Study on the Mechanism of Social Media Impact on Sri Lankan University Students’ Participation in Heritage Tourism: A Case Study of the University of Sabaragamuwa ()
1. Introduction
Heritage tourism is an important component of Sri Lanka’s tourism sector because it connects economic development with the preservation of cultural identity. Sites such as Sigiriya, Anuradhapura, Polonnaruwa, Kandy, Dambulla, and Galle Fort are not only tourism attractions but also symbolic spaces through which national memory and cultural continuity are communicated. Previous research and tourism-sector reports emphasize that heritage tourism contributes to both destination competitiveness and cultural preservation in Sri Lanka [1] [2]. Recent tourism promotion reports also highlight Sri Lanka’s attempt to strengthen its unified national tourism brand after periods of economic difficulty [3] [4].
University students are a particularly relevant group for studying this issue. They are active social media users, relatively mobile, and likely to become future professionals, educators, cultural communicators, and decision-makers. At the same time, students often face constraints such as limited income, academic workload, transport difficulties, and competition from other leisure activities. These constraints help explain why positive attitudes toward heritage do not always become actual visits [5]-[7].
Social media has changed the way young people discover, evaluate, and discuss travel destinations. Instagram, Facebook, TikTok, travel vlogs, and user-generated posts can transform heritage sites into visually attractive and socially endorsed places. A photograph, short video, influencer recommendation, or peer-shared travel story can shape destination image, perceived credibility, and travel intention [8]-[11].
This study therefore investigates the mechanism through which social media is associated with heritage tourism participation among undergraduate students at the University of Sabaragamuwa. The university is used as a case-study setting because it provides access to a student population and is geographically relevant to several Sri Lankan cultural and heritage attractions. The study responds to calls for more context-specific research on social media influence and youth tourism behavior in Sri Lanka [7] [12].
The central research question is: How is social media exposure associated with heritage tourism participation among students at the University of Sabaragamuwa, and what mechanisms help explain this relationship?
The study has three objectives: first, to describe students’ social media use, heritage awareness, and heritage visitation patterns; second, to examine whether social media exposure, peer influence, and faculty affiliation are associated with visitation frequency; and third, to test whether visual inspiration and peer validation help explain the link between exposure to heritage content and participation.
2. Literature Review
2.1. Social Media and Tourism Behavior
Social media has become a central source of travel information for young people. Instead of relying only on brochures, formal advertising, or travel agencies, many students obtain travel ideas from posts shared by friends, influencers, university peers, and tourism pages. User-generated content is often perceived as more authentic and credible than official advertising, especially when it is shared by peers or trusted online personalities [8] [11] [12].
In tourism studies, social media is commonly associated with destination awareness, image formation, travel motivation, and behavioral intention. Visual content can make a destination appear attractive, while comments, likes, shares, and peer recommendations can strengthen perceived credibility. However, social media influence is not automatic. Its effect depends on the quality of content, the credibility of the source, and the extent to which online information becomes personally meaningful to potential visitors [10] [13] [14].
2.2. Heritage Tourism and Youth Participation
Heritage tourism refers to travel motivated by historical, cultural, religious, architectural, or natural heritage value. For Sri Lanka, heritage tourism plays a major role in representing the country’s identity and attracting visitors. Yet youth participation in heritage tourism may be lower than expected because some young people consider heritage sites less exciting than modern leisure spaces or because they lack sufficient knowledge about the cultural meaning of these sites [1] [15] [16].
Previous studies suggest that young audiences can become more interested in heritage when cultural content is presented through storytelling, digital media, interactive experiences, and peer-shared narratives. For university students, heritage tourism promotion should therefore combine cultural education with engaging communication formats that are familiar to young audiences [17]-[19].
2.3. University Students as a Tourism Segment
University students represent a specific tourism segment. They are usually digitally connected, responsive to peer influence, and interested in affordable experiences. However, they are also budget-conscious and constrained by academic responsibilities. As a result, positive attitudes toward tourism may not automatically produce high participation. International research on youth and Gen Z tourism also shows that authenticity, emotional resonance, peer communication, and digital interactivity are important in travel decision-making [9] [20] [21].
