Integrated Reporting Frameworks and Long Term Value Creation for Stakeholders

Abstract

This research investigates the novel application of computational network analysis and
semantic modeling techniques to evaluate and enhance Integrated Reporting Frameworks
(IRFs) for long-term stakeholder value creation. Departing from traditional accounting and
qualitative assessment methods, we propose a hybrid methodology that combines principles from complex systems theory, natural language processing, and multi-agent simulation
to model the dynamic, non-linear relationships between corporate disclosures, stakeholder
perceptions, and long-term value outcomes. The core innovation lies in conceptualizing
an IRF not as a static document but as a dynamic information ecosystem. We develop a
computational model that simulates how different structural and semantic properties of an
integrated report—such as connectivity density between financial and non-financial capitals,
narrative coherence, and temporal linkage strength—propagate through a network of heterogeneous stakeholders (investors, employees, communities, regulators). Our results, derived
from both simulated data and a curated corpus of early adopter reports from 2000-2004, reveal previously unexamined leverage points. We identify a non-linear threshold effect where
the value-creation impact of connectivity within a report accelerates significantly only after
achieving a minimum semantic integration score. Furthermore, the simulation demonstrates
that optimizing for a narrow set of powerful stakeholders can create systemic fragility, reducing long-term resilience. The model predicts that frameworks emphasizing bidirectional
feedback loops and temporal narratives outperform those focused on contemporaneous snapshot integration. This research contributes a new, computationally-grounded paradigm for
designing and evaluating reporting frameworks, moving beyond compliance to engineer them
as tools for systemic value creation. The findings suggest that the next evolution of IRFs
requires embedded computational tools to manage complexity and stakeholder interaction