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Article

Decoding Sustainable Air Travel Choices: An Extended TPB of Green Aviation

by
Jakkawat Laphet
1,
Dultadej Sanvises
1,
Duangrat Tandamrong
2 and
Pongsatorn Tantrabundit
2,*
1
College of Aviation, Tourism and Hospitality, Sripatum University, Khon Kaen 40000, Thailand
2
Mahasarakham Business School, Mahasarakham University, Mahasarakham 44150, Thailand
*
Author to whom correspondence should be addressed.
Tour. Hosp. 2025, 6(5), 232; https://doi.org/10.3390/tourhosp6050232
Submission received: 16 October 2025 / Revised: 3 November 2025 / Accepted: 4 November 2025 / Published: 5 November 2025
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Abstract

The aviation sector faces increasing pressure to address climate change as its contribution to global CO2 emissions continues to rise. This study investigates how passengers’ awareness of environmental issues and perceptions of sustainable airline practices affect their Green Air Travel Behavior (GTB). Drawing upon the Theory of Planned Behavior (TPB) and extending it with constructs such as Environmental Awareness (EA), Perceived Service Quality (PSQ), and Green Trust (GT), the research examines their impact on GTB. Using a quantitative design, data were collected from 300 airline passengers and analyzed with Structural Equation Modeling (SEM). Results reveal that EA strongly influences PSQ, GT, Attitude (ATT), and Intention (ITN), highlighting its role as a key antecedent. PSQ significantly enhances GT, while both GT and ATT directly predict GTB. However, the effect of ITN on GTB was not significant, indicating an intention–behavior gap. The findings underscore the importance of awareness, trust, and service quality in promoting sustainable air travel, while also pointing to barriers that hinder intentions from becoming actions. Theoretically, the study extends TPB within green aviation, and practically, it provides guidance for airlines and policymakers seeking to advance SDG 13: Climate Action through sustainable air travel strategies.

1. Introduction

In response to the growing threat of climate change, sustainable air travel has emerged as a critical area of concern, particularly due to the increasing greenhouse gas emissions associated with the aviation industry (Kumari et al., 2024; W. Liao et al., 2023). This issue is directly aligned with Sustainable Development Goal 13: Climate Action, which calls for urgent action to combat climate change and its impacts. Aviation currently contributes approximately 2% of global CO2 emissions, and as passenger volumes and air cargo demands continue to rise, this figure is expected to grow, further intensifying environmental challenges (Reyes-García et al., 2024; Bayramoğlu et al., 2025). Although air transport plays a pivotal role in global economic integration and mobility, its environmental impact cannot be overlooked.
To mitigate these emissions, the International Civil Aviation Organization (ICAO) introduced the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) (Scheelhaase & Maertens, 2020), a global initiative encouraging airlines to adopt environmentally responsible practices through carbon offsetting and sustainable aviation strategies (IATA, 2024; Schleich & Alsheimer, 2024). At the same time, many airlines are embedding Corporate Social Responsibility (CSR) values within their operations to support eco-conscious initiatives and respond to consumer demand for greener options.
In the Thai context, the transportation sector accounts for 34% of total national CO2 emissions, with aviation contributing increasingly due to tourism-driven growth. Although Thailand’s net-zero target by 2065 is less ambitious compared to neighboring countries such as Cambodia, Indonesia, and Singapore, the country is making gradual progress through mechanisms like carbon pricing, renewable energy integration, and the Thailand Voluntary Emission Reduction Program (T-VER) (Kim et al., 2025; Barker & Peters, 2023). Ongoing discussions regarding the appropriate application of either a carbon tax or an Emissions Trading System (ETS) reflect efforts to establish an effective and inclusive emissions framework (van den Bergh et al., 2024).
While policy mechanisms are vital, the behavioral dimension of travelers also plays a significant role in promoting sustainable air travel. Empirical evidence suggests that tourists with high environmental awareness are more likely to support carbon offset programs such as T-VER, even though Thailand currently represents only 7.61% of the global carbon credit market (Leenoi, 2023; TGO, 2024). The growing participation in voluntary carbon markets highlights the potential influence of traveler psychology and perception on sustainable aviation outcomes.
This study draws upon the Theory of Planned Behavior (TPB), which posits that behavior is guided by Attitude (ATT), Subjective Norms, and Perceived Behavioral Control (PBC). However, to address aviation-specific challenges, this study proposes an extended TPB model by integrating environmental and aviation constructs namely, Environmental Awareness (EA), Green Trust (GT), and Perceived Service Quality (PSQ) to better explain the factors influencing Green Air Travel Behavior (GTB). Prior research has demonstrated that EA significantly affects ATT, Perceived Sustainability, and PBC, ultimately leading to stronger pro-environmental behavioral intentions (Jibran et al., 2025). In this framework, awareness of climate issues such as carbon footprints and eco-initiatives influences how tourists perceive their responsibilities and choices as air passengers.
Furthermore, perceived service quality especially in terms of sustainable offerings like carbon offsetting, sustainable aviation fuel (SAF), and eco-friendly services also shapes travelers’ trust in airlines’ environmental claims (Bakır & Itani, 2024). Green trust, in this context, reflects whether travelers believe that an airline’s sustainability measures are authentic rather than greenwashing, which, in turn, influences their intentions and final travel choices (Sung et al., 2021; Tan et al., 2022). These perceptions are particularly relevant in Thailand, where the success of voluntary initiatives like T-VER depends heavily on travelers’ willingness to engage in eco-friendly actions, often based on trust and belief in the transparency of environmental programs (Chen, 2013; Crosby et al., 2024).
Through this integrated framework the Extended TPB Green Aviation Model the current study aims to decode the psychological and perceptual factors that drive sustainable air travel choices, offering insights for both policy implementation and airline strategic planning. This research contributes to the broader objective of achieving SDG 13: Climate Action by providing a behavioral framework to guide sustainable strategies within the aviation sector.

