Data envelopment analysis may obfuscate corporate financial data: using support vector machine and data envelopment analysis to predict corporate failure for nonmanufacturing firms

This is an Accepted Manuscript of an article published by Taylor & Francis in INFOR: Information Systems and Operational Research in 2017, available online: https://doi.org/10.1080/03155986.2017.1282290Corporate failure prediction has drawn numerous scholars’ attention because of its usefulness in corporate risk management, as well as in regulating corporate operational status. Most research on this topic focuses on manufacturing companies and relies heavily on corporate assets. The asset size of manufacturing companies play a vital role in traditional research methods; Altman’s score model is one such traditional method. However, a limited number of researchers studied corporate failure prediction for nonmanufacturing companies as the operational status of such companies is not solely correlated to their assets. In this paper we use support vector machines (SVMs) and data envelopment analysis (DEA) to provide a new method for predicting corporate failure of nonmanufacturing firms. We show that using only DEA scores provides better predictions of corporate failure predictions than using the original, raw, data for the provided dataset. To determine the DEA scores, we first generate efficiency scores using a slack-based measure (SBM) DEA model, using the recent three years historical data of nonmanufacturing firms; then we used SVMs to classify bankrupt and non-bankrupt firms. We show that using DEA scores as the only inputs into SVMs predict corporate failure more accurately than using the entire raw data available.Natural Sciences and Engineering Research Council of Canad

Association between dopamine transporter (DATI) genotype, left-sided inattention, and an enhanced response to methylphenidate in attention-deficit hyperactivity disorder

A polymorphism of the dopamine transporter gene (DAT1, 10-repeat) is associated with attention-deficit hyperactivity disorder (ADHD) and has been linked to an enhanced response to methylphenidate (MPH). One aspect of the attention deficit in ADHD includes a subtle inattention to left space, resembling that seen after right cerebral hemisphere damage. Since left-sided inattention in ADHD may resolve when treated with MPH, we asked whether left-sided inattention in ADHD was related to DAT1 genotype and the therapeutic efficacy of MPH. A total of 43 ADHD children and their parents were genotyped for the DAT1 30 variable number of tandem repeats polymorphism. The children performed the Landmark Test, a well-validated measure yielding a spatial attentional asymmetry index ( leftward to rightward attentional bias). Parents rated their child's response to MPH retrospectively using a three-point scale ( no, mediocre or very good response). Additionally, parents used a symptom checklist to rate behavior while on and off medication. A within-family control design determined whether asymmetry indices predicted biased transmission of 10-repeat parental DAT1 alleles and/or response to MPH. It was found that left-sided inattention predicted transmission of the 10-repeat allele from parents to probands and was associated with the severity of ADHD symptomatology. Children rated as achieving a very good response to MPH displayed left-sided inattention, while those rated as achieving a poorer response did not. Our results suggest a subgroup of children with ADHD for whom the 10-repeat DAT1 allele is associated with left-sided inattention. MPH may be most efficacious in this group because it ameliorates a DAT1-mediated hypodopaminergic state