OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A data-driven robust decision-making model for configuring a resilient and responsive relief supply chain under mixed uncertainty
Bahar Javan-Molaei, Reza Tavakkoli‐Moghaddam, Mohssen Ghanavati-Nejad, et al.
Annals of Operations Research (2024)
Closed Access | Times Cited: 7

Showing 7 citing articles:

A hybrid machine learning-based decision-making model for viable supplier selection problem considering circular economy dimensions
AmirReza Tajally, Mahla Zhian Vamarzani, Mohssen Ghanavati-Nejad, et al.
Environment Development and Sustainability (2025)
Closed Access | Times Cited: 1

A Hybrid Machine Learning Approach to Evaluate and Select Agile-Resilient-Sustainable Suppliers Considering Supply Chain 4.0: A Real Case Study
Mahyar Abbasian, Amin Jamili
Process Integration and Optimization for Sustainability (2025)
Closed Access

Sustainable supplier selection and order allocation problem considering the agility and resilience dimensions: a novel multi-stage data-driven decision-making approach
AmirReza Tajally, Benyamin Babakhani, Emaad Jeyzanibrahimzade, et al.
International Journal of Systems Science Operations & Logistics (2025) Vol. 12, Iss. 1
Closed Access

A Multi-stage Machine Learning Model to Design a Sustainable-Resilient-Digitalized Pharmaceutical Supply Chain
Mostafa Jafarian, Iraj Mahdavi, Ali Tajdin, et al.
Socio-Economic Planning Sciences (2025), pp. 102165-102165
Closed Access

A Heuristic-based Multi-Stage Machine Learning-based Model to Design a Sustainable, Resilient, and Agile Reverse Corn Supply Chain by considering Third-party Recycling
Fardin Rezaei Zeynali, Mohammad Parvin, Ali Akbar ForouzeshNejad, et al.
Applied Soft Computing (2025), pp. 113042-113042
Closed Access

A Hybrid Machine Learning-Based Model for Evaluating the Performance of Agile-Sustainable Supply Chains in the Context of Industry 4.0: A Case Study
Aboozar Ghorbani, Mehdi Fadaei, Mansour Soufi, et al.
RAIRO - Operations Research (2024) Vol. 58, Iss. 5, pp. 4681-4700
Open Access

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