2. Literature Review

2.1. Environmental Awareness

Environmental awareness (EA) has emerged as a fundamental determinant of pro-environmental behavior, especially in the tourism and aviation sectors. EA reflects an individual’s cognitive understanding of environmental issues and the urgency of taking action to mitigate climate change. In the context of sustainable travel, studies have shown that environmentally aware individuals are more likely to adopt responsible behaviors such as reducing emissions, purchasing carbon offsets, and supporting green airline policies (Demir, 2025). Within the framework of the Theory of Planned Behavior (TPB), EA is often integrated as an antecedent to attitude and perceived behavioral control (Jibran et al., 2025). Individuals with greater awareness are more likely to perceive climate action as personally relevant, which strengthens their intention to act sustainably (Despotović et al., 2021).
Empirical research has demonstrated the positive impact of EA on sustainable behavioral intentions. For example, Fu et al. (2025) found that tourists with high environmental awareness exhibit more favorable attitudes towards eco-friendly travel and have a stronger intention to support sustainable practices such as voluntary carbon offsetting. EA also mediates the relationship between external information sources (e.g., environmental campaigns, CSR communications) and consumer decision-making (Warburg et al., 2021). Additionally, in aviation-specific studies, EA enhances the perception of the environmental responsibility of airlines, leading to increased consumer trust and willingness to pay for carbon-neutral flights (Sung et al., 2021).
Although EA may not directly predict behavior, its role as a key antecedent to attitude and perceived behavioral control makes it a critical component in any extended TPB model for explaining green air travel choices (Leal Filho et al., 2023; Baumeister et al., 2022). Thus, improving environmental literacy among travelers is essential for advancing sustainable behavior in the aviation sector.

2.2. Perceived Service Quality

Perceived Service Quality (PSQ) plays a pivotal role in shaping customer evaluations and behavioral intentions in the service industry, including aviation. In the context of sustainable air travel, PSQ encompasses not only traditional aspects such as reliability and comfort but also environmental dimensions such as carbon offset options, eco-friendly in-flight practices, and sustainable fuel usage. According to S.-H. Liao et al. (2025), travelers who perceive airlines as offering high-quality and environmentally responsible services are more likely to develop positive attitudes toward the brand and exhibit greater willingness to engage in green travel behaviors.
The TPB framework has been extended in several studies to include PSQ as a determinant of both attitude and perceived behavioral control. For example, Demir (2025) found that PSQ significantly influences green attitudes and contributes indirectly to sustainable travel intentions. Similarly, Schleich and Alsheimer (2024) emphasized that PSQ acts as a confidence-building mechanism that increases the perceived ease and value of supporting sustainable airline programs. PSQ has also been shown to strengthen green trust, a mediating factor that amplifies the relationship between perceived sustainability and behavioral intention (Jibran et al., 2025).
Importantly, in competitive tourism markets, service quality tied to environmental values differentiates airlines and builds brand loyalty among eco-conscious consumers (Zeren & Kara, 2021). By communicating clearly about environmental initiatives and delivering consistent green service quality, airlines can enhance their reputation and influence consumer behavior more effectively. Thus, PSQ is an essential construct in models aiming to predict and promote green air travel behavior.

