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Factors Influencing Environmentally Friendly Air Travel: A Systematic, Mixed-Method Review

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Veröffentlicht/Copyright: 13. August 2025
Economics
Aus der Zeitschrift Economics Band 19 Heft 1

Abstract

Assessing the environmental impact of air travel is a complex endeavour with various solution scenarios and stakeholders, including the passengers. This article focuses on identifying factors influencing air passengers’ environmental awareness and resulting behaviour change towards more environmentally friendly air travel behaviour. A conceptual factor model is developed based on a systematic literature review of prevailing research (N = 111) and semi-structured interviews with experts (N = 14) from the aviation industry and beyond in Europe. The model distinguishes between demographic factors, internal factors, such as knowledge and values, and external factors, such as media usage and government policies. Three main parties emerge as forces that drive passengers towards increasing awareness and behaviour change: government, airlines, and social movement groups. The media is found to be a mediator. Focusing on the gap between attitude and behaviour, we summarize the factors that contribute to it and propose strategies to mitigate it.

1 Introduction

Climate change is one of the biggest environmental challenges of our time, and the general public has increasingly become aware of it, for instance, the global Fridays For Future movement of the young generation (Fisher, 2019; Hagedorn et al., 2019), the stay grounded campaign (Stay Grounded Network, 2022), and the flygskam (flight shaming) movement (Chiambaretto et al., 2021). It is common knowledge that actions need to be taken to tackle the climate crisis, but industries still heavily contribute to the problem by emitting greenhouse gases. In Europe, for instance, around 25% of greenhouse gas (GHG) emissions can be attributed to transport (The European Commission, 2016), with 3.8% attributed to aviation alone (i.e. 13.3% of all emissions from transportation) (The European Commission, 2020), making this sector a strong lever for potential emissions reduction. Furthermore, the tourism industry, responsible for approximately 8% of global greenhouse gas emissions (Lenzen et al., 2018), heavily relies on transportation, particularly air travel. This interdependence suggests that significant changes in air travel practices could have a profound impact on both tourism and overall emission levels.

Reducing climate impact is a challenge for the entire air transport system and a key priority on political agendas that look into the future of transport. The International Air Transport Association has set a goal of reaching zero net CO2 emissions by 2050 for aviation operations (IATA (The International Air Transport Association), 2021). There are various scenarios to reach that target (NLR (Royal Netherlands Aerospace Centre) & SEO (Amsterdam Economics), 2021). Next to technical solutions, operational changes such as CO2 offsetting programs, air traffic management adaptations, or slow flying can bring some relief. When travelling by air, passengers make decisions to select an airline (Baumeister, 2020), and choose the respective airport feeder services (Miyoshi & Mason, 2013). Passengers’ acceptance and adoption are hence relevant for the introduction of new types of eco-friendly aircraft such as electric- and hydrogen-powered aircraft (Fu & Moeckel, 2024). However, little is published to systematically review all the factors that influence passengers’ environmental awareness, provide a comprehensive overview, and outline how to translate this awareness into an actual behaviour change in travel and booking. Given the well-known attitude–behaviour gap (Gössling et al., 2009; Higham & Cohen, 2011) (meaning that a pro-environmental attitude does not automatically lead to true, long-term behaviour change in a person) and arguments passengers bring up to justify their air travel (Árnadóttir et al., 2021), reducing this research gap is of high relevance for the research community and the aviation industry.

Environmental awareness has received scrutiny in the literature. Conducting a text-mining exercise with scientific papers from the 15 top transport-related journals, Schmalz et al. (2021b) found that 502 scientific articles were published around environmental awareness between 2006 and 2020. Some of these are reviews. For instance, Baumeister (2020) published a literature review article exploring strategies for potential behaviour changes on the passenger side to mitigate their environmental impact when flying. Next to emissions offsetting schemes, the article focuses on the choice of a more environmentally friendly airline. The author argues that there is a lack of research focusing on understanding the impacts of behaviour changes on the mitigation of the environmental impact of aviation. Ryley et al. (2020) conducted a literature review to explore the effects of climate change, caused, for instance, by rising sea levels and extreme temperatures, and how aviation stakeholders have adapted to it. The study does not include the passenger as a stakeholder in the aviation system, nor does it focus on the passenger (demand) side. Studies using choice experiments estimate willingness to pay (WTP) for green travel (e.g. Hinnen et al., 2017); however, they lack an in-depth understanding of all the driving factors for the decision-making of passengers, as results always depict a relative picture between the chosen attributes and levels (Orme, 2019).

In contrast, the present work provides a conceptual model that includes currently researched internal and external factors that affect the environmental awareness and behaviour change of air passengers. Concurrently with our research, Gössling and Dolnicar (2023) similarly explored factors that influence air travel behaviour within the context of climate change, focusing on various technological and behavioural strategies to mitigate aviation’s environmental impact. However, our study extends and deepens their work by employing a mixed-method approach that combines a systematic literature review (SLR) with semi-structured expert interviews (Grant & Andrew, 2009) to identify critical factors influencing both environmental awareness/attitudes and air travel behaviour. This approach not only enriches the identification and validation of critical factors shaping environmental awareness, attitudes, and air travel behaviours but also examines the interplay and persistent gap between these attitudes and behaviours. By clarifying these complex interactions, our conceptual model provides novel insights and practical implications, guiding the decision-making processes of policymakers, airlines, social groups, and travellers towards more effective and coordinated interventions. Our contribution to the literature is threefold. Firstly, we present an updated compilation of recent studies and factors, including underexplored elements such as the influence of social media. Secondly, our mixed-method approach integrates and enhances findings from both the SLR and expert interviews, providing a comprehensive view of the thematic landscape. Finally, we articulate the practical implications of our findings, rendering our research pertinent to various stakeholders in the field.

The remainder of the article is structured as follows. Section 2 presents the applied methodology, a mixed approach combining SLR and semi-structured interviews. Section 3 elaborates on the results and our conceptual model. Section 4 discusses the limitations of the study and the practical implications of the findings. Section 5 concludes the article.

2 Methodology

2.1 Research Approach

This work aims to comprehensively review and structure the internal and external factors that affect the environmental awareness and behaviour change of air passengers. Internal factors are defined as factors based on humans’ intrinsic motivation. External factors influence humans from the outside. Both types of factors have the potential to affect human awareness. For our research process, we applied a mixed-method approach. First, we performed an SLR to identify those factors affecting passengers’ environmental awareness that have already been discussed in the scientific community. Second, we conducted semi-structured expert interviews (Bogner et al., 2014) to validate the external factors and find initial solutions to close or reduce the awareness–behaviour gap. Interviews with experts from the industry are an established research method to complement findings (Bogner et al., 2014). The interviews were necessary because the literature on external factors, such as policy and information, is scarce, and the method seemed to be suitable in this research context to complement the literature review. Comparing the findings of the SLR and expert interviews, we see that the SLR findings are partially confirmed by the experts, especially regarding the impacts of the known external factors. Other opinions from the experts are included to extend the theoretical model developed based on the SLR. Finally, we propose a final conceptual model based on the results of the SLR and expert interviews. Figure 1 illustrates the methodology framework.

Figure 1 
                  Overview of the research approach.
Figure 1

Overview of the research approach.

2.2 Systematic Literature Review

We entered our search terms into the Scopus and Google Scholar databases and cross-checked them in the OpenAlex catalogue (Priem et al., 2022), including environmental attitude, environmental behaviour, environmental awareness, environmental concern, pro-environmental attitude, pro-environmental behaviour, attitude–behaviour gap, aviation, air passenger, air travel, and air transportation. The search included title, abstract, and keywords. Based on the search, we identified 2,612 studies published between 2002 and early 2024. After excluding 2,052 studies that were not relevant to air transport, 560 studies remained. In the next round, we identified 256 studies focused on investigating air passengers’ environmental attitudes and behaviours. Driven by our goal to identify the most relevant factors that could influence air passengers’ environmental attitudes and behaviours, in the end, we selected the 111 most relevant studies that reveal the factors and their direct and indirect impacts on air travellers’ pro-environmental attitudes and pro-environmental behaviour. Studies that reveal the relationship between attitudes and behaviours, for instance, the attitude–behaviour gap, were also selected. The remaining 145 studies were not focusing on studying the impacts of individual factors or the attitude–behaviour relationship and were therefore out of the scope of our study. Among these 111 most relevant studies, 105 investigate passengers’ attitudes and behaviours regarding general air travel, while the remaining six studies reveal attitudes and behaviours toward adopting novel aircraft, such as drones and electric aircraft. The studies were published as journal articles, PhD dissertations, and book chapters. Figure 2 summarizes the steps involved in the SLR. The results of the SLR are in Section 3, as well as the appendices.

Figure 2 
                  A flow diagram for the selection of relevant studies.
Figure 2

A flow diagram for the selection of relevant studies.

2.3 Semi-Structured Interviews

For the expert interviews, we identified and approached suitable sustainability experts via the professional social media platform LinkedIn, company websites, and our own professional networks. We selected experts from Europe to keep the geographical scope. Various stakeholders belong to the air transport system. Hence, we interviewed a diverse panel to include many points of view. To gain a practical view on the topic, we approached industry experts. Further, we approached academic experts who have also published studies discussed in this article. Out of 81 interview requests, 14 experts agreed to participate in the interviews, leading to an overall response rate of 17.3%. All interviewees were anonymized in this study. Due to geographical barriers, the interviews were conducted using online communication platforms such as Skype, Zoom, Google Meet, and Microsoft Teams. The interviews were conducted between mid-2019 and spring 2020, providing a pre-COVID-19 view. As part of the initial interview request, all experts were informed about the background of the study and provided with contact details about the interviewer and all institute information. Informed consent regarding the use of their interview data was obtained from all individuals prior to the study. All interviews were conducted voluntarily. The interview design was semi-structured (Bryman, 2016), following three sub-sections with a list of leading questions (Qs). All interviews were recorded and transcribed and lasted around 30 min. The interviews were structured as follows:

  1. After an introduction about the interview purpose and aim of this research, the first section started with two open questions, asking for personal and organizational views:

    • Q1: How would you describe the situation of environmental awareness of European air passengers?

