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Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach
https://orcid.org/0000-0002-1426-0255
Abstract The intense price competition has hurt the revenue performance of the U.S. airline industry. In this context, network-legacy carriers (NLCs), low-cost carriers (LCCs), and ultra-low-cost carriers (ULCCs) in the U.S rely on different competitive advantages to create and promote their revenue efficiency. This study investigates the revenue efficiency differentials of the three airline business models in the U.S – NLC, LCC, and ULCC, using a two-stage data envelopment analysis (DEA) approach. In the first stage, a bootstrap non-convex meta-frontier framework is developed to estimate the DEA-based revenue efficiency of the airlines adopting different business models. In the second stage, a bootstrap truncated regression is employed to explain the differences in the airlines' revenue efficiency. Based on a data sample of the major airlines in the U.S. from 2015 to 2019, the study reveals the following findings: (1) The revenue efficiency varied significantly across the three airline business models. In which, ULCC type exhibited the lowest revenue efficiency; (2) Due to technological constraints, ULCCs averagely collected less than 17.6% of their potential revenue during the study period. Both LCC and NLC types demonstrated the most advanced technologies in generating revenue; however, NLCs generally outperformed LCCs; (3) Service quality, operational size, and airfare significantly impacted the airlines’ revenue performance.
Highlights We proposed a DEA model to assess revenue efficiency across ULCCs, LCCs, NLCs. Revenue efficiency differed significantly across airline business models. ULCCs forwent 17.6% of potential revenue due to technology constraints. Both LCCs and NLCs gained competitive advantages in collecting revenue. Service quality, operational size, and airfare drove airlines' revenue efficiency.
Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach
https://orcid.org/0000-0002-1426-0255
Abstract The intense price competition has hurt the revenue performance of the U.S. airline industry. In this context, network-legacy carriers (NLCs), low-cost carriers (LCCs), and ultra-low-cost carriers (ULCCs) in the U.S rely on different competitive advantages to create and promote their revenue efficiency. This study investigates the revenue efficiency differentials of the three airline business models in the U.S – NLC, LCC, and ULCC, using a two-stage data envelopment analysis (DEA) approach. In the first stage, a bootstrap non-convex meta-frontier framework is developed to estimate the DEA-based revenue efficiency of the airlines adopting different business models. In the second stage, a bootstrap truncated regression is employed to explain the differences in the airlines' revenue efficiency. Based on a data sample of the major airlines in the U.S. from 2015 to 2019, the study reveals the following findings: (1) The revenue efficiency varied significantly across the three airline business models. In which, ULCC type exhibited the lowest revenue efficiency; (2) Due to technological constraints, ULCCs averagely collected less than 17.6% of their potential revenue during the study period. Both LCC and NLC types demonstrated the most advanced technologies in generating revenue; however, NLCs generally outperformed LCCs; (3) Service quality, operational size, and airfare significantly impacted the airlines’ revenue performance.
Highlights We proposed a DEA model to assess revenue efficiency across ULCCs, LCCs, NLCs. Revenue efficiency differed significantly across airline business models. ULCCs forwent 17.6% of potential revenue due to technology constraints. Both LCCs and NLCs gained competitive advantages in collecting revenue. Service quality, operational size, and airfare drove airlines' revenue efficiency.
Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach
https://orcid.org/0000-0002-1426-0255
Abstract The intense price competition has hurt the revenue performance of the U.S. airline industry. In this context, network-legacy carriers (NLCs), low-cost carriers (LCCs), and ultra-low-cost carriers (ULCCs) in the U.S rely on different competitive advantages to create and promote their revenue efficiency. This study investigates the revenue efficiency differentials of the three airline business models in the U.S – NLC, LCC, and ULCC, using a two-stage data envelopment analysis (DEA) approach. In the first stage, a bootstrap non-convex meta-frontier framework is developed to estimate the DEA-based revenue efficiency of the airlines adopting different business models. In the second stage, a bootstrap truncated regression is employed to explain the differences in the airlines' revenue efficiency. Based on a data sample of the major airlines in the U.S. from 2015 to 2019, the study reveals the following findings: (1) The revenue efficiency varied significantly across the three airline business models. In which, ULCC type exhibited the lowest revenue efficiency; (2) Due to technological constraints, ULCCs averagely collected less than 17.6% of their potential revenue during the study period. Both LCC and NLC types demonstrated the most advanced technologies in generating revenue; however, NLCs generally outperformed LCCs; (3) Service quality, operational size, and airfare significantly impacted the airlines’ revenue performance.
Highlights We proposed a DEA model to assess revenue efficiency across ULCCs, LCCs, NLCs. Revenue efficiency differed significantly across airline business models. ULCCs forwent 17.6% of potential revenue due to technology constraints. Both LCCs and NLCs gained competitive advantages in collecting revenue. Service quality, operational size, and airfare drove airlines' revenue efficiency.
Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach
Nguyen, Minh-Anh Thi (author) / Yu, Ming-Miin (author) / Lirn, Taih-Cherng (author)
Transport Policy ; 117 ; 108-117
2022-01-10
10 pages
Article (Journal)
Electronic Resource
English
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