Meet the Member: Dr James Quang Duong – Driven by Curiosity, Guided by Impact

Dear Reader, you’ve met James before – he talked to us about silent dissatisfaction and artificial intelligence in product returns and he’s been an author on many of the papers featured on the blog, like those on electric battery closed-loop supply chains, the paper that presented four visionary models for decentralising operations in supply chains and the paper on resilience is closed-loop supply chains– but today, you’re going to get to know this magnificent researcher a little better!

James, or Dr James Quang Duong, joins us from Vietnam originally, from an industrial management background. He came to the UK for supply chain management at Nottingham Trent before joining us at the University of Greenwich to complete his PhD (James and I, the author of this blog post, actually studied for our PhDs together so I know first hand what a real asset he is to both the university and to NUSC). Receiving the Vice-Chancellor’s Scholarship in 2020 provided James with “the freedom and confidence to pursue ambitious research on data-driven return behaviour and demonstrated how rigorous analytics can help solve real operational challenges.”

James is a prolific and award winning researcher – most recently he received the University of Greenwich’s Research & Knowledge Exchange Staff Award in 2025. He describes this as a “defining milestone. It reinforced my commitment to producing research with tangible academic, industrial, and societal impact, and continues to inspire my work on circular economy, sustainable operations, and battery value chains through projects such as Horizon Europe-funded CIRCUBATT“ In the short time he’s been with us, he’s made a real impact.

As James explains, his journey resulted in quite an unusual passion:

Along the way I became fascinated by how data — big, messy, real-world data — can unlock smarter decisions in logistics, operations and supply chains. Today I work at the intersection of machine learning, circular economy, and operations management.

I was drawn to the practical messiness of retail operations — things go wrong, products come back, systems break down. I wanted to understand why, and more importantly, predict when and how many. The rise of e-commerce and the avalanche of behavioural data made that ambition suddenly tractable with the right analytical tools.

James’ day-to-day work may not fit what some people expect of an business academic – he’s not all surveys, interviews and spreadsheets. No. As he elaborates, “I write code as part of my daily research — Python & R. Most people imagine business academics working with spreadsheets and surveys; I’m often building machine learning pipelines and running natural language processing on large text datasets. The engineering side of my work is quite hands-on.” Indeed, if he wasn’t in academia it would be easy to imagine him in a consultancy or engineering job – he says so himself; “Probably working as a data scientist or analytics consultant in the logistics industry — applying the same methods but closer to the operational coal-face. Though honestly, I think I’d miss the freedom to ask why rather than just how.”

This is the key to understanding James’ work. He is driven by a deep curiosity. He is not looking for citations but rather impact, explainability, the freedom to ask why. When asked what research success looks like, James is clear in his answer:

It’s when a framework I’ve built gets picked up by a practitioner and changes how they make a decision — not just a citation count. The 2025 Outstanding Contribution in Reviewing award from the Journal of Simulation meant a lot, but what would mean more is seeing a manufacturer adopt a return policy recommendation that came from our models. That’s the goal.

He goes on to explain how his 2025 paper in International Journal of Production Economics, predicting online product return behaviour using interpretable machine learning, stands out for this reason, “It grew directly from my PhD thesis but pushed further — not just predicting returns, but doing so in a way that practitioners can actually understand and act on. Explainability matters.”

Explainability matters. Yet while understanding and improving operational decisions remains central to James’ work, his research has expanded far beyond product returns. More recently, his interests in circular economy, urban logistics and sustainability have brought him into conversation with a much broader set of challenges.

It was this evolution that drew him to NUSC. As James explains, “My research on circular economy, urban logistics, and sustainability projects, including mapping circular economy activity in the London Borough of Hounslow, naturally connected me to NUSC’s mission around urban systems. The Centre brought together the kind of interdisciplinary thinking that my work increasingly requires.”

That interdisciplinary perspective is particularly important as cities grapple with the environmental consequences of the transition to electric mobility. For James, one challenge stands above all others:

“The end-of-life management of EV batteries in cities. We’re heading towards millions of spent batteries with nowhere to go. Through the CIRCUBATT project, we’re developing circular business models and social impact frameworks to tackle this. It’s one of the most pressing urban sustainability challenges of the next decade.”

Characteristically, James approaches emerging trends with a mixture of curiosity and healthy scepticism. He is constantly looking beyond established ideas to understand which new technologies and concepts might genuinely improve the systems we rely upon. Recently, this has led him to explore the growing literature on Web3 and decentralised supply chains.

“The emerging literature around Web3 and decentralised supply chains has been thought-provoking. My recent Transportation Research Part E paper on Web3 and metaverse applications for EV battery supply chains came partly from immersing myself in that space and asking whether the hype had a real operational basis.”

Then, with a smile, he adds: “Spoiler: some of it does.”