    • Q2: What channels and methods are most effective for activating European air travellers’ ecological action?

  2. The second section began with providing the first interim results from the prior literature review on external factors, asking about their experts’ reflections and professional feedback. By giving these interim results, experts were triggered to rethink their points of view and evaluate the first model draft (e.g. whether they agree or disagree and to determine the reason behind each answer):

    • Q3: Which one do you think is the most effective channel (from government, from customers’ intrinsic intention, or social media parties) and why?

    • Q4: Should all the channels mentioned above target the customers with pro-environmental awareness first or target the entire society?

  1. The third section was open (meaning in this context that no specific answers or areas to cover were expected) and adapted depending on the conversation during the interview. After that, the interview was closed.

    • Additional related information from other experts was provided (anonymously) in this section, potentially to trigger more ideas and opinions across all the organizations on the interview list.

    • The interview closed with a review and summary of the experts’ opinions.

2.4 Interview Sample

Seven types of organizations were approached and interviewed: (1) airlines, (2) non-governmental organizations (NGOs), (3) academic organizations, (4) aerospace companies, (5) private transport companies, (6) airports, and (7) other international aviation organizations. Most experts were located professionally in Western and Northern Europe. Out of the total interviewee sample of 14 experts, 29% are female (N = 4) and 71% are male (N = 10), each with different seniority levels (Table 1 for an overview). The results of the interviews will be presented in Section 3.

Table 1

Characteristics of interviewed experts

# Form of organization Seniority level Gender Located in/Country
1 Academia Professor Male Germany
2 Academia Professor Male Finland
3 Academia Research Associate Male Switzerland
4 Aerospace company Research Associate Male Germany
5 Aerospace company Senior Associate Male Germany
6 Aerospace company Senior Associate Male Germany
7 Airline Director Male Germany
8 Airline Research Associate Female Belgium
9 Airport Senior Associate Male Germany
10 International aviation organization Senior Associate Female Belgium
11 NGO Director Male United Kingdom
12 NGO Research Associate Female Sweden
13 NGO/Public consultancy Senior Associate Female Italy
14 Private transportation company Director Male Belgium

3 Results

3.1 Findings from the Literature Review

While 111 studies were initially identified as relevant to the broader topic, only 71 of them explicitly investigated the impact of specific factors on environmental attitudes/awareness (terms used interchangeably in this article) and/or air travel behaviours. The remaining studies were excluded from the analysis because they either lacked empirical examination of such factors or focused on unrelated aspects. Among the 71 studies analysing the impacts of various factors, most collected empirical data using survey-based approaches. The sample sizes of these studies vary between N = 10 to N = 3,998. Qualitative studies based on interviews, focus groups, and lab experiments tend to have smaller samples (maximum 78 in this context), whereas quantitative analyses based on surveys have larger sample sizes (at least 128 in this context). Figure 3 shows that the majority of the studies were published after 2012. Some studies, such as those by Cocolas et al. (2020), Garrard (2013), Markham et al. (2018), Moira and Parthenis (2022), and Sobieralski and Hubbard (2020), were excluded due to undefined sample sizes. Additionally, the study by Mattioli et al. (2023) was based on secondary data analysis. It can also be seen in the scatter plot that sample sizes have increased slightly in recent years, likely due to the proliferation of the Internet, the expansion of data collection tools, and possibly the growing relevance of the topic. The primary study areas included the United Kingdom (UK), Australia, and the United States of America (USA), as shown in Figure 4. Studies like Cocolas et al. (2020) and Garrard (2013) did not specify the study areas.

Figure 3 
                  Sample size of survey-based studies (66 studies).
Figure 3

Sample size of survey-based studies (66 studies).

Figure 4 
                  Amount of published studies per study area (68 studies).
Figure 4

Amount of published studies per study area (68 studies).

Among all 71 studies investigating the relevant factors, the majority (75%) collected empirical data through surveys or secondary sources. Quantitative statistical methods were commonly applied to analyse this data. Main data analysis methods include path analysis, structural equation modelling (SEM), regression analysis, and discrete choice modelling. Following the quantitative data collection and analysis methods, 15% of the studies conducted interviews, focus group studies, or combined surveys with interview studies. Qualitative analysis approaches, such as thematic analysis and comparative analysis, were the predominant methods employed for the qualitative data. Figures 5 and 6 present an overview of the methods applied for data collection and analysis in all 71 studies.

Figure 5 
                  Applied data collection methods (71 studies).
Figure 5

Applied data collection methods (71 studies).

Figure 6 
                  Applied data analysis methods (71 studies).
Figure 6

Applied data analysis methods (71 studies).

In general, our study finds three main aspects that are relevant to air passengers’ environmental attitudes, environmental awareness, and air travel behaviour. These aspects include social-demographic characteristics such as age and income, internal factors that influence behaviour from within the individual, such as knowledge and values, as well as external factors that originate from an individual’s environment and shape behaviour from outside the individual, such as policy intervention and social factors. These factors can directly impact environmental attitude or awareness and air travel behaviours, or they can indirectly drive behaviour changes by affecting attitude and awareness. Figure 7 displays these factors in clusters, differentiating those that have impacts on the environmental attitude, air travel behaviour, or both. For instance, knowledge about climate change can directly affect individuals’ environmental attitudes, thereby influencing their travel behaviours. In other cases, external factors might initially affect individuals’ internal factors or particular sociodemographic groups, subsequently influencing their environmental attitude, awareness, and behaviour. For example, communication and policy strategies can be tailored to address the specific behaviours and circumstances of different demographic groups, taking into account their specific attitudes and behaviours. Based on the SLR, we focused on a few frequently mentioned behaviours and analysed how the factors mentioned above are related to these behaviours. These behaviours include reducing flying, considering flight eco-efficiency when booking, WTP more for carbon offsets, preference for air travel, choice of eco-friendly airlines, flight shame, support of airlines’ environmental policies, and intention to adopt novel aircraft technologies. Additionally, we draw conclusions about how general air travel demand is affected by the relevant factors.

Figure 7 
                  Summary of factors identified through the SLR.
Figure 7

Summary of factors identified through the SLR.

3.1.1 Social-Demographic Factors

3.1.1.1 Age

Studies have found that environmental attitudes and behaviours differ across age groups, and the findings vary by study area. Davison et al. (2014), Niu et al. (2016), and Ryley et al. (2013) find that younger people tend to have stronger environmental attitudes, while Çabuk et al. (2019) indicate an opposing result that older passengers are more environmentally concerned. Some studies find that younger people also tend to be more willing to pay for carbon offset (Blasch & Farsi, 2014; Cordes et al., 2024; Lu & Shon, 2012; Segerstedt, 2015) and have relatively higher intentions to reduce flying than older people (Hansmann & Binder, 2021). Meanwhile, younger age groups seem to be affected more by their personal norms and therefore have stronger intentions to adopt novel eco-friendly aircraft (Han et al., 2019c). However, Shaari et al. (2020) draw a different conclusion and indicate that WTP for carbon offset increases with increasing age. Nevertheless, older people tend to fly less (Graham & Metz, 2017; Mattioli et al., 2023; O’Garra & Fouquet, 2022). Moreover, middle-aged passengers tend to care about the eco-efficiency of the flight when booking (Araghi et al., 2016).

3.1.1.2 Gender

Consistent conclusions have been drawn regarding how environmental attitudes and behaviours differed between males and females. In general, females tend to have stronger environmental attitudes or respond more positively to environmental issues (Çabuk et al., 2019; Ryley et al., 2013). Moreover, female travellers are more likely to have a higher WTP for carbon offset or air ticket tax (Choi & Ritchie, 2014; Rotaris et al., 2020; Sonnenschein & Smedby, 2019), and they also intend to reduce flights more than males (Hansmann & Binder, 2021). In addition, Chen et al. (2011) and Hwang and Choi (2018) indicate in their studies that females are more engaged in green travel behaviours in general.

3.1.1.3 Income

A few studies state that passengers with higher incomes are generally associated with more travel by air (Enzler, 2017; Graham & Metz, 2017; Mattioli et al., 2023). However, studies such as Çabuk et al. (2019) state that high-income groups tend to have positive attitudes toward green airline operations. In the study of Ryley et al. (2013), respondents with higher incomes stated that they try to fly less for environmental reasons. Shaari et al. (2020) and Cordes et al. (2024) also find a higher WTP to offset carbon emissions for higher-income people.

3.1.1.4 Education

A few studies that find education level influential reveal the consistent result that people with higher education levels have stronger environmental attitudes (Chen et al., 2011) and are more willing to pay for carbon offset (Cordes et al., 2024; Rotaris et al., 2020; Shaari et al., 2020).

3.1.1.5 Employment

Rotaris et al. (2020) and Shaari et al. (2020) also find a significant relationship between employment status and WTP for carbon offset. They both indicate that people holding jobs are more willing to contribute to carbon offsetting donations.

3.1.1.6 Other Social-Demographic Factors

Furthermore, two studies conclude that having children in the household has an impact on stronger environmental attitudes (Ryley et al., 2013) and reducing air travel (Enzler, 2017). In addition, migrants (Mattioli et al., 2023), urban residents (Mattioli et al., 2023), and people living closer to the airport (particularly the large ones) (Enzler, 2017) seem to fly more. Further, passengers’ awareness of climate change and the supportiveness of airlines’ environmental policies differed across their nationalities or country of residence (Higham et al., 2014; Niu et al., 2016).

3.1.2 Internal Factors

3.1.2.1 Frequency of Flying

With regard to air passengers’ flying frequency, the more frequently they fly, the less likely they are to state strong environmental attitudes (Ryley et al., 2013), and the less likely they are to pay air ticket tax or carbon offset donations (Rotaris et al., 2020; Sonnenschein & Smedby, 2019). In contrast, as flying is not relevant to people who do not fly, they reported a higher willingness to undertake flight reduction sacrifices (Kantenbacher et al., 2018).

