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Operational performance of Indian passenger airlines using hierarchical categorical DEA approach
The challenges faced by the Indian Aviation market are complex and perplexing for the decision-makers in this sector. This industry has faced debilitating losses during COVID-19 pandemic times. The travel restrictions have been gradually lifted worldwide, and therefore the airlines can expect to wit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808679/ http://dx.doi.org/10.1007/s13198-022-01852-6 |
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author | Seth, Bharti Saxena, Punita Arora, Shalini |
author_facet | Seth, Bharti Saxena, Punita Arora, Shalini |
author_sort | Seth, Bharti |
collection | PubMed |
description | The challenges faced by the Indian Aviation market are complex and perplexing for the decision-makers in this sector. This industry has faced debilitating losses during COVID-19 pandemic times. The travel restrictions have been gradually lifted worldwide, and therefore the airlines can expect to witness a growth in domestic and international air passenger traffic during 2021–22. The losses incurred during the pandemic times need to be recovered. Thus, there is an urgent need to strategically plan and improve the operations so that the airlines can perform efficiently and earn revenues. Airlines in India work under heterogeneous environments depending upon their segment of operations. Some of the airlines operate for only domestic passengers and others for both domestic and international passengers. Therefore these airlines must be assessed as per their homogeneous peer group to obtain substantial results. The proposed study has discussed an approach to study airlines' operational performance using hierarchical categorical data envelopment analysis (DEA). The airlines have been categorized based upon their segment of operations. The efficiency of the airlines has been evaluated for the period 2014–19 as per their categorical input value. Window analysis has also been performed for a meaningful analysis of the results. The outcomes of the study will be helpful for policymakers to improvise the present working model of the industry and alleviate their performance. |
format | Online Article Text |
id | pubmed-9808679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-98086792023-01-04 Operational performance of Indian passenger airlines using hierarchical categorical DEA approach Seth, Bharti Saxena, Punita Arora, Shalini Int J Syst Assur Eng Manag Original Article The challenges faced by the Indian Aviation market are complex and perplexing for the decision-makers in this sector. This industry has faced debilitating losses during COVID-19 pandemic times. The travel restrictions have been gradually lifted worldwide, and therefore the airlines can expect to witness a growth in domestic and international air passenger traffic during 2021–22. The losses incurred during the pandemic times need to be recovered. Thus, there is an urgent need to strategically plan and improve the operations so that the airlines can perform efficiently and earn revenues. Airlines in India work under heterogeneous environments depending upon their segment of operations. Some of the airlines operate for only domestic passengers and others for both domestic and international passengers. Therefore these airlines must be assessed as per their homogeneous peer group to obtain substantial results. The proposed study has discussed an approach to study airlines' operational performance using hierarchical categorical data envelopment analysis (DEA). The airlines have been categorized based upon their segment of operations. The efficiency of the airlines has been evaluated for the period 2014–19 as per their categorical input value. Window analysis has also been performed for a meaningful analysis of the results. The outcomes of the study will be helpful for policymakers to improvise the present working model of the industry and alleviate their performance. Springer India 2023-01-03 /pmc/articles/PMC9808679/ http://dx.doi.org/10.1007/s13198-022-01852-6 Text en © The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Seth, Bharti Saxena, Punita Arora, Shalini Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title | Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title_full | Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title_fullStr | Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title_full_unstemmed | Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title_short | Operational performance of Indian passenger airlines using hierarchical categorical DEA approach |
title_sort | operational performance of indian passenger airlines using hierarchical categorical dea approach |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9808679/ http://dx.doi.org/10.1007/s13198-022-01852-6 |
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