2.3. Green Air Travel Behavior

Green Air Travel Behavior (GTB) refers to actions taken by air travelers that minimize environmental impact, such as choosing low-emission flights, participating in carbon offsetting programs, or selecting airlines with strong sustainability credentials. This construct has gained increasing attention as global concerns over aviation-related emissions grow. TPB has been widely applied to explain GTB, with behavioral intentions often influenced by attitude, subjective norms, and perceived behavioral control (Ajzen, 1991). However, recent studies argue for the inclusion of environmental-specific variables to improve predictive accuracy (Jibran et al., 2025; Fu et al., 2025).
S.-H. Liao et al. (2025) identified that travelers’ green air travel behavior is significantly driven by their perception of risk, environmental values, and trust in airline sustainability. Furthermore, Sung et al. (2021) found that green trust, shaped by service quality and CSR transparency, is a strong predictor of willingness to engage in carbon offsetting (Yraola & Mendiola, 2024). The role of intention is also influenced by the traveler’s belief in the efficacy of their actions whether their choices truly contribute to reducing emissions (Chen, 2013).
Importantly, cultural context matters. In emerging markets like Thailand, where government-led carbon programs (e.g., T-VER) are still developing, GTB is strongly linked to awareness and institutional trust (Leenoi, 2023). Incentives such as carbon offset discounts or reward programs can further motivate travelers to adopt sustainable behaviors. Thus, GTB is not merely an individual choice but one shaped by knowledge, service experience, and perceived institutional support. Integrating GTB as an outcome variable in extended TPB models enables a holistic understanding of how psychological, social, and service-related factors converge to influence sustainable air travel decisions (Albayati et al., 2023).

3. Conceptual Framework Development and Hypothesis

To better understand the psychological and perceptual drivers of environmentally responsible air travel, this study adopts and extends the Theory of Planned Behavior (TPB) by integrating green-related constructs into its core framework. While TPB posits that Attitude, Subjective Norms, and Perceived Behavioral Control are the primary predictors of behavioral intention (Ajzen, 1991), recent studies have demonstrated that this model may not fully capture the unique factors influencing sustainable travel behavior in the context of aviation (Jibran et al., 2025; S.-H. Liao et al., 2025).
Building on this theoretical foundation, the conceptual framework of this research includes Environmental Awareness (EA) as a fundamental antecedent, recognizing its established influence on shaping pro-environmental attitudes and intentions (Fu et al., 2025). EA is proposed to directly affect not only travelers’ Attitude (ATT) toward green flying but also their perception of Service Quality (PSQ) and the formation of Green Trust (GT) in airlines that promote environmental initiatives (Alfaro & Chankov, 2022).
Perceived Service Quality (PSQ), another key construct, has been widely acknowledged in service and tourism research as a determinant of trust and loyalty (Schleich & Alsheimer, 2024). In this model, PSQ is hypothesized to positively influence Green Trust, reflecting the belief that airlines delivering high-quality and eco-conscious services earn greater consumer confidence.
Green Trust (GT) itself is considered a crucial driver of Green Air Travel Behavior (GTB), mediating the relationship between environmental perception and actual behavioral outcomes (Sung et al., 2021). In addition, Attitude (ATT) and Behavioral Intention (ITN) core TPB components are posited to directly influence GTB, in line with the theoretical expectation that favorable attitudes and strong intentions lead to action (Ajzen, 1991; Helferich et al., 2023).
The research model is summarized in Figure 1, which visualizes the hypothesized relationships among the key constructs. Based on this framework, the following eight hypotheses are proposed:
According to literature review and conceptual framework, the following hypotheses can be articulated.
H1. 
Environmental Awareness (EA) has a positive influence on Perceived Service Quality (PSQ).
H2. 
Environmental Awareness (EA) has a positive influence on Green Trust (GT).
H3. 
Environmental Awareness (EA) has a positive influence on Attitude (ATT).
H4. 
Environmental Awareness (EA) has a positive influence on Intention (ITN).
H5. 
Perceived Service Quality (PSQ) has a positive influence on Green Trust (GT).
H6. 
Green Trust (GT) has a positive influence on Green Air Travel Behavior (GTB).
H7. 
Attitude (ATT) has a positive influence on Green Air Travel Behavior (GTB).
H8. 
Intention (ITN) has a positive influence on Green Air Travel Behavior (GTB).

4. Methodology

4.1. Data Acquisition

A quantitative research design was adopted, with data collected via structured surveys administered to a broad sample of airline passengers traveling within or through Thailand. The analysis applies Structural Equation Modeling (SEM) to test the proposed relationships within the extended TPB Green Aviation framework. Particular attention is given to understanding how factors influence decision-making related to eco-conscious flight choices, including preference for airlines with visible sustainability initiatives, perceived environmental responsibility, and engagement in low-carbon travel practices.

