Abstract
In many real-world situations, the cost and revenue performance of heterogeneous decision making units (DMUs) should be assessed while uncertain data are presented. The exiting data envelopment analysis (DEA) models have dealt with the economic efficiency of nonhomogenous DMUs without considering random performance measures. In this paper, a stochastic DEA approach is, therefore, proposed to estimate meta-frontier stochastic cost and revenue efficiencies under the convex technology. To illustrate, group cost and revenue efficiencies and meta cost and revenue efficiency scores under convex metatechnology are measured using cost-based and revenue-based chance-constrained DEA models. Furthermore, the deterministic frameworks of approaches are provided. Cost and revenue gap ratios and sources of meta-frontier stochastic cost and revenue inefficiencies are also handled. An empirical study of the banking industry is used to show the applicability and reliability of the proposed technique.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Information Technology & Decision Making
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