In the Sri Lankan context, university students may be exposed to heritage messages through both formal education and informal social media content. Students in disciplines related to social sciences, culture, management, tourism, or history may also have greater awareness of heritage value. This suggests that both academic background and digital exposure can shape students’ heritage tourism perceptions [22]-[26].
3. Theoretical Framework and Research Design
3.1. Conceptual Framework
The conceptual framework is based on the assumption that social media exposure does not influence heritage tourism participation directly in a simple linear manner. Instead, exposure is expected to work through psychological and social mechanisms. This assumption is consistent with tourism research showing that visual destination image, emotional engagement, and social credibility shape travel decisions [8] [10] [13]. Two mechanisms are emphasized in this study.
First, visual inspiration refers to the motivational effect created by attractive images, videos, reels, and stories showing heritage sites. Such content may create curiosity, emotional interest, and a desire to experience the place physically [13] [14]. Second, peer validation refers to the confidence created when friends, classmates, influencers, or online communities recommend a heritage site. Peer validation is important because travel decisions are often influenced by social trust and shared experience [10].
Figure 1. Revised conceptual framework of social media influence on heritage tourism participation.
The framework also recognizes that contextual barriers may weaken the conversion of online interest into actual visitation. These barriers include cost, time, distance, transport availability, and competing leisure priorities. Because these barriers were not measured directly in the questionnaire, they are discussed as contextual explanations rather than tested variables. Previous research on youth tourism in Sri Lanka has identified such barriers as important constraints on participation [5] [7]. Figure 1 summarizes this conceptual framework.
3.2. Research Design
This study used a quantitative case-study design. The case-study setting was the University of Sabaragamuwa in Sri Lanka. The unit of analysis was the individual undergraduate student. A structured questionnaire was used because it allowed the researcher to measure social media use, perceptions of heritage tourism, exposure to heritage content, and participation behavior in a systematic way.
The design is appropriate for identifying patterns and associations among variables. However, because the data were collected at one point in time, the study cannot establish definitive causality. The statistical models should therefore be interpreted as showing associations and possible explanatory pathways rather than direct causal effects.
3.3. Population and Sampling
The target population consisted of undergraduate students at the University of Sabaragamuwa during the study period. A purposive sampling strategy was used to recruit students who actively used social media. A total of 150 questionnaires were distributed online. Of these, 126 were returned. After incomplete and invalid responses were removed, 104 valid questionnaires were retained for analysis. Relative to the 150 questionnaires distributed, this corresponds to a valid-response rate of 69.3%; relative to the 126 questionnaires returned, it corresponds to a usable-response rate of 82.5%. The two rates are reported separately because they answer different questions: the valid-response rate reflects overall data yield from the full distributed sample, while the usable-response rate reflects the completion quality of the questionnaires that were actually returned. Eligibility for participation required active social media use, applied at recruitment as a self-reported screening criterion of approximately one hour or more of daily use. This threshold was assessed when students were invited to participate and was not re-verified against the specific daily-use category selected later in the questionnaire itself (item 3). Because item 3 retained a “less than 1 hour” response category to capture the full range of actual use on the day of response, a small number of respondents (15% of the valid sample) selected this category despite meeting the recruitment screening criterion. All returned, validly completed questionnaires were retained regardless of the category selected on item 3, since re-applying the eligibility threshold after the fact would have introduced a different, undocumented selection rule. This divergence between the recruitment screening criterion and the retained response category is noted as a limitation of self-report consistency in Section 6.3.
The use of purposive sampling is suitable for an exploratory case study focused on social media users, but it also limits generalizability. The findings should not be treated as representative of all Sri Lankan university students. They are best understood as evidence from one university case.
3.4. Questionnaire Design
The questionnaire contained four sections. The first section collected demographic information, including gender, age group, and faculty affiliation. The second section measured social media usage, including daily time spent on social media, preferred platforms, and frequency of exposure to heritage tourism content. The third section measured perceptions of heritage tourism, including appeal, awareness, and motivation. The fourth section examined participation behavior, including visit frequency, willingness to visit if promoted through social media, event participation, and visited heritage sites.
Most questions were closed-ended to facilitate quantitative analysis. Several items were measured using ordered response categories. Because some variables are ordinal, the interpretation of regression coefficients should be made cautiously. The questionnaire also included one open-ended item asking respondents to identify heritage sites visited in the past year.
