Strategic Management of Low Carbon Travel in Longevity Tourism Evidence from Thailand

1. Introduction

Several carbon-intensive sectors connected with the tourism development are the energy production, construction, transportation, and food supply systems. These areas support tourism mobility and cultural and natural attraction development and make tourism be essentially reliant on the energy and resources-intensive activities. It is common that the carbon footprint of tourism so called tourism carbon consumption effects both direct and indirect emissions through the transportation, accommodation and food consumed by the tourists in addition to the production and distribution of goods and services consumed by the tourists (Yang et al., 2022; Zhong et al., 2025; Raihan, 2024b). Low-carbon tourism has originated as one of the important avenues towards realizing carbon neutrality in the tourism sector in response to the mounting environmental pressures. Low-carbon tourism aims at minimizing the emission of GHGs and the utilization of resources without jeopardizing the quality and economic feasibility of tourism. This approach has continued to attract more attention both in academia and the industry by combining environmental sustainability and tourism operations. It is particularly applicable to longevity tourism where prolonged periods of stay and activities that are focused on lifestyles would greatly contribute to cumulative carbon footprint of a destination, unless controlled (Wang et al., 2023; Wan et al., 2025; Mao et al., 2022). This is because the need to embrace low-carbon tourism practices has been compounded by the fact that the world has become more exposed to climatic changes and growing carbon emissions, which pose a threat to tourism destinations. Tourism industry that had earlier been termed as being a low-impact industry or a smoke-free industry is being mentioned as one of the key contributors to carbon emissions to the planet and this has been catalysed largely by the transportation sector, accommodation, and activities, which make part of the lifestyle. The new sustainability issues are further aggravated by the fast growth of longevity tourism, which implies increased periods of stay and wellness tourism and prolonged patterns of consumption, which have increased per-capita emissions in the destinations (Zhan et al., 2025; Hatamifar et al. (2025a,b)). Transportation is the largest contributor to tourism-related emissions, with transportation providing over 75% of total tourism-related CO₂ emission, especially by air and road transportation. Due to the strong impact of the transport options on the total tourism carbon footprint, awareness on tourist travel behavior and mobility patterns is important in finding some effective means of reducing the emission. The measurement of tourism-related CO₂ emission is therefore a critical source of evidence to the formulation of low-carbon travel practices and strategic management interventions that could lessen the environmental effects and contribute to sustainable destination development (Yan & Phucharoen, 2024; Wu et al., 2023). Longevity tourism presents health benefits through long-term stays and wellness lifestyles; however, they can significantly increase carbon emissions due to resource consumption and mobility. Implementing low-carbon travel frameworks that are integrated and behavior-sensitive can help mitigate these environmental impacts in longevity tourism destinations.

2. Related works

Naik et al., (2025) considered variables in determining the selection of eco-friendly tourist by the Indian tourists, emphasizing on the sustainability knowledge, awareness of the carbon footprint, and environmental issues. The research conducted a PLS-SEM analysis to explore the impact of sociodemographic factors and sustainability consciousness on tourism destinations. It found a positive correlation between environmental concern and sustainable travel intentions, with age moderating both the intention-behavior relationship and the link between sustainability consciousness and travel intention. However, the research focus on specific Indian locations can limit the generalizability of its findings. The techniques, important conclusions, and constraints pertinent to the development of sustainable tourism are highlighted in Table 1, which highlights recent research on how tourism, energy usage, and innovation affect carbon emissions.

The recent studies emphasize the complicated correlation between tourism, carbon emissions, and low-carbon developmental policies. For example, Zhou et al. (2025) conducted surveys in Western Australia to determine how tourists make choices about transportation, with variables such as cost, time, and accessibility playing a significant role. However, this study is region-specific and may not be directly applicable to other geographical regions. Another study by Hatamifar et al. (2025a,b) assessed the carbon-neutral travel behavior of young Finnish tourists using questionnaires and found that positive results and social norms significantly influence sustainable behavior in this group. Unfortunately, this study was limited to Finland and may have limited relevance to other settings. Gallego et al. (2025) used composite indicators and carbon measures to evaluate the effects of focusing on low-emission tourism markets economically and ecologically. They concluded that focusing on low-emission markets is financially beneficial, but their study may oversimplify market processes and not consider how tourists will react to such changes. In their study, Pousa-Unanue et al. (2025) focused on the actions of urban tourists in Donostia/San Sebastian and evaluated environmental performance using spatiotemporal data and emissions. They found that nature tourists are the largest CO2 emitters, but this finding is limited by the study’s scope, which only covers one city.

