Operational efficiency-based ranking framework using uncertain DEA methods

Abstract

Purpose – Competition in dynamic markets requires operational excellence and effective operations strategy. Hence, organizations have to evaluate their operational performance in comparison to their rivals. The purpose of this paper is to present an operational performance evaluation framework for analyzing and ranking the organizations based on the effectiveness of their operations strategies. Design/methodology/approach – In this study three uncertain data envelopment analysis (DEA) models consist of fuzzy DEA (FDEA), imprecise DEA (IDEA) and Grey DEA are applied to assess the performance of organizations in terms of the operations. The applicability of the proposed framework is demonstrated through a case study at Fars province cement manufacturers of Iran. Findings – The ranking results assist the mangers of service and manufacturing enterprises in finding out the current positions of their companies and the effectiveness of their operations strategies in comparison to their rivals. Accordingly they can make proper strategic and operational decisions to improve the performance of the operations. Originality/value – Based on the previous literature, this is the first study which uses FDEA and IDEA methods in an operational performance evaluation problem. Furthermore this study proposes a novel framework for evaluating and ranking the operational performance of firms from the perspective of operations strategy.

Performance of Indian Cement Companies: A Super Efficiency DEA Study

“…Scale and technical efficiencies of Iranian cement companies were measured using various techniques such as DEA,TOPSIS, etc. in different studies [10,13,14]. Similar kind of exercise was undertaken in India [12].…”

Operational efficiency of ASEAN airlines: based on DEA and bootstrapping approaches

“…There is also other recent literature in the airline efficiency studies that has applied DEA models. Abbasi and Kaviani (2016) use three uncertain DEA models that consist of fuzzy DEA, imprecise DEA, and Grey DEA to assess the performance of organizations in terms of the operations. Ji et al (2015) employ Choquet integrals as an aggregating tool and give a novel DEA model to evaluate the efficiencies of decision-making units (DMUs).…”

Integrated data envelopment analysis and multicriteria decision-making ranking approach based on peer-evaluations and subjective preferences: case study in banking sector

“…Performance assessment and organizational rankings have attracted the attention of many researchers in the past few decades. Several performance assessment tools have been developed to assess organizational performances and analyze their rankings (Moore, 2007; Puri and Yadav, 2013, 2014; Mahdavi and Hesamamiri, 2014; Abbasi and Kaviani, 2016; Lv and Ma, 2019; Chen et al , 2020b). Data envelopment analysis (DEA), developed by Charnes et al (1978), is one among these performance tools.…”

“…In the literature, various approaches have been reported to increase the discrimination power of the DMUs. The literature on complete ranking of the DMUs can be seen in the studies like Sexton et al (1986), Adler et al (2002), Amin and Toloo (2007), Liang et al (2009), Jahanshahloo et al (2010), Guo and Wu (2013), Abbasi and Kaviani (2016), Hong and Jeong (2017), Kritikos (2017) and Liu and Wang (2018). Adler et al (2002) classified DEA ranking approaches into six techniques.…”