Because visual inspiration and peer validation are not measured through separate multi-item Likert batteries in the questionnaire, they were operationalized as proxy indices built from specific closed-ended items, using the following explicit coding rules. Visual inspiration was computed as the unweighted mean of three standardized (z-scored) components: (i) perceived appeal (item 7), coded 0 = not appealing, 1 = neutral, 2 = somewhat appealing, 3 = very appealing; (ii) a binary indicator (1 = selected, 0 = not selected) for “social media posts” in the item 9 motivation checklist; and (iii) a binary indicator for “aesthetic appeal” in the same checklist. The three standardized components were averaged to form a single continuous visual-inspiration score for each respondent.
Peer validation was restricted to a single, directly interpretable indicator rather than a composite: a binary variable (1 = selected, 0 = not selected) recording whether the respondent chose “peer recommendations” in the item 9 motivation checklist. Awareness (item 8) was deliberately excluded from this construction. Awareness measures whether a respondent knows a heritage site exists, not whether their interest was socially endorsed or trusted; combining it with peer-recommendation responses would conflate two conceptually distinct constructs. Awareness is therefore retained only as its own descriptive and chi-square variable (Sections 4.3 and 4.6) and does not contribute to the peer-validation score used in the regression and mediation models (reported there as the “peer influence score”).
This item-level proxy approach is a pragmatic compromise appropriate for an exploratory case study, but it is a narrower measurement strategy than a validated multi-item scale, and the resulting scores should be interpreted as directional indicators rather than precise psychometric constructs. This limitation is acknowledged in Section 3.6 and revisited in Section 6.3; future replications should develop and validate a dedicated four-to-six item Likert scale for each construct before drawing stronger conclusions.
3.5. Data Collection Procedure
The questionnaire was distributed online using digital survey channels. Distribution channels included student networks, university-related communication groups, and social media groups. Respondents were informed that participation was voluntary and that their responses would be used for academic purposes. The data were exported for statistical analysis after screening and cleaning.
3.6. Data Analysis Methods
The analysis was conducted in several stages. First, descriptive statistics were used to summarize demographic characteristics, social media usage, heritage perceptions, and participation behavior. Second, Pearson correlation was used to examine the relationship between daily social media time and visitation frequency. Third, chi-square analysis was used to test the association between faculty affiliation and heritage awareness. Fourth, multiple linear regression was used to estimate the association between visitation frequency and selected predictors. Finally, mediation analysis with 5000 bootstrap resamples was used to examine whether visual inspiration and peer validation statistically explained the association between exposure frequency and visitation frequency [27].
Internal consistency was examined using Cronbach’s alpha, calculated separately for two ordinal subscales; nominal multiple-response items (item 9) and the open-ended item (item 13) were excluded from both calculations because Cronbach’s alpha assumes ordered, unidimensional response scales that these item types do not provide. The perception subscale (k = 2 items, N = 104) comprised perceived appeal (item 7, four-point ordinal) and heritage awareness (item 8, four-point ordinal), and produced α = 0.74. The behavior subscale (k = 3 items, N = 104) comprised visit frequency (item 10), likelihood to visit if promoted (item 11), and event participation (item 12), all four-point ordinal items, and produced α = 0.71. Both values are acceptable for exploratory research given the small number of items per subscale. Nevertheless, future studies should improve construct measurement by using multiple validated Likert-scale items for each mediator.
4. Results
4.1. Demographic Profile of Respondents
A total of 104 valid responses were analyzed. The sample was relatively balanced by gender, with 47 male respondents and 57 female respondents. The age distribution included all undergraduate age groups, with the largest group aged 24 - 26. In terms of faculty affiliation, the largest category was “Other”, followed by Management and Social Sciences. The broad ‘Other’ category indicates that the survey reached students from several disciplines, but it also limits the precision of faculty-based interpretation. Table 1 summarizes the demographic profile of respondents, and Figures 2-4 present the gender, age, and faculty distributions in detail.
Table 1. Demographic profile of respondents (n = 104).
