Measuring Corporate Sustainability with Data Envelopment Analysis: A Multi-Technique Bibliometric Review and Future Research Agenda

Gokulananda Patel (), Violeta Cvetkoska () and Bojan Kitanovikj ()
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Gokulananda Patel: Birla Institute of Management Technology
Violeta Cvetkoska: Ss. Cyril and Methodius University in Skopje
Bojan Kitanovikj: Ss. Cyril and Methodius University in Skopje

A chapter in Advances in the Theory and Practice of Data Envelopment Analysis, 2025, pp 77-94 from Springer

Abstract: Abstract The interest in assessing companies’ sustainability has been growing among both scholars and practitioners, peaking in recent years. Motivated by that, in this article, we systematically reviewed the literature on using data envelopment analysis (DEA) for measuring corporate sustainability thanks to a multi-technique bibliometric approach consisting of descriptive bibliometric analysis, co-authorships analysis, bibliographic coupling, and keyword co-occurrence analysis. Visualization maps of keyword networks were created based on data from a sample of 392 articles published in Scopus-indexed journals between 2002 – the first year an article on the topic emerged – and 2023, the last completed year at the time of writing. The data was acquired and cleared following the rigorous Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. After the bibliometric analysis, the authors conducted a systematic literature review, separating the literature into five main clusters, including sustainability performance and eco-efficiency, (supply chain) sustainability assessment, environmental implications of corporate sustainability, outcomes of measuring corporate sustainability, and ESG efforts and sustainability support. The article presents the foundational articles and most productive countries and authors, unveiling the inherent intellectual structure of the topic, its recent developmental trajectory, and six avenues for future research.

Keywords: Corporate Sustainability; Data Envelopment Analysis; Bibliometric Analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/978-3-031-98177-7_7

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