From Awareness to Stated Willingness to Pay: A Mixed-Methods Study of Self-Reported Sustainable Travel Practices and Social-Digital Influence among Young Indonesian Consumers

Abstract

COPYRIGHT © 2026 Armielia and Listiana. Sustainable tourism research has concentrated on awareness, ethical behaviour, This is an open-access article and the willingness to pay separately; so far little is known about how these factors distributed under the terms of connect to social-digital influence and perceived barriers in young Indonesian the Creative Commons consumers. We have used a cross-sectional, quantitative-dominant embedded Attribution License (CC BY). The mixed-method design. After convenience sampling, we have 115 valid responses use, distribution or reproduction from Indonesian consumers aged 18 to 29 years old and selected from the eligible in other forums is permitted, sample. We analyze the quantitative data using descriptive statistics, reliabilityprovided the original author(s) and the copyright owner(s) are checks, Pearson correlation, multiple regression, and embedded open-ended credited and that the original responses to understand and contextualize the statistics. Awareness was the publication in this journal is strongest predictor of self-reported sustainable travel habits (β = .433, p < .001) cited, in accordance with and the model explained 40.1% of the variance (R² = .401). The stated willingness accepted academic practice. No to pay was predicted by self-reported sustainable practices (β = .215, p = .030) and use, distribution or reproduction social-digital influence (β = .316, p < .001). The model explained 37.2% of theis permitted which variance (R² = .372). Qualitative findings indicated that affordability, access,does not comply with these terms. credible information and visible environmental or community benefits shaped respondents' willingness to support sustainable options. The findings suggest that awareness does not translate directly into financial commitment and social-digital influence is an important link between sustainable engagement and stated willingness to pay. The convenience sample, regional concentration and reliance on self-reported measures makes it a very cautious approach.

Introduction

Figure 1. Conceptual Framework of the Study

reported generally favorable views of sustainable tourism among young Indonesian tourists, but the extent to which this understanding affected travel behavior was less apparent. Indonesian green hotels have also been studied; positive green aspects and trust do not necessarily mean travelers are willing to pay a premium (Gunawan et al., 2023; Wiastuti et al., 2022). At the same time, digital information is becoming a part of the decision-making process for young travelers. Zahrudy et al. (2025), for example, found that user-generated content, word-of-mouth, firm-generated content, and electronic word-of-mouth influenced destination perception of young tourists to Indonesian cultural heritage destinations.

These studies highlight an important issue: sustainability awareness, responsible behavior, willingness to pay, and digital influence have emerged as closely related but distinct streams of tourism research in Indonesia.

This separation creates both an empirical and theoretical gap. Empirically, there is little proof of whether young Indonesian consumers who understand sustainable tourism are also contributing to their own sustainable activity and, as importantly, whether that engagement is associated with a willingness to accept financial trade-offs. Most existing Indonesian research has focused primarily on specific products (such as green hotels) or on specific aspects of sustainable and

We do not assume that such perspectives are interchangeable or that the whole TPB model is tested. Rather, TPB provides an insightful behavioral framework for the understanding of why positive orientation may or may not appear in the reported practices, and attitude-behavior gap perspectives point to disconnections between what consumers value and what they report doing. In reality, perceived barriers relate to economic, informational, infrastructural, and practical constraints that are conceptualized as behavioral control but are here seen as contextual constraints rather than as the substitute for perceived behavioral control. Social influence theory takes into account the social and digital environment in which people make travel choices today and willingness-to-pay literature is a way to understand that positive attitudes are not the only relevant, but rather financial commitment is as well. The Value-Belief-Norm (VBN) perspective is a complementary lens to consider how sustainability-based values and beliefs can guide personal behavior and environmental behavior (Stern, 2000). Indeed, in this study we do not have the entire sequence of VBNs but this can be used to see how sustainable thinking can guide behavior as well as financial commitments.

In this perspective awareness is the perception of the environmental and social implications of tourism, so that consumers are aware of the environmental and social impact. Previously, environmental knowledge and sustainability awareness can promote good attitudes and responsible behavior (Aydın & Alvarez, 2020; Myung, 2018). But recent reviews warn against a linear path from knowledge to action. Sustainable tourist behavior is influenced by psychological, social, economic, and contextual factors (Hansen et al., 2024; Li et al., 2024). Consumers may accept the necessity of waste reduction, resource conservation, local purchasing, and environmental protection, but price, convenience, accessibility, and comfort are part of the equation when it comes to travel decisions.

This tension is represented in the attitude-behavior and intention-behavior gap literature. Hansen et al. (2024) and Wut et al. (2023) show that positive intentions towards sustainable tourism do not produce real behavior and Nieto- García et al. (2024) caution that attitudes and intentions can overestimate consumers' true commitment to sustainability. Liu-Lastres et al. (2025) and mixed methods with younger generations also showed that sustainable intentions and travel behavior are not linked in the same way and that cost, resources, and knowledge are all key constraints. Ultimately, awareness is imperative but may not be enough when sustainable alternatives have practical or economic implications.

Willingness to pay is a more difficult engagement since consumers must accept an economic cost. Sustainable accommodation, certification, community-based tourism, and greener hospitality research have shown that willingness to pay is not only about environmental concern but also about price sensitivity, perceived value, trust, service quality, and visibility of sustainability benefits (Boronat-Navarro & Pérez- Aranda, 2020; Damigos, 2023; Kang & Nicholls, 2021;

This disconnect may be explained by perceived barriers. Higher prices, limited availability, inadequate infrastructure, inconvenience, unclear certification, and limited information do not make sustainable choices accessible to even consumers who are committed to sustainability. Tölkes (2020) argues that communication alone will not close the attitude and behavior gap when it is unclear whether responsible options are even possible or affordable. So barriers may be different from awareness: consumers may not only see sustainability as good but also see the major obstacles in the market. It is especially relevant in the Indonesian context, where the availability and visibility of sustainable tourism products differ across destinations.

