Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS

Chamodrakas, Ioannis; Alexopoulou, Nancy; Martakos, Drakoulis

doi:10.1016/j.eswa.2008.09.050

Cited by 90 publications

(40 citation statements)

References 20 publications

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“…Thus, we can use (16) to calculate the overall criteria weights, and the calculated results are listed in Table 5.…”

Section: Application Of the Developed Techniquementioning

confidence: 99%

“…To adequately solve various actual decision making problems, many prominent MCDM approaches including the TOPSIS [4,5], the PROMETHEE method [6], and the QUALIFLEX [7,8] have been developed during the past decade. As one of the most popular MCDM methods, the TOPSIS approach which ranks objects based on closeness degrees, according to the principle that the best objects should have the shortest distance from positive ideal solutions (PISs) and the farthest distance from negative ideal solutions (NISs) [4], has successfully been applied in realworld MCDM problems including the selection of suppliers [9,10], performance measurement [11], the selection of plant location [12,13], personnel selection [14], the risk assessment of bridges [15], and customer evaluation [16].…”

Section: Introductionmentioning

confidence: 99%

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Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

Zhang

Yang

Liang

et al. 2018

Discrete Dynamics in Nature and Society

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The aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF) multicriteria decision making (MCDM) approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the proposed HTrF MCDM method is the consideration of uncertain qualitative information represented by flexible linguistic expressions based on HTrF values and the construction of compromise solution with the revised closeness degree. The revised closeness degree can make sure that the most appropriate solution has the shortest distance from the HTrF positive ideal solution and the farthest distance from the HTrF negative ideal solution, simultaneously. This proposed HTrF MCDM technique not only offers a simple and efficient decision support tool to aid the food firms for identifying the optimal suppliers in food supply chain but also can enable the managers of food firms to better understand the complete evaluation and decision processes. In addition, this study provides a novel defuzzification technique to manage the HTrF weights values of main-criteria and subcriteria, respectively.

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“…Thus, we can use (16) to calculate the overall criteria weights, and the calculated results are listed in Table 5.…”

Section: Application Of the Developed Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

Zhang

Yang

Liang

et al. 2018

Discrete Dynamics in Nature and Society

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show abstract

“…In this study, the emphasis was placed on the choice of an appropriate number of priority classes to avoid promising scarce capacity to wrong customers. Chamodrakas et al (2009)considered customer evaluation and prioritization in the context of the order acceptance process of suppliers and proposed the use of fuzzy methods to this end. They used four qualitative criteria which were ranked in an ordinal manner to assess customers' value and assign capacity accordingly.…”

Section: Customer Segmentationmentioning

confidence: 99%

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

Mobini

Behdani

Lukszo

et al. 2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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SummaryOrder acceptance (OA) has a large inuence on the performance of an enterprise. On the one hand, always accepting an order when capacity is available may restrict the system to accept more protable orders in the future. On the other hand, rejecting too many orders leads to low capacity utilization and also has repercussions for future customer relations. In addition, accepting too many orders leads to an over-loaded production environment, where lead times increase and orders are delivered late. Most of these aspects of order acceptance decision-making can be handled by having proper negotiations with customers on order terms. However, this is a complex problem primarily because there are dierent actors who have various (conicting) interests, needs and objectives. Accordingly, to provide insight for the decision makers in the rms in order to develop proper strategies for order acceptance, developing appropriate models seems necessary.The objective in this research is to improve the order acceptance performance of a make-to-order multi-plant enterprise (MPE) by incorporating buyer-seller negotiations in its OA procedure with the main research question of How can the buyer-seller negotiation process contribute to the improvement of order acceptance performance in the multi-plant enterprise?For this purpose, we have developed an agent-based model to support order acceptance decisions in a multi-plant enterprise particularly using dierent negotiation settings.The research starts with literature review on order acceptance in general and negotiation in particular. A gap is identied in the OA literature: the major perspectives on the OA procedure rest on the underlying assumption that order terms are already determined which is not always tenable. In reality, order terms are usually specied by negotiation between the buyer and the seller and they are not predetermined. A negotiation-based order acceptance approach is consequently suggested in order to consider the whole activities in a negotiation process with three phases. The proposed process involves the initiation conditions for negotiation (pre-negotiation phase), the main interaction (negotiation phase) and the consequences of negotiation on the future decisions of the involved actors (post-negotiation phase). This negotiation process is a part of more general negotiation framework which is then extended into a negotiation ontology. The ontology introduces the main concepts and their relations in a negotiation problem. Next, the conceptualization of the order negotiation process in OA and the negotiation ontology are used in developing an agent-based model for buyer-seller negotiations in a case of multi-plant enterprise. The general assumptions and settings for model development are taken from a model have been presented by Behdani et al. (2010) for a lube oil multi-plant case study motivated by a real supply chain.In this research, the previous model is extended by incorporating negotiation between the ii enterprise and its customers on order terms. Final...

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“…Chamodrakas et al (2009) investigated customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS. Kelemenis et al (2011) studied on support managers' selection using an extension of fuzzy TOPSIS.…”

Section: Topsis Techniquementioning

confidence: 99%

An application of TOPSIS method for ranking different strategic planning methodology

Esfandiari¹,

Rizvandi²

2014

10.5267/j.msl

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Strategic planning is one of the most popular methods for setting up long-term objectives, which normally deals with various criteria. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method for ranking different alternatives based on various criteria. The method has been widely used among practitioners in different industries. This paper presents an empirical investigation to rank different business development strategies for information technology improvement. The study considers five different strategies including Critical Success Factors Analysis, Business Systems Planning, Porter's forces model, SWOT analysis, Value chain Analysis and MIN and rank them based on TOPSIS technique. The results of the implementation of TOPSIS has indicated that MIN method is ranked first as the most important factor followed by Business Systems Planning, Porter's forces model, Value chain Analysis, SWOT and CSF for development of strategic planning for information technology in municipality organization.

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Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS

Cited by 90 publications

References 20 publications

Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

An application of TOPSIS method for ranking different strategic planning methodology

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