Evaluating the Resident Support for Cultural Tourism Through a Revised Social Exchange Theory Approach

2.1 The Influence of Residents’ Community Attachment (CA) on Residents’ Perceived Cultural Impact (PCI) and Residents’ Support for Cultural Tourism (SFCT)

A sociologist Brehm, Eisenhauer, and Krannich (2004), defined community attachment as people’s strong positive feelings, rootedness, and sense of belongingness to their community. It is individuals’ connection or ties towards a community at an emotional or affective level based on how they are assimilated into community life. A stronger attachment to the community has been thought to strongly influence concerns about whether tourism will benefit the local community (Andereck et al. 2005). Such ideas have been employed in tourist support models to investigate the effects on residents’ perceptions of tourism impact and attitudes toward the tourism business (Adongo, Choe, and Han 2017; Gabriel Brida, Disegna, and Osti 2014). Eslami et al. (2019); Nicholas, Thapa, and Ko (2009) revealed that community attachment significantly influenced positive perceived economic, social, and environmental impact and their influence on increased support for tourism development. Adongo, Choe, and Han (2017) have found that stronger community attachment leads to more positive attitudes towards tourism impacts and support for tourism development. Chen and Chen (2010; and López et al. (2018), have also attempted to study the relationship between the degree of attachment to the community, perceived benefits, and support for tourism development. Furthermore, Choi and Murray (2010) hypothesised that community attachment positively correlates with the level of support for current and is inversely related to the negative impacts of tourism. Building on these insights, this study integrates community attachment as a potential predictor of residents’ perceived cultural impacts and their support for cultural tourism in the SET framework. Therefore, the following hypotheses are proposed:

2.2 The Influence of Residents’ Community Involvement (CI) on Residents’ Perceived Cultural Impact (PCI) and Residents’ Support for Cultural Tourism (SFCT)

Residents’ community involvement is the degree to which people of a community work together to achieve common goals that benefit everyone (Jaafar et al. 2015). Scholars have analysed the extent to which individuals feel involved in the tourism development of their place (Çelik and Rasoolimanesh 2021; Lee 2013; Nicholas, Thapa, and Ko 2009; Rasoolimanesh and Jaafar 2016). It is noteworthy that local issues can directly affect the tourist experience and, consequently, the tourist image of the destination. Past researchers have employed perceived benefits and costs as the intermediate factors linking the backing for community involvement and support for tourism development, such as Nicholas, Thapa, and Ko (2009), found that community involvement does not substantially influence perceived impact nor resident support for tourism development in Pitons Management Area (PMA), a world heritage site. At the same time, it is inversely related to the negative impacts of tourism on support for tourism development (Choi and Murray 2010). However, Lee (2013); López et al. (2018); and Orgaz-Agüera et al. (2022), indicated that community involvement plays a significant role in shaping residents’ support for tourism activities. Regrettably, the intervening repercussions of community involvement on perceived cultural impact and support for cultural tourism have yet to be witnessed in the SET framework. Hence, it is valuable to scrutinise this direct correlation.

2.3 The Influence of Residents’ Perceived Cultural Impact (PCI) on Residents’ Attitudes Towards Cultural Tourism (ACT) and Tourists (ATCT) and Residents Support for Cultural Tourism (SFCT)

In SET, research on residents’ perceptions of tourism impacts consistently show mixed effects across economic, socio-cultural, and environmental dimensions (Látková and Vogt 2012; McGehee and Andereck 2004). Due to its essential role in sustainable tourism development and management in a tourist destination, residents’ awareness, perceptions, and support for tourism have been widely considered in the context of tourism (Çelik and Rasoolimanesh 2021; Huong and Lee 2017; Sharpley 2014). In Thailand, residents viewed cultural preservation and economic benefits as top impacts (Mcdowall and Choi 2010). Residents’ perceptions of cultural benefits have realised a substantial positive cultural benefit in managing the byway area to enhance and preserve, such as safeguarding traditional folklore and helping locals learn more about culture (Besculides, Lee, and Mccormick 2002) and thus directly influencing the resident support for tourism (Gursoy and Rutherford 2004). Moreover, almost without exception, studies of residents’ perceptions focus on all three dimensions of perceived impact, that is, economic, sociocultural, and environmental impact, which are used to predict residents’ support for tourism (Eslami et al. 2019; Lee 2013; Nunkoo 2016; Sharma et al. 2008; Sinclair-Maragh, Gursoy, and Vieregge 2015; Stylidis 2017; Wang and Xu 2015). Residents’ support is indispensable to avoid threatening sustainable tourism (Nunkoo and Gursoy 2012; Roxas, Rivera, and Gutierrez 2020). Chen and Chen (2010); and Rasoolimanesh et al. (2015) also studied residents’ positive and negative perceptions of tourism and found that such perceptions strongly influenced the support for tourism.