3.1.2.2 Business Travellers

Business travellers are often frequent travellers. Therefore, their environmental attitudes and behaviours received attention as strong levers. Nevertheless, although knowledge workers generally tend to be aware of environmental issues, no connection is found between their environmental attitude and their actual travel behaviour (Lassen, 2010; Schmalz et al., 2021a). Meanwhile, Rotaris et al. (2020) conclude that business travellers tend to have a lower value of carbon offset donations.

3.1.2.3 Knowledge

Two aspects of knowledge are found to affect passengers’ attitudes and behaviour change. First, whether people have adequate knowledge about the environmental footprint of air transport is positively linked to awareness of air travel impacts and attitudes towards air travel (Becken, 2007; Chen et al., 2011). Moreover, more knowledge about air travel leads to “flight shame” and reduced flying (Chiambaretto et al., 2021; Garrard, 2013; Jacobson et al., 2020). The other aspect is knowledge about environmental policies and measures, such as carbon offsetting. Studies show that the more knowledge passengers have about carbon offsetting, the more they are willing to offset their flights (Babakhani et al. 2017; Denton et al. 2020; Kim et al. 2014; Kim et al., 2016; Zhang, 2021). Similarly, adequate knowledge about global climate change policies forms stronger beliefs about the effectiveness of those policies (Ritchie et al., 2020).

3.1.2.4 Personal Moral Norms

Multiple studies confirm the critical role of personal moral norms and a sense of social responsibility in increasing awareness and changing attitudes and behaviours. Studies indicate that people with stronger moral norms and a sense of social responsibility tend to reduce travel by air (Büchs, 2017; Gössling et al., 2019; Jacobson et al., 2020; Whitmarsh et al., 2020) and are more likely to be willing to compensate for the emissions and pay air ticket tax (Brouwer et al., 2008; Sonnenschein & Smedby, 2019; van Birgelen et al., 2011). In a study by Han et al. (2019b) focusing on passenger adoption of electric aircraft, results indicate that stronger moral norms also increase the intention to adopt electric aircraft.

3.1.2.5 Other Internal Factors

In addition, two previously mentioned studies reveal that factors such as perception of the severity of CO2 emissions, the perception that individual efforts can reduce CO2 emissions, and sense of social embeddedness positively influence participation and WTP for voluntary carbon offsetting (Brouwer et al., 2008; Kim et al., 2014; van Birgelen et al., 2011). Having efficacy beliefs that avoiding air travel contributes to climate change mitigation and intergenerational justice concerns may contribute to reducing air travel (Berneiser et al., 2022). Furthermore, other groups of people, such as those with stronger self-identity and with high commitment to the environment in the home environment, also have stronger motivation to reduce the potential impacts of flying on the climate (Barr et al., 2011b; Morten et al., 2018; O’Garra & Fouquet, 2022). Moreover, flying habits, attachment to eco-friendly products, and trust in new mobility technology are considered powerful predictors of air travel intentions and intentions to adopt eco-friendly aircraft (Fu & Moeckel, 2024; Han et al., 2019a, b; Hansmann & Binder, 2021).

In contrast, the perceived sacrifice of, for instance, comfort and convenience negatively influences air passengers’ intention to adopt some green practices (e.g. check-in online) (Wong et al., 2020). Meanwhile, dispersed social networks (Mattioli et al., 2023) and global social interconnectedness and international experience increase travel to visit friends and family and, therefore, increase flight kilometres (Oswald & Ernst, 2021).

3.1.3 External Factors

3.1.3.1 Information About the Environmental Impacts of Air Travel

Information, education, and policy intervention have been found to affect air passengers’ behaviours. Providing adequate, transparent, and tailored information helps passengers gain knowledge about air travel impacts (Baumeister & Onkila, 2018; Breen & Pensini, 2022; Cocolas et al., 2023; Lu & Wang, 2018). Further, this increased awareness drives the change in behaviours, for instance, stronger support for institutional policies to reduce flying (Whitmarsh et al., 2020), increase willingness to offset flights (Lu & Wang, 2018; Zhang et al., 2019a, b), and even reduce preference for air travel (Raux et al., 2021).

3.1.3.2 Subjective Norms

Subjective norms or social norms refer to the perception of other people’s opinions of how the individual should behave (Ham et al., 2015). Social surroundings can affect behaviours by impacting individuals’ personal norms (Han et al., 2019c) or can directly motivate behaviour change due to “peer pressure.” For instance, people affected more by social norms tend to have stronger intentions to reduce air travel (Büchs, 2017; Busche & Sargisson, 2020; Cocolas et al., 2020; Cocolas et al., 2021) and to offset the carbon emissions of their flights (Ritchie et al., 2020). Meanwhile, Morten et al. (2018) and Cohen et al. (2011) also found that social norms help promote motivation to reduce leisure or holiday air travel.

3.1.3.3 Tax and Carbon Pricing

The impacts of monetary measures taken by the government, such as fuel tax and its reflection on the ticket price, have been found to be different across studies. One study conducted by Becken (2007) confirms that the air travel tax effectively restricts air travel. Other studies, on the contrary, find no evidence or a weak impact on reducing air travel demand (Markham et al., 2018; Sobieralski & Hubbard, 2020; Wild et al., 2021).

3.1.3.4 Other External Factors

Chuah et al. (2020) highlight that corporate social responsibility (CSR) is positively linked to consumers’ environmental concerns and green trust, which Chen and Chang (2013) define as the willingness to depend on a product or service based on the belief in its credibility, benevolence, and ability regarding environmental performance. Similarly, university sustainability policies affect academic air travel (Glover et al., 2018; Schmidt, 2022; Wenger, 2023). Several studies also mentioned the positive impact of the green image of an airline on passengers’ intentions to fly with that airline and their WTP (Busche & Sargisson, 2020; Hwang & Lyu, 2020). Moreover, other social factors, such as family commitments (Whitmarsh et al., 2020) and the behaviour of celebrities (Gössling, 2019), can also be significant predictors of flying behaviours. In addition, drastic events like the COVID-19 pandemic are seen as a catalyst for re-evaluating and possibly reshaping the air travel industry and tourism sectors to tackle immediate health issues and achieve long-term goals of environmental sustainability. (Kallbekken & Sælen, 2021; Manca et al., 2023; Moira & Parthenis, 2022; O’Garra & Fouquet, 2022). However, O’Garra and Fouquet (2022) highlight the urgent need to confront affluent consumption habits and to use the present momentum to foster travel behaviour change.

Table 2 summarizes the statistics of the major influential factors. Overall, a preponderance of studies has found demographic characteristics of individuals, such as age and gender, followed by personal moral norms and responsibility. Moreover, multiple studies confirm a significant relationship between how much people know about the environmental impact of air travel and whether people would change their behaviours. The knowledge people gain regarding air travel impact and carbon offsetting also depends on how much relevant information they receive. Meanwhile, a few studies also confirm that people tend to be affected by the environmental attitudes and behaviours of their social circles due to the so-called “peer pressure.” Additionally, income and education, purpose and frequency of flying, as well as the airlines’ images, have been identified as relevant factors in several studies. Moreover, the significant impact of the COVID-19 pandemic has been confirmed by the most recent research.

Table 2

Statistics of the main influential factors

Category Factor Number of studies per factor Number of studies per category % Of studies per category % Of all studies p-Value (within category) p-Value (across categories) p-Value (across factors)
Demographic Age 16 22 72.7 22.5 0.03 0.33 0.01
External Information about the environmental impacts of air travel 8 29 27.6 11.3 0.23
Internal Personal moral norms and social responsibility 8 33 24.2 11.3 0.48
Demographic Gender 8 22 36.4 11.3 0.03
Demographic Income 7 22 31.8 9.9 0.03
External Subjective norms 7 29 24.1 9.9 0.23
Internal Knowledge of air transport footprint 5 33 15.2 7.0 0.48
Internal Knowledge about carbon offsetting 5 33 15.2 7.0 0.48
Demographic Education 4 22 18.2 5.6 0.03
External COVID-19 4 29 13.8 5.6 0.23
Internal Frequent flyers 3 33 9.1 4.2 0.48
Internal Business travellers 3 33 9.1 4.2 0.48
External Green image of an airline 2 29 6.9 2.8 0.23

We performed chi-square goodness-of-fit tests to gain further insights into the relevance of all factors. First, the chi-square test across categories indicates that all categories are equally relevant (p = 0.33). In contrast, the chi-square test across all factors indicates that certain factors have been examined more frequently than others (p = 0.01). Post-hoc binomial tests reveal that only age has been studied to a degree that significantly exceeded chance. Across the full sample of 71 studies, age appeared in 16 cases (p = 8 × 10−5), and within the 22 demographic-focused studies, it appeared in 16 (p = 0.0095). Nevertheless, there is no strong evidence indicating that the remaining factors have been investigated more often than others.

Moreover, it is worth noting that the studies we selected were conducted in different countries or regions. Therefore, the impact of various cultures and values could be relevant and can be further studied based on a larger sample in an international context. Appendix A provides a detailed summary of all influential factors revealed by the SLR.

3.1.4 Attitude–Behaviour Gap

To further understand the association between environmental attitude/awareness and relevant air travel behaviours, we focus on analysing 58 studies that highlight the relationship between attitudes and behaviours. Interestingly, we observe that different conclusions have been drawn.

Out of 58 studies, 19 studies (33%) confirm the strong association between passengers’ environmental attitudes, consciousness, or concerns on their behaviour changes, such as intentions to reduce flights, preference for eco-friendly airlines, intentions to take voluntary climate actions (e.g. participate in voluntary carbon offsetting), support for aviation climate policies, adoption of eco-friendly electrified aircraft, and other sustainable engagement behaviours (Ahmed et al., 2021; Bakır, 2024; Barr et al., 2011b; Baumeister, 2015; Breen & Pensini, 2022; Busche & Sargisson, 2020; Choi et al., 2016; Chuah et al., 2020; Garrow et al., 2020; Graham & Metz, 2017; Haddad et al., 2020; Hansmann & Binder, 2021; Kantenbacher et al., 2018; Mair, 2011; Ritchie et al., 2021; Rotaris et al., 2020; Seegebarth et al., 2024; van Birgelen et al., 2011; Zhang, 2021).

