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Media type:
E-Article
Title:
The OpenESEA Modeling Language and Tool for Ethical, Social, and Environmental Accounting
Contributor:
Ramautar, Vijanti;
España, Sergio
Published:
Riga Technical University, 2023
Published in:
Complex Systems Informatics and Modeling Quarterly (2023) 34, Seite 1-29
Language:
Not determined
DOI:
10.7250/csimq.2023-34.01
ISSN:
2255-9922
Origination:
Footnote:
Description:
Assessing business operations’ ethical, social, and environmental impacts is a key practice for establishing sustainable development. There is a multitude of methods that describes how to perform such assessments. Often these methods are supported by an ICT tool. In most cases, the tools are developed to support a single method only and do not allow any tailoring. Therefore, they are rigid and inflexible. In this article, we present a novel model-driven approach for alleviating managerial issues that arise as a consequence of the complex landscape of ethical, social, and environmental accounting methods and tools. We have developed an open-source, model-driven tool, called openESEA. OpenESEA parses and interprets textual models, that are specified according to a domain-specific language (DSL). We have performed another iteration of the DSL engineering process, which is in line with the design science paradigm. We have validated the new DSL version by means of a user study. As a result, we present a new version of the openESEA modeling language and interpreter. The results of the user study with regards to performance, perceived usefulness, and perceived ease of use of modeling language are encouraging and provide us with a basis to continue developing new versions with more functionalities. The contributions of this work include a new version of the modeling language, a new version of the interpreter, knowledge surrounding the development of these artifacts, and a protocol for evaluating the quality of textual DSLs. The modeling language and interpreter are relevant for sustainability practitioners and consultants since our tool support has the potential to reduce redundancy in ethical, social, and environmental accounting. Our work is valuable to researchers that aim to assess and reduce the complexity of their modeling languages.