The importance of enterprise risk management in large companies in Colombia

The main aim of this paper is to establish that essential aspects are determinant in the enterprise risk identification (ERI) and the existing interrelationship between each corporate risk goals, in the large companies of Colombia. Study proposes a parametric analysis and a non-parametric. The first uses correlation matrices for statistical analysis, a multiple linear regression statistical tools to identify that essential aspects are determinant in the (ERI). The second proposes a new aggregation called the Bonferroni Induced Ordered Weighted Average Adequacy Coefficient (BON-IHOWAAC) operator and Bonferroni Induced Ordered Weighted Average the Maximum and Minimum level (BON-IHOWAIMAM) to establish the existing interrelationship between each corporate risk goals using the risk management information and manager perception. Of the results obtained is highlighted that for all economic sectors; first, control measures are highlighted in the (ERI) and second, the goal with the greatest interrelationship for the other ones to be achieved is protect people. Finally, the study concludes with a holistic analysis of the importance that executive team gives to the management of risks from the prioritization of objectives and the use of tools for the treatment of information to improve the process of decisions-making in uncertain contexts.  First published online 5 April 201

A Comparison of Two Balance Calibration Model Building Methods

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance

Global testing under sparse alternatives: ANOVA, multiple comparisons and the higher criticism

Testing for the significance of a subset of regression coefficients in a linear model, a staple of statistical analysis, goes back at least to the work of Fisher who introduced the analysis of variance (ANOVA). We study this problem under the assumption that the coefficient vector is sparse, a common situation in modern high-dimensional settings. Suppose we have $p$ covariates and that under the alternative, the response only depends upon the order of $p^{1-\alpha}$ of those, $0\le\alpha\le1$. Under moderate sparsity levels, that is, $0\le\alpha\le1/2$, we show that ANOVA is essentially optimal under some conditions on the design. This is no longer the case under strong sparsity constraints, that is, $\alpha>1/2$. In such settings, a multiple comparison procedure is often preferred and we establish its optimality when $\alpha\geq3/4$. However, these two very popular methods are suboptimal, and sometimes powerless, under moderately strong sparsity where $1/2<\alpha<3/4$. We suggest a method based on the higher criticism that is powerful in the whole range $\alpha>1/2$. This optimality property is true for a variety of designs, including the classical (balanced) multi-way designs and more modern "$p>n$" designs arising in genetics and signal processing. In addition to the standard fixed effects model, we establish similar results for a random effects model where the nonzero coefficients of the regression vector are normally distributed.Comment: Published in at http://dx.doi.org/10.1214/11-AOS910 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Dimensionality of the Pay Satisfaction Questionnaire: A Confirmatory Factor Analytic Investigation

The present study applied confirmatory factor analysis in investigating the dimensionality of the Pay Satisfaction Questionnaire. Using a more rigorous and extensive series of tests than has been the case with past research, and employing longitudinal data from 2 samples of workers, the present study supported the 4 dimensions suggested by Heneman and Schwab (1985). The four-factor solution was supported both at Time 1 and Time 2, despite the fact that a compensation intervention occurred between the time intervals. Implications of the results are discussed

'Possunt, quia posse videntur': They can because they think they can. Development and Validation of the Work Self-Efficacy Scale: Evidence from two Studies

Self-efficacy (SE) has been recognised as a pervasive mechanism of human agency influencing motivation, performance and well-being. In the organisational literature, it has been mainly assessed in relation to job tasks, leaving the emotional and interpersonal domains quite unexplored, despite their relevance. We aim to fill this gap by presenting a multidimensional work self-efficacy (W-SE) scale that assesses employees' perceived capability to manage tasks (task SE), negative emotions in stressful situations (negative emotional SE), and their conduct in social interactions, in terms of both defending their own point of view (assertive SE) and understanding others' states and needs (empathic SE). Results from two independent studies (Study 1, N=2192 employees; Study 2, N=700 employees) adopting both variable- and person-centred approaches support the validity of the scale. Findings of factor analyses suggest a bi-factor model positing a global W-SE factor and four specific W-SEs, which are invariant across gender and career stages. Multiple regressions show that global W-SE is associated with all considered criteria, task SE is associated positively with in-role behaviours and negatively with counterproductive behaviours; negative emotional SE is negatively associated with negative emotions and health-related symptoms; empathic SE is positively associated with extra-role behaviour; and, unexpectedly, assertive SE is positively associated with counterproductive work behaviour. However, results from a Latent Profile Analysis showed that the relationship between the SEs and criteria is complex, and that W-SE dimensions combine into different patterns, identifying four SE configurations associated with different levels of adjustment