4.2. Population and Sampling

The target population for this study consists of passengers who have traveled with airline passengers operating in Thailand. These travelers were selected due to their higher likelihood of engaging in environmentally responsible behaviors and their stronger expectations for service quality, which are relevant to the extended Theory of Planned Behavior (TPB) model employed in this research. Airline passengers generally demonstrate greater environmental awareness and are more attentive to airlines’ sustainability efforts, such as carbon offset programs, eco-conscious service delivery, and corporate social responsibility (CSR) initiatives. Therefore, focusing on this group aligns with the study’s aim of understanding psychological and perceptual factors influencing green air travel behavior.
A combination of purposive sampling and stratified sampling techniques was used to ensure the sample was both relevant and representative. Purposive sampling allowed the selection of participants with prior experience in airline passengers, while stratified sampling enabled the categorization of respondents based on demographic factors such as age, gender, and travel frequency. This approach enhances the generalizability of the findings across different tourist profiles.
According to the general rule of thumb for Structural Equation Modeling (SEM), the minimum sample size should be at least ten times the number of observed variables. Given that this study includes 30 observed variables, a minimum of 300 participants was required. To ensure statistical reliability and robustness, data were collected from 300 airline passengers in Thailand. This sample size was considered sufficient for testing the proposed conceptual framework and the hypothesized relationships among environmental awareness, service perception, green trust, and pro-environmental air travel behavior.

4.3. Research Instrument

The research instrument used in this study was a standardized questionnaire comprising 30 items designed to measure key constructs within the Extended Theory of Planned Behavior (TPB) framework applied to sustainable air travel. The questionnaire was organized into four sections. The first section collected demographic information, including age, gender, education, income, frequency of air travel, and environmental exposure. The second section focused on Environmental Awareness (EA) with 8 items assessing respondents’ knowledge, concern, and connection to environmental issues related to aviation. The third section captured psychological constructs central to the Extended TPB model, including Attitude (ATT), Perceived Service Quality (PSQ), Green Trust (GT), and Intention (ITN), with a total of 10 items. The fourth and final section measured Green Air Travel Behavior (GTB) through 6 items that evaluated participants’ environmentally responsible travel choices and behaviors. All items in the latter three sections were rated using a 5-point Likert scale, ranging from “Strongly Disagree” (1) to “Strongly Agree” (5), providing detailed insight into participants’ perceptions and intentions.
The questionnaire was developed based on a thorough review of existing literature related to green consumer behavior, sustainable air travel, and the Theory of Planned Behavior (Ajzen, 1991; Chen, 2013; Park et al., 2017; Ruangkanjanases et al., 2020; Adams et al., 2025). The items were adapted and modified from prior validated studies to fit the context of sustainable aviation. The instrument was reviewed by subject matter experts to ensure content validity. The Index of Item Objective Congruence (IOC) was used to confirm alignment with research objectives. A pilot test verified the reliability of the instrument, with Cronbach’s Alpha values exceeding the accepted threshold of 0.70 across all constructs, indicating good internal consistency.

4.4. Data Collection and Analysis

Data collection was conducted online via Google Forms and distributed through social media platforms such as Facebook and LINE groups. The survey remained open for ten days, resulting in 300 complete responses, which exceeded the minimum sample size requirement for rigorous statistical analysis. Data analysis followed a multi-step approach: descriptive statistics summarized demographic profiles and key variables; Confirmatory Factor Analysis (CFA) was employed to validate the measurement model, ensuring convergent and discriminant validity. Structural Equation Modeling (SEM) was then applied to test the hypothesized relationships. Model fit was assessed using standard indices including SRMR, d_ULS, d_G, and the chi-square to degrees of freedom ratio. Bootstrapping procedures were utilized to estimate confidence intervals and evaluate the significance of path coefficients, thereby reinforcing the robustness and validity of the hypothesis testing and the overall conceptual model.