A study conducted by Popović et al. (2025) used the greentripper tool to estimate the amount of carbon emitted by foreign tourists in Serbia, discovering that 80 percent of the carbon emissions were attributed to transportation and that the total carbon footprint was below what the rest of the world approximates. The results of this study, however, rely on national data and fail to consider regional or individual variations. Tsoggerel et al. (2025) used a panel dataset between the years 2000 and 2021 to analyze the implications of sustainable tourism and information and communication technology (ICT) on the quality of the environment in China in terms of its asymmetry. They found a trend with tourism reducing emissions at low, but also high quantiles, but restricting the generalizability of their findings to other countries since the study is centered on China. Over a sample of econometric methods, Raihan (2024a) evaluated the effects of tourism and energy-economic variables on emission levels in Malaysia, thus concluding that tourism and the use of fossil fuels increment production of emissions whereas the use of renewable energy sources reduces them. Nonetheless, geographic or environmental differences that could affect such findings were not taken into consideration in this study. The study by Voumik et al. (2024) looking at tourism’s contribution to CO2 emissions in 40 Asian countries revealed that tourism and renewable energy projects reduce carbon emissions, whereas economic growth and energy consumption produce the opposite effect. However, their conclusions fail to reflect all the regional differences and policymaking.

In a study by Yue et al. (2021) on green innovation and tourism in Thailand, it was found that the two industries have the potential to reduce CO₂ emissions. However, the study has limitations due to its focus on sector-specific and local factors that may not be universal. In a study by Yue et al. (2025) on the impact of Low Carbon City Policies (LCCPs) on urban tourism growth in China, it was discovered that LCCPs effectively boost tourism receipts in urban areas by stimulating markets and enhancing the ecological environment, but the experiments were limited to Chinese cities. Zhao et al. (2024) investigated the effects of tourism development on carbon emission efficiency in 31 cities in China, finding that tourism has a positive influence on efficiency while foreign direct investment (FDI) has a negative influence. However, the city-specific focus of this research may overlook external factors that could impact the results. In a study by Janchai and Suvittawat (2025), surveys and structural equation modeling were used to assess tourists’ preferences for low-carbon destinations, revealing that destination characteristics and marketing activities significantly influence tourists’ perceptions and decision-making. Nevertheless, the reliance on self-reported data and the focus on a single location raise questions about the generalizability of these results.

In addition, a quantitative assessment of the CO₂ emissions of the Chinese tourism industry was conducted by Chen et al. (2022). They found that the increase in emissions did not correspond to a decrease in intensity, but rather significant regional trends. However, the aggregated information method can mask information at the city level. Similarly, Tong et al. (2022) demonstrated the role of tourism in carbon drawdown in 92 Chinese cities. They found that tourism produced a net positive effect on carbon dioxide emissions, but the adoption of structural equation modeling did not allow them to examine non-linear relations and spatial transformations. Khiaolek et al. (2025) also revealed the potential for greenhouse gas (GHG) reduction in tourist destinations like Chiang Mai, Thailand. This was acknowledged through surveys and gap analysis, providing an overall greenhouse gas reduction potential of 15,304.72 tCO2eq to be achieved in Chiang Mai, especially through the use of solar energy. However, since they focused on one province, their findings may be limited in wider applicability. Fakfare and Wattanacharoensil (2024) suggested specific low-carbon tourist segments using cluster analysis and a survey, but their study was restricted to domestic tourists, limiting the applicability of the findings to international settings. In a hybrid life cycle assessment, Platts et al. (2023) found the carbon footprint of visitors to 16 UNESCO World Heritage Sites and produced trip-wise footprint data that may be more useful in communicating climate impact. However, their results may not be widely applicable to a broader range of tourism sites due to their UNESCO-centric focus. Finally, Guo et al. (2025) interviewed tourists in Macao about their carbon awareness using a special questionnaire. They found that a significant portion of tourists are at the initial level of carbon awareness, with their Carbon Action activities contributing to some of them. The results, however, are limited by the localized nature of the study and would require cross-cultural validation. All of these studies highlight the complex relationship between tourism and carbon emissions, showing unique patterns and issues, as well as the need for further investigation in various settings to develop successful low-carbon strategies in the tourism industry (Nathaniel et al., 2023).