The remaining 39 studies (67%) show different results; 11 studies find that environmental attitude is not always a reliable indicator of behaviour, or there is no association between environmental attitude/awareness and actual air travel behaviour change for both business and leisure travel. (Aasen et al., 2023; Alcock et al., 2017; Barr et al., 2011a; Buckley, 2011; Davison et al., 2014; Lassen, 2010; Mayer et al., 2012; Morten et al., 2018; Oswald & Ernst, 2021; Reis & Higham, 2017; Wynes et al., 2019). Furthermore, 28 studies confirm the gap or inconsistency between attitude and behaviour. Earlier studies already acknowledge the general attitude–behaviour gap in human behaviours (e.g. Blake, 1999; Gross & Niman, 1975; Kollmuss & Agyeman, 2002). In terms of air travel behaviours, researchers find two types of inconsistencies: first, a gap between environmental attitudes, awareness, values, or beliefs and actual behaviours, particularly in the tourism sectors (Cohen et al., 2013; Denton et al., 2020; Dickinson et al., 2013; Hares et al., 2010; Hibbert et al., 2013; Higham et al., 2015; Jurjonas & Aldana, 2020; Kroesen, 2013; Lu & Wang, 2018; Schmalz et al., 2021a; Sonnenschein & Smedby, 2019; Tölkes, 2020); second, a significant gap between general environmental behaviour and pro-environmental air travel behaviour (Chen et al., 2011; McDonald et al., 2015).

The differences between the findings summarized above could be attributed to various factors such as study area, sample size, and analysis methodology. Focusing on the means of data gathering, the significant p-value of the statistical test gives us reason to believe that the study results are affected by the applied methods. As shown in Table 3, all studies confirming a direct impact of environmental attitude or awareness on air travel behaviour have collected and analysed primary survey data. In contrast, among the studies indicating some inconsistent findings, almost 40% of them conducted interviews or focus group studies, which provide opportunities to gain a more thorough understanding and make interpretations concerning factors that cannot be observed through questionnaires, such as respondents’ feelings and emotions. This finding could be further investigated in future studies by comparing results obtained using different methods in the same study area. Appendix B provides a more detailed summary of all 58 studies.

Table 3

Methods applied to analyse the attitude–behaviour relationship

Applied method Study result
Studies that confirm a direct impact of environmental attitude/awareness on air travel behaviour (N = 19) [%] Studies that reveal an attitude–intention gap or a non-direct impact of environmental attitude/awareness on air travel behaviour (N = 39) [%]
Survey-based quantitative method 100 41.0
Interview-based qualitative method 0 38.5
Qualitative conceptual and theoretical study 0 10.3
Secondary-data-based quantitative method 0 7.7
Mixed method 0 2.6

Fisher’s exact test: p-value = 9.391 × 10−5.

3.2 Findings from Interviews

Turning from our systematic literature review to our research, we will address the interviews first. Our expert interviews confirm some of the external factors explored above. Overall, we identify three main driving forces: governments, airlines, and social movement groups. The interview findings below are divided into three sections, presenting viewpoints representing these three groups.

From the governmental viewpoint, the experts suggest that governments should invest more in Research and Development (R&D) in sustainability. Governments should regulate the energy label with CO2 emissions on flight tickets. It is an essential step to educate the public about the scale of the negative impact of greenhouse gas emissions by aviation (GHG-A). Besides, governments should tax fuel and reflect it on the ticket price, as multiple experts point out that most flight tickets are unreasonably low. That gives the public the wrong impression that there is only a minor environmental impact when travelling by air.

Governments should utilize the media as a communication tool for all the target audience types. Content should clarify how the tax the passenger pays in turn pays for fuel, creating more transparency for the passenger, providing GHG-A emission information, and encouraging the use of alternative transportation modes. Besides, the government should also regulate flight booking sites to display the GHG-A emission of each flight.

Furthermore, consistency is the key factor in minimizing the environmental attitude–behaviour gap. The government should consistently provide transparent information to the public, as many experts point out that human memory about the environmental impact is short. If the information is only provided periodically, the effectiveness of minimizing the attitude–behaviour gap is limited.

Last, information to educate the public is mentioned by almost 100% in response to Question 2 (What channels and methods are the most effective for activating European air travellers’ ecological action?). Interestingly, one of the experts mentions the importance of integrating the environment as a topic into the mandatory curriculum in the educational system. The positive impact of education can be significant over time. It is critical to educate children about nature and the importance of environmental consciousness from an early age. In the long run, the effectiveness of this approach is likely to be higher than attempting to re-educate adults, as the status quo has been established. Furthermore, the expert pointed out that children can often educate their parents about the topic more effectively than any external educational measure.

The importance of airlines’ efforts in changing consumer behaviour is noted 100% of the time. However, experts from non-airline organizations are sceptical about the effectiveness of programs for offsetting emissions and whether they can change consumer behaviour, as offsetting has no direct relationship with reducing GHG-A emissions. Some experts even perceive offsetting as a “distraction” and “white lie,” misleading the public into believing they can compensate for their GHG-A footprint by paying a small fee, which is a delusion that the environmentally negative impact can be easily erased. Overall, offsetting schemes are not seen as an effective, long-term way to change consumer behaviour but merely to trigger awareness. Given the extensive literature on offsetting, its actual effect should be reconsidered.

In fact, according to the interviewees, airlines should rework the entire purchase journey of the flight ticket. Airlines should always provide information about each flight’s emissions. At the time of this research, in most cases, the data are provided within the confirmation email after the booking process. Presenting the information about emissions before finalizing the booking would give passengers at least the opportunity to reconsider the necessity of flying – especially domestic flights within Europe. After reading the information about GHG-A emissions, offsetting should be set as the default and opt-out option during the booking process to increase awareness.

Alongside offsetting, there are multiple approaches that airlines can adopt to raise environmental awareness and possibly change consumer behaviour. The media can be used as an intermediary to communicate with the public. Adopting media as a channel is mentioned by 43% of the experts during the interview. First, accurate information should be provided in the in-flight magazine. Several experts indicate that there is no standard calculation of GHG-A emissions, and airlines typically underestimate the GHG-A of each flight intentionally. Therefore, providing accurate details on GHG-A emissions can be a practical approach to minimizing the attitude–behaviour gap. More than half of the experts interviewed argue that the unrealistically low-cost flight deals should be banned. Ticket price competition among airlines has been on-going for decades. Most experts point out that airline operators use price as a strategy to create a competitive advantage over others and to indirectly convey the wrong message to the public that environmentally harmful externalities, such as flight emissions, are free. Banning unrealistic deals and rethinking the competitive strategy to include environmental concerns could be a viable solution. Business operations should be combined with taking care of social responsibilities by sending direct and indirect messages about the environmental impact of air travel to the public. Doing so can benefit the reputation of airline operators themselves and gain support from the public.

All in all, information is the key to triggering environmental behaviour change among air travellers. Airlines should ensure that the information about GHG-A is conveyed correctly and consistently, as our interviews identify misinformation and a lack of education as the primary causes of the environmental attitude–behaviour gap. It is essential to keep in mind that information about GHG-A emissions should be clear and precise.

Interviewees mention social movements as driving forces in more than half of the interviews. Experts from different organizations mention Greta Thunberg, Extinction Rebellion, and the flygskam (flight shaming) phenomenon, which have gained momentum in recent years. Social activities indeed have the advantage of triggering environmentally friendly behaviour change. As the literature reviews show, governmental intervention is the most effective way to activate environmental behaviour change and mitigate the attitude–behaviour gap. However, several experts mention that social movements have a more significant impact on society and a better chance of changing air travellers’ behaviour. These public figures actively disseminate relevant information about GHG emissions, potentially influencing the public. The values, concerns, and movements aimed at fighting climate change are effectively spread through media channels. Notably, the power of peer-to-peer communication is significant on all kinds of social media platforms. Initially, the target audiences of some social movements are primarily younger generations. Recently, however, raising environmental awareness and changing consumer behaviour influenced by these environmental social movements have been observed across all age groups within Europe. They convey a powerful message addressing the urgency of solving environmental issues and climate change, capturing the public’s attention along with that of international organisations and governments. Experts point out that these environmental social movements are one of the forces driving the improvement of environmental awareness and behaviour change over the past few years. All generations are paying more attention to climate change and are more conscious about travelling and their lifestyle.

Conversely, some experts express concerns about the environmental groups mentioned. Their basis of information might be biased because it is emotionally charged and sometimes only familiar with a partial context of the related topic. Although the role of social movements is debatable and contradictory, they still play a vital role in addressing the issue and influencing policies.

3.3 Formation of a Conceptual Model

Overall, the expert interviews confirm the findings from the SLR, particularly regarding the impacts of external measures on attitudes and behaviour change. These measures include fuel tax, educating the public, providing emissions information, and social movements. Complementary to the SLR results, the experts highlight governments, airlines, and social movement groups as three major parties driving these marketing and policy interventions. Besides economic measures and educating the public to improve environmental awareness, the government is expected to provide more transparent information about emissions, as do the airlines. Extending the findings from the SLR, the experts also point out the relevance of and issues with low air ticket prices, which convey the wrong message and lead to people’s underestimation of the environmental impacts of air travel.

Moreover, extensive studies consider passenger support of carbon offsetting to be an environmentally friendly action. Although the effectiveness of carbon offsetting is questioned by the experts during our interviews, evaluating that issue is outside the scope of this study. Finally, despite potential emotional bias, interviewees emphasise the importance of social movements, which aligns with the relevance of social norms revealed by the SLR. Based on insights from the SLR and expert interviews, a conceptual model is developed and shown in Figure 8. The model explicitly clarifies how various factors interact and influence traveller decisions and highlights the prevalent attitude–behaviour gap in aviation. The primary purpose of the model is to enhance clarity and mutual understanding among key stakeholders, including policymakers, airlines, social movement groups, NGOs, and passengers themselves. By explicitly identifying the relationships and responsibilities associated with each factor, this model provides a shared framework to guide collaborative efforts towards more effective interventions and targeted policy measures aimed at bridging the attitude–behaviour gap in aviation. The model depicts the main external and internal drivers of passengers’ environmental awareness, some of which might influence behaviour directly (e.g. monetary measures) or indirectly via increasing awareness (e.g. education). For instance, raising awareness with external strategies (e.g. marketing campaigns) is a topic of education and transparency, and passengers need more information to make an informed decision (e.g. via eco-labels, transparent information on emissions within the booking process). Strategies need to be targeted toward different segments according to the demographic characteristics or travel patterns (e.g. young passengers, business passengers) and relevant internal factors (e.g. norms, knowledge). Social media could be a mediator providing channels to influence passengers’ decisions.

