Ranking fuzzy cognitive map based scenarios with TOPSIS

Salmeron, Jose L.; Vidal, Rosario; Mena, Ángel

doi:10.1016/j.eswa.2011.08.094

Cited by 85 publications

(34 citation statements)

References 23 publications

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“…Also, the expert panel can include department managers of companies which have implemented an ERP system, ERP consultants from ERP vendors and university academics who university academics who work in the area of ERP systems. In this sense, Salmeron et al [20] applied the Delphi method for FCM construction. The Delphi method was developed in the Rand Corporation during the 1950s [52].…”

Section: Gathering the Datamentioning

confidence: 99%

“…High influence dispatcher activities are activities where an improvement in their readiness situation will cause a significant improvement in the readiness situation of other activities. Salmeron et al [20] proposed the first multicriteria-based methodology for ranking FCM output with TOPSIS. Due to this study's purpose, we are proposing the decision-making trial and evaluation laboratory (DEMATEL) method [21] for prioritizing activities based in their influence.…”

Section: A Readiness Management Approachmentioning

confidence: 99%

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Managing readiness-relevant activities for the organizational dimension of ERP implementation

Ahmadi

Papageorgiou

Yeh

et al. 2015

Computers in Industry

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Section: Gathering the Datamentioning

confidence: 99%

Section: A Readiness Management Approachmentioning

confidence: 99%

Managing readiness-relevant activities for the organizational dimension of ERP implementation

Ahmadi

Papageorgiou

Yeh

et al. 2015

Computers in Industry

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“…Fuzzy Cognitive Maps are dynamical systems involving feedbacks, where changing the effect in a node this may affect other nodes (Equations and in Section 3.2), which in turn can affect the node initiating the change . According to Bueno and Salmeron, the threshold function is of outmost importance for dynamic FCMs because the FCM convergence is a critical point in dynamics FCM and analysis of results.…”

Section: Case Studymentioning

confidence: 99%

A Fuzzy Cognitive Maps Tool for Developing a RBI&M Model

Ciarapica

Mazzuto

2014

Qual. Reliab. Engng. Int.

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A proper maintenance plan is directly related to the definition of critical indexes for ensuring a high level of safety and high level in service quality for all equipments in the plants. The traditional approach, according to risk‐based inspection and maintenance (RBI&M), requires that each parameter considered in the definition of critical indexes shall be divided into intervals in order to assign it a score. By the elaboration of these scores, the critical indexes are calculated. However, what are the rules that allow the company the definition of the range and the assignment of the relative score? Are these rules subjective or objectives? Literature in the field highlights that these decisions are often carried out by maintenance managers. In order to overcome this approach, in this paper, a method based on Fuzzy Cognitive Maps (FCMs) is presented. FCMs have been used for structuring and supporting decisional processes. The criticality of equipments is described in terms of concepts affecting its functioning. No ranges or scores are defined, but only structural and functional features are considered in order to define a criticality index. The resulting fuzzy model can be used to analyse, simulate, test the influence of concepts and predict the behaviour of the system. The RBI&M model, proposed in this work, has been analysed through a case study of an Italian refinery Copyright © 2014 John Wiley & Sons, Ltd.

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“…Glykas (2012) analyzed financial strategy map scenarios using FCMs. Salmeron et al (2012) integrated Delphi analysis, FCMs, and TOPSIS methods for scenario-based decision-making problems. TOPSIS method was used to rank the simulated scenario alternatives.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy multiple-attribute decision making model to evaluate new product pricing strategies

2015

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The aim of this paper is to provide a new fuzzy Multiple-Attribute Decision Making model for evaluating product pricing strategies. The problem is structured in a hierarchical setting. Possible interactions and interdependencies among hierarchically structured criteria are taken into consideration. Since new product pricing decisions entail decision makers' uncertain judgments concerning many interacting factors, Fuzzy Cognitive Maps are employed to analyze causal dependencies among attributes. Finally, decision makers' linguistic assessments are transformed into ranking orders of the pricing strategies using the Technique for Order Preference by Similarity to Ideal Solution. The proposed model is implemented in a Turkish software company. The case study has showed that the proposed model is practical and easy to apply. The proposed model can be incorporated into marketing strategies of wide variety of new products.

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Ranking fuzzy cognitive map based scenarios with TOPSIS

Cited by 85 publications

References 23 publications

Managing readiness-relevant activities for the organizational dimension of ERP implementation

Managing readiness-relevant activities for the organizational dimension of ERP implementation

A Fuzzy Cognitive Maps Tool for Developing a RBI&M Model

A fuzzy multiple-attribute decision making model to evaluate new product pricing strategies

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