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Measuring airline efficiency using a dynamic network data envelopment analysis in the presence of innovation capital

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dc.citedby3
dc.contributor.authorAbdul Rashid A.en_US
dc.contributor.authorSee K.F.en_US
dc.contributor.authorYu M.-M.en_US
dc.contributor.authorid36968755400en_US
dc.contributor.authorid53464206000en_US
dc.contributor.authorid7404273246en_US
dc.date.accessioned2025-03-03T07:42:18Z
dc.date.available2025-03-03T07:42:18Z
dc.date.issued2024
dc.description.abstractThis 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo123457
dc.identifier.doi10.1016/j.techfore.2024.123457
dc.identifier.scopus2-s2.0-85197296843
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85197296843&doi=10.1016%2fj.techfore.2024.123457&partnerID=40&md5=96e26100c2accd05364841532f433d64
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36411
dc.identifier.volume206
dc.publisherElsevier Inc.en_US
dc.sourceScopus
dc.sourcetitleTechnological Forecasting and Social Change
dc.subjectAir transportation
dc.subjectCompetition
dc.subjectData envelopment analysis
dc.subjectAirline efficiency
dc.subjectAnalysis frameworks
dc.subjectCarry-over effects
dc.subjectData envelopment analysis models
dc.subjectDynamic network
dc.subjectInnovation capital
dc.subjectNetwork data
dc.subjectNetwork data envelopment analyse
dc.subjectPerformance
dc.subjectProduction stage
dc.subjectairline industry
dc.subjectcapital
dc.subjectdata envelopment analysis
dc.subjectefficiency measurement
dc.subjectinnovation
dc.subjectsustainability
dc.subjectEfficiency
dc.titleMeasuring airline efficiency using a dynamic network data envelopment analysis in the presence of innovation capitalen_US
dc.typeArticleen_US
dspace.entity.typePublication
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