Figure 8 
                  Final conceptual model of factors influencing environmentally friendly air travel.
Figure 8

Final conceptual model of factors influencing environmentally friendly air travel.

The model emphasises the gap between environmental awareness/attitudes and behaviour or behavioural intention, the latter often considered a proxy for actual behaviour (Ajzen, 1991). To narrow the attitude–behaviour gap, measures should be implemented to enhance awareness and simultaneously foster behavioural change. The proposed strategies include

  • Government and policy Interventions: These include a range of measures from “soft” regulatory efforts like social marketing and public health campaigns to “hard” policy measures such as taxation, caps on emissions, and inclusion of aviation in emissions trading schemes. The necessity of government action to achieve radical emissions reductions is emphasised, suggesting a belief in the insufficiency of voluntary measures alone to induce significant behavioural change. (Eijgelaar, 2011; Gössling & Peeters, 2007; Higham et al., 2016; Mkono, 2020). Policies should not only aim to reduce overall emissions but also consider the varied ways individuals contribute to transport emissions. (Mattioli et al., 2023) To operationalize these goals, a phased approach could be implemented: in the short term, governments could launch national campaigns highlighting the climate impact of aviation, maintaining continuous visibility across television, digital media, and public spaces. In the medium term, mandatory eco-labelling of flight options displaying CO2 emissions at the point of ticket purchase could enable more informed consumer choices. In the long term, for example, progressive ticket taxation based on travel distance and emissions class could be introduced.

  • Improving the carbon offsetting framework: Measures proposed include enhancing the credibility and transparency of carbon offsetting schemes, integrating offset options more seamlessly into booking processes, and considering mandatory offsetting. The need for offsetting schemes to follow consistent standards for validation and verification is highlighted to build trust among consumers (Eijgelaar, 2011; Gössling et al., 2009). It requires collaboration between governments and regulatory bodies, airlines, and carbon offset providers. All offset projects offered should be certified by recognized third-party standards. Nevertheless, Eijgelaar (2011) addresses the importance of prioritising reduction over offsetting.

  • Educational efforts: The need for improved education and transparent communication tailored to specific demographics (such as female consumers and younger generations) regarding the environmental impacts of air travel and the potential actions to mitigate these effects. This includes education campaigns to inform about aviation’s climate impacts and the promotion of eco-labels for ticket purchases to aid consumers in making informed decisions. (Büchs, 2017; Eijgelaar, 2011; Gössling & Peeters, 2007; Gössling et al., 2009; Mkono, 2020) Joint efforts are expected from governments, educational institutions, environmental organizations (such as NGOs), airlines, and social influencers. A multi-level approach to education could be particularly impactful: on a fundamental level, basic knowledge of climate change and the environmental consequences of transportation, including air travel, should be implemented into primary and secondary school curricula. In higher education institutions, collaborative projects with NGOs, airlines, and travel platforms could facilitate the development of serious games and short online courses, offering certificates or rewards to encourage participation. On a third level, environmental education should become a standard requirement within professional training programs, particularly targeting frequent flyers, corporate travel managers, and the tourism industry workforce.

  • Industry initiatives: A more comprehensive response is expected from the aviation industry to the changing market attitudes, focusing not only on the development of more sustainable practices, such as more fuel-efficient aircraft, alternative fuels, and operational improvements (Eijgelaar, 2011; Higham et al., 2016; Mkono, 2020) but also on actively promoting transparency and incentivizing environmentally conscious behaviour among passengers. As a first step, airlines should publicly disclose per-flight CO2 emissions both during the booking process and at check-in counters to enhance consumer awareness and enable informed travel decisions. In an additional step, loyalty programs could be redesigned to reward passengers for selecting lower-emission flight options, such as routes operated by newer and more fuel-efficient aircraft. In the long run, the industry is encouraged to invest in and promote the development of innovations in aviation technologies, while communicating progress and associated challenges transparently to the public.

  • Promotion of behavioural and structural changes: Suggestions include promoting alternatives to air travel, such as train travel, and encouraging individual responsibility and moral obligation towards reducing air travel’s environmental impact. This is also related to institutional changes to support sustainable travel practices within academic and professional contexts (Büchs, 2017; Eijgelaar, 2011; Mkono, 2020; Schrems & Upham, 2020). Governments, businesses and corporations, academic institutions, environmental organizations (such as NGOs), and the transportation industry (notably the rail sector) are critical actors in facilitating this transition. For example, the integration of multi-modal booking systems that allow users to seamlessly combine air and rail travel within a single platform should be prioritized, making lower-emission alternatives more visible and convenient. Generally, sustained lobbying and investment in high-speed rail infrastructure are necessary, especially in regions where rail could serve as a realistic substitute for flights under a certain distance.

  • Psychological and sociocultural interventions: This includes addressing eco-anxiety and guilt associated with air travel through research into psychological dynamics and developing evidence-based coping strategies. Additionally, there is a focus on changing social norms and expectations related to air travel and promoting values of self-transcendence and self-direction towards more sustainable travel behaviours. (Büchs, 2017; Cocolas et al., 2020; Mkono, 2020) This requires joint efforts from academic researchers and psychologists, environmental organizations (such as NGOs), government, educational institutions, and social influencers. To start shifting fixed social norms, targeted campaigns could be launched by NGOs, companies, and the government to showcase that reducing air travel is a common and respected behaviour among admired groups, such as thought leaders, athletes, celebrities, and others.

In general, joint efforts from various stakeholders – including policymakers, the aviation industry, NGOs, and academics – are needed to implement a holistic approach that combines policy, educational, technological, and sociocultural strategies to effectively reduce the attitude–behaviour gap.

4 Discussion, Limitations, and Further Research

Increasing public awareness of climate change and sustainability has placed substantial pressure on the aviation sector to reduce CO2 emissions. While passengers increasingly prefer environmentally responsible products and services (Rennollet et al., 2020), their actual behaviour depends significantly on their trust in airlines’ environmental performance. Despite airlines’ engagement in sustainability movements such as B Corp certification (Honeyman & Jana, 2019), Economy for the Common Good (Felber, 2012), or Conscious Business practices (Mackey & Sisodia, 2013; Stahlhofer et al., 2018), consumer scepticism remains, largely due to concerns about greenwashing (Gatti et al., 2019).

External shocks, notably the COVID-19 pandemic and the war in Ukraine, severely disrupted global aviation from 2020 onwards, drastically reducing international flights and shifting climate discussions temporarily into the background. Yet, these disruptions also demonstrated clear environmental benefits associated with reduced travel, such as improved air quality and clearer waters. As travel rebounds, it remains unclear whether these changes will sustainably influence travel behaviours or if the rebound in demand and resumed business travel will widen the existing attitude–behaviour gap. For instance, the pandemic-induced normalization of video conferencing suggests a potential long-term reduction in business flights, but further research is necessary to confirm long-term shifts in travel behaviours.

Gössling and colleagues have extensively analysed why pro-environmental attitudes often fail to translate into reduced flying (Gössling & Dolnicar, 2023; Gössling et al., 2009; Gössling et al., 2019; Gössling, 2019; Gössling, Humpe & Bausch, 2020; Hibbert et al., 2013; Ritchie et al., 2020). Their research identifies normative levers, such as flight-shame campaigns, and economic interventions like carbon offsets and taxes to address this gap. Flight-shame campaigns led to modest and context-dependent reductions (8.7% in Sweden, 3.7% in Germany) (Gössling, Humpe & Bausch, 2020), whereas voluntary carbon offsets had limited uptake (∼5%) (Gössling et al., 2009). Gössling and Dolnicar (2023) argue for embedding offsets as defaults and applying pricing signals to achieve robust behavioural change. While Gössling et al. (2009) suggest better information alone might boost uptake, Ritchie et al. (2020) emphasize the necessity of combining information with policy measures (e.g. defaults or mandates). These different outcomes may result from differences in data collection (self-reported versus revealed behaviours), timeframes (cross-sectional versus longitudinal), and research contexts (limited media exposure versus broader regulatory contexts). Future mixed-method research across varied contexts is essential to clarify lasting drivers of behavioural change across different contexts.

The studies by Gössling and colleagues discussed some strategies such as opt-out offsets during booking, carbon pricing and taxes, carbon labels and low-carbon defaults, and identity-based messaging that frames a desired behaviour. Yet the evidence also shows that no single lever suffices. As presented above, social-norm campaigns and voluntary offsets achieve only modest, context-specific effects. Our findings address that single interventions are insufficient. A hybrid approach combining normative (social campaigns) and structural measures (defaults, labelling, pricing) offers greater promise by making sustainable choices simpler and more automatic. Furthermore, transparent communication about environmental impacts and mitigation measures is crucial for fostering consumer trust. Governments should mandate transparent reporting of airline emissions and fuel performance, backed by stringent regulations.

