Work

Computational Intelligence and Digital Pathways in Green Logistics: A Comparative Study Using LLM-Driven ESG Analytics

Year: 2026

Type: conference-paper

Abstract: The logistics industry faces mounting pressure to reduce carbon emissions, and digital technologies have been increasingly recognized as key enablers of green transition. However, existing research has primarily focused on establishing correlations between digitalization and environmental performance, leaving the underlying mechanisms—and the reasons for divergent pathways across firms—largely unexplored. This study addresses this gap by conducting a comparative case analysis of three leading logistics enterprises in China: SF Express, Cainiao, and JD Logistics, using a novel LLM-based computational ESG data analytics pipeline that automates the extraction of structured indicators from unstructured ESG reports.

Source: International Conference on Sustainable Development and Digital Transformation

DOI: 10.1145/3838938.3838968

Authors: Juanjuan Luo, Yue Zong, Di Ouyang

Institution: Anhui Sanlian University

Language: English

Topic: Sustainable Supply Chain Management

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Climate action, Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W7221323213

FWCI:

Cites: 7

Cited by:

Related to: 10