Social-digital influence adds another layer to the process. Younger consumers increasingly use social media, online reviews, influencers, booking platforms, friends and family to make decisions about traveling. These sources can shape not only destination awareness, but also perceived credibility, social norms and whether or not an extra cost appears to be justified. Bae and Han (2020) illustrate the importance of trustworthy online reviews in sustainable hotel booking and Tanford et al. (2020) demonstrate how social-media framing can influence sustainable hotel choice. Indonesian research also finds digital content and social validation to play a key role in young tourists’ destination perceptions and experiences (Zahrudy et al., 2025). Thus, social-digital influence might matter at different stages: it can impact sustainability efforts and consumers’ perception of sustainable products as credible and valuable enough to give money to.

These concerns also apply to younger consumers. Young travelers who are very concerned about the environment and spend a lot of time and money on digital information are often more financially constrained, but with less money and travel options. Studies have found that sustainable intentions of younger tourists are related to environmental attitudes, personal and social norms, and destination images (D’Arco et al., 2025; Nowacki et al., 2023; Schönherr & Pikkemaat, 2023). On the other hand, new research suggests that younger travelers are a sustainability paradox of their own: they might be interested in sustainable tourism but may struggle to uphold that wish when price, availability, convenience or infrastructure are a major problem (Liu-Lastres et al., 2025; Seyfi, Hall, & Strzelecka, 2025; Seyfi, Hall, Saarinen, et al., 2025). Indonesian evidence suggests that understanding sustainable tourism does not automatically settle how young consumers behave or what they are willing to pay.

To position the present study more precisely, Table 1 compares it with the closest Indonesian and international research.

This comparison shows that the novelty of the present study does not rest simply on adding several established variables to one model. Rather, it lies in connecting three strands that have generally remained separate: the movement from sustainability awareness to reported practice, the movement from practice to stated financial commitment, and the social-digital and contextual conditions surrounding those movements. The embedded mixed-methods design adds a further analytical layer by using consumers’ own explanations of affordability, accessibility, credibility, and perceived benefits to interpret the quantitative relationships. In this sense, the study examines whether sustainable engagement among young Indonesian consumers can be understood as a straightforward

Based on this framework, sustainable travel awareness, perceived barriers, and social-digital influence are examined in relation to self-reported sustainable travel practices. Awareness, sustainable practices, perceived barriers, and social-digital influence are then examined in relation to stated willingness to pay. The proposed relationships are presented in Figure 1.

The study also addresses three complementary research questions. RQ1 asks: What are the levels of sustainable travel awareness, self-reported sustainable travel practices, perceived barriers, social-digital influence and stated willingness to pay among young Indonesian consumers? RQ2 asks: How are these constructs related, and to what extent do awareness, perceived barriers, and social-digital influence predict self-reported sustainable travel practices, and awareness, practices, barriers and social-digital influence predict stated willingness to pay? RQ3 asks: How do young consumers explain the barriers that restrict sustainable choices and the conditions that would encourage them to choose and financially support sustainable travel alternatives?

Similarly the study has three different objectives. It identifies the levels of the five study constructs among young Indonesian consumers. Explanatorily, it explores their relationship and tests to what extent they predict self-reported sustainable travel practices and willingness to pay. Qualitatively, it examines how consumers explain barriers, enabling conditions, and expectations around sustainable travel choices. The cross-sectional, quantitative-dominant embedded mixed-methods design is used, with the qualitative responses integrated into the predominantly quantitative study to clarify and contextualize the patterns identified in the statistical analysis.

The study contributes conceptually; it brings behavioral engagement, contextual constraints, social-digital influence and financial commitment into the picture, rather than treating awareness or willingness to pay as independent variables. Methodologically, it combines regression-based evidence and consumers’ explanations of decisions made based on the conditions that made them say they made with respect to their stated choices. This approach is also helpful for tourism businesses and destination managers in managing issues related to awareness, credibility, affordability, accessibility and digital communication in order to differentiate between problems of awareness, credibility, accessibility and digital communication to develop sustainable tourism products for younger consumers.

Methods

For this study, we used a cross-sectional and quantitative- dominant embedded mixed-methods approach to explore sustainable travel awareness, self-reported sustainable travel practices, perceived barriers, social-digital influence and willingness to pay among young Indonesian consumers. The quantitative component was the main strand and the qualitative component was added to explain patterns that could not be explained by the statistical data alone.

Both types of data were provided at the same time in an online questionnaire. The quantitative information was used to define the study constructs, to analyze their relationships and to test the hypotheses. The open-ended questions were about the practical conditions of sustainable travel for a tourist which involve affordability, access, information, credibility, convenience and the expected actions of tourism

The integrations are planned from the beginning of the survey as the open-ended questions were created to complement the quantitative ones. The two forms of evidence were integrated into the interpretation process and presented together in the Results. Qualitative findings were used not only to confirm statistical results but also to increase or qualify them, particularly when perceived barriers were frequently mentioned by respondents and did not stand out as credible independent predictors in the regression models. This is consistent with mixed-method applications in sustainable tourism research (Molina-Azorín & Font, 2016).

We selected two regression models that fit the hypotheses proposed in the Introduction. The first looked at sustainable travel awareness, perceived barriers, and social-digital influence as predictors of self-reported sustainable travel practices (H1, H4, and H6a) whereas the second studied awareness, sustainable travel practices, perceived barriers, and social-digital influence as predictors of stated willingness to pay (H2, H3, H5, and H6b)

The operational population consisted of Indonesian consumers aged 18-29 years. Recent travel frequency was recorded to describe respondents’ travel experience but was not used as an eligibility condition. So the study looks at young consumers' perception of sustainable travel rather than simply those of frequent travelers. Four respondents in the final sample did not travel at all in the last 12 months and were included as they answered the questionnaire based on awareness, perceptions and stated consumer choices rather than travel behavior alone.

