Accounting & Finance Research Community Seminar – Dr Roza Sagitova

Title: ‘As bad as bad can be’: Accounting for species extinction in the North Pacific

Guest Speaker: Dr Roza Sagitova is a Senior Lecturer in the School of Accounting, Economics and Finance at the University of Portsmouth and a Fellow of the Higher Education Academy.
Dr Sagitova completed her PhD in accounting and finance between in 2016 at Heriot-Watt University in Edinburgh, focusing on climate change-related disclosures by listed Russian companies.

Date: 06 March 2023
Time: 14:00-15:00
Location: NUBS 2.14

If you would like to attend, please register using the following link: https://forms.office.com/r/JZf5AdFUYm.

Abstract

Purpose – This paper explores the reporting of the Russian American Company (RAC), from 1840 to 1862. Trading in fur, company’s fears of animal extinctions viewed from a monetary perspective led to early extinction reporting practice. These were not altruistic reports, they were generated by a wish to exploit natural resources. Despite the motivations, these reports present an example of successful extinction management by a for-profit company and a workable example of emancipatory extinction accounting.
Design/methodology/approach – Using thematic analysis, this study demonstrates how extinction accounting can become emancipatory by exploring this historical business case of extinction management through the lens of Atkins and Maroun’s (2018) extinction framework.
Findings – The application of the framework on the RAC’s set of reports indicates that this offers a viable proposal to development of extinction management and a reporting tool for a for-profit company.
Originality – Exploring RAC’s reports focusing on their extinction management, the paper contributes to the contemporary debate on the development of the extinction reporting framework. These historical examples of extinction accounting, show extinction management and reporting is not a unique contemporary development in accounting. The research uses historical data as the empirical foundation for exploring applicability and further development of this extinction framework.