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.
Esposito Vinzi V.,ESSEC Business School Paris
International Journal of Production Economics | Year: 2012
In this paper, we investigate the relationships between environmental management (EM) and performance to verify: whether the implementation of an effective internal environmental is a firm's precondition to belong to a green supply chain; which type of environmental practices (either internal or external) contribute the most to increasing a firm's performances; and whether performing the environment translates into higher economic performance. We use structural equation modeling for testing our research hypotheses on a large sample of Italian firms, and estimate the structural paths between constructs by means of both covariance- and component-based approaches. The use of both estimation methods allows us contributing to the recent debate about the specification of the performance construct as an emerging rather than as a latent variable, and then using formative rather than reflective indicators. Formative indicators are used whenever a construct does not exist without its measures, any change in one of the indicators causes a change in the construct, and the measures are ingredients of the construct rather than being caused by it. For instance, economic performance is an emerging construct since economic measures (e.g.; profits and market share) contribute to forming the construct rather than reflecting the behavior of the latent variable. We show that the correct model specification changes the estimates of the path coefficients and leads to research findings aligned to the literature. Our results indicate that being green internally is a prerequisite for collaboration into a green supply chain, internal EM contributes to increasing performance more than external EM, while performing the environment does not lead to a higher economic performance. © 2011 Elsevier B.V. All Rights Reserved.
Kooli A.,ESSEC Business School Paris |
Serairi M.,CNRS Heuristic and Diagnostic Methods for Complex Systems
Computers and Operations Research | Year: 2014
In this paper, we consider the problem of scheduling on a one-machine, a set of operations subject to unequal release dates with respect to the total completion time. This problem is known to be NP-hard in the strong sense. We propose an algorithm based on a Mixed Integer Linear Programming. This algorithm includes the implementation of a preprocessing procedure together with the consideration of valid inequalities. A computer simulation to measure the performance of the algorithm shows that our proposed method outperforms state-of-the-art branch-and-bound algorithms. © 2014 Elsevier Ltd.
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.
Althuizen N.,ESSEC Business School Paris |
Wierenga B.,Erasmus University Rotterdam
Journal of Management Information Systems | Year: 2014
Attention for the division of work between computers and humans is growing due to ever-increasing computer capabilities. Over the past decades, creativity support systems (CSSs) have gained ground as a means to enhance individual, group, and organizational creativity. Whereas prior research has focused primarily on the main effects of CSSs, we explore the interaction effects with the creative ability of the individual. In this paper, we investigate the use of the case-based reasoning (CBR) technology, which is based on the principle of analogical reasoning, to aid individuals in solving business problems creatively. The expectations as to why the CBR technology should enhance individual creativity, and under what conditions (i.e., the type and number of cases that are made available), are derived from creative cognition theory, and are tested empirically. In a series of studies, a CBR system loaded with a diverse set of cases was found to enhance the performance of individuals with lower creative ability, but it did not help the most creative individuals. Although the literature suggests that cases from remote problem domains should lead to more novel solutions, loading the CBR system only with cases closely related to the problem domain proved more effective than remote cases only. Finally, loading the CBR system with a larger set of diverse cases was found to positively influence the creativity of the solutions. These findings have the following implications for CSSs and creative cognition theory: (1) when considering the effectiveness of CSSs it is important to take into account the creative ability of the individual (i.e., "one size does not fit all"), (2) making a sufficiently large and diverse set of cases available is better for stimulating creativity, and (3) providing cases that are too remote may be counterproductive. On a practical note, organizations seeking to redesign their division of labor between individuals and machines can easily follow the CBR approach presented here using their own set of cases. © 2014 M.E. Sharpe, Inc.
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.
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.
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.
Li J.,ESSEC Business School Paris
Computational Statistics and Data Analysis | Year: 2013
A smoothing algorithm based on the unscented transformation is proposed for the nonlinear Gaussian system. The algorithm first implements a forward unscented Kalman filter and then evokes a separate backward smoothing pass by only making Gaussian approximations in the state but not in the observation space. The method is applied to volatility extraction in a diffusion option pricing model. Both simulation study and empirical applications with the Heston stochastic volatility model indicate that in order to accurately capture the volatility dynamics, both stock prices and options are necessary. © 2010 Elsevier B.V. All rights reserved.
Sluis S.,VU University Amsterdam |
De Giovanni P.,ESSEC Business School Paris
Journal of Operations Management | Year: 2016
This paper seeks to empirically identify the key drivers for firms in selecting a contract in a supply chain by investigating their performance, supply chain orientation, and supply chain integration. A conceptual model is drawn up based on the existing literature in supply chain coordination contracts, performance, supply chain orientation, and supply chain integration and tested on a large sample of European firms. Multiple and multinomial logistic regression models allow for estimating the relationships between these variables. Our results demonstrate that the selection of contracts and the probability of their adoption depend on several combinations of firms' performance, supply chain orientation, and integration. Overall, the research provides an empirical contribution to the literature on coordination with contracts, which turns out to be mainly game theory based. © 2015 Elsevier B.V.