Model-driven sustainability accounting

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 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).