The participants were recruited by way of university and professional networks using convenience sampling. We could not perform probability sampling because we did not have a sampling frame that could identify the young Indonesian consumers throughout the age group of interest. Network- based approach was useful for the target age group but also resulted in possible selection and coverage bias. The results should be taken as representative of the sample obtained rather than as a national representation for all young Indonesian consumers.

The input in the exported survey file had 127 respondents. Three of the responses were submitted after the data collection period of July 13-16, 2026, and were excluded as out-of- window responses. That left 124 responses collected throughout the study period. Nine individuals aged 14-17 years were then excluded because they did not meet the adult eligibility criteria. The final analysis sample was therefore 115 people aged 18-29 years.

There were no missing responses in 25 quantitative items or the three open-ended questions for which data was reviewed. There were never duplicate records for the data. Because the invitation was sent through the network-based online channels, the total number of people who received or saw it was not known. A conventional response rate and the formal assessment of non-response bias was thus not possible. No attention check item was used, so inattentive responses cannot be ruled out completely.

A power analysis had not been performed prior to recruitment. The sensitivity calculation in the revision showed that the larger model, with 115 respondents, four predictors, and α = 0.05, had 80% power to detect an effect of about f² = .108 or more. For comparison, a standard medium effect of f² = .15 would require about 85 respondents. The sample size thus was sufficient to detect medium effects but may have been poorly sensitive to small effects (Cohen, 1992; Faul et al., 2009).

The study was conducted online in Indonesia through Google Forms rather than at a specific tourism destination. Respondents came from several provinces, although the sample was concentrated in Banten, Jakarta, and West Java.

The questionnaire contained demographic and travel- profile questions, 25 Likert-scale items, and three open- ended questions. Demographic and travel information included age, gender, province, occupation, travel frequency during the previous 12 months, and primary type of travel.

The quantitative instrument was developed by the researchers based on the existing literature and English- language measures rather than adopted verbatim from a single established scale. Item content relating to awareness and responsible travel practices was informed by research on sustainable tourism knowledge and behavior (Aydın & Alvarez, 2020; Hansen et al., 2024; Li et al., 2024; Myung, 2018). Barrier items reflected affordability, accessibility, information, and practicality concerns discussed in the sustainable- tourism literature (Liu-Lastres et al., 2025; Tölkes, 2020). Social-digital items drew on research concerning social media, online reviews, interpersonal influence, and sustainable tourism decisions (Bae & Han, 2020; Tanford et al., 2020). Willingness-to-pay items were informed by studies of sustainable accommodation and tourism price premiums (Boronat-Navarro & Pérez-Aranda, 2020; Damigos, 2023; Kang & Nicholls, 2021).

The item pool originated from English-language measures and literature and was translated and contextually adapted into Bahasa Indonesia for the survey. The wording was adjusted to make the items natural and understandable in the Indonesian travel context. No formal expert-panel review or pilot study was conducted before the main survey. The study therefore does not claim that the researcher-developed instrument had undergone full psychometric validation. This limitation is acknowledged when interpreting the findings, particularly for constructs with lower internal consistency. The full administered questionnaire should be provided in Appendix A or as supplementary material so that the measures can be evaluated and replicated.

The quantitative items were rated on a five-point scale from 1 (strongly disagree) to 5 (strongly agree). Five items measured each of the following constructs: sustainable travel awareness, self-reported sustainable travel practices, perceived barriers, social-digital influence, and stated willingness to pay.

The three open-ended questions asked respondents about difficulties in practicing sustainable travel, factors that would encourage them to choose sustainable alternatives, and actions expected from tourism businesses and destination managers.

Internal consistency was assessed using Cronbach's alpha, corrected item-total correlations, and alpha-if-item- deleted statistics. A coefficient of .70 was used as the preferred benchmark for Cronbach's alpha, while corrected item-total correlations around .30 or higher were treated as evidence that an item contributed meaningfully to its scale. Items were not deleted solely to maximize alpha because the five-item constructs were designed to capture theoretically relevant aspects of each concept.

Participation was voluntary. Before completing the questionnaire, respondents were provided with information about the purpose of the study, confidentiality, and the academic use of their responses. The intended analytical sample was restricted to respondents aged 18–29 years. However, because age was collected within the questionnaire rather than through a pre-survey eligibility gate, nine respondents aged 14–17 years were able to complete the survey. As parental or guardian consent had not been obtained, these nine records were excluded from all quantitative and qualitative analyses, segregated from the analytical dataset, and were not included in the reporting of

Formal documentation concerning the institutional ethical status of the study was not available at the time of manuscript revision. Accordingly, the manuscript does not claim that prior institutional ethical approval, exemption, or waiver had been obtained. Any subsequently issued institutional determination will be reported using the committee’s official designation, reference number, date, and stated approval or exemption status.

Data were collected through Google Forms from July 13 to July 16, 2026. The survey invitation was distributed through university and professional networks. Before completing the questionnaire, respondents received information about the purpose of the study, voluntary participation, confidentiality, and the academic use of their responses. No financial or material incentive was provided.

The raw export contained three responses submitted after the intended collection window, on July 19 and July 21. These responses were excluded before analysis. The remaining 124 in-window submissions were screened for age eligibility, completeness, and exact duplication.

Age was collected as part of the questionnaire rather than through an automated eligibility gate before respondents entered the substantive survey. As a result, nine respondents aged 14–17 years were able to complete the questionnaire. These cases were excluded from all quantitative and qualitative analyses because parental or guardian consent had not been obtained. This is acknowledged as a procedural limitation. Future use of the survey should employ an age-screening gate before consent and before access to the questionnaire.

Frequencies and percentages were used to describe respondent characteristics. Means and standard deviations summarized individual items and construct scores. Composite scores were calculated by averaging the five items within each construct.

Although individual Likert items are ordinal, the analyses were conducted on five-item averaged composite scores. These multi-item scores were treated as approximately continuous for Pearson correlation and multiple regression.

