement in the supply base. The best supplier management and development programs help suppliers--on a long-term basis--develop their own strength and expertise in suggestion systems, new product development, and high quality production results.     

Automatic neural network modeling for univariate time series

Artificial neural networks (ANNs) are an information processing paradigm inspired by the way the brain processes information. Using neural networks requires the investigator to make decisions concerning the architecture or structure used. ANNs are known to be universal function approximators and are capable of exploiting nonlinear relationships between variables. This method, called Automated ANNs, is an attempt to develop an automatic procedure for selecting the architecture of an artificial neural network for forecasting purposes. It was entered into the M-3 Time Series Competition. Results show that ANNs compete well with the other methods investigated, but may produce poor results if used under certain conditions.