A formal model for analyzing manager’s performance during stress

Managers who are exposed to stress have the risk of taking insufficient decisions, which will affect their performance levels. The affect could be either positive or negative, depending on the individual’s perception on stress. Many inadequate conventional studies have been conducted for analyzing the complicated relationship of stress and performance. Hence this study introduces a formal model supports managers’ performance during stress. This model can be encapsulated within an intelligent agent or robots that can be used to support managers. The methodology was used to explore human cognitive processes during stress consisted of four phases: identification of local and non-local properties, conceptualization of the model of these properties, formalization, and evaluation. Deferential equations have been used in formalizing the properties. The developed model has been simulated by applying it to different scenarios. Mathematical analysis has been used for the evaluation of the model. Results showed that the formal model was able to show the effects of different levels of stress on managers’ performance

On Firm Growth and Innovation. Some new empirical perspectives using French CIS (1992-2004)

In the paper we wish to examine if the firms that innovate know a higher growth than the firm that do not. We use diverse waves of CIS for the French industries over the period 1992- 2004 and carry out different models and new econometric methods (quantile regression). Our main findings are that innovative firms produce more growth than non innovative firms. The estimates show that the results are robust to the different types of models that we have implemented. Process innovators are more productive in terms of growth than product innovators when OLS and Random effects models are used. The reverse is true for Fix effect model and quantile regression. In the three growth equations estimated by GMM the coefficients related to innovation product are always higher. Our study does not give definitive results with respect to the magnitude of the effects of the type of innovation on firm growth.Innovation, process and product, firm growth, CIS

Explaining Predictions from Tree-based Boosting Ensembles

Understanding how "black-box" models arrive at their predictions has sparked significant interest from both within and outside the AI community. Our work focuses on doing this by generating local explanations about individual predictions for tree-based ensembles, specifically Gradient Boosting Decision Trees (GBDTs). Given a correctly predicted instance in the training set, we wish to generate a counterfactual explanation for this instance, that is, the minimal perturbation of this instance such that the prediction flips to the opposite class. Most existing methods for counterfactual explanations are (1) model-agnostic, so they do not take into account the structure of the original model, and/or (2) involve building a surrogate model on top of the original model, which is not guaranteed to represent the original model accurately. There exists a method specifically for random forests; we wish to extend this method for GBDTs. This involves accounting for (1) the sequential dependency between trees and (2) training on the negative gradients instead of the original labels.Comment: SIGIR 2019: FACTS-IR Worksho

Regional distribution, mobility and productivity of french prolific inventors

In this paper we present empirical evidence about some geographical characteristics of French prolific inventors through an analysis of French patents depos- its at the USPTO over a long time period (1975-2002). We found out that they are highly concentrated in the French space around three regional poles (Ile de France, Rhône- Alpes and PACA) and that inter-firms and geographic (regional) mobility is weak. Our estimates show that more mobile inventors (inter-firms) are more productive after con- trolling for effects of geomobility (with other control variables). By contrast, the more geomobile inventors are less productive after controlling for inter-firms’ mobility ef- fects. It means that the geographic dimension of mobility does not bring more effective- ness in the individual process of creativity. We must bear in mind there is a bias of si- multaneity within the relationship productivity/mobility that is not dealt with here