Residents’ attitudes toward tourism are influenced mainly by perceptions. Numerous studies have also examined how resident perceptions of tourism impacts influence their attitudes toward tourism in revising the SET (Dyer et al. 2007; Nunkoo and Gursoy 2012; Vargas-Sánchez et al. 2015). These studies typically categorise tourism’s economic, socio-cultural, and environmental impacts, with positive and negative influences on resident attitudes (Nunkoo 2016; Nunkoo and Gursoy 2012). Although most studies have focused on the residents’ attitudes towards tourism, very few have focused on the influence of perceived impact on resident attitudes toward tourists. For instance, Martín et al. (2017b) agreed and distinguished between residents’ specific perceptions of the positive and negative impacts of tourism activities on their communities and their overall attitudes toward the tourism phenomena resulting from these perceptions. By referencing the concept of “affective attitudes towards tourists” proposed by Martín, de los Salmones Sánchez, and Herrero (2017a), we consider it necessary also to examine the attitudes towards tourists. Therefore, it makes sense that residents are more likely to support tourism initiatives if they perceive benefits from tourists’ arrivals. Very limited work is carried out focusing on perceived cultural impact. Therefore, such perceptions are used to understand better the nature and formation of this critical issue that needs to be managed in the tourism development strategies of the region. The study proposes the following hypotheses.

2.4 The Influence of Residents’ Attitude Towards Cultural Tourism (ACT) on Residents’ Support for Cultural Tourism (SFCT)

The relationship between residents’ attitudes toward tourism and their perceptions of tourism’s economic, socio-cultural, and environmental impacts are frequently explained in the SET framework (Dyer et al. 2007; Gursoy and Kendall 2006), suggesting that both tourists and residents engage in exchange to achieve beneficial outcomes (Sharpley 2018). If residents perceive the positive effects of tourism as outweighing the negative impacts, they are more likely to have a positive attitude, and thus, such attitude supports tourism development in their communities (Sharpley 2014). Building on this, the study explores how residents’ attitudes influence their support for cultural tourism in the revised SET framework. Importantly, research has shown that resident attitudes vary based on the type of tourism and the stage of tourism development (Bujosa Bestard, Rosselló, and Rosselló Nadal 2007; Vargas-Sánchez, Plaza-Mejía, and Porras-Bueno 2009), making it crucial to develop a detailed model that can accurately reflect the complex realities of any host community. Therefore, the study proposes the following hypothesis.

2.5 The Influence of Residents’ Attitude Towards Cultural Tourists (ATCT) on Residents’ Support for Cultural Tourism (SFCT)

In 1997, Lindberg and Johnson introduced the idea that residents’ pleasure in interacting with tourists influenced their attitudes. Similarly, Teye, Sönmez, and Sirakaya (2002), identified a link between residents’ feelings from interacting with tourists and their attitudes toward tourism. Woosnam, Norman, and Ying (2009) developed the emotional solidarity framework to examine how emotional connections with tourists shape residents’ attitudes. He emphasised that residents’ emotional solidarity with tourists arises from shared interactions and beliefs. Later, Woosnam (2011, 2012) empirically demonstrated a positive relationship between emotional solidarity and support for tourism. While much of the literature has focused on cognitive attitudes toward tourism (Stylianou-Lambert, Boukas, and Christodoulou-Yerali 2014; Stylidis 2017; Vargas-Sánchez et al. 2015), there is a need to examine residents’ affective attitudes toward tourists, (Palmer, Koenig-Lewis, and Medi Jones 2013). Therefore, our study aims to enrich the literature by establishing a link between resident’s perceptions of cultural tourism’s impacts and their attitudes toward tourists. We argue that resident-tourist interactions are crucial in shaping residents’ support for cultural tourism. Favourable evaluations of these interactions are likely to influence how residents positively support cultural tourism development. Consequently, we revised the SET model by adopting resident attitudes towards cultural tourists and their support for cultural tourism. Thus, we propose hypotheses in this study.

