Abstract
Organisations across all industry sectors face the challenge of having to meet the
needs of the present, without compromising the ability of future generations to meet
their needs. A first step towards establishing sustainable development is measuring
and reporting on the environmental, social, and governance (ESG) impacts of organisations. The ESG reporting landscape
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is evolving rapidly; new laws and regulations
oblige organisations to disclose their ESG performance. Though potentially beneficial
to society, ESG accounting (ESGA) weighs a heavy burden on organisations. Especially given that the current process of assessing and reporting is cumbersome, and
oftentimes inefficient due to the vast number of ESGA methods that prescribe how
companies should perform the accounting.
To alleviate the lion’s share of the problems that impede the ESGA process, our
research aims to improve this process by employing the model-driven engineering
paradigm. Therefore, the main research question in this PhD thesis is:
How can model-driven engineering aid organisations to account for their environmental, social and governance impact?
The hypothesis underlying this research is that the question can be answered by
incrementally developing versatile, robust, and extendable tool support for organisations, along with accompanying knowledge about its usage. The tool support we
propose in this dissertation is a model-driven open-source ESGA framework, called
openESEA.
To develop openESEA we examine the landscape of ESGA methods and conduct
an analysis of the factors influencing companies’ adoption of ESGA practices (España
et al., 2023a). One family of ESGA methods has gained particular traction over the
years; the United Nations’ Sustainable Development Goals (SDGs) have been widely
adopted by governments and companies across all industry sectors. To discover how
the ICT sector can communicate its contributions towards realising the SDGs more
effectively, we perform an analysis of current SDG reporting practices in the ICT industry sector (Ramautar et al., 2023b).
OpenESEA consists of a domain-specific language (DSL), an interpreter, and a collection of domain models (Ramautar & España, 2023a). The framework has gone
through multiple development cycles (Ramautar et al., 2024f), which has allowed us
to study the completeness of DSL evolution activities and locate which DSL artefacts
result in most incompletions (Ramautar et al., 2023a). To reduce the redundancy
in ESGA, we present the possibility to automatically match and merge ESG indicators (Ramautar et al., 2024i). This allows users of our framework to assess their performance according to various ESGA methods, without using multiple information systems, or duplicate data in the same system.
The ESGA domain abounds with methods that state how to perform the accounting, leading to a mismatch between the needs and characteristics of companies and
the ESGA method they select. Hence, we elicit and validate a list of criteria that managers can take into account when selecting an ESGA method (Ramautar & España,
2022a) and operationalise the criteria as part of a model-driven selection framework (Ramautar et al., 2024d). This showcases another way in which information
systems can aid organisations in disclosing ESG performance.
Finally, we create a situational meta-method, that helps organisations use our
model-driven tools and create ESGA methods that align with their sustainability strategy (Ramautar et al., 2024a).
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