Supplier Selection by the Pair of Nondiscretionary Factors-Imprecise Data Envelopment Analysis Models

Discretionary models for evaluating the efficiency of suppliers assume that all criteria are discretionary, that is, controlled by the management of each supplier and varied at its discretion. These models do not assume supplier selection in the conditions that some factors are nondiscretionary. The objective of this paper is to propose a new pair of nondiscretionary factors-imprecise data envelopment analysis (NF-IDEA) models for selecting the best suppliers in the presence of nondiscretionary factors and imprecise data. A numerical example demonstrates the application of the proposed method.Full Tex

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

Strategic sourcing:a combined QFD and AHP approach in manufacturing

Purpose – This paper aims to develop an integrated analytical approach, combining quality function deployment (QFD) and analytic hierarchy process (AHP) approach, to enhance the effectiveness of sourcing decisions. Design/methodology/approach – In the approach, QFD is used to translate the company stakeholder requirements into multiple evaluating factors for supplier selection, which are used to benchmark the suppliers. AHP is used to determine the importance of evaluating factors and preference of each supplier with respect to each selection criterion. Findings – The effectiveness of the proposed approach is demonstrated by applying it to a UK-based automobile manufacturing company. With QFD, the evaluating factors are related to the strategic intent of the company through the involvement of concerned stakeholders. This ensures successful strategic sourcing. The application of AHP ensures consistent supplier performance measurement using benchmarking approach. Research limitations/implications – The proposed integrated approach can be principally adopted in other decision-making scenarios for effective management of the supply chain. Practical implications – The proposed integrated approach can be used as a group-based decision support system for supplier selection, in which all relevant stakeholders are involved to identify various quantitative and qualitative evaluating criteria, and their importance. Originality/value – Various approaches that can deal with multiple and conflicting criteria have been adopted for the supplier selection. However, they fail to consider the impact of business objectives and the requirements of company stakeholders in the identification of evaluating criteria for strategic supplier selection. The proposed integrated approach outranks the conventional approaches to supplier selection and supplier performance measurement because the sourcing strategy and supplier selection are derived from the corporate/business strategy

Supplier Selection and Evaluation Using Restricting Weights Method in Presence of Dual Factor under Fuzzy Environment.

As businesses grow more complex, so do their supply chains. Data envelopment analysis (DEA) is a useful method for supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. In some situations there are some factors which play both input and output roles as well. The purpose of this research is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This study shows the supplier selection process through a DEA model, while allowing for the incorporation of decision make

Development and application of a composite circularity index

Resource depletion and environmental pollution are increasingly a matter of concern for their adverse effects on ecosystems, human health, and the economy. Circular Economy (CE) practices can help us address these chal-lenges. This paper proposes a composite circularity index (CI) to assess the level of implementation of CE practices. The main advantage of the proposed index is its ability to combine multiple indicators of circularity for different units operating in a given sector (given as inputs), using a 'Benefit of the Doubt' model. This new model is innovative in the manner it deals with ordinal scales and also by considering both relative and absolute performance indices. These indices are computed using mathematical programming tools, building on ideas from Data Envelopment Analysis models.Although the model can be applied to any sector, this work addresses the hotel industry in particular. The selection of indicators for this CI was based on seven blocks of the Circular Economy Action Plan and a literature review of circular practices. An application of the proposed index is performed by using data from Portuguese and Spanish hotels. The proposed CI allows the identification of the organizations with the best and worst performance in implementing the CE practices and clarifying the benchmarks they could follow to improve their level of circularity. Moreover, the index analysis also provides specific targets for improvement, indicating which circular practices should be improved for the lower performers to reach the implementation levels of the best performers.info:eu-repo/semantics/publishedVersio

Supplier Selection and Evaluation Using Restricting Weights Method in Presence of Dual Factor under Fuzzy Environment.

As businesses grow more complex, so do their supply chains. Data envelopment analysis (DEA) is a useful method for supplier selection. Weight restrictions allow for the integration of managerial preferences in terms of relative importance levels of various inputs and outputs. In some situations there are some factors which play both input and output roles as well. The purpose of this research is to propose a method for selecting the best suppliers in the presence of weight restrictions and dual-role factors. This study shows the supplier selection process through a DEA model, while allowing for the incorporation of decision make