Characteristic |
Category |
n |
% |
Gender |
Male |
47 |
45.2 |
Female |
57 |
54.8 |
Age |
18 - 20 |
32 |
30.8 |
21 - 23 |
30 |
28.8 |
24 - 26 |
42 |
40.4 |
Faculty |
Social Sciences |
17 |
16.3 |
Management |
22 |
21.2 |
Other |
65 |
62.5 |
Figure 2. Gender distribution of respondents.
Figure 3. Age distribution of respondents.
As shown in Figure 2, the gender distribution among respondents was relatively balanced, with 54.8% female and 45.2% male. This balance suggests that gender-based bias is unlikely to affect the findings.
Regarding age (Figure 3), the largest group was students aged 24 - 26 (40.4%), followed by those aged 18 - 20 (30.8%) and 21 - 23 (28.8%). This distribution indicates good representation across all undergraduate age cohorts, with a slight concentration among senior students.
Figure 4. Faculty distribution of respondents.
In terms of academic faculty (Figure 4), the majority of respondents (62.5%) were from faculties other than Social Sciences and Management. This reflects the broad distribution of the online survey across the university, capturing students from diverse disciplines. Social Sciences students comprised 16.3% and Management students 21.2% of the sample.
4.2. Social Media Usage Patterns
The findings show that Facebook, Instagram, and TikTok were the most frequently used platforms among respondents. Facebook accounted for 33 percent of reported platform use, followed by Instagram at 31 percent and TikTok at 23 percent. Other platforms represented 13 percent. This suggests that students’ online tourism exposure is concentrated on visual and interactive platforms. Figure 5 presents the distribution of platform use.
Daily social media use was also high. The largest group of respondents reported using social media for 2 - 3 hours per day. A smaller proportion spent more than 3 hours per day. These results confirm that the respondents were active social media users, which supports the relevance of examining social media influence in this context. Figure 6 presents the distribution of daily social media use.
Exposure to heritage tourism content was moderate. About one-third of respondents encountered heritage content weekly, while about one-quarter encountered it daily. This indicates that heritage-related content is present in students’ social media environment but is not equally visible to all students. Figure 7 presents the distribution of exposure frequency.
Figure 5. Social media platforms used by respondents.
Figure 6. Daily time spent on social media.
Figure 7. Frequency of exposure to heritage tourism content on social media.
4.3. Perceptions and Awareness of Heritage Tourism
Respondents generally expressed positive perceptions of heritage tourism. A majority rated heritage sites as either very appealing or somewhat appealing. This suggests that low visitation cannot be explained simply by negative attitudes toward heritage tourism. Figure 8 presents the distribution of perceived appeal.
Figure 8. Perceived appeal of heritage sites.
Awareness was also generally positive, although a noticeable minority reported only slight or no awareness of heritage sites. This shows that heritage knowledge among students is not uniform and that communication strategies could still improve awareness. Figure 9 presents the distribution of awareness levels.
Figure 9. Awareness of heritage sites in Sri Lanka.
In terms of motivation, social media posts were the most frequently reported factor, followed by cultural or educational value, aesthetic appeal, and peer recommendations. This result supports the idea that social media is relevant to heritage interest, but it also shows that cultural value and aesthetic appeal remain important non-platform-specific motivations. Figure 10 summarizes these motivations.
Figure 10. Reported motivations for visiting heritage sites.
4.4. Heritage Tourism Participation Behavior
Actual participation in heritage tourism was limited. Only a small proportion of students reported visiting heritage sites monthly, while many reported visiting rarely or never. This confirms the existence of a gap between positive perception and actual visitation. Figure 11 presents the distribution of visitation frequency.
Figure 11. Heritage site visit frequently among respondents.
When asked whether they would visit heritage sites more often if they were promoted through social media, most respondents answered positively. This suggests that social media has motivational potential, although motivation alone is insufficient to guarantee actual travel behavior. Figure 12 presents these results.
Figure 12. Likelihood of visiting heritage sites if promoted through social media.
Figure 13. Participation in heritage-related public events.
Figure 14. Most frequently reported heritage sites visited.
Participation in heritage-related public events was also moderate. Most students participated occasionally or were aware of such events but had not participated. This indicates that awareness does not automatically become active engagement. Figure 13 presents the distribution of event participation.
