Sustainability performance of SMEs: a causal inference approach to the firm strategy and interval-scale DEA

Akram Dehnokhalaji, Shahin Ashkiani, Prasanta K. Dey and Chrisovalantis Malesios

Journal of Management Analytics, 2026, vol. 13, issue 1, 43-69

Abstract: We examine the sustainability performance of Smalland Medium-Sized Enterprises (SMEs) across four European countries, focusing on operational, economic, social, and environmental practices. Data were collected through a Likert-scale questionnaire. While Data Envelopment Analysis (DEA) has been widely used to assess SMEs' sustainability, most studies rely on conventional DEA models. This study adopts an interval-scale DEA model to better accommodate interval-scale data. We then apply dimensionality reduction and visualization techniques to explore intra- and inter-country differences at both aggregate and SME levels. Finally, we introduce a novel HHI-GPSM-LASSO framework to assess the causal effect of SMEs’ resource allocation strategies on efficiency. This framework integrates a Herfindahl-Hirschman-like index, Generalized Propensity Score Matching, and weighted Lasso regression to uncover the causal relationships between SMEs' resource allocation strategies and efficiencies. While visualization enhances interpretability for practitioners, the causal framework supports strategic and policy decisions. To our knowledge, this is the first DEA study that combines interval-scale DEA, advanced visualization, and causal inference to inform sustainability benchmarking and policy.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23270012.2025.2577383 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjmaxx:v:13:y:2026:i:1:p:43-69

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjma20

DOI: 10.1080/23270012.2025.2577383

Access Statistics for this article

Journal of Management Analytics is currently edited by Li Xu

More articles in Journal of Management Analytics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().