Internal consistency was examined using Cronbach's alpha, corrected item-total correlations, and alpha-if-item-deleted statistics. Because the awareness and self-reported practice scales produced coefficients below .70, results involving these variables were interpreted cautiously.

Pearson correlation was used to examine bivariate relationships among the five constructs. Two multiple regression models were then estimated in line with the conceptual framework and hypotheses. Model 1 examined awareness, perceived barriers, and social-digital influence in relation to self-reported sustainable travel practices. Model 2 examined awareness, sustainable travel practices, perceived barriers, and social-digital influence in relation to stated willingness to pay.

Regression assumptions were examined before interpreting the coefficients. Linearity and model form were assessed using residual plots and the Ramsey RESET test. Residual normality was examined using Q–Q plots and the Shapiro–Wilk test. Homoscedasticity was assessed with the Breusch–Pagan test. Multicollinearity was evaluated using variance inflation factors (VIF) and tolerance values. Potentially influential observations were examined using Cook's distance and studentized residuals, while independence of errors was assessed using the Durbin–Watson statistic.

The diagnostic analysis showed heteroscedasticity in the self-reported-practices model. HC3 heteroscedasticity-robust standard errors were therefore used for Model 1. The willingness-to-pay model did not show heteroscedasticity, although the Shapiro–Wilk test indicated a small departure

Regression coefficients, standard errors, standardized beta coefficients, t values, p values, R², and adjusted R² were reported. Statistical significance was set at p < .05. Because the data were cross-sectional and self-reported, all regression relationships were interpreted as associations rather than causal effects.

All 115 respondents replied to the three open-ended questions. The responses were analyzed thematically. Most of the analysis was inductive, but the questions themselves offered a lot of organizing space around barriers, enabling conditions, and tourism management actions.

Both authors read and coded the open-ended responses independently. The codes were initialized in a working codebook and then grouped into various categories and themes. In the end, the authors compared their interpretations after independent coding. They discussed differences and reached consensus and refined the codebook.

The inter-rater coefficients were not calculated as the final analysis was consensus coding. A single response could express several relevant ideas at the same time. For example, one respondent could mention higher prices, limited transportation, and insufficient information. The frequencies of themes do not mean the number of respondents talking about a particular theme and cannot be taken as exclusive.

Since the qualitative part was very brief written responses instead of a series of interviews, we did not consider theoretical saturation. The information was considered as it was repeated by all respondents and less frequent but meaningful views were also there. Quotations were chosen for their clarity, representativeness, and explanatory value and not simply because they were selected to be part of the most commonly mentioned themes. Appendix B: Coding examples of raw responses, codes, categories, and final themes.

Integration occurred at both the design and interpretation stages. At the design stage, the open-ended questions were embedded in the same questionnaire to explore conditions that could help explain the quantitative constructs. At the interpretation stage, quantitative findings were compared directly with supporting, expanding, or apparently contradictory qualitative evidence.

A joint display was used to make these relationships explicit. For example, the nonsignificant independent regression effect of perceived barriers was considered alongside frequent qualitative accounts of cost, access, facilities, and information problems. Similarly, the statistical importance of social-digital influence was interpreted together with respondents' requests for credible information, certification, transparent communication, and trustworthy digital promotion. Integration therefore affected the interpretation of the findings rather than simply placing quantitative and qualitative results side by side.

Result and Discussion

The exported survey file contained 127 submissions. Three responses were submitted after the stated data- collection period of July 13–16, 2026 and were excluded before analysis. Of the remaining 124 responses, nine were from participants aged 14–17 years and were excluded because they did not meet the adult eligibility criterion. The final analytical sample therefore consisted of 115

Most respondents were aged 22–25 years (57.4%), followed by those aged 18–21 years (22.6%) and 26–29 years (20.0%). Women represented 57.4% of the sample and men 42.6%. Private-sector employees formed the largest occupational group (39.1%), followed by students (35.7%), civil servants (17.4%), and entrepreneurs (7.8%). Leisure was the main type of travel for 80.9% of respondents. Geographically, the sample was concentrated in Banten (29.6%), Jakarta (25.2%), and West Java (24.3%), with 20.9% coming from other provinces.

Table 2 presents the descriptive statistics and internal consistency of the five constructs. Self-reported sustainable travel practices had the highest mean (M = 4.49, SD = 0.45), followed by sustainable travel awareness (M = 4.39, SD = 0.49) and social-digital influence (M = 4.25, SD = 0.59). Perceived barriers had a mean of 3.87 (SD = 0.67), while stated willingness to pay had the lowest construct mean at 3.82 (SD = 0.74). These values are reported descriptively rather than classified as “high” or “low” because no external cut-off criteria were used.

The willingness-to-pay scale showed the strongest internal consistency (α = .865), followed by perceived barriers (α = .751). Social-digital influence was close to the preferred .70 benchmark (α = .695). Awareness (α = .649) and particularly self-reported sustainable travel practices (α = .593) showed weaker internal consistency and are therefore treated more cautiously in the analyses that follow.

For awareness, the corrected item-total correlations ranged from .231 to .589. The item concerning the importance of reducing waste had the lowest corrected item-total correlation (.231); removing it would have increased alpha only modestly from .649 to .661. For the sustainable-practices scale, corrected item-total correlations ranged from .311 to .422, and removing any individual item would have reduced rather than improved the overall alpha. The five practice items were therefore retained because each represented a theoretically relevant form of sustainable travel practice, but the composite is treated as exploratory rather than as a fully validated homogeneous scale.

The exploratory factor checks supported this cautious interpretation. For awareness, sampling adequacy was acceptable but modest (KMO = .682), and Bartlett's test was significant, χ²(10) = 89.37, p < .001. One-factor principal-axis loadings ranged from .296 to .807. For self-reported sustainable travel practices, KMO was .665 and Bartlett's test was also significant, χ²(10) = 68.43, p < .001, with one-factor loadings ranging from .430 to .615. A second eigenvalue for the practice items was only slightly above 1.0 (1.013), suggesting that the scale may capture related but not fully identical forms of sustainable practice. No post-hoc item splitting was undertaken because doing so with this relatively small exploratory sample could overfit the data.