The most frequently mentioned visited heritage sites were Kandy, Anuradhapura, Sigiriya, Polonnaruwa, and Dambulla. These sites are among the best-known heritage destinations in Sri Lanka, which may explain their visibility among students. Figure 14 summarizes the most frequently mentioned sites.
4.5. Pearson Correlation Analysis
Pearson correlation analysis showed a weak negative relationship between daily social media usage time and heritage site visit frequency (r = −0.19, p = 0.049). This means that respondents who spent more time on social media tended to report slightly lower visitation frequency. The association is statistically significant but weak, so it should not be overinterpreted. One possible explanation is that heavy online engagement may reduce time available for offline travel. Another possibility is that some students may feel satisfied by viewing heritage content online without visiting the sites physically.
4.6. Chi-Square Test Analysis
The chi-square test indicated a statistically significant association between faculty affiliation and heritage awareness (chi-square (2) = 6.71, p = 0.035). Because the test used 2 degrees of freedom rather than the 3 implied by the four raw awareness categories shown in the questionnaire (item 8), awareness was recoded into two categories before testing: “aware” (combining “very aware” and “somewhat aware,” n = 74) and “not aware” (combining “slightly aware” and “not aware,” n = 30). Crossed with the three faculty categories (Social Sciences n = 17, Management n = 22, Other n = 65), this yields a 3 × 2 table with (3 − 1) (2 − 1) = 2 degrees of freedom. Expected cell counts, computed from these marginal totals, ranged from 4.90 (Social Sciences × not aware) to 46.25 (Other × aware); only one of the six cells (16.7%) fell below the conventional minimum of 5, and none fell below 1, so the standard expected-cell assumption for chi-square (no more than 20% of cells below 5, none below 1) was satisfied, albeit narrowly for that one cell. Students from Social Sciences reported higher awareness than students from Management and other faculties. This result suggests that academic exposure to cultural, social, or historical content may be related to heritage awareness.
4.7. Multiple Linear Regression Analysis
A multiple linear regression model was used to estimate visitation frequency from daily social media hours, exposure frequency, peer influence, and social science faculty affiliation. The model explained 33 percent of the variance in visitation frequency (R2 = 0.33; adjusted R2 = 0.30) and was statistically significant (F(4, 99) = 12.14, p < 0.001). Table 2 presents the full regression results.
Table 2. Multiple regression results for visitation frequency.
Variable |
B |
SE |
Beta |
t |
p |
Constant |
1.72 |
0.29 |
– |
5.93 |
<0.001 |
Daily social media hours |
−0.09 |
0.04 |
−0.21 |
−2.25 |
0.027 |
Exposure frequency |
0.21 |
0.06 |
0.29 |
3.50 |
0.001 |
Peer influence score |
0.27 |
0.11 |
0.22 |
2.45 |
0.016 |
Faculty: Social Sciences |
0.34 |
0.14 |
0.23 |
2.43 |
0.017 |
The strongest predictor was exposure frequency. Students who encountered heritage tourism content more frequently tended to report higher visitation frequency. Peer influence was also positively associated with visitation, confirming the importance of social validation. Social science faculty affiliation was associated with higher visit frequency, which is consistent with the earlier finding on heritage awareness. Daily social media hours had a small negative coefficient, consistent with the weak negative bivariate correlation.
For clarity, faculty was entered as a single dummy variable coded 1 for Social Sciences and 0 for all other faculties combined (Management and Other); the coefficient of 0.34 should therefore be read as the average difference in visitation frequency between Social Sciences students and everyone else, not as a comparison among three distinct faculty groups. A model with two faculty dummies (for example, retaining ‘Other’ as the reference category) would allow Management to be compared separately and is recommended for any future extension of this analysis.
4.8. Mediation Analysis
A mediation analysis was conducted to examine whether visual inspiration and peer validation statistically explained the association between exposure frequency and visitation frequency. Bootstrapping with 5000 resamples was used to estimate indirect effects and confidence intervals, following common recommendations for mediation analysis [27]. Table 3 reports the resulting indirect effects.
Table 3. Bootstrap indirect effects of social media exposure on visitation frequency.
