Analysing the determinants of technical efficiency in major Chinese retail firms: a bootstrap data envelopment analysis (DEA) and truncated regression approach

Oswin Aganda Anaba, Benjamin Azembila Asunka, Dawuda Abudu, Obed Dalad Mba and Edmund Nana Kwame Nkrumah

American Journal of Finance and Accounting, 2025, vol. 8, issue 3, 217-232

Abstract: This study examines the technical efficiency of major domestic retail enterprises using bootstrap data envelopment analysis (DEA) and truncated regression analysis. Key findings reveal that large businesses and department stores are more technically efficient than small medium enterprises (SMEs). Technical efficiency positively correlates with operating income-to-sales and interest coverage ratios but negatively with debt and quick ratios. Additionally, firm age, size, and business type positively influence efficiency. Managerially, retail firms should optimise operations and adopt new technologies to enhance efficiency. Policymakers should support firms during economic downturns through fiscal measures like low-interest loans and tax cuts. The study's cross-sectional nature suggests future research should include longitudinal analysis for deeper insights.

Keywords: retail enterprises; bootstrap; DEA; data envelopment analysis; truncated regression; technical efficiency; determinants; SMEs; large enterprises; department shops; china. (search for similar items in EconPapers)
Date: 2025
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