5. Results

Based on the common guideline for structural equation modeling, the minimum required sample size is typically ten times the number of observed variables. Since this study involves 30 observed variables, at least 300 participants were needed. To ensure the adequacy and reliability of the analysis, a total of 300 airline passengers in Thailand were surveyed to examine their demographic characteristics, levels of environmental awareness, and engagement in eco-friendly air travel practices. Among the respondents, 54% (n = 162) were aged between 25 and 34 years, and the majority, 65% (n = 195), reported being single. In terms of gender, females accounted for 59% (n = 177) and males for 41% (n = 123). Approximately 62% (n = 186) were employed in the private sector, while 27% (n = 81) reported a monthly income ranging from THB 25,000 to 35,000.
These findings indicate that the sample predominantly consisted of young, single, and environmentally conscious travelers, reflecting the emerging profile of airline passengers within Thailand’s aviation market. In addition to demographic characteristics, the data revealed a generally high level of environmental awareness among the participants. Many respondents expressed a strong connection to nature, emphasizing its importance for their personal well-being and mental health. Across multiple dimensions including knowledge of climate change, understanding of carbon reduction initiatives, awareness of aviation’s environmental impact, and familiarity with government policies addressing greenhouse gas mitigation, participants showed consistent concern and engagement. This heightened environmental awareness was reflected in their attitudes towards sustainable air travel and their support for green aviation initiatives. Moreover, in this study, Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze the data. The use of PLS-SEM allowed for the examination of complex relationships among observed variables, latent constructs, and the overall conceptual framework.
This approach ensured robust estimation of path coefficients, reliability, and validity of the constructs, as well as assessment of the structural model fit. The PLS-SEM analysis provided insights into the direct and indirect effects of demographic characteristics, environmental awareness, and engagement in eco-friendly air travel practices on the efficiency of sustainable airline behavior, supporting the study’s research objectives. The measurement model fit indices, detailed in Table 1, indicate that the data adequately supported the proposed conceptual framework.
Table 1 presents the fit statistics for the saturated and estimated measurement models. The Standardized Root Mean Square Residual (SRMR) for the estimated model is 0.056, which is below the recommended threshold of 0.08, indicating a good model fit.
The discrepancy measures, d_ULS = 1.980 and d_G = 1.020, are both low and close to their saturated model counterparts, suggesting a high level of consistency between the observed and model-implied covariance matrices. Additionally, the Normed Fit Index (NFI) value of 0.912 exceeds the acceptable cutoff of 0.90, further supporting the adequacy of the model.
Overall, these indices collectively confirm that the measurement model exhibits a satisfactory fit to the empirical data, providing a sound foundation for subsequent reliability, validity, and structural model analyses.These statistics provide an initial assessment of model fit, guiding further refinement and structural model analysis.
The evaluation of the measurement model in this study followed the guidelines established by J. Hair et al. (2017), emphasizing the assessment of reliability, convergent validity, and discriminant validity. As presented in Table 2, the measurement model demonstrated strong psychometric properties. All factor loadings exceeded the recommended threshold of 0.70 (Nunnally, 1978), ranging from 0.714 to 0.985, indicating that each item reliably measured its intended construct. Internal consistency was confirmed with Cronbach’s alpha and Composite Reliability (CR) values for all constructs surpassing 0.90, suggesting excellent reliability. Additionally, all Average Variance Extracted (AVE) values were above 0.50, confirming the presence of convergent validity across the constructs. Multicollinearity was not a concern, as all Variance Inflation Factor (VIF) values ranged from 1.000 to 1.497, remaining well below the critical threshold of 5.00 (J. Hair et al., 2017).
To further assess the distinctiveness of each construct, discriminant validity was evaluated using both the Heterotrait–Monotrait (HTMT) ratio and the Fornell–Larcker criterion. As shown in Table 3, all HTMT values were below the recommended cut-off of 0.85, confirming that no two constructs were too closely related and supporting the model’s discriminant validity (J. Hair et al., 2017). Table 4 presents the results of discriminant validity based on the Fornell–Larcker criterion (Fornell & Larcker, 1981). According to this method, the square root of the AVE for each construct (shown in the diagonal) should be greater than the correlations between the constructs (off-diagonal values).
All constructs met this criterion. For instance, the square root of AVE for Attitude (ATT) was 0.870, which is greater than its correlations with other constructs (e.g., 0.532 with PSQ, 0.543 with GT). Similarly, Green Air Travel Behavior (GTB) had a square root AVE of 0.932, which exceeded all its inter-construct correlations (e.g., 0.365 with ATT, 0.448 with PSQ).
These results confirm that each construct in the model is conceptually and statistically distinct, supporting acceptable discriminant validity in accordance with the criteria established by Fornell and Larcker (1981).
As shown in Table 5, the path analysis confirmed that seven out of eight hypothesized relationships in the model were statistically supported, while one was not. Environmental Awareness (EA) significantly and positively influenced Perceived Service Quality (PSQ) (H1: t = 6.441, p < 0.001), Green Trust (GT) (H2: t = 8.041, p < 0.001), Attitude (ATT) (H3: t = 8.994, p < 0.001), and Intention (ITN) (H4: t = 5.912, p < 0.001). Perceived Service Quality (PSQ) had a significant positive effect on Green Trust (GT) (H5: t = 6.097, p < 0.001). Green Trust (GT) significantly influenced Green Air Travel Behavior (GTB) (H6: t = 2.935, p = 0.003), and Attitude (ATT) also had a significant positive effect on GTB (H7: t = 3.616, p < 0.001). However, Intention (ITN) did not have a statistically significant effect on Green Air Travel Behavior (GTB) (H8: t = 0.425, p = 0.671).
Figure 2, the model emphasizes that Environmental Awareness (EA) is a key antecedent influencing multiple mediators, including perceived service quality, green trust, attitude, and intention, which in turn affect Green Air Travel Behavior (GTB). Among these mediators, Green Trust (GT) and Attitude (ATT) play a significant role in directly driving GTB, while Intention (ITN) does not significantly influence behavior.