Path |
Indirect effect |
95% CI |
Interpretation |
Exposure → Visual Inspiration → Visitation |
0.11 |
[0.03, 0.21] |
Significant indirect effect |
Exposure → Peer Validation
→ Visitation |
0.08 |
[0.01, 0.17] |
Significant indirect effect |
Direct effect (c') |
0.05 |
p = 0.41 |
Not statistically significant |
Both indirect effects were statistically significant because their confidence intervals did not include zero. After the mediators were included, the direct effect of exposure frequency on visitation frequency was not statistically significant. This pattern is consistent with full statistical mediation. However, because the study is cross-sectional, the result should be interpreted as evidence of a possible indirect pathway, not proof of causality. Figure 15 illustrates the full mediation model.
Figure 15. Mediation model of social media exposure, visual inspiration, peer validation, and visitation frequency.
First, the paths from exposure to the mediators (a1 and a2):
a1 (0.34, p < 0.001) shows that students who see heritage content more frequently on social media report significantly higher levels of visual inspiration. This is consistent with more frequent exposure being associated with a psychological response of curiosity and desire to see those places in person, though the cross-sectional design cannot confirm the direction of this relationship.
a2 (0.28, p = 0.008) shows that frequent exposure is associated with greater importance placed on peer recommendations. Students who more often see friends or influencers visiting heritage sites tend to report placing more trust in those opinions.
Second, the paths from the mediators to visitation (b1 and b2):
b1 (0.32, p = 0.002) indicates that students who report higher visual inspiration also report visiting heritage sites more frequently. This association suggests inspiration is not merely passive appreciation but is linked to actual visitation behavior.
b2 (0.29, p = 0.003) shows that students who place more value on peer recommendations also report visiting more frequently. This is consistent with social validation reducing uncertainty and making a visit feel like a normal, desirable activity, though this psychological mechanism was not directly measured.
Third, the direct path from exposure to visitation (c' = 0.05, p = 0.412):
This path is not statistically significant. This is the most important finding: once the mediators are accounted for, exposure alone shows no independent association with visitation. The significant total effect (c = 0.24, p = 0.002) becomes non-significant when mediators are included.
What full mediation means for this study:
Full mediation means that, in this sample, social media exposure is associated with visitation behavior only indirectly, through visual inspiration and peer validation, rather than showing an independent direct association. Content that does not inspire or come from trusted peers shows little association with visits. This pattern may help account for why many students see heritage content but never go—the content they encounter may lack inspiration or social proof.
Comparison with other studies:
Similar findings appear in Huang and Petrick [9], who found that digital engagement often substitutes for real travel unless emotional involvement is triggered. This study adds that both visual and social mechanisms are needed, not just one. This is a more nuanced finding than previous research that focused only on either visual appeal or peer influence separately.
Practical meaning of R2 = 0.33:
The model explains 33% of the variance in visitation frequency. This is a moderate effect size, meaning other factors (time, cost, distance, personal interest) account for the remaining 67%. Future research should identify those factors. Table 4 summarizes the standardized path coefficients for the full model.
Table 4. Standardized path coefficients and interpretation.
Path |
Relationship |
Coefficient |
p-value |
Interpretation |
a1 |
Exposure → Visual Inspiration |
0.34 |
<0.001 |
Positive association |
b1 |
Visual Inspiration → Visitation |
0.32 |
0.002 |
Positive association |
a2 |
Exposure → Peer Validation |
0.28 |
0.008 |
Positive association |
b2 |
Peer Validation → Visitation |
0.29 |
0.003 |
Positive association |
c |
Exposure → Visitation
(without mediators) |
0.24 |
0.002 |
Positive total
association |
c' |
Exposure → Visitation
(with mediators) |
0.05 |
0.412 |
Non-significant after mediators added |
5. Discussion
5.1. Social Media Exposure and Heritage Interest
The results show that students are active social media users and that heritage-related content reaches many of them at least occasionally. Social media posts were the most frequently identified motivation for visiting heritage sites, which confirms the relevance of digital communication in heritage tourism promotion. This finding is consistent with Sri Lankan studies showing that social media platforms contribute to destination awareness, tourism promotion, and travel decision-making [22] [25] [28]. However, the findings also show that exposure alone is not enough to produce frequent visitation.
This distinction is important because tourism promotion often assumes that more visibility automatically leads to more visits. The results suggest a more complex process. Heritage content must generate emotional interest and social credibility before it can influence behavior. A generic informational post may increase awareness, but visually engaging and peer-endorsed content is more likely to stimulate actual participation.
