Plácido Moreno

Cooperative game theory approach to allocating benefits of horizontal cooperation

Logistics costs in general, and transportation costs in particular, represent a large fraction of the operating costs of many companies. One way to try to reduce these costs is through horizontal cooperation among shippers. Thus, when the transportation needs of two or more companies are merged, their collective transportation requirements can be met at lower cost. The attainable cost savings are due to economies of scale, which translate into cheaper rates due to increased negotiation power, use of larger vehicles and bundling of shipments. In this paper, a linear model is presented and used to study the cost savings that different companies may achieve when they merge their transportation requirements. On the one hand, solving this optimization model for different collaboration scenarios allows testing and quantifying the synergies among different potential partners, thus identifying the most profitable collaboration opportunities. On the other, the problem of allocating the joint cost savings of the cooperation is tackled using cooperative game theory. The proposed approach is illustrated with an example in which different cooperative game solution concepts are compared. Extensive numerical experiments have also been carried out to gain insight into the properties of the corresponding cost savings game and the behavior of the different solution concepts.

A network DEA assessment of team efficiency in the NBA

In this paper, a Network DEA approach to assess the efficiency of NBA teams is proposed and compared with a black-box (i.e. single-process) DEA approach. Both approaches use a Slack-Based Measure of efficiency (SBM) to evaluate the potential reduction of inputs consumed (team budget) and outputs produced (games won by the team). The study considers the distribution of the budget between first-team players and the rest of the payroll. The proposed network DEA approach consists of five stages, which evaluate the performance of first-team and bench-team players, the offensive and defensive systems and the ability for transforming the points made by itself and by the opponents into wins. It has been applied to the 30 NBA teams for the regular season 2009–2010. The results show that network DEA has more discriminating power and provides more insight than the conventional DEA approach.

Analysis of the synergies of merging multi-company transportation needs

In this paper, the cost savings that different companies may achieve when they merge their transportation requirements are studied. The cost savings mainly come from the increased possibilities of connecting trips and the use of larger vehicles, in addition to cheaper transport rates due to increased negotiation power. To evaluate these cost savings, a mixed-integer linear programming model is presented allowing the estimation of the synergies among different partners. Then, a simple formula to evaluate an a priori index (based on the transportation demands of the participating companies) is proposed and experimentally validated against the optimal solution of the MILP model. This a priori index has the advantage of identifying the best partnership without having to solve any optimisation model. An analysis of the factors that have influence on the cost savings has also been performed. Apart from the transport rate reduction factor for bundling transportation requirements, the number of companies that cooperate and the degree of commonality between their distribution networks have a significant effect on the cost savings attainable.

Evaluation of Brazilian electricity distributors using a Network DEA model with shared inputs

Data Envelopment Analysis (DEA) is a methodology widely used to assess the efficiency of electricity distribution companies. Most papers use the network length as one of the variables in the modeling: some of them as an input, since it accounts for the total electricity distributed, and others as an output, since it consists in the product of the investments made and the geographic dispersion, thus showing different dimensions of the same problem. In order to deal with this situation, this work presents an innovative way to deal with this variable by using a Network DEA model with two stages. In our proposed approach, the network length has been set to be both the output of the first stage (whose input is a rate of the operating costs) and an input for the second stage (whose outputs are number of consumers and total consumption). In addition, factors for sharing the operating costs between the stages are taken into account. For the sake of completeness, two Network DEA models are introduced, namely relational and additive approaches. Finally, the results of both models are presented, compared and discussed.

Network Fuzzy Data Envelopment Analysis

In this chapter a general approach to handle fuzzy data when the units under analysis are formed by a network of processes is presented. Conventional DEA assumes a single-process that consumes all the different inputs and produces all the different outputs. Network DEA, on the contrary, considers different interrelated processes, each one with its own inputs, its own outputs and, very important, its own technology. This allows a more fine-grained analysis although at the expense of requiring more data. Conventional Network DEA approaches assume crisp data although recently two proposals have been made that can process fuzzy data in the special cases of a serial two-stage system and of parallel production processes. There is, however, a need to deal with general networks of processes which can have fuzzy input or output data. In this chapter, several Fuzzy DEA approaches are extended to Network DEA. The resulting models are illustrated on a dataset from the literature.

A constructivist approach to studying the bullwhip effect by simulating the supply chain

The Cider Game is a simulator for a supply chain-related learning environment. Its main feature is that it provides support to students in the constructivist discovery process when learning how to make logistics decisions, at the same time as noting the occurrence of the bullwhip phenomenon. This learning environment seeks a balance between direct instruction in the learning process on the part of the tutor, and a suitable and sufficient degree of freedom to regulate independent learning on the part of students. This article describes the basic learning mechanisms using the Cider Game and the graphical learning environments that it provides. We describe the functionality provided by this application, and analyse the effect over the rational understanding of the bullwhip phenomenon by the students and whether they are able to make decisions to minimise its impact, studying the differences when that decision-making learning is done individually or in groups.

An exploratory study of Spanish households’ WEEE disposal behaviour

This paper presents the findings of an exploratory study based on a survey of 1,537 households in Spain. The questionnaire included 23 key questions regarding the number of appliances in use, previous appliances lifetimes, reasons for buying each new appliance and end-of-life handling of discarded appliances. The distribution of the households along a number of relevant factors was analysed and a prototypical household was identified. A non-parametric analysis of the duration of each type of appliance has also been carried out and it was found that television sets are the most durable of the appliances considered. Survival rates for irons fall more rapidly than for microwaves. Moreover, television sets are the most durable of the appliances considered. Replacement rates of personal computers rapidly increase after approximately six to eight years. Finally, a statistical analysis of the respondents motivations for recycling the appliances considered in this study was carried out.

Influence of the environmental impact of logistics operations on the centralization strategy

Several factors must usually be taken into account when deciding the design of a supply chain network. In most cases, the economic impact and the resulting service quality are the most common. In this sense, one of the strategies with a big impact in both factors is which inventory centralization level is the most appropriate. High decentralization levels usually provides a better service but with a higher costs due to a more inefficient use of resources. However, the environmental impact of this decision has not been considered in this equation. Here it is analyzed whether considering environmental impact could affect the decision regarding the centralization level. An experimental framework has been designed to check the influence of two factors (the clustering of the clients and their closeness to the manufacturing plant), using a MILP model to look for the best distribution network for each instance.

A DEA model for two-stage systems with Fuzzy data

Data Envelopment Analysis (DEA) aims at assessing the relative efficiency of a number of comparable operating units. Network DEA is used when the units consist of interrelated processes. The simplest network DEA structure is a two-stage serial system. In this paper a well-known Fuzzy DEA approach is extended to this network DEA context. The proposed approach is simpler than the existing approach with which it is compared using a dataset from the literature.