EXPRESS: Integrating Operations and Finance for Sustainable Development: Theory, Practice, and Opportunities

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a methodological framework (LLM) for empirical research on sustainable finance and operations, addressing a critical gap in evidence.

🏢実務担当者:Offers insights into how to extract and utilize sustainability-related financial data from filings, useful for corporate disclosure teams.

🏛政策担当者:Highlights the importance of aligning incentives for sustainable development, suggesting that regulation could encourage data availability for such analyses.

Sustainable development demands addressing two core challenges: mobilizing financial resources and aligning stakeholder incentives. This paper surveys the operations-finance interface literature through the lens of “Mobilizing Resources” and “Aligning Incentives” framework. We highlight how the literature advances our knowledge of mitigating SME financing constraints and crafting operationally-informed financial contracts to internalize externalities. We identify a critical gap: while theoretical models for incentive alignment are well-established, empirical evidence remains limited due to the difficulty of analyzing unstructured data. To bridge this gap, we present Large Language Models (LLMs) as a rigorous methodological toolkit for empirical operations management research. We outline a four-step framework—Problem Definition, Model Selection, Prompt Engineering, and Validation—and illustrate its application via a case study that extracts novel data on supplier finance programs from corporate 10-K filings. We conclude by proposing a unified research agenda to advance future research at the intersection of operations, finance, and sustainability.

• semanticscholar https://doi.org/10.1177/10591478261454786first seen 2026-05-20 05:40:17 · last seen 2026-06-16 05:16:26