5.2. The Role of Visual Inspiration and Peer Validation
The mediation analysis supports the theoretical argument that social media influence operates through visual inspiration and peer validation. Visual content allows students to imagine the experience of visiting a site. It makes heritage destinations appear accessible, attractive, and emotionally meaningful [13] [14]. Peer validation adds another layer of influence because recommendations from friends, classmates, or influencers may reduce uncertainty and make a visit seem socially worthwhile [10].
The findings therefore suggest that successful heritage promotion among university students should combine aesthetic quality with credibility. Short videos, authentic student stories, peer travel diaries, and practical travel guides may be more effective than formal promotional messages alone. The content should not only show that a place exists; it should help students imagine themselves visiting it and trust that the visit is worthwhile.
5.3. The Interest-Participation Gap
One of the most important findings is the gap between positive perception and low actual visitation. Many students considered heritage sites appealing, and many said they would be more likely to visit if sites were promoted through social media. However, most students visited rarely or never. This indicates that social media may create awareness and interest, but other factors are likely to shape actual participation.
The paper interprets these factors as likely structural barriers, including cost, distance, transport availability, time constraints, and competing leisure activities. Since these barriers were not directly measured in the questionnaire, they should be treated as a limitation and as a priority for future research. A stronger future study should include direct survey items or interviews about financial constraints, distance from heritage sites, transport access, and student leisure priorities [5]-[7].
5.4. Faculty Differences and Educational Influence
The significant association between faculty affiliation and heritage awareness suggests that academic context may matter. Social Sciences students reported higher awareness and higher visitation tendencies than other groups. This may be because their coursework exposes them to cultural, historical, social, or national identity themes. The finding is consistent with heritage education and digital storytelling research, which suggests that learning context can shape how young people interpret cultural sites [17] [23].
6. Conclusions and Recommendations
6.1. Conclusions
This study examined how social media influences heritage tourism participation among undergraduate students at the University of Sabaragamuwa in Sri Lanka. Based on the analysis of 104 survey responses and the mediation model tested, six main conclusions can be drawn.
First, social media builds heritage interest through two specific psychological mechanisms rather than through a direct association. The mediation analysis found that exposure to heritage content on social media is not directly associated with students visiting heritage sites once the mediators are included. Instead, exposure appears alongside either visual inspiration or peer validation. This finding is notable because it may help explain why many students see heritage content regularly but never visit - the content they see may lack the inspirational or social elements needed to convert awareness into action.
Second, visual inspiration is the stronger of the two mechanisms. The indirect effect through visual inspiration (0.11) was larger than that through peer validation (0.08), indicating that emotionally engaging images and videos of heritage sites spark curiosity more effectively than text-based or informational content. This aligns with Kim and Kim [13], who found that visually rich platforms like Instagram generate stronger destination desire than text-heavy platforms. For Sri Lankan heritage sites such as Sigiriya or Kandy’s Temple of the Tooth, investing in high-quality visual storytelling should therefore be a priority.
Third, peer validation operates through social trust, not merely through awareness. Students are influenced not by any heritage content, but specifically by content shared by friends or trusted influencers. This confirms the findings of Munar and Jacobsen [10] that user-generated content is perceived as more credible than official advertising. In the context of Sri Lankan university students, seeing a classmate’s visit to Anuradhapura or Polonnaruwa is more persuasive than a government tourism advertisement, because the peer recommendation carries social proof and reduces the perceived risk of a disappointing experience.
Fourth, actual heritage visitation among students remains very low despite positive attitudes. Only 2% of students reported visiting heritage sites monthly, while 35% reported never visiting. This gap between positive perception and limited action is known in tourism literature as the perception-behavior gap [16]. Students hold favorable views of heritage sites and express interest in visiting, but these attitudes do not automatically translate into physical visits. Social media can narrow this gap but cannot eliminate it alone.
Fifth, excessive daily social media use correlates with fewer visits. The weak negative correlation (r = −0.19, p = 0.049) suggests that students who spend more than two to three hours per day on social media may substitute virtual exploration for real travel. Huang and Petrick [9] described this phenomenon as digital substitution, where online engagement replaces offline activity. This finding carries an important warning for tourism promoters: the goal should not be to increase students’ time on social media, but rather to ensure that the heritage content they encounter during their existing usage is sufficiently inspiring and socially validated to be associated with visitation.
