Academic Journal
Ecosystem Services Valuation Using Integrating Biodiversity and Natural Capital Into Corporate Reporting.
| Τίτλος: | Ecosystem Services Valuation Using Integrating Biodiversity and Natural Capital Into Corporate Reporting. |
|---|---|
| Συγγραφείς: | Dalvadi, Yagneshkumar1 (AUTHOR) yagneshroyal@spuvvn.edu |
| Πηγή: | Corporate Social Responsibility & Environmental Management. Oct2026, p1. 16p. 22 Illustrations. |
| Θεματικοί όροι: | *Corporation reports, *International Financial Reporting Standards, Ecosystem services, Natural capital, Simulation software, Environmental risk, Biodiversity |
| Περίληψη: | ABSTRACT Traditional corporate financial accounting frameworks prioritize manufactured and financial capital while treating biodiversity and natural ecosystems as externalities. This structural omission leads to fragmented risk models that fail to capture corporate dependencies on critical ecosystem services, generating systemic mispricing of nature‐related risks. To address these limitations, this study proposes a theoretical and computational framework designed to integrate biodiversity and natural capital metrics into corporate reporting architectures. The methodology introduces a formalized, multi‐tiered matrix of 20 interconnected indicators centered on the Ecosystem Service Value Index, Biodiversity Adjusted Financial Impact, and Natural Capital Risk Exposure—to map complex ecological‐financial interfaces. Because this research functions as a conceptual proof‐of‐concept, the framework's operational feasibility, mathematical tractability, and error tolerance were verified within a controlled simulation environment using a synthetic dataset of 1000 observations balanced across agricultural, manufacturing, and service sector profiles. The data‐routing engine achieved a stable closed‐system tracking accuracy of 91.8%, a weighting precision of 90.5%, and an overall structural consistency score of 91.3%. Computational sensitivity testing under a ±20% parameter variation level confirmed robust boundary security without arithmetic divergence. Rather than serving as an empirical field study or a predictive machine‐learning task, this model provides a consistent mathematical syntax that conceptually supplements global disclosure standards like IFRS and TNFD. This simulation establishes an essential methodological blueprint, with future empirical field studies required to optimize the illustrative parameters using active, real‐world corporate disclosure datasets. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Business Source Index |
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