Flight based relational carbon emission performance analysis using DEA: A case study

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Thesis Type: Postgraduate

Institution Of The Thesis: Galatasaray University, Fen Bilimleri Enstitüsü, LOJİSTİK VE FİNANSMAN YÖNETİMİ ANABİLİM DALI, Turkey

Approval Date: 2019

Thesis Language: English

Student: FURKAN AYDOĞAN

Supervisor: İlke Bereketli Zafeırakopoulos

Open Archive Collection: AVESIS Open Access Collection

Abstract:

Governments and international agencies act to prevent pollution. One these actions is limitation on greenhouse gases emission to prevent global warming. Today, world is fully industrialized and industries requires energy to operate. Energy creation from fossil fuel combustion, releases carbon dioxide into the atmosphere. Carbon dioxide is the major perpetrator of global warming. An aviation company should embrace the required carbon emission limitation acts if it wants to operate profitable as it is now. Recent studies and actions of government and authorities indicates that there will be high fines to polluters because of excessive amount of emission. One of examples for these applications is EU Emission Trading System (ETS) is already in action since 2012 for aviation industry operates in Europe and charging for excessive amount of carbon emission. The aim of our study is to provide a model to detecting improvement potential on flights by assessing carbon emission performance relatively for flights in a period. At the beginning, we ask 12 aviation experts 'which factors affect the emission amount produced by a flight?', and ask them to rank these factors using a fuzzy linguistic matrix we provide. Using historic flight data and weights, which are calculated using the insights from our experts, we construct and apply two DEA based on constant return to scale (CRS) and variable return to scale (VRS) on our empirical dataset. The results, similar with literature, showed our models would help environmental improvement responsible to determine improvement potentials.