At the item level, respondents reported particularly strong agreement with reducing waste during travel (M = 4.77), ensuring that tourism benefits local communities (M = 4.61), complying with environmental regulations (M = 4.78), and avoiding activities that might harm animals, natural environments, or local communities (M = 4.75). By comparison, willingness to pay more for environmentally responsible accommodation had a mean of 3.38, while willingness to choose a sustainable alternative when it cost slightly more had a mean of 3.61. These differences are descriptive and should not be treated as direct evidence of an attitude–behavior gap because the constructs measure different content and were all self-reported

Self-reported sustainable travel practices were positively associated with social-digital influence (r = .470, p < .001) and stated willingness to pay (r = .490, p < .001). The strongest bivariate relationship with stated willingness to pay was social-digital influence (r = .516, p < .001).

Perceived barriers were positively correlated with self- reported sustainable travel practices (r = .300, p = .001), social-digital influence (r = .265, p = .004), and stated willingness to pay (r = .270, p = .004). Item coding was checked against the raw data, and higher barrier scores consistently represented stronger perceived barriers; the positive correlations were therefore not caused by reversed item coding. Their substantive meaning is considered in the Discussion rather than interpreted here (see Table 3).

Regression assumptions were examined before interpreting the two models. The Ramsey RESET tests did not indicate misspecification for either the self-reported-practices model, F(1, 110) = 1.59, p = .210, or the stated-willingness- to-pay model, F(1, 109) = 0.83, p = .366.

There was no evidence of problematic multicollinearity. VIF values ranged from 1.110 to 1.276 in the first model and from 1.133 to 1.669 in the second, while tolerance values remained between .599 and .901. Durbin–Watson values were 2.016 and 1.998, respectively, suggesting no evident dependence among residuals.

Residual normality was acceptable for the self-reported- practices model (Shapiro–Wilk W = .982, p = .134). The willingness-to-pay model showed a small departure from normality (W = .976, p = .040). The Breusch–Pagan test indicated heteroscedasticity in the practices model (LM = 17.01, p < .001) but not in the willingness-to-pay model (LM = 2.89, p = .576). HC3 robust standard errors were therefore used for the first model. Maximum Cook's distances were .154 and .207, respectively. Neither approached 1.0, and inspection did not identify data errors that would justify removing the cases.

The first regression model examined awareness, perceived barriers, and social-digital influence in relation to self-reported sustainable travel practices. The model explained 40.1% of the variance in reported practices (R² = .401, adjusted R² = .385). With HC3 robust standard errors, the overall model remained statistically significant, F(3, 111) = 16.53, p < .001.

Sustainable travel awareness showed the strongest statistical relationship with self-reported practices (B = .393, SE = .073, β = .433, t = 5.372, p < .001). Social-digital influence was also positively associated with reported practices (B = .189, SE = .077, β = .250, t = 2.470, p = .015). Perceived barriers did not make a statistically significant independent contribution (B = .080, SE = .049, β = .118, t = 1.614, p = .109). Accordingly, H1 and H6a were supported, while H4 was not supported.

The model's R² corresponds to an overall Cohen's f² of approximately .67. Under conventional benchmarks, this represents a large model-level effect. In practical terms, the variables included in the model accounted for about two-fifths of the variation in reported sustainable practices within this sample, while almost 60% remained associated with factors not included in the model.

The second regression model explained 37.2% of the variance in stated willingness to pay (R² = .372, adjusted R²

= .349), F(4, 110) = 16.28, p < .001.

Social-digital influence was the strongest statistical predictor (B = .393, SE = .111, β = .316, t = 3.557, p < .001). Self-reported sustainable travel practices were also positively associated with stated willingness to pay (B = .353, SE = .161, β = .215, t = 2.200, p = .030). Awareness did not reach the .05 threshold once the other variables were included (B = .272, SE = .142, β = .182, t = 1.912, p = .059), and perceived barriers were also nonsignificant (B = .081, SE = .089, β = .073, t = .910, p = .365). H3 and H6b were therefore supported, while H2 and H5 were not supported.

The model corresponds to Cohen's f² = .59, also within the conventional large-effect range. This means that the included variables accounted for a meaningful share of variation in stated willingness to pay within the sample, although 62.8% of its variance remained unexplained.

Because the Shapiro–Wilk test showed a small departure from residual normality, a 10,000-resample bootstrap was used as a sensitivity check. The bootstrap results supported the same pattern: self-reported sustainable travel practices, 95% CI [.018, .696], and social-digital influence, 95% CI [.090, .673], remained positive, whereas the confidence intervals for awareness and perceived barriers included zero (see Table 4).

The qualitative responses showed that barriers were rarely experienced as isolated problems. Respondents often described cost, limited availability, time, information, and convenience as conditions that reinforced one another. Limited access, availability, transportation, or supporting facilities appeared in 51 responses (44.3%), while high costs or price premiums appeared in 50 (43.5%). Insufficient information or transparency was identified in 44 responses (38.3%), and practical or personal constraints appeared in 24 (20.9%).

The responses also varied in how participants understood the source of the difficulty. Some located the problem mainly in the tourism market. R26, for example, referred to “high costs, limited access to environmentally friendly options, and limited information.” Others described a tension between sustainability and the practical demands of travel. R11 explained:

“Sustainable travel options sometimes require more time

and planning, which makes them less practical for me.” R33 made the trade-off more explicit: “Sustainable travel options tend to be more expensive and less practical. Limited comfortable public transport often makes me choose private transport for time efficiency and personal comfort.” Several responses also brought credibility into the same decision. R32 explained that the problem was not simply finding a sustainable product, but deciding whether the claim could be trusted:

“I have to research which providers genuinely care about the environment and which are only greenwashing.” These accounts show that cost, access, convenience, and trust were closely connected in respondents' reasoning. A sustainable option could be viewed favorably but still lose out when it required more money, more time, additional research, or less convenient transport.

