Super efficiency and sensitivity analysis of the Indian hotels and restaurants

Abstract

Over the course of COVID-19, the global growth of the hospitality and restaurant (H&Rs) sector has declined. During this di cult period, this sector's overall performance declined. As a result, this industry must adopt fresh approaches to seize the potential and overcome the obstacles at this pivotal moment. One of these di culties is guring out how to evaluate H&Rs' effectiveness using a variety of factors. This study evaluates the performance of 45 signi cant H&R businesses operating in India using the Data Envelopment Analysis (DEA) method.The Basic DEA models usually do not disclose the improvement in the capability of different DMUs as these models calculate only radial e ciency. In this paper, the New Slack Model (NSM) of DEA has been employed to examine the e ciency of the different 45 large-scale Indian Hotels and Restaurants (H&Rs). The NSM model cognate the input and output slacks straight away. In this study, four inputs: Capital employed, Gross xed assets, Current assets, and Operating costs, and two outputs: Operating income and Pro t before depreciation, interest, and tax (PBDIT) are considered. The data for the study has been collected from the Prowess database of the Centre for Monitoring Indian Economy (CMIE). The study indicates that only 65.58% of H&R are technically e cient which shows that some resources are unutilized and therefore there is a huge scope for an upswing. To validate the stability of results sensitivity analysis is also carried out. brought on by scale or size (scale ine ciency) and/or management techniques (pure technical ine ciency). In 1978, Charnes et al. created the fundamental DEA model, which was further expanded by [1]. Numerous theoretical extensions have been created based on these fundamental DEA models, including the Cone Ratio Model (Cooper et al. 1997), the Slack Adjusted Model [2], the Slack Based Model [3], and the New Slack Model [4], etc.Slacks are not taken into account by the fundamental CCR and BCC models, whereas the radial features of DEA are not present in the additive model or the SBM model. The NSM model, which meets the monotone decreasing property with regard to slacks, is applied in this study while keeping these constraints in mind. Additionally, it satis es all of the other radial DEA model features. All multipliers have become positive, according to the dual of the NSM model, meaning that all input and output factors have been properly accounted for in the performance evaluation of the DMUs. Additionally, it satis es all of the other features of radial DEA model.Rest of the paper is organized as follows: Section 2 elaborates the literature revie, section 3 explains about methodology applied, a description of data and variable used is provide in section 4 which is followed by the section 5 which contains result and discussion, Sensitivity analysis and super e ciency are described in section 6, which is followed by the conclusion.