3. Research design

The research evaluates the long-term tourism industry carbon footprint of Thailand using a mixed-method approach. The structured survey and travel activity records of longevity tourists were used to gather primary data, whereas national energy and tourism databases were used to obtain secondary data on the factors of emissions. The carbon footprint analysis of the carbon emissions was done through an LCA and the analysis of the changes in lodging, transportation, food, and the activities was done using one-way ANOVA and descriptive statistics. Figure 1 depicts the general research framework for evaluating low-carbon behaviors and carbon footprint in Thai longevity tourism.

Figure 1. Research framework for assessing low-carbon practices and carbon footprint in Thai Longevity Tourism.

4. Result

Research of the travel preferences of longevity tourists found out that most of them liked local means of transport and mid-range and energy efficient accommodation. The descriptive statistics and One-Way ANOVA indicates that the nature of lodging and mode of transport are the two most important factors that lead to carbon emission. Prolonged occupancy paired with eating and exercising options that are sustainable can reduce the emission per capita to a considerable degree. The thematic study indicates that low-carbon behaviors such as environmentally-friendly hotel, environmentally-friendly transportation preferences, and environmentally-friendly lifestyle experiences are taken by longevity tourists. These behaviors are all helped by infrastructure, policy assistance, renewable energy experiences and eco-awareness. These results show that deliberate low-carbon travel methods can successfully reduce the environmental impact without affecting the satisfaction of tourists.

4.1 Demographic distribution

The demographic distribution of the 450 responses is shown in Table 2, which reveals a balanced gender distribution with a small male predominance. Most longevity travellers are 55 years of age or older due to the senior-focused nature of long-term wellness travel. The fact that foreigners make up most visitors highlights Thailand’s allure as a long-term tourism destination. Long stays and wellness-focused travel choices are encouraged by the sample’s high level of education and middle-class to upper-class demographics. A significant portion of travellers stay longer than a month to assess carbon emissions and low-carbon travel activities. The demographics of longevity tourism respondents, including (a) gender distribution, (b) age group distribution, (c) nationality composition, (d) education level, and (e) duration of stay, are shown in Figure 2.

Table 2. Demographic distribution of longevity tourists (n = 450).

Demographic variable	Category	Frequency (n)	Percentage (%)
Gender	Male	238	52.9
	Female	212	47.1
Age Group (Years)	45–54	96	21.3
	55–64	168	37.3
	65–74	142	31.6
	≥75	44	9.8
Nationality	Domestic (Thailand)	182	40.4
	International	268	59.6
Education Level	Secondary or below	68	15.1
	Undergraduate	184	40.9
	Postgraduate	198	44.0
Length of Stay	< 1 month	92	20.4
	1–3 months	173	38.4
	3–6 months	121	26.9
	> 6 months	64	14.3

Figure 2. Demographic characteristics of longevity tourism respondents: (a) Gender, (b) Age Group, (c) Nationality, (d) Education Level, (e) Length of Stay.

4.2 LCA-based carbon footprint analysis

According to the LCA-based carbon footprint analysis, lifestyle decisions, activities, and strategic awareness have less of an impact on emissions in longevity tourism than transportation and lodging shown in Table 3 and Figure 3. The adoption of renewable energy, energy-efficient accommodation, and sustainable transportation are only a few of the important areas where low-carbon interventions can successfully lower the overall carbon footprint when emissions are categorized by major themes.

Table 3. LCA-based carbon footprint of longevity tourism activities in Thailand (per capita, kg CO₂ e).

Main theme	Category	Average carbon emissions (kg CO2 e)
Low-Carbon Travel Behavior	Transportation	347
Sustainable Accommodation Choices	Accommodation	160
Low-Carbon Lifestyle Adoption	Diet & Activities	42.5
Strategic Awareness and Support	Renewable Energy & Infrastructure	50

Figure 3. LCA-based comparison of carbon emission drivers in longevity tourism.

4.4 One-Way ANOVA

According to the One-Way ANOVA findings in Table 5 and Figure 4, there are significant differences in the amount of carbon emissions among the essential travel factors, such as lodging, transport, food preference, and strategic awareness $\left(p<0.01\right).$ Public transportation, eco-certified housing, and plant-based diets generated the lowest emissions, while air travel and traditional hotels had the highest. This indicates opportunities for implementing low-carbon strategies in longevity tourism.

