Researcher biography

Hadi Shabanpour is a Ph.D. student in Environmental Management at the School of Environment (SENV) at the University of Queensland (UQ). Prior to joining UQ, he was a researcher for the "Young Researchers and Elites Club" at the IAU Karaj branch (KIAU) for eight years. He also lectured at IAU and the University of Applied Sci. & Tech. in Iran. He obtained a BSc degree in Industrial Management from KIAU and his master’s in strategic management from the IAU-Central Tehran Branch.

Research Interests

His research is interdisciplinary and focuses on the assessment of DMUs' sustainability and circularity as well as industrial eco-efficiency through DEA models. Specifically, he investigates real-world and state-of-the-art frameworks for assessing and predicting DMUs' sustainability and eco-efficiency, as well as benchmarks for practical improvement.

Journal Articles

  1. Yousefi, S., Shabanpour, H., Ghods, K., Farzipoor Saen, R. (2023), “How to improve the future efficiency of Covid-19 treatment centers? A hybrid framework combining artificial neural network and congestion approach of data envelopment analysis", Computers & Industrial Engineering, 176, 108933. (Q1, ERA rank: A),
  2. Azadi, M., Yousefi, S., Farzipoor Saen, R., Shabanpour, H., Jabeen, F. (2023), “Forecasting sustainability of healthcare supply chains using deep learning and network data envelopment analysis", Journal of Business Research, 154, 113357. (Q1, ERA rank: A),
  3. Shabanpour, Hadi., Yousefi, Saeed., Farzipoor Saen, Reza., (2021), “Forecasting sustainability of supply chains in the circular economy context: A dynamic network data envelopment analysis and artificial neural network approach", Journal of Enterprise Information Management, Vol. 17, No. 1-3, (Q1, ERA rankA),
  4. Yousefi, Saeed., Shabanpour, Hadi., Farzipoor Saen, Reza., (2021), "Sustainable clustering of customers using capacitive artificial neural networks: A case study in Pegah Distribution Company", RAIRO Operations Research, 55(1), 51-60. (Q2, ERA rank: B),
  5. Shabanpour, Hadi., Fathi, Amirali., Yousefi, Saeed., Farzipoor Saen, Reza., (2019) "Ranking sustainable suppliers using congestion approach of economies of scale theory of data envelopment analysis", Journal of Cleaner Production, Vol. 240, pp. 118190. (Q1, ERA rank: A),
  6. Shabanpour, Hadi., Yousefi, Saeed., Farzipoor Saen, Reza., (2017), “Forecasting efficiency of green suppliers by dynamic data envelopment analysis and artificial neural networks”, Journal of Cleaner Production, Vol. 142, No. 2, pp. 1098–1107. (Q1, ERA rankA)
  7. Shabanpour, Hadi., Yousefi, Saeed., Farzipoor Saen, Reza., (2017), “Future planning for benchmarking and ranking sustainable suppliers using goal programming and robust double frontiers DEA”, Transportation Research Part D: Transport and Environment, Vol. 50, pp. 129-143. (Q1, ERA rank: A),
  8. Shokri Kahi, V., Yousefi, S., Shabanpour, H., Farzipoor Saen, R., (2017), "How to evaluate sustainability of supply chains? A dynamic network DEA approach", Industrial Management & Data Systems, Vol. 117, No. 9, pp.1866-1889. (Q1, ERA rank: A),
  9. Tavana, Madjid., Shabanpour, Hadi., Yousefi, Saeed., Farzipoor Saen, Reza., (2017), “A Hybrid Goal Programming and Dynamic Data Envelopment Analysis Framework for Sustainable Supplier Evaluation”, Neural Computing and Applications, Vol. 28, No. 12, pp. 3683–3696. (Q1, ERA rank: B),
  10. Yousefi, Saeed., Shabanpour, Hadi., Fisher, Ron., Farzipoor Saen, Reza., (2016), “Evaluating and ranking sustainable suppliers by robust dynamic data envelopment analysis”, Measurement, Vol. 83, pp. 72-85. (Q1, ERA rank: A),
  11. Yousefi, Saeed., Shabanpour, Hadi., Farzipoor Saen, Reza., (2015), “Selecting the best supply chain by goal programming and network data envelopment analysis”, RAIRO Operations Research, Vol. 45, No. 3, pp. 601-617. (Q2, ERA rank: B),
  12. Yousefi, Saeed., Shabanpour, Hadi., Farzipoor Saen, Reza., Faramarzi, Gholam Reza., (2014), “Making an ideal decision-making unit using virtual network data envelopment analysis approach”, Int. J. Business Performance Management, Vol. 15, No. 4, pp. 316-328. (Q3, ERA rank: C).

More information


Title: How to assess circularity of OECD Countries? A novel dynamic network DEA framework

Description: In line with the goals of the 2030 Agenda (for sustainable development) and the Paris Climate Agreement, energy performance and especially carbon emissions should be urgently addressed. Increasing the circularity of OECD countries, (in addition to investing in renewable energy), can play an important role in reducing CO2 emissions and tackling the challenge of limitation of non-renewable energy and environmental degradation. Considering the shortcomings of macro-level circularity assessments methods and benchmarks, this project investigates a novel macro-level framework with the aim of identifying the circularity levels of OECD countries and ranking them and providing benchmarks for improving future less sustainable countries.

Funding: Research Training Program (RTP)
Advisory Team: Associate Professor Paul Dargusch, Dr David Wadley and Prof. Reza Farzipoor Saen
Duration: April 2022–September 2025