Combined Shannon's entropy and DEA: case of Indian hotel and restaurant sector Online publication date: Mon, 16-Jan-2023
by R.K. Pavan Kumar Pannala; Sandeep Kumar Mogha; Neha Sharma; Vikas Garg
International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 14, No. 3, 2022
Abstract: A non-parametric linear programming-based data envelopment analysis (DEA) has been broadly applied in many sectors to measure the performance of decision-making units (DMUs). Basic DEA models such as CCR and BCC can bifurcate the DMUs into efficient and inefficient sets but cannot further identify the most efficient DMUs. Numerous methods have been proposed to address this issue and allotted ranks to DMUs. The main objective of the current paper is to implement an integrated DEA with Shannon's entropy to measure efficiencies and to rank hotels and restaurants (H&R) operating in India. The present study is carried out by integrating an orientation independent CCR, orientation dependent BCC, and non-oriented SBM with Shannon's entropy. The combined DEA-Shannon's entropy method provides comprehensive efficiency scores (CES) to all DMUs. The adopted methods have been applied to the selected 45 H&R companies in India for the year 2019-2020.
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