6. Discussion

The structural model results (Table 5 and Figure 2) confirmed that Environmental Awareness (EA) exerts a strong influence on Perceived Service Quality (PSQ), Green Trust (GT), Attitude (ATT), and Intention (ITN), supporting H1–H4. This finding indicates that travelers with higher environmental awareness tend to perceive airline services as more sustainable and trustworthy, form more positive attitudes, and express stronger intentions toward green air travel. These outcomes align with prior studies emphasizing the role of environmental awareness in shaping pro-environmental attitudes and intentions (Fu et al., 2025; Choi et al., 2019).
PSQ was found to significantly enhance GT (H5), suggesting that airlines demonstrating service quality and transparency in sustainability efforts can strengthen passenger trust—a factor consistent with findings by Schleich and Alsheimer (2024). GT, in turn, significantly predicted Green Air Travel Behavior (GTB) (H6), underscoring that trust in sustainability claims is a key determinant of actual behavioral change (Chien, 2023).
Attitude (ATT) also exhibited a significant positive effect on GTB (H7), supporting the TPB framework which posits that favorable attitudes are a strong precursor to pro-environmental behavior (Chen, 2013). However, Intention (ITN) did not significantly influence GTB (H8), revealing an intention–behavior gap consistent with other studies on sustainable consumption (Chechi & Cottam, 2021; Rouse et al., 2024). This gap suggests that although individuals may intend to behave sustainably, practical constraints such as higher costs, limited availability of green options, or convenience barriers may inhibit behavioral realization.
Overall, the findings extend the TPB by incorporating EA, PSQ, and GT as integral constructs explaining sustainable air travel behavior. The results highlight that awareness and trust are pivotal drivers for transforming environmental concern into tangible actions (Akan et al., 2022). Practically, the study suggests that airlines and policymakers should enhance transparent communication, promote education on sustainability, and design incentive structures to reduce barriers between intention and action such as offering affordable carbon offsetting programs and visible eco-service options.

7. Conclusions

This study extends the Theory of Planned Behavior (TPB) by integrating Environmental Awareness (EA), Perceived Service Quality (PSQ), and Green Trust (GT) to explain Green Air Travel Behavior (GTB) in the context of Thailand’s aviation sector. The findings confirm that EA plays a pivotal role in shaping travelers’ perceptions, attitudes, and trust, which in turn influence their behavioral responses. PSQ enhances green trust, and GT emerges as a strong determinant of actual green travel behavior. Although Intention (ITN) was positively influenced by EA, its effect on GTB was not statistically significant, indicating an intention–behavior gap. This suggests that while travelers may express willingness to engage in sustainable practices, practical constraints such as higher costs, limited green options, or convenience barriers hinder the translation of intentions into action.
Figure 3 visually represents the key findings of the study, which extends the Theory of Planned Behavior (TPB) to explain what drives Green Air Travel Behavior (GTB) in the aviation sector. The diagram illustrates the significant relationships among the variables, highlighting the central role of environmental awareness and the crucial finding of the intention-behavior gap.

Research Limitations

This study has several limitations. First, the sample was limited to airline passengers in Thailand, which may affect the generalizability of the findings. Second, data were self-reported, which could be influenced by social desirability or recall bias. Third, the cross-sectional design captures intentions at a single point in time, limiting causal inference. Future studies could address these limitations by including international travelers, using longitudinal designs, and incorporating objective behavioral measures. Moreover, additional contextual factors such as cultural norms, airline policies, or economic considerations could be explored to deepen understanding of green air travel behavior. Recognizing these limitations provides a foundation for refining research methods and improving the accuracy of conclusions in future studies.

