TITLE:
Data Envelopment Analysis of Corporate Failure for Non-Manufacturing Firms Using a Slacks-Based Measure
AUTHORS:
Joseph C. Paradi, D’Andre Wilson, Xiaopeng Yang
KEYWORDS:
Corporate Failure, Non-Manufacturing Company, Services Industry, Predictions, Data Envelopment Analysis (DEA), Altman’s Z Score
JOURNAL NAME:
Journal of Service Science and Management,
Vol.7 No.4,
August
26,
2014
ABSTRACT: The problem of predicting corporate failure has intrigued many in the
investment sector, corporate decision makers, business partners and many
others, hence the intense research efforts by industry and academia. The
majority of former research efforts on this topic focused on manufacturing
companies with considerable assets commensurate with their size. But there is a
dearth of publications on predicting non-manufacturing firms’ financial
difficulties since these firms typically do not have significant assets that
rely heavily on assets, and a key variable cannot be adequate. Recently, data
envelopment analysis (DEA) rather than Altman’s Z score model and traditional parametric methods has become a
research interest in predicting corporate failure. However, there is still no
research showing how to fix appropriate cut-off points to distinguish the
performance of firms. Our research utilizes slack-based measure (SBM) DEA model
to generate efficiency scores for non-manufacturing firms; then we categorize
these firms into safe, grey and distress zones by proposing cut-off points
based on 5 years DEA analysis. The result shows that the proposed method has
obvious advantages in predicting corporate financial stress.