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SCIENCE ARTICLE
Determining the significance levels of individual and
organizational factors influencing logistics capabilities in the
healthcare sector using the Pythagorean Fuzzy AHP Method:
Türkiye example
1
Department of Management Information Systems, Istanbul Beykent University, Turkey
2
Deparment of Logistics Management, Istanbul Beykent University, Turkey
3
Department of Software Development, Istanbul Beykent University, Turkey
Submission date: 2026-05-14
Final revision date: 2026-06-22
Acceptance date: 2026-07-31
Online publication date: 2026-09-03
Publication date: 2026-08-31
Corresponding author
Management 2026;(2):91-130
KEYWORDS
JEL CLASSIFICATION CODES
D810
I110
M110
TOPICS
ABSTRACT
Research background and purpose:
The present study evaluates the significance levels of individual and organizational factors influencing logistics capabilities in the healthcare sector, particularly within private hospitals in Istanbul, utilizing the Pythagorean Fuzzy Analytic Hierarchy Process (AHP). The research addresses the gap in detailed prioritization of individual and organizational factors influencing logistics capabilities, crucial in healthcare logistics, especially during crises like the COVID-19 pandemic.
Design/methodology/approach:
A multi-stage approach was employed. First, a literature review identified key logistics capabilities, which were then refined by an expert group. Subsequently, a second expert group from private hospital procurement departments in Istanbul assessed the finalized capabilities. Expert opinions were linguistically expressed and converted into Pythagorean fuzzy numbers for AHP analysis. Finally, a sensitivity analysis was conducted by varying the main criteria weights by ±10%, ±20%, and ±30% across 24 scenarios to test the robustness of the resulting priorities.
Findings:
The study revealed that "Ethics and Social Responsibility" holds the highest significance, followed by "Human Resources and Relations", "Strategic Thinking and Management", and "Scientific Foundations and Technical Knowledge". Specifically, "Social Responsibility", "Conflict Management", "Risk Management", and "Information Systems" were identified as critical sub-items. The sensitivity analysis confirmed that these results—particularly the primacy of "Ethics and Social Responsibility"—remained robust to ±30% variations in the main criteria weights. This research uniquely applies Pythagorean Fuzzy AHP to prioritize individual and organizational factors influencing logistics capabilities within the Turkish private healthcare sector, offering a nuanced understanding of their significance.
Value added and limitations:
The study's focus on private hospitals in Istanbul limits generalizability. Future research could expand the geographical scope and include public hospitals. The findings highlight the necessity for integrating ethical considerations and robust human resource management into healthcare logistics. The results provide a framework for healthcare institutions to evaluate and enhance their logistics capabilities, informing training programs and operational strategies. By emphasizing social responsibility and ethical practices, this research underscores the significance of equitable healthcare resource distribution and sustainable logistics, contributing to improved public health outcomes.
The present study evaluates the significance levels of individual and organizational factors influencing logistics capabilities in the healthcare sector, particularly within private hospitals in Istanbul, utilizing the Pythagorean Fuzzy Analytic Hierarchy Process (AHP). The research addresses the gap in detailed prioritization of individual and organizational factors influencing logistics capabilities, crucial in healthcare logistics, especially during crises like the COVID-19 pandemic.
Design/methodology/approach:
A multi-stage approach was employed. First, a literature review identified key logistics capabilities, which were then refined by an expert group. Subsequently, a second expert group from private hospital procurement departments in Istanbul assessed the finalized capabilities. Expert opinions were linguistically expressed and converted into Pythagorean fuzzy numbers for AHP analysis. Finally, a sensitivity analysis was conducted by varying the main criteria weights by ±10%, ±20%, and ±30% across 24 scenarios to test the robustness of the resulting priorities.
Findings:
The study revealed that "Ethics and Social Responsibility" holds the highest significance, followed by "Human Resources and Relations", "Strategic Thinking and Management", and "Scientific Foundations and Technical Knowledge". Specifically, "Social Responsibility", "Conflict Management", "Risk Management", and "Information Systems" were identified as critical sub-items. The sensitivity analysis confirmed that these results—particularly the primacy of "Ethics and Social Responsibility"—remained robust to ±30% variations in the main criteria weights. This research uniquely applies Pythagorean Fuzzy AHP to prioritize individual and organizational factors influencing logistics capabilities within the Turkish private healthcare sector, offering a nuanced understanding of their significance.
Value added and limitations:
The study's focus on private hospitals in Istanbul limits generalizability. Future research could expand the geographical scope and include public hospitals. The findings highlight the necessity for integrating ethical considerations and robust human resource management into healthcare logistics. The results provide a framework for healthcare institutions to evaluate and enhance their logistics capabilities, informing training programs and operational strategies. By emphasizing social responsibility and ethical practices, this research underscores the significance of equitable healthcare resource distribution and sustainable logistics, contributing to improved public health outcomes.
AUTHORS' CONTRIBUTIONS
I.E.: article conception, theoretical content of the article. H.B.: theoretical content of
the article. K.O.: article conception, theoretical content of the article, research methods
applied, conducting the research, data collection, analysis and interpretation of results,
draft manuscript preparation.
ADDITIONAL INFORMATION
During the preparation of this work the authors did not use Generative AI and AIassisted
technologies in the writing process.
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| eISSN: | 2299-193X |
| ISSN: | 1429-9321 (1997-2019) |
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