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Cergy-Pontoise, France

Zargoush M.,ESSEC Business School Paris
Health care management science | Year: 2014

We examine the role of a common cognitive heuristic in unsupervised learning of Bayesian probability networks from data. Human beings perceive a larger association between causal than diagnostic relationships. This psychological principal can be used to orient the arcs within Bayesian networks by prohibiting the direction that is less predictive. The heuristic increased predictive accuracy by an average of 0.51 % percent, a small amount. It also increased total agreement between different network learning algorithms (Max Spanning Tree, Taboo, EQ, SopLeq, and Taboo Order) by 25 %. Prior to use of the heuristic, the multiple raters Kappa between the algorithms was 0.60 (95 % confidence interval, CI, from 0.53 to 0.67) indicating moderate agreement among the networks learned through different algorithms. After the use of the heuristic, the multiple raters Kappa was 0.85 (95 % CI from 0.78 to 0.92). There was a statistically significant increase in agreement between the five algorithms (alpha < 0.05). These data suggest that the heuristic increased agreement between networks learned through use of different algorithms, without loss of predictive accuracy. Additional research is needed to see if findings persist in other data sets and to explain why a heuristic used by humans could improve construct validity of mathematical algorithms. Source

De Giovanni P.,ESSEC Business School Paris
Dynamic Games and Applications | Year: 2016

This paper analyzes two incentive schemes available for a closed-loop supply chain (CLSC) in which a manufacturer and a retailer contribute to the return rate dynamics through their investments in green activity programs. Both firms have economic motivations to perform the return rate because customers who return end-of-use goods also repurchase new ones. In addition, the manufacturer exploits the returns’ residual value in operations to increase profits. Because the manufacturer has both operational and marketing motivations to close the loop, he can provide an incentive to the retailer to boost her investments in green activity programs. The incentive can be either state dependent or control dependent. The former assumes that the incentive depends on the fraction of customers who are willing to return end-of-use products; the latter is proportional to the retailer’s green activity programs efforts. Our results show that a state-dependent incentive is profit-Pareto-improving only when the retailer’s environmental effectiveness is large. In contrast, a control-dependent incentive mechanism is profit-Pareto-improving for low incentive values, high retailer’s environmental effectiveness, and customers’ repurchasing intention. In all other cases, players have divergent preferences and neither mechanism coordinates the CLSC. © 2015, Springer Science+Business Media New York. Source

Prat N.,France Business School | Akoka J.,Orange S.A. | Comyn-Wattiau I.,ESSEC Business School Paris
Expert Systems with Applications | Year: 2012

This paper proposes an MDA approach to knowledge engineering, centered on the CommonKADS knowledge model. The latter corresponds to the CIM level of MDA whereas PRR, which represents production rules and rulesets, corresponds to the PIM level. The paper explores the mapping between CommonKADS knowledge models and production rules and rulesets based on PRR. Mapping CommonKADS knowledge models into PRR is very useful, due to the fact that the CIM level remains relatively unexplored, despite its key role in MDA. This motivates our choice to focus on the CIM and PIM levels. Furthermore, the mapping between PIM and PSM (i.e. the implementation of production rules in specific rule-based systems) constitutes less of an issue. To map CommonKADS knowledge models into PRR production rules and rulesets, we propose and illustrate a set of transformations. To ease these transformations, we start by grouping elements of the CommonKADS knowledge models into so-called "inference groups". We propose and illustrate an algorithm that defines these inference groups automatically. The definition of transformations between models (CIM to PIM levels) requires a specific metamodel for CommonKADS as well as a dedicated metamodel for PRR. Unlike PRR, there is no published CommonKADS metamodel. This paper proposes a comprehensive CommonKADS knowledge metamodel. We describe and discuss an example, applying the whole approach. © 2012 Elsevier Ltd. All rights reserved. Source

Duan J.-C.,National University of Singapore | Fulop A.,ESSEC Business School Paris
Statistics and Computing | Year: 2011

This article develops a new and stable estimator for information matrix when the EM algorithm is used in maximum likelihood estimation. This estimator is constructed using the smoothed individual complete-data scores that are readily available from running the EM algorithm. The method works for dependent data sets and when the expectation step is an irregular function of the conditioning parameters. In comparison to the approach of Louis (J. R. Stat. Soc., Ser. B 44:226-233, 1982), this new estimator is more stable and easier to implement. Both real and simulated data are used to demonstrate the use of this new estimator. © 2009 Springer Science+Business Media, LLC. Source

Carbone V.,ESCP Europe | Moatti V.,ESCP Europe | Vinzi V.E.,ESSEC Business School Paris
Business Strategy and the Environment | Year: 2012

Corporate responsibility (CR) in general, and sustainable supply chain management in particular, have been a growing concern for companies and researchers over the past decade. However, in scholarly work, sustainability has often been dealt with in a generic fashion or from an anecdotal point of view. Further, research works examining CR on the one hand and sustainable supply chains on the other have been conducted separately. We undertake the multiple factor analysis of a CR rating database (Innovest) which reports longitudinal scores for both the social and environmental performance of 1198 companies in different countries and distinct industries, to demonstrate a strong relationship between CR and a sustainable supply chain. Our findings from exploratory analysis also illustrate the role of country of origin and industry in shaping CR behaviour, highlighting isomorphic as well as allomorphic trends for CR trough time. © 2012 John Wiley & Sons, Ltd and ERP Environment. Source

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