Gizem Çifçi

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.

Strategic analysis of healthcare service quality using fuzzy AHP methodology

Managers in the service sector are under pressure to demonstrate that their services are customer-focused and that continuous performance improvement is being delivered. It is essential that customer expectations are properly understood and measured under the constraints that organizations must manage. The majority of the work to date has attempted to use the SERVQUAL (service quality) methodology in an effort to measure service quality. In this study, firstly the concept and factors of service quality are examined. Then a fuzzy AHP (analytic hierarchy process) is structured to evaluate the proposed service quality framework. A case study in healthcare sector in Turkey is presented to clarify the methodology.

Evaluation of the green supply chain management practices: a fuzzy ANP approach

Environmentally responsible manufacturing, green supply chain management (GSCM), and related principles have become important strategies for companies to achieve profit and gain market share by lowering their environmental impacts and increasing their efficiency. As environment has become a key strategic consideration in supply chains, this study examines the components and elements of GSCM and suggests a novel GSCM evaluation framework. It also provides a real-case study of Ford Otosan, one of the pioneering companies about environmental subjects in Turkey, to illustrate the industrial application of our theoretical assessment model. The identified components are integrated into a strategic assessment and evaluation tool using analytical network process (ANP). The dynamic characteristics and complexity of the GSCM analysis environment make the ANP technique a suitable tool for this study. Moreover, to cope with ambiguity and vagueness of the decision makers evaluations, the fuzzy extension of the ANP method is preferred.

A new incomplete preference relations based approach to quality function deployment

Quality function deployment (QFD) is a widely-used methodology for developing a design quality aimed at satisfying the customer and translating the customers demand into design targets. As QFD methodology is based on the voices of customers, it requires a group of individuals, or decision makers (DMs), to express their preferences. However, there can be a bottleneck since DMs may not have a perfect knowledge of the problem to be solved. Thereby, the aim of this study is to improve the effectiveness of the evaluation process in QFD. The QFD methodology is extended by introducing a new group decision making (GDM) approach that takes into account incomplete information of DMs by means of the fuzzy set theory. The proposed approach is applied to a collaborative software development process to demonstrate its potential.

A Fuzzy MCDM Approach to Evaluate Green Suppliers

Nowadays the effect of industrial production on the environment brought out the importance of the green concept in supply chains. Particularly for supplier firms, greening is essential in a supply chain because with growing worldwide awareness of environmental protection, green production has become an important theme for almost every manufacturer. While literature related to supplier evaluation is plentiful, the works on green supplier evaluation are rather limited. Therefore, a green supplier evaluation model is proposed in this study. Due to its multi criteria nature, the green supplier evaluation process requires an appropriate multi criteria analysis and solution approach. Selecting a proper method involves an insight analysis among available multi-criteria decision making (MCDM) techniques. Among numerous methods of MCDM, this paper presents a decision framework based on group decision making (GDM) and fuzzy analytic hierarchy process (FAHP) for evaluating and selecting green suppliers. The applicability of the proposed approach is verified through a case study.

Fuzzy Multi-Criteria Evaluation of Knowledge Management Tools

In the knowledge economy, a key source of sustainable competitive advantage relies on the way to create, share, and utilize knowledge. Knowledge Management (KM) tools assumed an important role in supporting KM activities. The objective of this paper is to aid decision makers to identify the most appropriate KM tool to improve the effectiveness of their organization. In order to rate competing systems of different vendors, we propose an enhanced multi-criteria method, namely fuzzy VIKOR, that takes advantages of fuzzy logic and group decision making to deal with the vagueness and granularity in the linguistic assessments. The method aims to isolate compromise solutions, by providing a maximum group utility and a minimum of an individual regret. A case study is also given to demonstrate the potential of the methodology.

An Extended Quality Function Deployment Incorporating Fuzzy Logic and GDM Under Different Preference Structures

AbstractThe paper proposes a fuzzy logic-based group decision making (GDM) approach, which can be used for quality function deployment (QFD) in the development of product improvement strategies. Decision makers can state their preferences in various ways, including incomplete preferences which are difficult to evaluate in a coherent way. We extend the QFD methodology by using a GDM approach which considers multiple preference formats and incomplete information. Finally, a numerical analysis for “Portable Entertainment and Game Systems” design is given to verify the feasibility of the model.

An integration of fuzzy analytic network process and fuzzy decision making for mass customization strategies

Mass customization (MC) relates to the ability to provide customized products or services through flexible processes in high volumes and at reasonably low costs. There exist different strategies for the degree of customization in product development. Determining the right strategy of customization is essential to the competitiveness of a company. To support managerial decision making, this paper proposes an integrated strategic evaluation framework based on the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) and the fuzzy Analytic Network Process (ANP) to assess effectively MC strategies in product development process with a real case study.