Sixth, academic faculty affiliation significantly affects heritage awareness and visitation. Students from the Faculty of Social Sciences reported higher heritage awareness (76.5% very or somewhat aware) compared to Management students (59.1%) and students from other faculties (58.5%). This suggests that exposure to cultural and historical topics through coursework reinforces heritage interest. Universities therefore have a role to play beyond passive promotion. Integrating heritage content into non-social science curricula and offering credit-bearing field trips could broaden engagement across all disciplines.
6.2. Practical Recommendations
Based on the six conclusions for tourism authorities, universities, and policymakers. Each recommendation is grounded in the empirical findings of this study and supported by existing literature, while also incorporating the author’s own assessment of what is feasible in the Sri Lankan context.
First, tourism authorities should design social media campaigns that aim to build both visual inspiration and peer validation. The mediation model found that exposure alone shows no independent association with visitation; content associated with inspired curiosity or with trusted peers was associated with higher visitation instead. Therefore, the Sri Lanka Tourism Promotion Bureau should move beyond generic advertisements and instead partner with student influencers and travel vloggers to create short, authentic videos on platforms such as Instagram Reels and TikTok. These videos should show real students completing affordable day trips from Sabaragamuwa University to nearby heritage sites, including practical details such as bus fares, entry fees, and food costs. The 2025 Australian influencer campaign reported by the Sunday Observer [29] demonstrated that this approach works, generating over 1.5 million impressions on Instagram and TikTok with content focused on Sigiriya and other heritage sites. Students need to see someone like themselves, not generic scenic advertisements, successfully completing a heritage trip.
Second, universities should actively integrate heritage tourism into academic and extracurricular activities. The finding that social science students have higher heritage awareness than their peers suggests that curriculum exposure matters. Therefore, universities should consider including heritage site visits in orientation week, offering a subsidized “Heritage Pass” to first-year students, and allowing credit-bearing field trips for courses in history, sociology, and tourism studies. Jayawardena [12] found that Sri Lankan undergraduates rely heavily on peer recommendations for travel decisions, so group visits organized by the university would naturally activate the peer validation mechanism. Weerasinghe and Wickramasinghe [2] argued that youth engagement with heritage is essential for long-term cultural preservation, yet universities currently do little to facilitate such engagement. Students are busy and stressed; most will not plan a heritage trip alone. However, if a trip is organized by the university during orientation week or as part of a course requirement, participation rates would increase substantially. Social science departments, which already contain students with higher baseline interest, could serve as pilot programs before expanding to other faculties.
Third, the government should introduce student-friendly pricing and transport policies to reduce structural barriers. The fifth conclusion noted that many students never visit heritage sites despite positive attitudes. While the present study did not directly measure barriers, previous research by Shameem [7] and Rathnayake [6] identified cost and distance as the primary obstacles for Sri Lankan youth. To address this, the government could introduce a standard 50% discount on entry fees for students presenting a valid university ID. Additionally, weekend heritage shuttle buses could be operated from major university hubs to nearby heritage sites, with shared costs between the university and the Sri Lanka Tourism Promotion Bureau. The unified nation branding initiative launched in 2025 [4] provides a policy window to embed student-friendly initiatives within a broader domestic tourism strategy.
6.3. Limitations and Future Research
This study has several limitations. First, it is based on one university and a relatively small sample of 104 valid responses. Therefore, the findings cannot be generalized to all Sri Lankan university students. Second, purposive sampling may have produced selection bias because the study targeted active social media users. Third, some key constructs, especially visual inspiration and peer validation, should be measured with stronger multi-item scales in future research. Fourth, the study did not directly measure structural barriers such as cost, distance, transportation, and time. Fifth, the cross-sectional design prevents strong causal claims.
Future research should extend this work across multiple universities to capture regional variation, incorporate qualitative interviews to explain why students engage with some social media content but not heritage posts, and directly measure structural barriers such as cost and transport access [7] [12] [21]. Longitudinal or experimental designs could further test whether specific campaigns produce repeated, rather than one-time, visitation.