Chapter 10: Transport
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10.1 Introduction and Overview
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Table 10.1 | Transport and the Sustainable Development Goals: Synergies and trade-offs.
Please refer to page 1067 in the report to see Table 10.1, which refers to SDG 5: Gender Equality.
10.2 Systemic Changes in the Transport Sector
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10.2.2 Behaviour and Mode Choice
Behaviour continues to be a major source of interest in the decarbonisation of transport as it directly addresses demand. Behaviour is about people’s actions based on their preferences. Chapter 5 described an ‘Avoid, Shift, Improve’ process for demandside changes that affect sectoral emissions. This section discusses some of the drivers of behaviour related to the transport sector and how they link to this ‘Avoid, Shift, Improve’ process.
Avoid: the effect of prices and income on demand. Research has shown that household income and price have a strong influence on people’s preferences for transport services (Bakhat et al. 2017; Palmer et al. 2018). The relationship between income and demand is defined by the income elasticity of demand. For example, research suggests that in China, older and wealthier populations continued to show a preference for car travel (Yang et al. 2019) while younger and low-income travellers sought variety in transport modes (Song et al. 2018). Similarly, Bergantino et al. (2018b) evaluated the income elasticity of transport by mode in the UK. They found that the income elasticity for private cars is 0.714, while the income elasticities of rail and bus use are 3.253 (the greater elasticity, the more the demand will grow or decline, depending on income). Research has also shown a positive relationship between income and demand for air travel, with income elasticities of air travel demand being positive and as large as 2 (Gallet and Doucouliagos 2014; Valdes 2015; Hakim and Merkert 2016; Hakim and Merkert 2019; Hanson et al. 2022). A survey in 98 Indian cities also showed income as the main factor influencing travel demand (Ahmad and de Oliveira 2016). Thus, as incomes and wealth across the globe rise, demand for travel is likely to increase as well.
The price elasticity of demand measures changes in demand as a result of changes in the prices of the services. In a meta-analysis of the price elasticity of energy demand, Labandeira et al. (2017) report the average long-term price elasticity of demand for gasoline and diesel to be –0.773 and –0.443, respectively. That is, demand will decline with increasing prices. A similar analysis of long-term data in the United States (US), the United Kingdom (UK), Sweden, Australia, and Germany reports the gasoline price elasticity of demand for car travel (as measured through vehicle-kilometre – vkm – per capita) ranges between –0.1 and –0.4 (Bastian et al. 2016). For rail travel, the price elasticity of demand has been found to range between –1.05 and –1.1 (Zeng et al. 2021). Similarly, price elasticities for air travel range from –0.53 to –1.91 depending on various factors such as purpose of travel (business or leisure), season, and month and day of departure (Morlotti et al. 2017).
The price elasticities of demand suggest that car use is inelastic to prices, while train use is relatively inelastic to the cost of using rail. Conversely, consumers seem to be more responsive to the cost of flying, so that strategies that increase the cost of flying are likely to contribute to some avoidance of aviation-related GHG emissions. While the literature continues to show that time, cost, and income dominate people’s travel choices (Ahmad and de Oliveira 2016; Capurso et al. 2019; He et al. 2020), there is also evidence of a role for personal values, and environmental values in particular, shaping choices within these structural limitations (Bouman and Steg 2019).
For example, individuals are more likely to drive less when they care about the environment (De Groot et al. 2008; Abrahamse et al. 2009; Jakovcevic and Steg 2013; Hiratsuka et al. 2018; Ünal et al. 2019). Moreover, emotional and symbolic factors affect the level of car use (Steg 2005). Differences in behaviour may also result due to differences in gender, age, norms, values, and social status. For example, women have been shown to be more sensitive to parking pricing than men (Simićević et al. 2020).
