Promises vs. Performance

A Multi-Dimensional Greenwashing Risk Assessment Tool Integrating Environmental Performance Data with NLP Communication Analysis

Master Thesis (2025)
Author(s)

H.A. Baartman (TU Delft - Technology, Policy and Management)

Contributor(s)

Theodoros Chatzivasileiadis – Mentor (TU Delft - Policy Analysis)

Amineh Ghorbani – Mentor (TU Delft - System Engineering)

Faculty
Technology, Policy and Management
More Info
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Publication Year
2025
Language
English
Graduation Date
25-09-2025
Awarding Institution
Delft University of Technology
Programme
['Industrial Ecology']
Faculty
Technology, Policy and Management
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Abstract

Clean energy spending needs to reach $4.5 trillion per year by 2030 to maintain a realistic chance of limiting global warming, yet current investment represents just 37% of what is needed for net zero by 2050. This and other energy transition requirements put enormous pressure on electric utilities to transform their business models while maintaining energy security and attracting investment, creating conditions ripe for potential greenwashing as companies might oversell environmental progress or engage in misleading communication strategies to stay competitive. Three fundamental gaps have limited systematic greenwashing detection: the separation between performance and communication analysis, single-dimensional communication measurement, and the lack of sector-specific methods.
This research addresses the question: What greenwashing risk assessment tool can be developed for European electric utility companies based on environmental performance metrics and multi-dimensional communication analysis? This Master thesis research project developed and tested the first systematic Greenwashing Risk Assessment Tool (GRAT), designed specifically for electric utilities but adaptable to other sectors through modified inputs, weights, and terminology. The GRAT bridges theoretical gaps by integrating quantitative performance measurement with multi-dimensional communication analysis. Constrained ensemble methodology is used to handle weight uncertainty for both performance scoring and greenwashing risk. The greenwashing risk is measured by five different dimensions: performance-communication gap, substantiation weakness, language vagueness, temporal orientation, and reporting consistency.
The GRAT follows a clear three-step process that can be understood and adapted without advanced programming skills. Users gather environmental data from several sources: third-party verified information like Refinitiv Eikon, self-reported metrics like CDP, and English sustainability reports. Once this data is collected, the tool automatically handles performance scoring, runs communication analysis through rule-based NLP methods, and produces integrated risk assessments. Rather than using completely arbitrary weights, the constrained ensemble approach tests thousands of valid weight combinations within available theoretical boundaries.
The tool was tested on 14 European electric utility companies during 2021-2022. Among these companies, the analysis found significant environmental performance differences. Scores ranged from 15.0 to 95.0 points, with year-over-year changes spanning from -35.1 to +63.0 points. Companies used different communication strategies that did not align with their performance scores. Only 36% showed temporal changes where performance and communication moved in the same direction, revealing a pattern where communication strategies often work independently from actual environmental achievements. When combining both aspects including the other communication quality dimensions, risk scores fell between 16.5 and 81.3.
The validation approach is methodologically sound, though statistical limitations arise from the small sample size. External validation provides indicative evidence that the GRAT may distinguish between companies with documented greenwashing accusations and those with clean records, but results could represent random phenomena between 2021-2022. The GRAT enables regulators to screen companies requiring investigation rather than providing conclusive evidence of greenwashing. This helps investors assess risk patterns in sustainability portfolios and offers researchers a tool adaptable to other sectors.

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