Development and implementation of an emission optimization model for passenger flight bookings
2019 (English)In: SUSTAINABLE ENVIRONMENT RESEARCH, ISSN 2468-2039, Vol. 29, no 1Article in journal (Refereed) Published
Abstract [en]
In this analysis we discover the potential of a more transparent emission declaration system, in order to a) facilitate for environmentally concerned consumers to choose low-emission flights, and b) provide data for a future emission trading system where the aviation industry is accounted for its emission costs. Some air travel consumers book flights through low-cost flight ticket price comparison websites, that offer comparisons on price, convenience, travel time, and other factors relevant to the consumer. As a basis for this study, an algorithm designed for "flight CO2 emissions comparisons", was developed and implemented on Sweden's largest flight ticket price comparison website that compares flights by CO2 emissions in kg per passenger and trip. A visitor to the site can now also select a flight based on the ranking of carbon emission levels from each flight. In addition to the implementation of the algorithm in a commercial aviation booking system, a survey was conducted to analyze consumer preference data to glean insights and make conclusions about flight ticket price sensitivity, convenience, environmental awareness and potential for behavioral change among air travel consumers. The findings from this study indicate that the algorithm will not act as a catalyst for emission reductions in the aviation sector, unless it is complemented by emission reduction policies and/or introduction of a fair emission taxation system. Furthermore, the aviation sector should be obliged to report accurate emission data on all tickets in order to bring full transparency to consumers searching low emission transport modes.
Place, publisher, year, edition, pages
BMC , 2019. Vol. 29, no 1
Keywords [en]
Sustainability, Transport, Planning, Aviation, Climate, Emission
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:kth:diva-262949DOI: 10.1186/s42834-019-0024-5ISI: 000489108500001Scopus ID: 2-s2.0-85077311504OAI: oai:DiVA.org:kth-262949DiVA, id: diva2:1374491
Note
QC 20191202
2019-12-022019-12-022022-06-26Bibliographically approved