Furthermore, as highlighted consistently by existing literature and expert insights, the attitude–behaviour gap represents a critical challenge for sustainable aviation. We conclude that the gap is influenced by a complex interplay of individual-related factors, including personal knowledge, economic barriers, scepticism about individual impact, and resistance to change. Structural constraints, lack of supportive policies, and cultural norms also widen this gap. To effectively narrow the gap, a comprehensive approach is required, necessitating collaborative efforts from diverse stakeholders such as policymakers, the aviation industry, NGOs, and academics. Such an approach should combine targeted policy measures, educational initiatives, technological advancements, and sociocultural strategies. Based on our SLR and recurring research gaps identified across studies, we propose a focused agenda for future research that targets further reducing the attitude–behaviour gap in sustainable air travel. First, future research should urgently investigate the psychological mechanisms that sustain unsustainable air travel behaviour. There is an urgent need to bridge behavioural theory and policy by extending existing frameworks (such as the Theory of Planned Behaviour) to explicitly incorporate understudied factors like habit, emotion, identity, cognitive dissonance, and moral licensing, which have been shown to mediate environmentally relevant decisions but remain underexplored in aviation research. Understanding these drivers can support the development of evidence-based interventions, including identity-based messaging or opt-out offset defaults. Second, methodological advances are required, particularly through rigorous field experiments on offset-scheme designs, longitudinal tracking of passenger perceptions of trip necessity, and mixed-method studies that combine behavioural data with systematic assessment of institutional, political, and media-trust influences. (Gössling & Dolnicar, 2023; Gössling et al., 2009; Ritchie et al., 2020) Last but not least, it is critical to evaluate the impact of external disruptions over time. Research should investigate whether drastic events like COVID-19 induce temporary or lasting shifts in aviation demand, individual attitudes, and social norms (such as “flight shame”). Although initial studies have been conducted, it remains unclear whether behavioural shifts induced by the pandemic or other disruptions are temporary or permanent. Clarifying this is essential for designing durable policy and communication strategies.

The research presented here is subject to some limitations. First, the proposed conceptual model was developed based on a detailed literature review and expert interviews. However, it has not yet been empirically validated. A next step to verify the model using quantitative testing, e.g. via a customer survey, is recommended. Meanwhile, the expert interviews were conducted between mid-2019 and spring 2020, and thus may not reflect the most current perspectives in the field (e.g. considering the election of Trump in 2025). Nevertheless, the insights gained from these expert interviews still serve to validate and complement the findings of the literature review, ensuring that the conclusions drawn are both substantiated and enriched by experienced viewpoints.

We are still in the age of eco-efficiency and sustainability strategies. At best, these efforts lead to less damage to the environment than before. Nevertheless, there are still negative environmental influences, and in this respect, even sustainability strategies do not lead to improvement in the ecological situation. (Demastus & Landrum, 2024). By contrast, if humans behaved according to the eco-effectiveness criteria, the deterioration of the ecological situation would stop. “Cradle-to-cradle” (McDonough & Braungart, 2002), “net positive” (Polman & Winston, 2021), or paradigms of regenerative business (Landrum, 2018) are groundbreaking concepts that support positive changes. The aviation industry, however, is among the most difficult industries to decarbonize due to technological and regulatory challenges and long product circles. Sustainable aviation fuel, as it is increasingly being used, can be an interim solution and requires a ramp-up to be applied broadly. As mentioned earlier, new types of aircraft, such as hydrogen or electric aircraft, can contribute to a vision for the future long term.

5 Conclusion

Passengers’ behaviour change is a significant contributor to achieving the goal of climate impact reduction. Various internal and external factors can be strong levers that influence the change in awareness and behaviour. This study conducts a SLR (N = 111) and expert interviews (N = 14) to summarize relevant factors that can influence individuals’ air travel behaviour. Based on the literature review, we conclude the relevance of individuals’ demographic characteristics (such as age and gender), personal moral norms, and knowledge about the impact of air travel and carbon offsetting. Given the limited research on how external factors, such as policy and information, might affect decisions, we interviewed experts who highlighted the importance of education and providing transparent information regarding the impact of air transport. Meanwhile, three main parties are identified as driving forces within the model: government, airlines, and social movements. Based on the insights we gained from the literature review and the interviews, we propose a model to conceptualize the potential relationship between social-demographic characteristics, internal factors, external factors, environmental attitude/awareness, and air travel behaviours. The proposed conceptual model provides room for many strategies and opportunities for stakeholders to influence passengers to make more environmentally friendly travel decisions. Although quantitative confirmation is needed, our analysis suggests that the media is a suitable mediator. Strategy efforts and campaigns should also be targeted at passenger segments.

Overall, numerous studies have been carried out in the community. Greener flying should be at the top of the agenda of the aviation industry and governments, and passengers are one key to achieving this goal. We urge policymakers and aviation stakeholders to take action now, foster consumers’ trust, and support passengers in making greener travel choices using a hybrid approach of various effective levers.


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Acknowledgments

We would like to thank the anonymous reviewers for their valuable comments and suggestions, which helped to improve the quality and clarity of this article.

  1. Funding information: Authors state no funding involved.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. MF: conceptualization, methodology, formal analysis, writing – original draft, writing – review & editing, visualization; US: conceptualization, writing – original draft, writing – review & editing, visualization; K-N T: conceptualization, methodology, formal analysis, writing – original draft; CS: conceptualization, resources, writing – original draft, writing – review & editing.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability statement: All data generated or analysed during this study are included in this published article and its supplementary information files.

  5. Article note: As part of the open assessment, reviews and the original submission are available as supplementary files on our website.

