Abstract
This paper aims to provide a novel construct that is based on data envelopment analysis (DEA) range adjusted measure (RAM) of efficiency and demonstrate its practical implementation by evaluating the financial performance of a sample of three upper-class contracting license (Classes 5–7) Greek construction firms. In a two-step framework, firm efficiency (i.e., composite indicators (CIs)) is produced firstly by means of RAM using single financial ratios, which are selected by grey relational analysis (GRA), and then Tobit regression is employed to model the CIs. In light of the results, only 4% of the sampled firms are efficient, and the firm ranking is consistent with the ranking of Grey Relational Grande (GRG) values produced by GRA. Moreover, the firms with a contracting license of the highest level (Class 7) appear not to be superior in efficiency to their counterparts that belong to Classes 5–6.
Highlights
IntroductionThe managers of any company must measure the financial performance of the firm they manage
The managers of any company must measure the financial performance of the firm they manage.Assessing the performance of modern construction companies is a complex issue from both an international and local perspective [1]
The effect of the class dummy variable is significant in explaining inefficiency. This finding shows that the Class 7 contracting license firms seem to not be superior in efficiency to their counterparts that belong to Classes 5–6
Summary
The managers of any company must measure the financial performance of the firm they manage. Assessing the performance of modern construction companies is a complex issue from both an international and local perspective [1]. The financial success of construction firms very much depends on the location [2], proper management [3], environmental characteristics [4], selected technologies [5], staff qualification [6], and specific circumstances [7,8]. At the project level, the influence of various factors on the project success may be responsible for the production of differently significant outcomes [9]. Management accounting information is mainly used for firm financial performance assessment The managers can predict the data describing the projects accurately and determine them at certain intervals, or they should treat them as fuzzy data [10,11].
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