Abstract
Sustainable development and sustainability assessment have been of great interest to both academe and practitioners in the past decades. In this study, we review the literature on data envelopment analysis (DEA) applications in sustainability using citation-based approaches. A directional network is constructed based on citation relationships among DEA papers published in journals indexed by the Web of Science database from 1996 to 2019. We first draw the citation chronological graph to present a complete picture of literature development trajectory since 1996. Then we identify the local main DEA development paths in sustainability research by assigning an importance index, namely search path count (SPC), to each link in the citation network. The local main path suggests that the current key route of DEA applications in sustainability focus on the environmental sustainability. Through the Kamada–Kawai layout algorithm, we find four research clusters in the literature including corporate sustainability assessment, regional sustainability assessment, sustainability composite indicator construction, and sustainability performance analysis. For each of the clusters, we further identify the key articles based on citation network and local citation scores, demonstrate the developmental trajectory of the literature, and suggest future research directions.
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Notes
- 1.
The input degree of a vertex means the number of edges pointing to this vertex, which represents the vertex paper is cited by how many other papers.
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The current chapter is based upon Zhou, H., Yang, Yi., Chen, Y., and Zhu, J., Data envelopment analysis application in sustainability: The origins, development and future directions, European Journal of Operational Research, Vol. 264, Issue 1 (2018), 1–16, with permission from Elsevier.
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Zhou, H., Yang, Y., Chen, Y., Zhu, J., Shi, Y. (2021). DEA Application in Sustainability 1996–2019: The Origins, Development, and Future Directions. In: Chen, C., Chen, Y., Jayaraman, V. (eds) Pursuing Sustainability. International Series in Operations Research & Management Science, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-58023-0_4
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