Measuring airline efficiency using a dynamic network data envelopment analysis in the presence of innovation capital
This study aims to analyze the efficiency of global airlines by incorporating innovation capital into a two-stage dynamic network data envelopment analysis (DEA) framework. This paper addresses these concerns by developing a dynamic network DEA model that considers the interconnectedness between air...
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Elsevier Inc.
2025
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| Summary: | This study aims to analyze the efficiency of global airlines by incorporating innovation capital into a two-stage dynamic network data envelopment analysis (DEA) framework. This paper addresses these concerns by developing a dynamic network DEA model that considers the interconnectedness between airlines' internal processes and the carry-over effects between time periods. It incorporates the dynamic impact of shared carry-over items, enabling accurate computation of efficiency scores for these two stages. The study divides the airline operation system into two stages: production stage and service stage, where intertemporal shared innovation capital occurs. The results reveal that, despite majority airlines prioritizing the service stage, production stage contributed most to overall efficiency. In terms of periodic results, the efficiency score of airlines in 2017 is marginally higher compared to 2016 and 2018, respectively. In general, airlines place a slightly greater emphasis on service stage than production stage. Innovation is essential for airlines to achieve a sustainable competitive advantage. Despite considerable interest in analyzing performance, this is one of the first studies to incorporate innovation capital in airline efficiency studies. The proposed model can help airline managers, regulators, and policymakers measure performance reliably and improve airline efficiency and sustainability. ? 2024 Elsevier Inc. |
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