Appendices

Appendix A
Factor Authors, year Study area; sample size Data collection method Data analysis method Impact on AT/AW/B Effect
Demographic factors
Age Davison et al., 2014 UK; 560 Survey Path analysis AT Younger people tend to have stronger environmental attitudes (−)
Niu et al., 2016 Taiwan; 442 Survey Bootstrapping method of smart partial least square
Çabuk et al., 2019 Turkey; 346 Survey t-test, ANOVA, and regression analysis AT Older passengers have stronger environmental awareness (+)
Ryley et al., 2013 UK and USA; 605 and 504 Survey Chi-square analysis AT Young females and/or those with children respond more positively to messages surrounding air travel and environmental issues (−)
Hansmann & Binder, 2021 Switzerland; 1,206 Survey Linear regression model B Lower flight reduction intentions of older persons (−)
Araghi et al., 2016 The Netherlands; 261 Survey Discrete choice model B Middle-aged people tend to care about the eco-efficiency of a flight when booking (+)
Chen et al., 2011 Taiwan; 350 Survey Independent t-tests and one-way ANOVA B Older people (above 50) tend to engage more in general environmental behaviours (+)
Blasch & Farsi, 2014 Switzerland; 1,010 Survey Latent class model B Younger respondents are more willing to pay for offsets (−)
Segerstedt, 2015 Germany; 449 Survey Discrete choice model
Lu & Shon, 2012 Taiwan; 1,339 Survey Interval regression
Shaari et al., 2020 Malaysia; 823 Survey Contingent valuation method B Age has a positive relationship in the model for carbon offset (+)
Han et al., 2019c USA; 309 Survey Structural equation model (SEM) B Personal norms and green intentions are associated more strongly in the low age group than the high age group (regarding intentions to adopt electric aircraft) (−)
Graham & Metz, 2017 UK; 3,000 Survey Descriptive statistics B Younger and older people tend to be infrequent flyers
Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis B Younger people tend to have higher emissions from air travel (+)
O’Garra & Fouquet, 2022 UK; 2,398 + 1,600 Survey Regression analysis B Older people tend to reduce air travel (+)
Cordes et al., 2024 47 Literature review Literature review B Younger people have a higher WTP for carbon offsets
Gender Çabuk et al., 2019 Turkey; 346 Survey t-test, ANOVA, and regression analysis AT Women have stronger environmental attitudes
Ryley et al., 2013 UK and USA; 605 and 504 Survey Chi-square analysis AT Young females and/or those with children respond more positively to messages surrounding air travel and environmental issues
Choi & Ritchie, 2014 Australia; 349 Survey Discrete choice model B Female travellers have a higher economic value of carbon mitigation, higher WTP air ticket tax, and a higher value of carbon offset donations
Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model
Sonnenschein & Smedby, 2019 Sweden; 500 Survey Regression analysis
Hansmann & Binder, 2021 Switzerland; 1,206 Survey Linear regression model B Higher flight reduction intentions among females than males
Chen et al., 2011 Taiwan; 350 Survey Independent t-tests and one-way ANOVA B Females were found to engage in more general environmental behaviour than males do
Hwang & Choi, 2018 Korea; 322 Survey Structural equation model (SEM) B Green travel behaviour is more important to females than to males
Income Enzler, 2017 Switzerland; 3,369 Secondary survey data Lognormal hurdle model B Higher incomes are associated with more air travel (−)
Çabuk et al., 2019 Turkey; 346 Survey t-test, ANOVA, and regression analysis AT High-income groups are more likely to have positive attitudes towards green airline operations (+)
Ryley et al., 2013 UK and USA; 605 and 504 Survey Chi-square analysis AT High-income groups are “trying to fly less for environmental reasons” (+)
Shaari et al., 2020 Malaysia; 823 Survey Contingent valuation method B Higher incomes have a positive impact on WTP (willingness to pay) (+)
Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis B Higher-income groups tend to have higher emissions from air travel (−)
Graham & Metz, 2017 UK; 3,000 Survey Descriptive statistics B Low-income people tend to be infrequent flyers (−)
Cordes et al., 2024 47 Literature review Literature review B High-income people have a higher WTP for carbon offsets
Education Chen et al., 2011 Taiwan; 350 Survey Independent t-tests and one-way ANOVA AT Respondents with a master’s or higher degree have stronger environmental attitudes than those with a high school degree (+)
Shaari et al., 2020 Malaysia; 823 Survey Contingent valuation method B Positive relationship regarding WTP and donation values of carbon offset (+)
Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model
Cordes et al., 2024 47 Literature review Literature review B High-educated people have a higher WTP for carbon offsets
Employment Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model B Positive relationship regarding WTP and donation values of carbon offset (+)
Shaari et al., 2020 Malaysia; 823 Survey Contingent valuation method
Have children in the household Ryley et al., 2013 UK and USA; 605 and 504 Survey Chi-square analysis AT Young females and/or those with children respond more positively to messages surrounding air travel and environmental issues (+)
Enzler, 2017 Switzerland; 3,369 Secondary survey data Lognormal hurdle model B Living with children is associated with less air travel. (+)
Migrants Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis B Migrants tend to have higher emissions from air travel
Urban residents Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis B Urban residents tend to have higher emissions from air travel
Country Niu et al., 2016 Taiwan; 442 Survey Bootstrapping method of smart partial least square B Different preferences regarding how to support airlines’ environmental policies
Higham et al., 2014 Norway, UK, Germany; 48 Semi‐structured interviews Comparative analysis (qualitative) AW High awareness of climate change in Norway and Germany; widespread concerns with uncertainty in the UK
Distance to airport Enzler, 2017 Switzerland; 3,369 Secondary survey data Lognormal hurdle model B The shorter distance between home and airport, in particular the large ones, is correlated to more air travels (−)
Internal factors
Frequent flyers Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model B Less likely to be willing to pay the air ticket tax or carbon offset donations (−)
Sonnenschein & Smedby, 2019 Sweden; 500 Survey Regression analysis
Ryley et al., 2013 UK and USA; 605 and 504 Survey Chi-square analysis AT Less likely to agree with the attitudinal statements regarding the environment (−)
Non-flyers Kantenbacher et al., 2018 UK; 2,066 Survey Multivariate regression model B Higher willingness to undertake reduction sacrifices (+)
Business travellers Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model B A lower value of carbon offset donations (−)
Lassen, 2010 Denmark; 13 interview based on a survey Analysis of interview results AW, B In general consider themselves environmentally aware but it hardly affects the mode choice
Schmalz et al., 2021a Germany; 11 + 67 Interview and survey Descriptive statistics AW, B In general consider themselves environmentally aware, but it hardly affects the mode choice
Knowledge of air transport footprint Chiambaretto et al., 2021 France; 1,018 Survey Descriptive statistics B Overestimation/underestimation of air transport carbon emissions and fuel consumption of new aircraft → flight shame (+)
Becken, 2007 New Zealand; 63 Focus group Analysis of focus group study results AW More knowledge leads to higher awareness of air travel impacts and individual responsibility (+)
Chen et al., 2011 Taiwan; 350 Survey Independent t-tests and one-way ANOVA AT More knowledge leads to higher levels of environmental knowledge and an overall favourable environmental attitude (+)
Jacobson et al., 2020 Sweden; 26 Semi-structured interviews Analysis of interview results AT, B Knowledge about climate change reduces air travel (+)
Garrard, 2013 / Qualitative content Literature analysis (conceptual and theoretical study) AW, B literature can shape environmental consciousness and encourage more sustainable behaviours (+)
Knowledge about carbon offsetting Kim et al., 2014 USA; 323 Survey Structural equation model (SEM) B More knowledge leads to leads to higher willingness to offset their flights (+)
Babakhani et al., 2017 Australia; 20 Lab experiment Descriptive statistics
Zhang, 2021 China; 228 Survey Structural equation model (SEM)
Denton et al., 2020 North America; 144 Survey Structural equation model (SEM) B More knowledge leads to leads to higher willingness to offset their flights (+)
Kim et al., 2016 USA;256 Survey Structural equation model (SEM)
Global policy knowledge Ritchie et al., 2020 Australia; 146 Survey Structural equation model (SEM) B More knowledge leads to beliefs in the effectiveness of climate change policies (+)
Personal moral norms and a sense of social responsibility Jacobson et al., 2020 Sweden; 26 Semi‐structured interviews Analysis of interview results B Stronger moral norms and responsibility to reduce flying (+)
Gössling et al., 2019 Sweden; 587 Survey Descriptive statistics AW, B
Whitmarsh et al., 2020 International; 1,408 + 362 Survey Regression analysis B
Büchs, 2017 UK; 52 Semi-structured interviews Analysis of interview results B Perceived responsibility and moral obligation reduce holiday air travel (+)
van Birgelen et al., 2011 Netherlands; 128 Survey Structural equation model (SEM) B Positively linked to the willingness to compensate (+)
Sonnenschein & Smedby, 2019 Sweden; 500 Survey Regression analysis B People with stronger moral norms and responsibility are more likely to be willing to pay air ticket tax (+)
Brouwer et al., 2008 Amsterdam; more than 400 Survey Contingent valuation methodology B Moral obligation has a positive impact on WTP for carbon offset (+)
Han et al., 2019b USA; 302 Survey Structural equation model (SEM) B Intention to adopt electric airplane (+)
Attachment to eco-friendly products Han et al., 2019a USA; 302 Survey Structural equation model (SEM) B Stronger attachment has a stronger effect on attitude and on intention to adopt electric aircraft (+)
Han et al., 2019b USA; 302 Survey Structural equation model (SEM) B Stronger attachment increases intention to adopt electric aircraft (+)
Trust of new mobility technology Fu & Moeckel, 2024 Germany; 3,010 Survey Structural equation model (SEM) B Trust in new mobility technology has a positive impact on acceptance of electric aircraft (
Consumers perceive that their individual efforts to prevent or reduce CO2 van Birgelen et al., 2011 Netherlands; 128 Survey Structural equation model (SEM) B Positively linked to the likelihood of compensation (+)
Flying habits Hansmann & Binder, 2021 Switzerland; 1,206 Survey Linear regression model B A most powerful predictor of air travel intentions
Perception of the severity of CO2 emissions van Birgelen et al., 2011 Netherlands; 128 Survey Structural equation model (SEM) B Positively linked to the willingness to compensate (+)
Brouwer et al., 2008 Amsterdam; more than 400 Survey Contingent valuation methodology B Anticipation of future risks has a positive impact on WTP for carbon offset (+)
Perception that individual efforts can reduce CO2 emissions van Birgelen et al., 2011 Netherlands; 128 Survey Structural equation model (SEM) B Positively linked to the willingness to compensate (+)
Perceived sacrifice (comfort, convenience, and effort an airline passenger is willing to surrender when adopting green practices Wong et al., 2020 Malaysia; 379 Survey Structural equation model (SEM) B Negatively influence air passengers’ intention to adopt green practices (e.g. check-in online) (−)
Perceived uncertainty of outcomes Han et al., 2019a USA; 302 Survey Structural equation model (SEM) B The lower the uncertainty, the stronger the influence of attitude, subjective norms, and perceived behavioural control on intention (−)
Attitudes regarding reducing leisure air travel Morten et al., 2018 UK; 194 Survey Bivariate correlations and one-way analyses of variance B The attitudes help promote motivation to reduce leisure air travel (+)
Behaviour-specific self-identity Morten et al., 2018 UK; 194 Survey Bivariate correlations and one-way analyses of variance B The behaviour-specific self-identity helps promote motivation to reduce leisure air travel (+)
O’Garra & Fouquet, 2022 UK; 2,398 + 1,600 Survey Regression analysis B Individuals who perceive themselves as having a higher quality of life are willing to reduce air travel (+)
Global social interconnectedness and international experience Oswald & Ernst, 2021 International; 393 Survey Structural equation model (SEM) B Increased travel visiting friends and family and an overall increase in flight kilometres (−)
Dispersed social networks Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis B People with dispersed social networks tend to have high emissions from air travel (−)
Sense of social embedded-ness Kim et al., 2014 USA; 323 Survey Structural equation model (SEM) B Positively influences attitudes toward participation in voluntary carbon offsetting (+)
Beliefs that avoiding air travel mitigates climate change Berneiser et al., 2022 Germany; 2,530 Survey Regression analyses B The strongest predictors to reduce air travel (+)
Intergenerational justice concerns Berneiser et al., 2022 Germany; 2,530 Survey Regression analyses B The strongest predictors to reduce air travel (+)
Commitment to the environment in terms of home activities Barr et al., 2011b UK; 202 Survey Segmentation analysis B Stronger commitment increases willingness to consider measures to reduce the potential impacts of flying on climate (+)
External factors
Information about the environmental impacts of air travel Raux et al., 2021 France; 789 Survey Discrete choice model B More knowledge helps reduce preference for air (+)
Whitmarsh et al., 2020 International; 1,408 + 362 Survey Regression analysis B More knowledge increases behavioural intentions and support for institutional policies to reduce flying (+)
Lu & Wang, 2018 Taiwan; 552 Survey Path analysis AT, B People with more knowledge are more willing to offset their flights (+)
Zhang et al., 2019a Australia; 1,680 Survey Confirmatory factor analysis, ANOVA B
Zhang et al., 2019b Australia; 30 + 1,500 Interview and survey Structural equation model (SEM) B
Baumeister & Onkila, 2018 Europe; 12 Expert interviews Interview analysis AW Providing adequate, transparent, and tailored information helps passengers gain knowledge about air travel impacts
Breen & Pensini, 2022 Australia; 325 Survey Mediation analysis AW, B
Cocolas et al., 2023 Australia; 672 Survey Experimental design AT, B
Subjective norms Busche & Sargisson, 2020 Netherlands; 134 Survey ABC model (Cognitive Behaviour Therapy) B People affected more by subjective norms have a higher intention to reduce the environmental impact of air travel (+)
Cocolas et al., 2020 / Qualitative content Literature analysis (conceptual and theoretical study) AT, B Positive to reduce flying (+)
Cocolas et al., 2021 Australia; 20 Semi-structured interviews Interview analysis AT Positive to reduce flying (+)
Büchs, 2017 UK; 52 Semi-structured interviews Interview analysis B Reduces holiday air travel (+)
Morten et al., 2018 UK; 194 Survey Bivariate correlations and one-way analyses of variance B Helps promote motivation to reduce leisure air travel (+)
Ritchie et al., 2020 Australia; 146 Survey Structural equation model (SEM) B Encourages aviation carbon offsetting (effects getting stronger) (+)
Cohen et al., 2011 UK; Norway; 30 Interview Analysis of interview results B Affects holiday flying behaviour
Green image of an airline Busche & Sargisson, 2020 Netherlands; 134 Survey ABC model (Cognitive Behaviour Therapy) B Positive influence on the willingness to take an environmentally friendly airline (+)
Hwang & Lyu, 2020 Korea; 320 Survey Structural equation model (SEM)
CSR Chuah et al., 2020 International; 582 Survey Structural equation model (SEM) AT Positively links to environmental concern and green trust (+)
Air travel tax Becken, 2007 New Zealand; 63 Focus group Analysis of focus group study results B Restrict air travel (+)
Wild et al., 2021 Switzerland; 237 Survey Descriptive statistics B Have a weak impact on air demand
Jet fuel tax Sobieralski & Hubbard, 2020 USA; monthly air traffic data from 2001 to 2019 Secondary data Quasi-experimental approach B Cuts increased air traffic by 0.2% on average but faded within a year
Carbon pricing Markham et al., 2018 Australia; demand data from January 1984 to June 2017 Secondary data Time-series regression analysis B No evidence that the carbon price reduced the level of domestic aviation
Social factors such as family commitments Whitmarsh et al., 2020 International; 1,408 + 362 Survey Regression analysis B Strongly predict actual flying behaviour
Social factors such as behaviour of celebrities Gössling, 2019 International; 10 Qualitative content Qualitative analysis AW Celebrities have both positive and negative impacts on reducing air travel
University sustainability policies Glover et al., 2018 Australia; 43 Qualitative content Qualitative content and textual analysis B Positively affects academic air travel (+)
Schmidt, 2022 USA; 44 Qualitative content Thematic analysis B Positively affects academic air travel (+)
Wenger, 2023 International; 21 Semi-structured interviews Interview analysis B Virtual forms of academic exchange
COVID-19 pandemic O’Garra & Fouquet, 2022 UK; 2,398 + 1,600 Survey Regression analysis B Potential for voluntary behavioural changes, prompted by the COVID-19 pandemic, to contribute to reducing carbon emissions and supporting sustainable development (+)
Kallbekken & Sælen, 2021 Norway; 1,010 Survey Ordered logistic regression B Effectiveness of proposed measures could increase public support for air travel restrictions aimed at reducing greenhouse gas emissions (+)
Manca et al., 2023 UK; 388 Survey Hybrid choice model B The pandemic may serve as an impetus for re-evaluating and potentially transforming the air transport sector to address longer-term environmental sustainability goals (+)
Moira & Parthenis, 2022 France;/ Qualitative content Policy analysis B COVID-19 as a ‘policy window’ for promoting a green recovery and transformation of the air transport and tourism sectors (+)

