A Multi objective model for supplier evaluation and selection in the presence of both cardinal and imprecise data

Imprecise data envelopment analysis (IDEA) has been applied for supplier selection in the presence of both cardinal and imprecise data. In addition to its popularity, IDEA has some drawbacks such as unrealistic inputs-outputs weights and poor discrimination power among all DMUs. To alleviate these deficiencies, this paper develops a multi objective imprecise data envelopment analysis (MOIDEA) based on the common weights. The proposed MOIDEA model is utilized for supplier evaluation and selection in the case where there exist both cardinal and imprecise data. To show both robustness and discriminating power of the proposed approach, it is applied on a numerical example taken from the literature. The results reveal several merits of the common weight MOIDEA model for supplier selection

A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers

An interval efficiency analysis with dual‑role factors

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Data envelopment analysis (DEA) is a data-driven and benchmarking tool for evaluating the relative efficiency of production units with multiple outputs and inputs. Conventional DEA models are based on a production system by converting inputs to outputs using input-transformation-output processes. However, in some situations, it is inescapable to think of some assessment factors, referred to as dual-role factors, which can play simultaneously input and output roles in DEA. The observed data are often assumed to be precise although it needs to consider uncertainty as an inherent part of most real-world applications. Dealing with imprecise data is a perpetual challenge in DEA that can be treated by presenting the interval data. This paper develops an imprecise DEA approach with dual-role factors based on revised production possibility sets. The resulting models are a pair of mixed binary linear programming problems that yield the possible relative efficiencies in the form of intervals. In addition, a procedure is presented to assign the optimal designation to a dual-role factor and specify whether the dual-role factor is a nondiscretionary input or output. Given the interval efficiencies, the production units are categorized into the efficient and inefficient sets. Beyond the dichotomized classification, a practical ranking approach is also adopted to achieve incremental discrimination through evaluation analysis. Finally, an application to third-party reverse logistics providers is studied to illustrate the efficacy and applicability of the proposed approach

Evaluation of the mail delivery sourcing strategy in EDP: saving costs vs excellence quality provided decision

The choice of a company to perform a service that impacts the core operations of a firm can affect the effectiveness of the business and be a major driver for success. In addition, defining a good system to check the performance of the chosen external service providers improves the chances of success. This research paper has the objective of studying what should be behind this important decision, what are the factors to considerate in this choice, how should the service providers be evaluated along the way, what should be the strategy in the sourcing decision. Using as example a company like EDP and its outsourced service of mail delivery, the paper gains even more relevance and constitute a practical view of what happens in real life business. The main findings of this dissertation suggest that a multiple-sourcing strategy, with the allocation between the service providers being decided in consistency with the performance assessed at the time of decision, is the most suitable for EDP, with quality associated being the principal driver of the choice

Relative efficiency measurement in the public sector with data envelopment analysis

PhDTraditional efficiency measures have two significant drawbacks. Firstly, they fail to recognise that output is the result of all inputs operating in combination; thus output per head is a misleading indicator of intrinsic labour productivity. Secondly, they have often been defined in terms of average levels of performance in least squares production functions. In practice, average performance norms may institutionalise some level of inefficiency. The first of these problems may be overcome in a total-factor view of efficiency. This implies the extension of traditional ratio measures to include all inputs and outputs simultaneously. The second requires the comparison of performance with frontier possibilities. Both of these improvements are embodied in Data Envelopment Analysis (DEA). Two applications of DEA are undertaken on U. K. public sector data. The first of these defines frontier efficiency in local education authorities (LEAs). It develops an 8 variable model with 3 outputs (based on exam pass rates) and 5 inputs. Four of the inputs are uncontrollable background variables allowing for differences in student catchment area; the fifth, teaching expenditure, is under LEA control and can be targeted. The results suggest that 44 authorities are best-practice and at the remainder spending per pupil could have been reduced by an average of 6.8%. These results are replicated on smaller clusters of LEAs to examine the sensitivity of DEA to the size of the performance comparison. The clustering procedure produces marked effects on targets, peer groups and the efficiency status of certain authorities. A second case study investigates the performance of a sample of 33 prisons with a high remand population. The model separately identifies the effects of remand prisoners on costs, and includes separate variables to reflect the levels of overcrowding and offences. In 1984/85 the combined budget of these prisons was overspent by 4.6% vis a vis best-practice costs. Using an alternative constant returns technology this overspend rises to 13.1%. Two aspects of DEA targets are explored. A model of Leibenstein's inert area suggests reasons for the persistence of inefficiency and hence that targets may be unattainable without coercion. Secondly, the literature has justified the recommendation of DEA targets in their being Pareto efficient. This interpretation is disputed and an alternative DEA-Dominance criterion is proposed as a more appropriate basis for targeting

Library websites popularity: does Facebook really matter?

The purpose of this paper is to determine whether the utilization of social media (Facebook) is an important factor in increasing the visibility of the library site usage in Malaysian public universities. Nine top ranked Malaysian public universities involved in this research and number of Facebook followers for each library website is listed. Alexa software was used as the approach to study the issue of visibility. Alexa is able to determine web site usage, by showing the percentage of visitors of library related subdomain(s) as listed in the top subdomains for each University website (domain) over a month. It is found that Universiti Utara Malaysia library website scored the highest percentage of visitors based on the library related subdomain(s) as listed in the top subdomains for the University website in Alexa. To check such irregularities in access, this paper use EvalAccess 2.0 and it is found that Universiti Sains Malaysia’s library website scored higher irregularities. In term of number of Facebook followers, Univesity of Malaya library has the highest score. It is showed that the utilization of social media (Facebook) is not yet an important factor in increasing the visibility of the library websites. However, expectedly, top ranked universities’ library web sites, are more visible and popular. This research is limited to the situation in Malaysia where public universities are more noticeable and seldom face financial constraints rather than private universities. It is highly important for those universities’ library web sites that are not highly visible to initiate the necessary measures in improving the development of their web sites as the usage of the website is an indicator of online quality