Abstract:
This study aims to provide a conceptual foundation for Financial Data Envelopment Analysis
(DEA), which refers to DEA models that exclusively use accounting data from external
financial reports to measure firm performance. Researchers have argued that using
accounting measures in DEA models without appropriate methodological rationalisation
might distort performance evaluations (Färe et al., 1985; Färe et al., 2017). Researchers have
also questioned the kind of efficiency measures being calculated by DEA when the inputs and
outputs are accounting measures since they cover both quantities and prices (Banker et al.,
2007; Cross & Färe, 2008; Portela, 2014; Zelenyuk, 2020). This study is motivated by the
growth in Financial DEA research, where DEA model are potentially being applied without
underpinning by an articulated conceptual foundation
A two-phase analytical approach is used to examine the uses of Financial DEA and develop a
conceptual foundation to assist the design and interpretation of Financial DEA. Phase I
provides a typology of Financial DEA literature and reviews the methodological issues in the
application of Financial DEA. Phase II quantifies selective methodological issues with
empirical illustrations, using Monte Carlo simulations and analysis of archival data.
The key findings and contributions are three-fold. First, the typology identifies 12
dimensional constructs of firm performance and nine indicators. This contributes a
conceptual framework at the construct level, which provides an overview of the scope of
Financial DEA and can be used to position the application of Financial DEA and apprise
Financial DEA practice. Second, the methodological issues are formed into a four quadrant
framework of measurement models with various measurement errors in Financial DEA. This
contributes a conceptual framework at the modelling level, which can be used to highlight
potential methodological pitfalls in Financial DEA. Third, the empirical tests demonstrate the
quantitative magnitudes of selective methodological issues on Financial DEA results,
exploring how research contexts affect results to varying degrees. This contributes a
conceptual framework at the factor level, which can guide accounting variable selection in
Financial DEA practice so that the measurement errors can be reduced. These three
frameworks form a conceptual foundation for future studies of Financial DEA.