The Indian hotel and restaurant (H&R) industry is up against fierce competition from large hotels and the rapidly expanding online market, particularly in the aftermath of the epidemic. This research employs data envelopment analysis (DEA) to evaluate the impact of COVID-19 on relative efficiency of 265 H&R firms in India. The analysis reveals substantial operational and scale efficiency (SE) discrepancies, underlines exemplary enterprises that could serve as benchmarks for underperforming firms, and offers a discerning evaluation of operational and strategic management modifications. Moreover, underscored by slack analysis are significant inefficiencies in resource usage, which are aggravated by increasing competition from overseas hotel brands and online food delivery firms. The study recommends that H&Rs optimize workforce management, review staffing needs and apply takeout services to increase efficiency. The analysis of slack indicates considerable inefficiencies in capital allocation, asset management and operational cost regulation. The findings offer strategic insights for management strategies, emphasizing the need for scale optimization, workforce rationalization and technology integration. Furthermore, by implementing strategic interventions, the government can play a significant role in industry revival, efficiency enhancement and long-term sustainability in a highly competitive market.
AlarconJ. P. A. (2022). COVID-19 and its effects on rent prices for the hospitality industry: An economic model for the Rebus Sic Stantibus clause. Studies in Microeconomics, 12(3), 308–325.
2.
AndersonR. I., FokR., & ScottJ. (2000). Hotel industry efficiency: An advanced linear programming examination. American Business Review, 18(1), 40–48.
3.
AssafA. G., & AgbolaF. W. (2011). Modelling the performance of Australian hotels: A DEA double bootstrap approach. Tourism Economics, 17(1), 73–89. https://doi.org/10.5367/te.2011.0021
4.
AssafA. G., & BarrosC. (2011). Performance analysis of the Gulf hotel industry: A Malmquist index with bias correction. International Journal of Hospitality Management, 30(4), 819–826.
5.
AssafA. G., DeeryM., & JagoL. (2011). Evaluating the performance and scale characteristics of the Australian restaurant industry. Journal of Hospitality and Tourism Research, 35(4), 419–436.
6.
AvkiranN. K. (1999). An application reference for data envelopment analysis in branch banking: Helping the novice researcher. International Journal of Bank Marketing, 17(5), 206–220.
7.
BankerR. D., CharnesA., & CooperW. W. (1984). Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078–1092.
8.
BarrosC. P. (2004). A stochastic cost frontier in the Portuguese hotel industry. Tourism Economics, 10(2), 177–192.
9.
BarrosC. P. (2005). Measuring efficiency in the hotel sector. Annals of Tourism Research, 32(2), 456–477.
10.
BarrosC. P., & AlvesF. P. (2004). Productivity in the tourism industry. International Advances in Economic Research, 10(3), 215–225.
11.
BartikA. W., BertrandM., CullenZ. B., GlaeserE. L., LucaM., & StantonC. T. (2020). How are small businesses adjusting to COVID-19? Early evidence from a survey (No. w26989). National Bureau of Economic Research.
12.
Centre for Monitoring Indian Economy (CMIE). (2023). Prowess database. Retrieved fromhttps://prowessiq.cmie.com
13.
CharnesA., CooperW. W., & RhodesE. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429–444.
14.
CoelliT. J., RaoD. S. P., O’DonnellC. J., & BatteseG. E. (2005). An introduction to efficiency and productivity analysis. Springer.
15.
FarrellM. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253–290.
16.
Federation of Hotel and Restaurant Associations of India. (2021). Hotel industry survey. www.fhrai.com
17.
GhoshS., & BhattacharyaM. (2022). Analyzing the impact of COVID-19 on the financial performance of the hospitality and tourism industries: An ensemble MCDM approach in the Indian context. International Journal of Contemporary Hospitality Management, 34(8), 3113–3142.
18.
GösslingS., ScottD., & HallC. M. (2020). Pandemics, tourism and global change: A rapid assessment of COVID-19. Journal of Sustainable Tourism, 29(1), 1–20.
19.
GursoyD., & ChiC. G. (2020). Effects of COVID-19 pandemic on hospitality industry: Review of the current situations and a research agenda. Journal of Hospitality Marketing & Management, 29(5), 527–529.
20.
HsiehL. F., & LinL. H. (2010). A performance evaluation model for international tourist hotels in Taiwan—An application of the relational network DEA. International Journal of Hospitality Management, 29(1), 14–24.
21.
