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Determining the Effect of Trust on Supply Chain Network Performance with Linguistic Summarization Over Heterogeneous Information Network
Volume 36, Issue 3 (2025), pp. 525–555
Pub. online: 16 September 2025      Type: Research Article      Open accessOpen Access
Received
1 September 2024
Accepted
1 September 2025
Published
16 September 2025

Abstract

Industries have increasingly adopted supply chain management practices to sustain competitive advantage, fostering collaboration among supply chain partners for effective coordination. While prior research has explored whether inter-partner relationships influence supply chain network performance, these studies have primarily focused on perceived effects rather than emprical observations. This study investigates the impact of trust on supply chain network performance through linguistic summarization. Its originality lies in integrating linguistic summarization with heterogeneous information network modelling, a novel method for evaluating trust-driven performance effects in supply chains. We modelled supply chain networks as heterogeneous information networks, representing companies and products as distinct node types, and their interactions as varied link types. A linguistic summarization framework was developed for these networks, and its application in the automotive industry enabled the validation of literature-derived hypotheses through the truth degree of linguistic summaries. The findings demonstrate that trust significantly enhances organizational performance, particularly in terms of profitability. Supply chain managers, analysts, and researchers especially gain from this study since it offers a data-driven, interpretable framework for assessing how trust affects network performance, which promotes cooperation, transparency, and decision-making.

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Biographies

Aydogan Sena
senaaydogan@gazi.edu.tr

S. Aydoğan received her PhD degree in industrial engineering from Gazi University, Ankara, Türkiye, in 2021. In year 2019, she was a visiting scholar with the Iowa State University, USA. She is currently an assistant professor with the Department of Industrial Engineering, Gazi University. Her research interests include fuzzy sets and systems and machine learning.

Akay Diyar
diyarakay@hacettepe.edu.tr

D. Akay received his PhD degree in industrial engineering from Gazi University, Ankara, Türkiye, in 2006. Between 2007 and 2009, he was a postdoctoral researcher with the University of Leeds, Leeds, U.K. He is currently a full professor with the Department of Industrial Engineering, Hacettepe University. His research interests include fuzzy sets and systems and affective design.

Demiray Alptekin
alptekindemiray@gmail.com

A. Demiray received his PhD degree in industrial engineering from Gazi University, Ankara, Türkiye, in 2016. He is currently an experienced operations manager at ORS Bearings, Ankara, Türkiye.

E. Kremer Gül
gkremer2@udayton.edu

G. E. Kremer received her PhD degree in engineering management from Missouri University of Science and Technology, USA. She is currently a full professor with the School of Engineering, University of Dayton, USA. Her research interests are applied decision sciences and operation research for product and design systems.

Boran Fatih Emre
emreboran@gazi.edu.tr

F.E. Boran received his PhD degree in industrial engineering from Gazi University, Ankara, Türkiye, in 2013. He is currently a full professor with the Department of Energy Systems Engineering, Gazi University. His research interests include fuzzy sets and systems and decision making.


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Keywords
heterogeneous information network linguistic summarization operational performance organizational performance supply chain management trust

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