Track Description
This track examines how information systems (IS) and knowledge management (KM) transform sustainability data into decision-useful knowledge for accounting, banking, and finance. Organizations increasingly rely on heterogeneous environmental and social information, from sensor and satellite readings to narrative disclosures and supply chain records, yet face persistent challenges in data quality, interoperability, and assurance (Bellamy et al., 2020; Sun et al., 2024). We invite research that designs, evaluates, and theorizes IS and KM solutions that enable credible measurement, reporting, risk management, and value creation in the sustainability domain.

Topics of interest include (but are not limited to): ESG data architectures and governance; data provenance, traceability, and internal controls for sustainability assurance; semantic and interoperability standards and taxonomies; AI/ML, natural language processing, and knowledge graphs for extracting and synthesizing unstructured disclosures; climate and nature related risk analytics, stress testing, and scenario analysis; measurement systems for circularity, biodiversity, and social equity; FinTech, RegTech, and SupTech applications; privacy preserving data sharing and responsible AI; digital twins and IoT for environmental performance monitoring; organizational learning, communities of practice, and cross functional knowledge flows; and the role of IS/KM in public sector and SME contexts.

We welcome conceptual, empirical (archival, experimental, field), design science, and mixed methods studies. Papers may focus on private or public organizations, financial intermediaries, regulators and supervisors, or civil society actors. Comparative and interdisciplinary work bridging accounting, information systems, finance, data science, and sustainability science is especially encouraged, as are replications and open data/software contributions that advance cumulative knowledge.