8. Future Research Directions

Based on the findings, several recommendations can be proposed for both practice and future research within the Thai aviation industry. From a practical standpoint, airlines in Thailand such as Thai Airways, Bangkok Airways, and other domestic carriers should emphasize the implementation of visible and accessible green initiatives that reflect the nation’s commitment to sustainable development under the Bio-Circular-Green (BCG) Economy framework. Transparent communication about carbon offset programs, the adoption of sustainable aviation fuels (SAFs), and environmentally friendly in-flight operations can help enhance passengers’ trust and engagement with green air travel.
Moreover, service improvements aligned with sustainability principles such as waste reduction on board, digital ticketing, energy-efficient ground operations, and eco-friendly catering should be prioritized. Policymakers and regulatory bodies, including the Civil Aviation Authority of Thailand (CAAT) and the Ministry of Transport, could support these efforts by offering incentives or tax benefits to airlines adopting green technologies and by launching nationwide awareness campaigns to promote sustainable travel behavior among passengers.
For future research, further studies could explore comparative analyses between domestic and international travelers regarding their perceptions of green air travel or investigate the long-term impact of sustainability communication on passenger loyalty. In addition, research may examine collaborative models among Thai airports, airlines, and tourism organizations to integrate sustainability practices more effectively across the entire air transport ecosystem. These directions would provide deeper insights and support Thailand’s transition toward a more sustainable aviation sector.

Author Contributions

Conceptualization, J.L. and P.T.; methodology, J.L. and P.T.; software, D.S.; validation, J.L. and P.T.; formal analysis, J.L.; investigation, J.L. and D.T.; resources, J.L.; data curation, D.S.; writing—original draft preparation, J.L. and D.S.; writing—review and editing, J.L. and D.S.; visualization, D.T.; supervision, P.T.; project administration, P.T.; funding acquisition, P.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research project was financially supported by Mahasarakham University.

Institutional Review Board Statement

The study was approved the Ethics Committee in Human Research, Mahasarakham University (Approval Code: No. 086-106/2568, date of approval: 17 February 2025).

Informed Consent Statement

Oral informed consent was obtained from all survey participants in April 2025 by the research team. The consent covered study participation, data use, and permission to publish anonymized results. Participants were assured of their anonymity, informed of the study’s purpose, data usage, and notified that no risks were involved.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to privacy and confidentiality agreements with participants.

Conflicts of Interest

The authors declare no competing interests.