IBEF. (2024). Growth of hotel industry in India. https://www.ibef.org/research/case-study/growth-of-hotel-industry-in-india
22.
JafariK., ÖzduranA., & SaydamM. B. (2023). Hospitality and tourism industry amid COVID-19 pandemic: Voices from small Mediterranean town. International Hospitality Review, 37(2), 243–264.
23.
MahajanV., MoghaS. K., & PannalaR. P. K. (2024). Evaluation of efficiency and ranking of Indian hotels and restaurants: A bootstrap DEA approach. Benchmarking: An International Journal, 31(1), 186–198.
24.
MahajanV., NauriyalD. K., & SinghS. P. (2014). Technical efficiency analysis of the Indian drug and pharmaceutical industry: A non-parametric approach. Benchmarking: An International Journal, 21(5), 734–755.
25.
MajumdarR. (2021). Surviving and growing in the post-COVID world: The case of Indian hotels. Worldwide Hospitality and Tourism Themes, 13(5), 584–598.
26.
MatricanoD., CandeloE., & SorrentinoM. (2022). Start-ups’ innovation processes and performance in the food industry: A stochastic frontier analysis. British Food Journal, 124(3), 936–950.
27.
MhlangaO. (2018). Factors impacting restaurant efficiency: A data envelopment analysis. Tourism Review, 73(1), 82–93.
28.
Muneer BabuM., & KulshreshthaP. (2014). Productivity change and technical efficiency in Indian microfinance institutions. Studies in Microeconomics, 2(2), 165–200.
29.
NevesJ. C., & LourençoS. (2009). Using data envelopment analysis to select strategies that improve the performance of hotel companies. International Journal of Contemporary Hospitality Management, 21(6), 698–712.
30.
PhucharoenC., & SangkaewN. (2020). Does firm efficiency matter in the hospitality industry?Journal of Tourism Analysis: Revista de Análisis Turístico, 27(1), 62–80.
31.
RamanathanR. (2012). An exploratory study of marketing, physical and people related performance criteria in hotels. International Journal of Contemporary Hospitality Management, 24(1), 44–61.
32.
Rodríguez-LópezM. E., Alcántara-PilarJ. M., Del Barrio-GarcíaS., & Muñoz LeivaF. (2020). A review of restaurant research in the last two decades: A bibliometric analysis. International Journal of Hospitality Management, 87, 102387.
33.
SanjeevG. M. (2007). Measuring efficiency of the hotel and restaurant sector: The case of India. International Journal of Contemporary Hospitality Management, 19(5), 378–387.
34.
SharmaN., & MoghaS. K. (2024). Super efficiency and sensitivity analysis of the Indian hotels and restaurants. OPSEARCH, 61(4), 2131–2157.
35.
SinghR., CharanP., & ChattopadhyayM. (2022). Evaluating the hotel industry performance using efficiency and effectiveness measures. International Journal of Hospitality & Tourism Administration, 23(2), 408–431.
36.
SufianF. (2016). Determinants of efficiency in the Malaysian banking sector: Evidence from semi-parametric data envelopment analysis method. Studies in Microeconomics, 4(2), 151–172.
37.
TewariS., & AryaA. (2024). Analyzing the efficiency of the Indian hotel industry using the Malmquist DEA approach. Benchmarking: An International Journal, 31(9), 2839–2870.
38.
ThanassoulisE. (2001). Introduction to the theory and application of data envelopment analysis. Springer.
39.
TiwariS., & SanjeevG. M. (2021). Conclusion: Emerging issues for Indian hospitality and tourism businesses: How are managers responding to the COVID-19 pandemic?Worldwide Hospitality and Tourism Themes, 13(5), 677–682.
40.
TsaiH., PanS. L., & LeeJ. S. (2011). Recent research in hospitality financial management. International Journal of Contemporary Hospitality Management, 23(7), 941–971. https://doi.org/10.1108/09596111111167551
41.
Van DorenC. S., & GustkeL. D. (1982). Spatial analysis of the US lodging industry. Annals of Tourism Research, 9(4), 543–563.
42.
WassenaarD. J., & StaffordE. R. (1991). The lodging index: An economic indicator for the hotel/motel industry. Journal of Travel Research, 30(1), 18–21.
43.
WuJ., TsaiH., & ZhouZ. (2011). Improving efficiency in international tourist hotels in Taipei using a non-radial DEA model. International Journal of Contemporary Hospitality Management, 23(1), 66–83.
