Tracking the Energy Transition of Spanish Firms (2023–2025): A Large-Scale Web and LLM-Based [Dataset]

Abstract

This article introduces a nationwide dataset that maps how 104,553 Spanish firms communicate and implement energy transition practices on their corporate websites in 2023 and 2025. Using a scalable pipeline based on large language models (LLMs), website text is segmented, semantically filtered, and evaluated through a structured rubric designed to identify explicit evidence of: (1) energy efficiency and energy consumption reduction actions, (2) decarbonization and greenhouse gas emissions reduction strategies, and (3) the use, production, or procurement of renewable energy.

The resulting indicators are aggregated at the province (NUTS-3), sector (NACE 2-digit), and firm-size level, providing a detailed picture of corporate energy transition patterns across the Spanish economy. To preserve anonymity and statistical robustness, only aggregated cells containing at least four firms with valid website content are included in the public dataset. For each province–sector–size combination, the dataset reports the share of firms associated with each transition dimension together with the number of firms represented in the cell.

By covering two years, the dataset enables the analysis of temporal changes in corporate sustainability and energy transition strategies across regions, industries, and firm-size categories. The dataset provides a reproducible and extensible framework for studying energy transition dynamics using web-based evidence and LLM-assisted classification, offering valuable applications for sustainability research, regional analysis, industrial transformation studies, and energy policy evaluation.