Table 5. One-Way ANOVA of carbon emissions by key travel factors (n = 450).

Main theme	Sub-group	Mean (kg CO2 e)	F−value	p−value	Significance
Low-Carbon Travel Behavior	Air travel	950	28.45	<0.001	Significant
	Private vehicle	420
	Public transport/walking/cycling	90
Sustainable Accommodation Choices	Hotel/Resort	210	19.32	<0.001	Significant
	Serviced Apartment	150
	Eco-certified hotel	90
Low-Carbon Lifestyle Adoption	Standard diet	60	12.87	<0.001	Significant
	Plant-based/local diet	25
Strategic Awareness and Support	Low awareness	90	10.12	0.006	Significant
	High awareness/policy support	50

Figure 4. One-Way ANOVA–based comparison of carbon emissions in longevity tourism.

4.5 Thematic analysis

The thematic analysis shows that the low-carbon travelling behavior such as the eco-friendly living that is reported in Table 6 and Figure 5 is being adopted by longevity travellers. The knowledge and availability of renewable energy in the region enhances travel satisfaction and destination loyalty. These insights underscore the significance of intentional low-carbon management to reduce emissions while maintaining Thailand’s appeal as a long-term vacation spot.

Table 6. Thematic analysis of low-carbon practices in longevity tourism.

Main theme	Sub-theme	Short description
Low-Carbon Travel Behavior	Sustainable transport preference	Tourists preferred public transport, walking, and cycling to reduce travel-related emissions.
	Environmental awareness	Transport choices were influenced by concern for carbon reduction.
Sustainable Accommodation Choices	Energy-efficient lodging	Preference for eco-certified and energy-saving accommodations during long stays.
	Comfort with sustainability	Visitors valued comfort and wellness alongside low-carbon features.
Low-Carbon Lifestyle Adoption	Local and plant-based diets	Adoption of low-carbon food choices for health and environmental benefits.
	Low-impact activities	Interest in walking tours and locally organized, low-emission activities.
Strategic Awareness and Support	Renewable energy awareness	Awareness of renewable energy use enhanced destination image and trust.
	Policy and infrastructure support	Demand for better low-carbon infrastructure and information support.

Figure 5. Thematic framework of low-carbon practices in longevity tourism in Thailand.

5. Discussion

Current low-carbon tourism and carbon footprint studies have yielded results that are not as extensive because they have a variety of limitations. The high level of reliance on self-reported data on travel activities and focus on specific geographic locations can introduce response bias and make findings not as generalizable to other tourism settings (Janchai & Suvittawat, 2025). Moreover, it is constrained by the nature of the SEM due to its common usage in SEM which generally provides descriptive information only (Tong et al., 2022). Moreover, it needs to be cross-cultural and multi-regional to ensure it is applicable to more than just domestic tourism within any one country such as Thailand as research carried out in a single country such as Thailand cannot give the true picture of the travelling habits and emission patterns of the international longevity tourists (Fakfare & Wattanacharoensil, 2024; Guo et al., 2025).

The research offers detailed, context-sensitive information going beyond the classical low-carbon tourist research through assessing longevity tourism in Thailand through an LCA-based carbon footprint model. It integrates both statistical analysis and process-based emission accounting to show how the long-term travel patterns, accommodation choices and mode of transportation lead to measurable carbon outputs. This form of synergy reduces the impact of the longevity tourism on the environment without having an impact on the wellbeing of the tourists and can strategize the low carbon travel and provides a model that can be tested and altered in other geographic and cultural locations (Raihan, 2024a, 2024b).

6. Conclusion

To estimate the carbon footprint of longevity tourism in Thailand and give strategic suggestions on how to promote low-carbon tourism and retain the satisfaction of tourists. The research employed a mixed method design to collect survey data on 450 longevity visitors and applied one-way ANOVA, thematic analysis, descriptive statistics and carbon footprint analysis based on the LCA. The average per-capita carbon footprint according to the results was 582 kg CO2e, housing (160 kg CO2e) and transportation (347 kg CO2e) were the highest contributors. The extensive differences in emissions were observed in the type of housing, activity patterns, food habits, and the choice of the mode of transportation $\left(p<0.001\right).$ Thematic analysis indicates that low-carbon practices, green lodging, veganism, low-impact activities, and green energy awareness significantly influence travel decisions. To enhance sustainable tourism, deliberate low-carbon interventions, optimized infrastructure, and behavioral coaching are essential.