Forecasting in aviation: a systematic review of passenger, fleet and emissions models

Purpose To explore the benefits and challenges of utilising different forecasting tools within the aviation industry to establish best practice techniques for forecasting global passenger growth, fleet evolutions and carbon emission generation. Design/methodology/approach A systematic literature review of the Scopus database is conducted by applying a PRISMA methodology in order to identify academic papers related to aviation forecasting. Supplementary industry sources are also included as these are often commonly cited within this field. Findings Results from carbon emission forecasting models have historically underperformed when compared to actual data. This is indicative of systematic issues that need to be addressed when considering the aims of the industry to become net-zero by 2050. The most commonly cited methodologies for forecasting include regression, machine learning and scenario models. Their applications are dependent on the desired outputs of the model, underlying assumptions and availability of data inputs. Research limitations/implications Environmental impacts of this study are measured solely with respect to carbon dioxide emissions. Whilst this is the primary climate concern of the aviation industry, other environmental impacts are a hindrance to achieving sustainability for example other GHG emissions, local air/noise pollution. Practical implications To provide aviation planners, operators and policy makers with guidance on how to choose and apply appropriate forecasting models for passenger demand, fleet growth, and emissions. To identify best practices to improve forecasting accuracy, which supports better informed decision-making at local and national levels. Social implications Improved aviation forecasting directly supports sustainable development by providing more accurate projections of passenger demand, fleet evolutions, and emissions. This will help to identify the scale of the challenge posed by decarbonising the industry and allow for progress to be checked more accurately through to 2050. Originality/value The interdependent relationship that exists when forecasting carbon emissions, passenger growth and fleet evolutions in the aviation industry has not been synthesised into one review before. By combining these topics in such a way, this creates a more succinct picture for assessing the challenge posed by decarbonising the aviation industry.