AT: Attitudes toward the environment; AW: Environmental awareness; B: Environmentally friendly behaviour.

(+) indicates a positive relationship between the factor and AT/AW/B; (−) indicates a negative relationship between the factor and AT/AW/B.

Appendix B
Authors, year Study area; sample size Data collection method Data analysis method Findings
Hansmann & Binder, 2021 Switzerland; 1,206 Survey Regression analysis General environmental attitudes were shown to be the strongest positive predictors of intentions to reduce flights
Baumeister, 2015 International; 148 Survey Descriptive statistics Some people consider the environment when booking flights
van Birgelen et al., 2011 Netherlands; 128 Survey Structural equation model (SEM) Consumers who perceive that their efforts to prevent or reduce CO2 emissions from air travel have a positive effect on the environment
Busche & Sargisson, 2020 Netherlands; 134 Survey ABC model (Cognitive Behaviour Therapy) Environmental attitudes toward air travel are highly predictive of intentions to reduce the environmental impact of one’s air travel
Choi et al., 2016 Australia; 2,000 Survey Structural equation model (SEM) More positive orientation towards the environment could be an important predictor of environmental intentions operating both directly on intentions as well as guiding beliefs that relate to intentions of air travellers’ voluntary climate action
Kantenbacher et al., 2018 UK; 2,066 Survey Multivariate regression model Support for aviation climate policies strengthens with pro-environmental attitudes
Ritchie et al., 2021 Australia; 998 Survey Discrete choice model Pro-environmental attitudes may influence carbon offset preferences in the youngest segment
Rotaris et al., 2020 Italy; 1,228 Survey Discrete choice model Environmental consciousness increases air travellers’ WTP for CO2 offsetting
Zhang, 2021 China; 228 Survey Structural equation model (SEM) Pro-environmental values affect the intention to participate in voluntary carbon offsetting
Garrow et al., 2020 USA; 1,405 Survey Factor analysis and cluster analysis Early urban air mobility (UAM) adopters have stronger pro-environment attitudes
Haddad et al., 2020 Europe; 221 Survey Discrete choice model Environmental concerns affect the adoption of UAM
Ahmed et al., 2021 USA; 584 Survey Probit model Environmental concerns affect the adoption of UAM
Barr et al., 2011b UK; 202 Survey Segmentation analysis Those with the highest commitments in the home environment also tended to be individuals who were more willing to consider measures to reduce the potential impacts of flying on climate
Chuah et al., 2020 International; 582 Survey Structural equation model (SEM) Environmental concern and green trust positively affect air passengers’ sustainable engagement behaviour
Mair, 2011 UK and Australia; 470 Survey Regression analysis Those who purchase carbon offsets have pro-environmental attitudes
Bakır, 2024 Turkey; 156 Survey Structural equation model (SEM) Pro-environmental attitude has an impact on green purchase intention in air travel
Breen & Pensini, 2022 Australia; 325 Survey Mediation analysis Pro-environmental attitude reduces leisure air travel
Graham & Metz, 2017 UK; 3,000 Survey Descriptive statistics Pro-environmental attitude reduces air travel
Seegebarth et al., 2024 Germany; 1,263 Survey Structural equation model (SEM) Pro-environmental attitude reduces air travel
Davison et al., 2014 UK; 560 Survey Path analysis Pro-environmental attitude is not always a reliable indicator of behaviour
Alcock et al., 2017 UK; 3,923 + 5,500 Secondary data Zero-inflated Poisson regression models No association between environmental attitudes and discretionary air travel
Barr et al., 2011a UK; 57 Focus group Analysis of focus group study results Participants who were committed to environmental practices at home were unwilling to reduce holiday air travel
Lassen, 2010 Denmark; 13 Interview based on survey results Analysis of interview results No connection between environmental attitude and the actual travel behaviour of business air travellers
Mayer et al., 2012 UK; 612 Survey Non-parametric statistical tests Green attitudes do not necessarily translate into a change in behaviour or even the WTP higher fares
Morten et al., 2018 UK; 194 Survey Bivariate correlations and one-way analyses of variance No evidence that a general measure of pro-environmental self-identity contributed to the prediction of intentions to reduce the number of flights taken for leisure or to visit family or friends
Oswald & Ernst, 2021 International; 393 Survey Structural equation model (SEM) Ecological awareness was not related to refraining from overseas travel
Reis & Higham, 2017 Australia; 20 Semi-structured interviews Analysis of interview results Widespread concern about climate change combined with an unwillingness to change established air travel behaviours
Buckley, 2011 Australia; 30 Semi-structured interviews Analysis of interview results Environmentally knowledgeable people continue to holiday air travel
McDonald et al., 2015 UK; 29 Semi-structured interviews Analysis of interview results People having green attitudes do not change flying behaviour
Aasen et al., 2023 Norway; 2,842 Survey Structural equation model (SEM) Pro-environmental attitude has no direct impact on reducing leisure air travel
Wynes et al., 2019 UK; 705 Survey Regression analyses Pro-environmental attitude has no direct impact on reducing academic air travel
Hares et al., 2010 UK; 34 Focus group Analysis of focus group study results The gap lies between awareness and attitude rather than a gap between attitude and behaviour
Chen et al., 2011 Taiwan; 350 Survey Independent t-tests and one-way ANOVA A significant gap between general environmental behaviour and pro-environmental air travel behaviour
Lu & Wang, 2018 Taiwan; 552 Survey Path analysis The gap between attitude and behaviour (intention)
Sonnenschein & Smedby, 2019 Sweden; 500 Survey Regression analysis Respondents expressed positive WTP, but did not feel that it is mainly the air travellers’ responsibility to reduce emissions
Dickinson et al., 2013 Poland; 369 Survey Structural equation model (SEM) Value–action gap in tourism
Cohen et al., 2013 Australia, Norway, UK; 50 Interviews Analysis of interview results The scope for voluntary positive behaviour change in the air travel context is limited
Denton et al., 2020 USA; 505 Survey Structural equation model (SEM) The gap between consumers’ beliefs toward carbon offsetting and their actual behaviours
Hibbert et al., 2013 UK; 24 Interviews Thematic analysis The gap between attitude and behaviour in tourism mobility
Higham et al., 2015 Australia; 20 Semi-structured interviews Analysis of interview results The gap between attitude and behaviour in tourism mobility
Jurjonas & Aldana, 2020 International Secondary data Descriptive statistics Attitude–behaviour gap
Kroesen, 2013 Netherlands; 491 Survey Q-factor analysis Inconsistency between attitude and behaviour
Tölkes, 2020 Germany, Austria; 20 Semi-structured interviews Analysis of interview results The gap between attitude and behaviour in tourism mobility
Schmalz et al., 2021a Germany; 11 + 67 Interview and survey Descriptive statistics Attitude–behaviour gap
Blanchard et al., 2022 France; more than 6,000 Survey Descriptive statistics Attitude–behaviour gap
Buckley, 2011 International; 50 Interviews Interview analysis Attitude–behaviour gap
Gössling et al., 2020 Germany; 1,002 Survey Regression and factor analysis Attitude–behaviour gap
Higham & Cohen, 2011 Norway; 15 Interviews Interview analysis Attitude–behaviour gap
Higham et al., 2016 Norway, UK, Germany, Australia; 68 Interviews Interview analysis Attitude–behaviour gap
Mkono, 2020 / Literature content Literature analysis Attitude–behaviour gap
Schrems & Upham, 2020 Germany; 11 Literature content Content analysis Attitude–behaviour gap
Stubenvoll & Neureiter, 2021 Germany; 199 Survey Regression and factor analysis Attitude–behaviour gap
Gössling et al., 2009 Sweden; 300 Survey Descriptive statistics Attitude–behaviour gap
Eijgelaar, 2011 /; 64 Literature content Content analysis Attitude–behaviour gap
Büchs, 2017 UK; 52 Semi-structured interviews Interview analysis Attitude–behaviour gap
Cocolas et al., 2020 / Literature content Literature analysis Attitude–behaviour gap
Gössling & Peeters, 2007 / Literature content Qualitative analysis of statements Attitude–behaviour gap
Mattioli et al., 2023 England; 34,318 Secondary survey data Regression analysis Attitude–behaviour gap

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Received: 2025-02-19
Revised: 2025-06-05
Accepted: 2025-06-27
Published Online: 2025-08-13

© 2025 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Heruntergeladen am 22.3.2026 von https://www.degruyterbrill.com/document/doi/10.1515/econ-2025-0160/html
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