Selecting an MRI System: A Multi Criteria Decision Making Model for MRI Technicians

Gulsah Hancerliogullari Koksalmis, Cuneyt Calisir, Murat Durucu and Fethi Calisir
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Gulsah Hancerliogullari Koksalmis: Industrial Engineering Department, Management Faculty, Istanbul Technical University, Istanbul, Turkey
Cuneyt Calisir: Faculty of Medicine, Department of Radiology, Eskisehir Osmangazi University, Eskisehir, Turkey
Murat Durucu: Industrial Engineering Department, Management Faculty, Istanbul Technical University, Istanbul, Turkey
Fethi Calisir: Industrial Engineering Department, Management Faculty, Istanbul Technical University, Istanbul, Turkey

International Journal of Business Analytics (IJBAN), 2018, vol. 5, issue 3, 22-32

Abstract: This article describes how magnetic resonance imaging (MRI) systems play a crucial role in radiology, specifically in the diagnosis of diseases and management of patient treatment. The objective of this article is to present MRI technicians' perspective on the relative importance of the required factors when selecting and purchasing an MRI system. Analytic Hierarchy Process (AHP) methodology was used to determine the relative priorities for different criteria along with the consistency of responses. A set of criteria for MRI system were identified based on the literature and interviews with experts (i.e., MRI technicians), and organized into a rational hierarchical framework consisting of the five main criteria and nineteen sub-criteria. An online survey including demographic questions was conducted to identify the relative weights of these criteria. Survey responses from 87 technicians indicate that brand is found to be the most important criteria, followed by patient comfort, usability, technical issues, and performance. Among the sub-criteria, the highest weights are assessed for country of origin, user-friendly independent workstation, reputation, software support. The findings demonstrate the factors that can be critical discriminators between different MRI systems.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jban00:v:5:y:2018:i:3:p:22-32

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