Multi-Factor Policy Evaluation and Selection in the One-Sample Situation

Firms nowadays need to make decisions with fast information obsolesce. In this paper I deal with one class of decision problems in this situation, called the “one-sample” problems: we have finite options and one sample of the multiple criteria with which we use to evaluate those options. I develop evaluation procedures based on bootstrapping DEA (Data Envelopment Envelopment) and the related decision-making methods. This paper improves the bootstrap procedure proposed by Simar and Wilson (1998) and shows how to exploit information from bootstrap outputs for decision-making

Supply Chain Management and Management Science: A Successful Marriage

The last century has witnessed extant studies on the applications of Management Science (MS) to a diverse set of Supply Chain Management (SCM) issues. This paper provides an overview of the contribution of MS within SCM. A framework is developed in this paper with a sampling of MS contributions to major SCM dimensions. Future research directions are presented

Enhancing Supplier Development: An Efficiency Perspective

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147112/1/jbl12197_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147112/2/jbl12197.pd

Small firms captive in a box like lobsters

The paper empirically investigates whether a lack of competition determines the poor productivity performance of the European business services. It uses detailed panel data for 13 EU countries over the period 2000-2005. We apply parametric and nonparametric methods to estimate the productivity frontier and subsequently explain the distance to the productivity frontier by market characteristics, entry and exit dynamics and national regulation. We find that the most efficient scale in business services is close to 20 employees. Scale inefficiencies show a hump-shape pattern with strong potential scale economies for the smallest firms. Nonetheless, some 95% of the firms operate at a scale below the minimal optimal scale. While they are competitive in the sense that their productivities are very similar, they have strong scale diseconomies compared to the larger firms. Their scale inefficiency is persistent over time, which points to growth obstacles that hamper the achievement of scale economies. Regulation characteristics explain this inefficiency; in particular, regulation-caused exit and labour reallocation costs are found to have a large negative impact on productivity performance.

Competitive, but too small - productivity and entry-exit determinants in European business services

The paper investigates whether scale effects, market structure, and regulation determine the poor productivity performance of the European business services industry. We apply parametric and nonparametric methods to estimate the productivity frontier and subsequently explain the distance of firms to the productivity frontier by market characteristics, entry- and exit dynamics and national regulation. The frontier is assessed using detailed industry data panel for 13 EU countries. Our estimates suggest that most scale advantages are exhausted after reaching a size of 20 employees. This scale inefficiency is persistent over time and points to weak competitive selection. Market and regulation characteristics explain the persistence of X-inefficiency (sub-optimal productivity relative to the industry frontier). More entry and exit are favourable for productivity performance, while higher market concentration works out negatively. Regulatory differences also appear to explain part of the business services' productivity performance. In particular regulation-caused exit and labour reallocation costs have significant and large negative impacts on the process of competitive selection and hence on productivity performance. Overall we find that the most efficient scale in business services is close to 20 employees and that scale inefficiencies show a hump-shape pattern with strong potential scale economies for the smallest firms and diseconomies of scale for the largest firms. The smallest firms operate under competitive conditions, but they are too small to be efficient. And since this conclusion holds for about 95 out of every 100 European business services firms, this factor weighs heavily for the overall productivity performance of this industry

A contribution to supply chain design under uncertainty

Dans le contexte actuel des chaînes logistiques, des processus d'affaires complexes et des partenaires étendus, plusieurs facteurs peuvent augmenter les chances de perturbations dans les chaînes logistiques, telles que les pertes de clients en raison de l'intensification de la concurrence, la pénurie de l'offre en raison de l'incertitude des approvisionnements, la gestion d'un grand nombre de partenaires, les défaillances et les pannes imprévisibles, etc. Prévoir et répondre aux changements qui touchent les chaînes logistiques exigent parfois de composer avec des incertitudes et des informations incomplètes. Chaque entité de la chaîne doit être choisie de façon efficace afin de réduire autant que possible les facteurs de perturbations. Configurer des chaînes logistiques efficientes peut garantir la continuité des activités de la chaîne en dépit de la présence d'événements perturbateurs. L'objectif principal de cette thèse est la conception de chaînes logistiques qui résistent aux perturbations par le biais de modèles de sélection d'acteurs fiables. Les modèles proposés permettent de réduire la vulnérabilité aux perturbations qui peuvent aV, oir un impact sur la continuité des opérations des entités de la chaîne, soient les fournisseurs, les sites de production et les sites de distribution. Le manuscrit de cette thèse s'articule autour de trois principaux chapitres: 1 - Construction d'un modèle multi-objectifs de sélection d'acteurs fiables pour la conception de chaînes logistiques en mesure de résister aux perturbations. 2 - Examen des différents concepts et des types de risques liés aux chaînes logistiques ainsi qu'une présentation d'une approche pour quantifier le risque. 3 - Développement d'un modèle d'optimisation de la fiabilité afin de réduire la vulnérabilité aux perturbations des chaînes logistiques sous l'incertitude de la sollicitation et de l'offre

Green supplier selection problems with data scaling and production frontier estimations in a DEA model

Considering ecological issues in supplier evaluation and management alongside business considerations is getting more recognition among firms. Data envelopment analysis (DEA) is one of those methods, which is frequently suggested by the literature to support management decisions. However, the data requirements of the method should be an important consideration. The literature often addresses the issue of desirable outputs and undesirable input as an important data related problem in case of the ecological use of DEA. This paper will present a new solution to manage these data problems along with connecting the evaluation of management criteria, environmental criteria and total cost aspects. The proposed environmental supplier selection problem is an extension of a former paper. The new model examines the effect of inventory related costs, such as EOQ costs of inventory holding or ordering costs on the selected supplier, extended with newly introduced scaled values of input and output indicators. The usage of scaled values is motivated by the problem of invariance to data alteration. In addition to the uncertainty of the data, the paper looks for a functional relationship between the input and output criterion values and the efficiency that can be assigned to them using DEA

Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

Multiple attribute decision making (MADM) problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China

A methodology for project portfolio selection under criteria prioritisation, uncertainty and projects interdependency – combination of fuzzy QFD and DEA

© 2018 Elsevier Ltd Resources of an organisation (people, time, money, equipment, etc) are never endless. As such, a constant and continuous challenge for decision makers is to decide which projects should be given priority in terms of receiving critical resources in a way that the organisation's productivity and profitability is best guaranteed. Previous literature has already developed a plenitude of project portfolio selection methodologies ranging from simple scoring to complex mathematical models. However, most of them too often fail to propose one integrated and seamless method that can simultaneously take into account three important elements: (1) prioritisation of selection criteria over each other, (2) uncertainty in decision-making, and (3) projects interdependencies. This paper aims to fill this gap by proposing an integrated method that can simultaneously address all these three aspects. The proposed method combines Quality Function Development (QFD), fuzzy logic, and Data Envelopment Analysis (DEA) to accounts for prioritisation, uncertainty and interdependency. We then apply this method in a numerical example from a real world case to illustrate the applicability and efficacy of the proposed methodology