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Tourismhosp 06 00232 g001
Figure 1. Conceptual Framework.
Figure 1. Conceptual Framework.
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Figure 2. Results of the structural equation modeling (** p < 0.01., n.s. = p > 0.05).
Figure 2. Results of the structural equation modeling (** p < 0.01., n.s. = p > 0.05).
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Figure 3. Key Research findings.
Figure 3. Key Research findings.
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Table 1. Summarizes the fit statistics of the measurement model.
Table 1. Summarizes the fit statistics of the measurement model.
Saturated ModelEstimated Model
SRMR0.0450.056
d_ULS1.3321.980
d_G0.9821.020
Note: SRMR = standardized root mean squared.
Table 2. Measurement model results.
Table 2. Measurement model results.
ConstructsMeasurement LabelLoadingt-Value
Environmental Awareness (EA) VIF = 1.000; CR = 0.946; α = 0.928; AVE = 0.777EA2. I am aware of the environmental impacts caused by air travel.0.94326.498
EA2. I understand the importance of reducing carbon emissions from flights.0.89720.471
EA3. I stay informed about current environmental policies related to aviation.0.86216.235
EA4. I recognize the role of individual travelers in minimizing air travel’s environmental footprint.0.86819.325
EA5. I am concerned about the effects of climate change caused by greenhouse gas emissions.0.83216.068
Perceived Service Quality (PSQ) VIF = 1.121; CR = 0.934;
α = 0.910; AVE = 0.739		PSQ1. The airline provides clear information about its environmental initiatives.0.959 23.705
PSQ2. The airline offers high-quality services that reflect its commitment to sustainability.0.866 14.475
PSQ3. The in-flight services meet my expectations for eco-friendly practices.0.891 13.854
PSQ4. The airline demonstrates transparency about its carbon offset programs.0.774 12.717
PSQ5. I feel that the airline’s sustainability efforts enhance my overall travel experience.0.794 10.139
Green Trust (GT) VIF = 1.442; CR = 0.978; α = 0.971;
AVE = 0.757		GT1. I trust that the airline’s claims about sustainability are genuine.0.941 32.057
GT2. I believe the airline genuinely cares about reducing its environmental impact.0.914 25.792
GT3. The airline’s environmental policies are reliable and well-implemented.0.943 32.603
GT4. I feel confident that my carbon offset contributions are used effectively.0.985 50.236
GT5. The airline’s green initiatives positively influence my trust in their brand.0.951 32.766
Attitude (ATT) VIF = 1.497; CR = 0.940;
α = 0.920; AVE = 0.757		ATT1. I have a positive attitude toward choosing airlines that prioritize environmental sustainability.0.873 17.192
ATT2. Supporting airlines with green policies is important to me when making travel decisions.0.831 12.205
ATT3. I believe that sustainable air travel is necessary for protecting the environment.0.864 13.692
ATT4. I feel responsible for reducing my carbon footprint when flying.0.913 21.430
ATT5. I am motivated to choose eco-friendly travel options whenever possible.0.868 13.985
Intention (ITN) VIF = 1.153; CR = 0.956;
α = 0.940; AVE = 0.813		ITN1. I intend to select airlines that offer carbon offset programs in my future travels.0.714 7.538
ITN2. I plan to support airlines that demonstrate strong environmental responsibility.0.945 16.295
ITN3. I am willing to change my travel habits to be more environmentally sustainable.0.931 16.035
ITN4. I intend to participate in carbon offsetting when booking flights.0.957 17.311
ITN5. I plan to encourage others to choose sustainable air travel options.0.939 18.633
Green Air Travel Behavior (GTB) CR = 0.971; α = 0.962; AVE = 0.869GTB1. I actively choose flights from airlines with strong environmental commitments.0.934 18.742
GTB2. I participate in carbon offset programs when booking air travel.0.978 26.418
GTB3. I avoid unnecessary flights to reduce my environmental impact.0.960 23.404
GTB4. I prefer airlines that use sustainable aviation fuels or technologies.0.881 11.656
GTB5. I seek information about the environmental performance of airlines before purchasing tickets.0.905 12.030
Note: CR: composite reliability; α: Cronbach’s alpha values; AVE: average variance extract.
Table 3. Discriminant validity—Heterotaint–monotrait (HTMT).
Table 3. Discriminant validity—Heterotaint–monotrait (HTMT).
ConstructEAPSQGTATTINTGTB
Environmental Awareness (EA)
Perceived Service Quality (PSQ)0.353
Green Trust (GT)0.4330.428
Attitude (ATT)0.4550.5790.575
Intention (ITN)0.3400.2130.3030.364
Green Air Travel Behavior (GTB)0.3190.4750.3450.3810.174
Table 4. Discriminant validity using the Fornell–Larcker criterion.
Table 4. Discriminant validity using the Fornell–Larcker criterion.
ConstructEAPSQGTATTINTGTB
Environmental Awareness (EA)0.881
Perceived Service Quality (PSQ)0.329 0.859
Green Trust (GT)0.412 0.4070.947
Attitude (ATT)0.426 0.5320.5430.870
Intention (ITN)0.317 0.1950.2900.3430.902
Green Air Travel Behavior (GTB)0.302 0.4480.3350.3650.1650.932
Table 5. Path analyses (direct effects).
Table 5. Path analyses (direct effects).
Direct EffectPatht-Valuep-ValuesResults
H1EA→PSQ6.441 ***0.000Supported
H2EA→GT8.041 ***0.000Supported
H3EA→ATT8.994 ***0.000Supported
H4EA→ITN5.912 ***0.000Supported
H5PSQ→GT6.097 ***0.000Supported
H6GT→GTB2.935 **0.003Supported
H7ATT→GTB3.616 **0.000Supported
H8INT→GTB0.425 (n.s.)0.671Not supported
Notes: *** p < 0.01; ** p < 0.05; n.s. = p > 0.05.
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MDPI and ACS Style

Laphet, J.; Sanvises, D.; Tandamrong, D.; Tantrabundit, P. Decoding Sustainable Air Travel Choices: An Extended TPB of Green Aviation. Tour. Hosp. 2025, 6, 232. https://doi.org/10.3390/tourhosp6050232

AMA Style

Laphet J, Sanvises D, Tandamrong D, Tantrabundit P. Decoding Sustainable Air Travel Choices: An Extended TPB of Green Aviation. Tourism and Hospitality. 2025; 6(5):232. https://doi.org/10.3390/tourhosp6050232

Chicago/Turabian Style

Laphet, Jakkawat, Dultadej Sanvises, Duangrat Tandamrong, and Pongsatorn Tantrabundit. 2025. "Decoding Sustainable Air Travel Choices: An Extended TPB of Green Aviation" Tourism and Hospitality 6, no. 5: 232. https://doi.org/10.3390/tourhosp6050232

APA Style

Laphet, J., Sanvises, D., Tandamrong, D., & Tantrabundit, P. (2025). Decoding Sustainable Air Travel Choices: An Extended TPB of Green Aviation. Tourism and Hospitality, 6(5), 232. https://doi.org/10.3390/tourhosp6050232

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