The conditions that encouraged sustainable choices mirrored many of the reported difficulties, but respondents did not simply ask for lower prices. Visible environmental or community benefits were mentioned by 54 respondents (47.0%), access and convenience by 40 (34.8%), affordable prices or incentives by 38 (33.0%), and clear information, education, certification, or transparency by 27 (23.5%).

Several respondents combined these conditions in the same answer. R62, for example, wanted “direct incentives, such as discounts or reward points, easy and integrated public transport, and transparent eco-certification.” This response connects economic value, practical access, and credibility

R32 placed greater emphasis on seeing where the benefit went:

“I would choose sustainable travel more often if I felt that my trip really had a purpose—for example, knowing that my homestay payment directly helps a local family.”

The same respondent added that the decision became much easier when “the options are easy to find and the price is not much different.” In contrast, R87 gave a much shorter but revealing answer: the sustainable option would be more attractive if it “looked more practical.” These differences suggest that the same sustainable product may be evaluated through different priorities: social benefit for some respondents, affordability for others, and ease of use for others.

The expectations of the respondents also ranged in many directions. Education, clear information and promotion were mentioned in 47 responses (40.9%), environmental operations and conservation in 46 (40.0%), infrastructure and accessibility in 31 (27.0%), local community involvement in 28 (24.3%), and affordable pricing and/or incentives in 27 (23.5%).

Most responses were focused on operational practices. R5 called for reducing single-use plastics, better waste management, less energy and water use, support for local products and workers, visitor education and better environmental facilities. Others highlighted the social side of sustainability. R37 simply said that tourism providers must “make local residents the main actors.” Trust also emerged in very straightforward terms. When asked what tourism providers should do, R101 said: “Be honest and trustworthy.”

The responses suggest that respondents didn’t regard sustainable tourism as a purely environmental label. They were expecting the offer to work, to make the benefits visible, to be based on local communities and give consumers enough information to decide if it was credible to them.

Quantitative and Qualitative Findings. The integration led to convergence, complementarity and divergence. The qualitative results generally supported the statistical relationship between awareness and self-reported practices but also demonstrated why knowledge alone could not resolve questions of price or convenience. The strongest complementarity is to the stated willingness to pay: the regression results indicated self-reported practices and social-digital influence as significant predictors, and the written responses stated that financial support was based on tangible benefits, credible information, manageable price differences, and practical access.

The biggest divergence was to the perceived barriers. Barriers exhibited small positive bivariate correlations with some desirable outcomes but did not make a significant independent contribution in either regression model. However, cost, access, information and convenience appeared often in open-ended responses as well. The qualitative evidence thus does not overturn the regression result but shows that barriers can remain important in consumers' evaluations but not be easily independent negative predictors once other variables are considered (see Table 5). RQ1: Reported Sustainable Engagement and Financial Caution

As the first research question we asked, the descriptive pattern was across awareness, self-reported practices, perceived barriers, social-digital influence and willingness to pay. Awareness and reported sustainable practices were relatively high mean scores in this sample and stated willingness to pay was lower. This difference is interesting descriptively, but should not be viewed as evidence of a gap in attitude and behavior. Both practices and willingness to pay are reported by the same respondents in the same survey,

A more critical reading is that the respondents found a lot of low-cost or non-financial sustainable practices to be easy to endorse and were more cautious on questions on the additional payment. This is consistent with previous studies that have shown that environmental concern and responsible intentions do not automatically drive consumers to pay price premiums (Damigos, 2023; Pulido-Fernández & López- Sánchez, 2016). Qualitative responses also add a critical qualification: respondents did not reject paying more in principle. Their willingness to pay more was affected by the additional cost and its environmental or community benefit.

This is especially important as the surveyed group consisted of young adults from Banten, Jakarta and West Java and was recruited through convenience sampling. This sample is not “young Indonesian consumers”; rather it describes this sample. RQ2: From Awareness to Practice and Stated Willingness to Pay

Awareness had the strongest statistical relationship with self-reported sustainable travel practices. After the other predictors were taken into account, respondents with higher awareness scores also tended to report stronger sustainable practices. This is consistent with research treating knowledge and awareness as important foundations for responsible tourism behavior (Aydın & Alvarez, 2020; Li et al., 2024; Myung, 2018).

The size of the model is also worth considering. Awareness, barriers, and social-digital influence together accounted for 40.1% of variation in reported practices. The corresponding f² of .67 is large under Cohen's conventional benchmark (Cohen, 1992). This should not be interpreted as evidence that the model explains 40% of actual travel behavior, because the outcome is self-reported and the sample is not representative (Hansen et al., 2024; Nieto-García et al., 2024; Wut et al., 2023). It does, however, indicate that the three variables account for a sizeable share of differences in the practice scores observed in this sample. The remaining 59.9% points to other influences that were not measured, such as income, personal norms, destination conditions, previous travel experience, or service availability (Hansen et al., 2024; Li et al., 2024; Liu-Lastres et al., 2025; Seyfi, Hall, & Strzelecka, 2025; Tasci et al., 2021).

Awareness behaved differently when stated willingness to pay became the outcome. Its coefficient remained positive but did not reach statistical significance once practices, barriers, and social-digital influence were included. This distinction helps refine the simple assumption that greater awareness should lead directly to greater financial commitment (Damigos, 2023; Myung, 2018; Pulido-Fernández & López-Sánchez, 2016). Within these data, awareness was more clearly associated with reported practice than with stated willingness to pay (Aydın & Alvarez, 2020; Li et al., 2024).

