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Applications are invited for a fully-funded three year PhD to commence in October 2026.

The PhD will be based in the School of Accounting, Economics and Finance at the ÍÃ×ÓÏÈÉú, and will be supervised by Dr Panagiotis Tzouvanas and Dr Konstantinos Vergos. 

Candidates applying for this project may be eligible to compete for one of a small number of bursaries available. Successful applicants will receive a bursary to cover tuition fees for three years and a stipend in line with the UKRI rate (£20,780 for 2025/26). Bursary recipients will also receive a contribution of £2,000 towards fieldwork.

Costs for student visa and immigration health surcharge are not covered by this bursary. For further guidance and advice visit our international and EU students ‘Visa FAQs’ page.

This funded PhD is only open to new students who do not hold a previous doctoral level qualification.

This research proposes to investigate the relationship between corporate real options and biodiversity-related strategies, examining how biodiversity can enhance the value of environmental real options such as those related to land use, afforestation, and conservation projects. Real options theory emphasises managerial flexibility; the ability to defer, expand, or modify investments in response to uncertainty.  At the same time, building on financial options theory the natural-resource-based view of the firm, this study will develop a valuation framework that captures both the financial and ecological dimensions of corporate decision-making. By incorporating biodiversity performance into real options valuation, we aim to advance the theoretical foundations of sustainable finance.

Recent developments in biodiversity finance highlight opportunities for firms to leverage biodiversity initiatives as strategic assets that attract investors, improve risk management, and strengthen long-term sustainability. Empirically, the project will estimate biodiversity-related real options using extended financial models and analyse their relationship with biodiversity performance through panel data methods, big data analytics, and machine learning. Firm-level data will be drawn from LSEG, Bloomberg, and Capital IQ databases to capture detailed information on financial and environmental performance across a global sample. Ultimately, the research will provide new insights into how biodiversity can affect firm performance, offering both theoretical and practical guidance for integrating biodiversity into strategic and financial decision-making.

References

Flammer, C., Giroux, T., & Heal, G. M. (2025). Biodiversity finance. Journal of Financial Economics, 164, 103987.

Garel, A., Romec, A., Sautner, Z., & Wagner, A. F. (2024). Do investors care about biodiversity?. Review of Finance, 28(4), 1151-1186.

Karolyi G. A., and Tobin-de la Puente, J. (2023). Biodiversity finance: A call for research into financing nature. Financial Management, 52: 231-251.

Kassar, I., & Lasserre, P. (2004). Species preservation and biodiversity value: a real options approach. Journal of Environmental Economics and Management, 48(2), 857-879.

Trigeorgis, L., & Reuer, J. J. (2017). Real options theory in strategic management. Strategic Management Journal, 38(1), 42-63.

How to apply

We’d encourage you to contact Dr Panagiotis Tzouvanas (Panagiotis.tzouvanas@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, you can use our . Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.

Please also include a research proposal of 1,000 words outlining the main features of your proposed research design – including how it meets the stated objectives, the challenges this project may present, and how the work will build on or challenge existing research in the above field.

If you want to be considered for this funded PhD opportunity you must quote project code AEF50760126 when applying.