Sezin Güleryüz

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.

A new integrated intuitionistic fuzzy group decision making approach for product development partner selection

This study proposes an integrated IF GDM approach to the partner selection problem.The partner selection criteria weights are determined by using IF AHP.The potential partner alternatives are evaluated by using IF TOPSIS.A case study from Turkey is provided to validate the proposed approach. Globally, customers are getting increasingly demanding in terms of quality, price and performance of products and are asking for shorter product development periods with more predictable cycles. These market pressures drive firms to collaborate with possible partners in product development (PD) processes. Nevertheless, choosing the suitable partner for an effective PD is a challenging, complex decision. This study proposes a combined Intuitionistic Fuzzy (IF) Group Decision Making (GDM) model that consists of the Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) and Intuitionistic Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) methods for effectively evaluating PD partners. In order to obtain a more complete evaluation and more precise results, IF-AHP is used for determining criteria weights, whereas IF-TOPSIS methodology is conducted for ranking partner alternatives. This study contributes to partner selection and IF set literature by providing a combined framework based on IF-AHP and IF-TOPSIS with GDM methodology for the first time. To assess the validity of the proposed integrated IF GDM approach, a case study is also provided. This study contributes to literature as it provides a better insight into the theoretical ground of the PD partner selection problem. It also supports organizations which aim to improve their PD evaluation systems.

Extending Fuzzy QFD Methodology with GDM Approaches: An Application for IT Planning in Collaborative Product Development

Collaborative product development (CPD) is a technology intensive process and effective planning in information technologies (IT) can improve the performance of CPD activities. Considering that quality function deployment (QFD) can be utilized as a planning tool for products and systems, the use of the QFD can enable IT systems to align their structure for CPD. In the QFD approach, the house of quality matrix is used for converting customer requirements into engineering characteristics. The challenge in this process is the profile of the inputs that are collected from the participants who provide feedback on customer requirements. Individual judgments of these participants can be in various formats, or can indicate preferences that are incomplete. This study aims to tackle with this issue by making use of an extended QFD methodology in CPD for IT planning. For this purpose, two group decision making (GDM) approaches are used to address both challenges of multiple preference formats and incomplete information. The validity of the developed IT planning model for CPD is tested with a case study at a Turkish software company using the two GDM approaches, and the obtained results are discussed. As customer requirements are important at every phase of CPD, the proposed model can help implementers to improve their decision processes.

A new integrated group decision making framework with linguistic interval fuzzy preference relations

The high complexity of socio-economic environments often makes it difficult for a single decision maker (DM) to consider all important aspects of decision problems. Therefore, a group decision making (GDM) process is often preferred by organizations. Moreover, during the decision process, DMs may have difficulties in the prioritization of alternatives. Linguistic interval fuzzy preference relation is a strong tool which can deal with uncertainty in case of subjective and vague information. For this reason, this paper develops a new GDM approach based on integrated linguistic interval fuzzy preference relation and analytic network process. To demonstrate the applicability of the proposed approach, an illustrative example is presented.