Self-reported practices, by contrast, were positively associated with stated willingness to pay. This may indicate that respondents who already report incorporating sustainability into their travel decisions are also more open to accepting some financial trade-off (Boronat-Navarro & Pérez- Aranda, 2020; Damigos, 2023; Kang & Nicholls, 2021; Nelson et al., 2021). That interpretation nevertheless requires restraint because the practice scale had relatively low internal consistency (α = .593). The item-level analysis showed that no single problematic item was responsible for the low alpha; instead, the scale appears to combine several related practices - waste reduction, regulation compliance, local consumption, reusable items, and avoidance of harmful activities. The exploratory factor check also suggested some heterogeneity. The relationship with willingness to pay should therefore be treated as suggestive rather than as evidence from a fully validated behavioral measure (Nieto-García et al., 2024; Wut et al., 2023).

One possibility is that recognition of barriers requires knowledge of the sustainable tourism market. Respondents who are more interested in sustainable travel may be more likely to see that responsible accommodation is difficult to find, public transport is scarce, certification is unclear or sustainable alternatives cost more. In this sense, the higher barrier perception may reflect more engagement than resistance to sustainability. Tölkes (2020) points out that information and communication alone cannot remove structural constraints (cost, access and convenience).

Another explanation is motivated reasoning and selective attention. When an issue matters to a person, that person may respond more actively to relevant information including information about obstacles that prevent the preferred choice from being made (Kunda, 1990). So a respondent who is already interested in sustainable tourism might be aware of its deficiencies more than less.

There is also a methodological reason that should not be neglected. Awareness, barriers, practices, social-digital influence, and willingness to pay were measured in the same questionnaire, at the same time as self-report. Common- method variance can affect or reinforce correlations among variables in a similar response context (Podsakoff et al., 2003). This is particularly interesting if we consider the surprising positive associations with perceived barriers. We do not know how much of the pattern is meaningful and how much is due to shared measurement conditions.

The qualitative findings help to provide a reason why regression and open-ended results should not be viewed as contradictory. Cost, transport, access, information and convenience, for example, were frequently described as real problems to respondents. But these problems often appeared with continued interest in sustainable options. R32, for example, was concerned about price, time, limited options and greenwashing, but still considered it appropriate to go for a sustainable option when the benefits were evident and the price difference was manageable. So barriers don’t seem to be so much a “stop” signal as they seem to be conditions that determine when sustainable preferences can be acted on.

Social-digital influence was influential with self-reported practices and willingness to pay. This was the strongest statistical predictor in the willingness-to-pay model (β = .316). The study is cross-sectional and therefore we should interpret it as an association as opposed to evidence that social media, reviews, influencers, friends, or family make consumers pay more.

But the relationship is relevant in today’s travel decision- making when it comes to online reviews and social media that consumers don’t have access to on their own. They can make sustainable alternatives more visible, provide evidence of other travelers’ experiences, and help consumers assess whether environmental claims are credible. This view is consistent with Bae & Han (2020) and Tanford et al. (2020) who show the relevance of online trust and social media framing to sustainable tourism decisions.

The qualitative data confirm this conclusion. Respondents asked for transparent information, credible certification, honest reviews, and evidence of what tourism businesses were really doing. This suggests that the relationship is not only about exposure to more digital promotion. Quality and credibility of information also mattered to them.

This is where the risk of greenwashing becomes

The third research question asked how respondents explained the barriers and conditions surrounding sustainable choices. Their answers suggest that affordability, convenience, credibility, and visible benefit are not separate issues in the consumer's decision. They work together.

Price was important, but respondents rarely described it in isolation. They compared price with what they received in return. A higher price became more acceptable when it supported local communities, conservation, better environmental management, or another benefit that could be seen and understood. This is consistent with the willingness-to- pay literature, which shows that consumers evaluate a premium in relation to perceived value rather than environmental concern alone (Damigos, 2023; Kang & Nicholls, 2021).

Convenience was equally important. R33's preference for private transport when sustainable transport was less comfortable or more time-consuming shows why sustainable products cannot rely solely on ethical appeal. If the responsible option requires considerably more effort, the practical cost may matter alongside the monetary one.

Trust provides a third condition. Some respondents wanted certification and transparent information; one simply asked tourism providers to be “honest and trustworthy.” This matters because a consumer cannot evaluate the value of a sustainability premium when the underlying claim is unclear. The practical lesson is therefore not simply to promote sustainability more strongly, but to make sustainable options easier to verify, easier to access, and easier to use.

Our findings confirm the conceptual framework laid out in Figure 1. They do not support a linear process in which awareness becomes sustainable practice and then financial commitment automatically and then money is paid. The data suggest a more conditional progression.

Awareness was the most correlated with self-reported practice. In turn, reported practice was associated with stated willingness to pay but awareness alone was not a predictor of willingness to pay when we consider the other variables. Social- digital influence was found in both stages, with perceived barriers still present in respondents’ accounts even without negative regression effects.

This pattern adds to our Theory of Planned Behavior and attitude–behavior gap perspectives that informs the study. The results suggest that positive orientations toward sustainability may work differently depending on the outcome to be considered. Everyday responsible behavior and paying an additional financial cost are not equivalent. The latter seems to require more judgment on price, credibility, access, convenience, and perceived value.

This study does not replace TPB and does not propose a new causal model. Instead, it suggests that the path from sustainability awareness to financial assistance in this Indonesian sample is conditional rather than automatic. Social and digital information may also be important when considering sustainable choices, and market pressures may remain salient even if respondents report relatively sustainable practices.

The study also broadens the Indonesian evidence beyond green hotel selection. Previous Indonesian studies have

The mixed methods add another layer to the picture. The regression models in themselves might have led to a conclusion that perceived barriers were relatively unimportant, as independent coefficients in the regression were not quite significant. The qualitative accounts explain why such a conclusion would be too narrow. Respondents continued to speak about price, transport, infrastructure, information, and convenience when describing the conditions under which they could act on their sustainability preferences.

For tourism businesses and destination managers serving consumer groups similar to those surveyed, the findings suggest that sustainability should not be positioned simply as a premium label. Consumers may be more receptive when responsible options remain reasonably priced, easy to find, convenient to use, and clear about where the environmental or community benefit comes from (Damigos, 2023; Liu- Lastres et al., 2025; López-Sánchez & Pulido-Fernández, 2017; Pulido-Fernández & López-Sánchez, 2016; Tölkes, 2020).