Using chi-squared automatic interaction detection modelling to identify student opinion profiles regarding same-sex couples as a family structure

The aim was to determine the opinions held by a sample of students in relation to homoparenting as a family modality. A cross-sectional study was conducted on a sample of university students specialization: social sciences using the AHFH. It is patent that opinions of students about the three factors (support, rejection and acceptance) that compose the construct of attitudes towards same-sex couples as a family structure, differ greatly depending on the positive or negative nature of these components. In conclusion, in relation to the dimension pertaining to rejection of same-sex couples as a family entity, we derived a configuration determined by 1 of the 4 predictor variables. In this case, gender was the only one of the 4 variables considered to support formation of a profile. This profile was constituted by male students who, independent of their birthplace setting, qualification and whether they personally know any same-sex couples, showed stronger agreement with the dimension describing rejection of same-sex couples as a family structure

Conditional Screening for Ultra-high Dimensional Covariates with Survival Outcomes

Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a critical component of precision medicine. The emergence of large-scale biomedical survival studies, which typically involve excessive number of biomarkers, has brought high demand in designing efficient screening tools for selecting predictive biomarkers. The vast amount of biomarkers defies any existing variable selection methods via regularization. The recently developed variable screening methods, though powerful in many practical setting, fail to incorporate prior information on the importance of each biomarker and are less powerful in detecting marginally weak while jointly important signals. We propose a new conditional screening method for survival outcome data by computing the marginal contribution of each biomarker given priorly known biological information. This is based on the premise that some biomarkers are known to be associated with disease outcomes a priori. Our method possesses sure screening properties and a vanishing false selection rate. The utility of the proposal is further confirmed with extensive simulation studies and analysis of a Diffuse large B-cell lymphoma (DLBCL) dataset.Comment: 34 pages, 3 figure

New aggregation operators for decision-making under uncertainty: an applications in selection of entrepreneurial opportunities

The main aim of this paper is to study how economic environment and logic reasoning guidance the decision-making process to start-up a new business by potential entrepreneurs. The study proposes a new method using the family of selection indices with OWA operator, which allows aggregating information according to the level of importance and their level of objectivity and subjectivity in the same formulation within the decision-making process. To develop case study, we have taken into account some industries of the sports sector and some critical environmental factors that influence the competitiveness and entrepreneurship in Colombia to start a new business. The results show in an orderly way all information aggregated, which can help potential investors and entrepreneurs to make a decision based on their preferences. Finally, the applicability of this method in real case can be given in aggregation different sources of information to help at dealing decision-making processes

An Exploration of Alternative Scoring Methods Using Curriculum-Based Measurement in Early Writing

This manuscript describes two empirical studies of alternative scoring procedures used with curriculum-based measurement in writing (CBM-W). Study 1 explored the technical adequacy of a trait-based rubric in first grade. Study 2 explored the technical adequacy of a trait-based rubric, production-dependent, and production-independent scores in third grade. Results of Study 1 suggest that the rubric holds promise as a valid measure of sentence writing ability in first grade and has utility as a supplemental scoring procedure when using CBM-W as a screening tool. Results of Study 2 show that correct word sequences maintained the highest correlation coefficients across time with the trait-based rubric, but the other scoring procedures might offer promise as reliable alternative scoring methods. However, high internal correlations among the text features of the rubric along with highly variable interrater reliability suggest that caution must be taken in interpreting results

Life satisfaction in retirement and assessment of need for pre-retirement planning /

This study seeks to examine the relationship between current life satisfaction of retirees and the desire retirees, now that they are in retirement, have for further information to improve the quality of retirement life. The study's examination of current retirement life satisfaction and the retiree's desire for additional information to improve the quality of retirement should reinforce stated observations that pre-retirement planning minimizes the negative effects of retirement and increases retirement life satisfaction.A study was made of 180 retirees from a multinational corporation in the southwest to determine the relationship between state of health, educational level, financial level, marital status, and gender and positive life satisfaction in retirement. The retiree's concept of life in retirement was assessed. The results of this study showed that marital status was the most significant factor in positive life satisfaction in retirement for this sample. State of health was also a factor but the level of significance was not as great. There was no relationship between educational level, financial level, and gender and positive life satisfaction in retirement. The sample as a whole had done no pre-retirement planning