Digital communication is especially useful when it provides evidence rather than general environmental claims. Booking pages, websites, social media, online reviews, and certification information can explain specific practices: where products are sourced, how waste is managed, what share of a payment supports a community or conservation program, and what measurable results have been achieved (Bae & Han, 2020; Ponnapureddy et al., 2017; Rantsi et al., 2023; Tanford et al., 2020; Tölkes, 2018; Vinzenz et al., 2019).

Infrastructure also matters. Sustainable choices become more practical when destinations offer usable public transport, refill points, waste-separation facilities, pedestrian access, locally produced goods, and clear environmental guidance (Font & McCabe, 2017; Liu-Lastres et al., 2025; Tölkes, 2020). The qualitative findings suggest that asking consumers to behave sustainably without making those choices practical places too much responsibility on the traveler (Hansen et al., 2024; Liu-Lastres et al., 2025; Wut et al., 2023).

Pricing strategies can also reduce the financial barrier. Modest premiums, bundled products, loyalty rewards, discounts, or transparent contributions may be more acceptable than a large unexplained premium (Boronat- Navarro & Pérez-Aranda, 2020; Damigos, 2023; Kang & Nicholls, 2021; Nelson et al., 2021). The important point is not that respondents will necessarily pay more, but that their stated willingness appears more favorable when the added cost is understandable and connected with a visible benefit (López-Sánchez & Pulido-Fernández, 2017; Pulido-Fernández & López-Sánchez, 2016; Rantsi et al., 2023; Su & Li, 2024).

Several limitations need to be highlighted. First, the cross- sectional study design makes statistical relationships at some point in time and cannot be taken as causal, either temporal or causal for the study. Words like predictor refer to regression relationships and have not shown causal effects.

Second, the convenience sample was selected from university and professional networks and was primarily from Banten, Jakarta and West Java. It is not the case that the results should be generalized to all young people in the state of Indonesia in general, but young people with different income levels, access to digital access, transport or tourism.

Third, sustainable practices and willingness to pay were self-reported. Respondents might have described their practices in a socially desirable way, and willingness to pay may be quite different from actual purchase of a given type of

Fourth, all quantitative constructs were collected in an identical questionnaire. Some correlations in common-method variance may have been improved by the unexpected positive relationship with perceived barriers.

Fifth, the quality of measures was uneven. Awareness was α = .649 and self-reported sustainable travel practices scale α = .593. Item-level and exploratory factor analyses suggest that the practice items indicate related but partly different behaviors. These measures should therefore be treated as exploratory and inferences regarding them should be made with caution.

The qualitative data were written open-ended responses rather than interviews or focus groups. They were useful for demonstrating how respondents connected cost, convenience, credibility, and benefit, but they could not be followed up when an answer was brief or ambiguous.

There should be larger and more geographically diverse samples and stronger measurement instruments for future studies to test these relationships. The sustainable-practices construct in particular would benefit from scale development that distinguishes environmental behavior, sustainable purchasing, transport choice, local-community support, and destination behavior before examining whether they become one higher-order construct.

Longitudinal studies and experiments may also investigate whether changes in sustainability information, price, certification, or infrastructure lead to changes in choice. Choice experiments would also provide more realistic combinations of accommodation, transport, certification, community benefit, and price premium rather than only general willingness-to-pay statements.

Actual purchasing or booking data would be particularly valuable. Such data could also help us understand whether stated willingness translates into market behavior when respondents are actually facing genuine budget constraints.

In the future, trust and perceived value should be thoroughly examined. And from the qualitative results presented here, it seems that both of these aspects may also explain why social-digital information is related to stated willingness to pay. Mediation or moderation models can explore if this relationship is affected by income, price sensitivity, travel frequency, destination type, or digital literacy.

Finally, interviews or focus groups can address things the open-ended survey could not, such as whether respondents have strong sustainable practices but little willingness to pay or if they have many barriers to travel but are still willing to financially support sustainable travel.

Conclusion

The study examined sustainable travel awareness, self- reported sustainable travel practices, perceived barriers, social-digital influence and stated willingness to pay among 115 Indonesian adults aged 18-29 years who were recruited in convenience sampling from Banten, Jakarta and West Java. As a result, awareness in this sample was observed to be positively indicative of self-reported sustainable travel practices and social-digital influence and stated willingness to pay. Social-digital influence was associated with the strongest independent relation with stated willingness to pay. In both regression models perceived barriers did not significantly affect the independent relationship between perceived barriers though cost, access, information, convenience and credibility remained prevalent in the written accounts of respondents. We can interpret them as associations rather than causal relationships.

The results suggest that the progress from sustainability

Author’s Contribution Statement

Adestya Ayu Armielia: Conceptualization, Methodology, Investigation, Data Curation, Formal Analysis, Qualitative Coding, Writing – Original Draft, Writing – Review & Editing, and Validation. Tri Ananti Listiana: Conceptualization, Methodology, Investigation, Data Curation, Formal Analysis, Qualitative Coding, Writing – Original Draft, Writing – Review & Editing, and Validation. Both authors contributed equally to the study design and interpretation of the findings. Both authors independently reviewed the qualitative responses, participated in resolving coding differences, verified the quantitative analyses and reported results, reviewed the final manuscript, and approved the version submitted for publication.

Conflicts of Interest

The authors declare that they have no financial, professional, or personal conflicts of interest that could have influenced the research process, interpretation of the findings, or preparation of this manuscript.

Source of Funding Statements

This research received no external funding or financial support from any public, commercial, or nonprofit organization. The study was conducted independently, and no external party was involved in the research design, data collection, analysis, interpretation, or manuscript preparation.

Acknowledgments

The authors sincerely thank all respondents who voluntarily participated in this study and shared their perspectives on sustainable travel. Their participation and contributions were essential to the completion of this research.

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