2.6 Simple Mediating Effect

Recent studies have focused on exploring the direct relationships influencing resident support for tourism development (Choi and Murray 2010; López et al. 2018; Martín et al. 2017b; Stylidis 2017). Some studies have explored the complex relationships between residents’ perceptions, attitudes, and support for tourism development. Such as Eslami et al. (2019), found that perceived socio-cultural and economic impacts influenced residents’ material, non-material, and quality of life, affecting support for sustainable tourism development. A study by Nunkoo and Gursoy (2012), tests the mediating effects of attitudes on the positive and negative impacts on the relationship between occupational identity and support for tourism and the mediating effects of attitudes on the negative impacts on the relationship between gender identity and support for tourism. These studies highlight the importance of understanding indirect relationships between various constructs in SET in shaping residents’ perceived cultural impact, attitudes, and support for tourism development. Therefore, the simple mediating effect between the constructs has been hypothesised as follows:

2.7 Parallel Mediation Effect

Residents’ attitudes towards tourism and tourists are important for destination development (Milman 2004). Residents’ attitudes towards tourism development have received increasing interest from academicians, policymakers, and tourism industry managers. Previous researchers have studied the factors that directly impact the residents’ attitude toward tourism development (Martín, de los Salmones Sánchez, and Herrero 2017a; Nunkoo and Gursoy 2012). However, the indirect impact of resident attitudes towards tourism and tourists has been largely ignored. Gursoy and Rutherford (2004) observe that although much of the research on residents’ reactions has lacked a theoretical foundation, several researchers have explored the topic using various theoretical frameworks. In this context, a review of the existing literature has revealed the application of diverse modelling approaches, which establish quantifiable relationships between this dependent variable and other factors considered independent variables.

Residents’ perceptions of cultural impact often shape their attitudes toward cultural tourism development in their locality. Positive cultural impacts, such as the preservation of local heritage, promotion of cultural pride, and economic benefits from tourism, tend to foster favourable attitudes among residents, thereby increasing their support for cultural tourism initiatives. According to Gursoy and Rutherford (2004), residents are more likely to support tourism development when they perceive it as a tool for cultural preservation and community enhancement. Similarly, research by (Andereck et al. 2005; McGehee and Andereck 2004) emphasise that positive perceptions of cultural tourism benefits significantly influence residents’ attitudes and their willingness to endorse tourism activities.

Favourable attitudes toward cultural tourists can emerge when tourists are perceived as appreciative and respectful of the host culture. This, in turn, strengthens the link between perceived positive cultural impacts and residents’ support for tourism (Stylidis 2017) suggesting that positive interactions between residents and tourists can foster mutual respect and understanding, thereby encouraging greater resident support for tourism activities. The resident attitude towards tourists and tourism underscores the importance of fostering positive resident perceptions of cultural impacts and tourists to ensure sustainable support for cultural tourism. This aligns with the social exchange theory (Jani 2018; Özel and Kozak 2016), which posits that residents’ support for tourism is contingent on their evaluation of its benefits and costs. When residents perceive cultural tourism as beneficial and view tourists positively, their attitudes act as mediators, channelling these perceptions into tangible support for tourism development.

2.8 Serial Mediation Effect

Using the SET framework, Gannon, Rasoolimanesh, and Taheri (2020), demonstrated that residents’ perceptions of tourism impacts mediated the relationships between community attachment, environmental attitudes, and economic gain on support for tourism development. Su, Huang, and Huang (2018) showed that destination social responsibility enhanced residents’ perception of positive tourism impacts, indirectly increasing support for tourism and perceived quality of life. Another study by Çelik and Rasoolimanesh (2021), concluded that cost-benefit attitude significantly mediated the relationship between positive-negative impact and support for tourism development. Moreover, Sher et al. (2015) revealed that perceived benefits and costs mediate the relationship between community attachment, involvement, and support for sustainable tourism.

Further, due to the overlapping concepts of attitude and perception (Sharpley 2014), the previous research fails to examine how the attitude of residents can affect the relationships between residents’ community attachment, community involvement, perceived impact, and support for tourism, especially in cultural tourism. Limited research based on SET has empirically evident the influence of resident perceptions of tourism’s impacts on their attitudes toward tourism or their attitudinal support (Nunkoo and Gursoy 2012; Sharma et al. 2008; Vargas-Sánchez et al. 2015; Wang and Xu 2015; Yoon, Gursoy, and Chen 2001). These studies highlight the importance of understanding the direct and indirect relationships between various constructs in shaping community attachment, community involvement, residents perceived cultural impact, attitudes, and support for tourism development. Therefore, the serial mediating effect between the constructs has been hypothesised as follows:

Figure 1:

Conceptual research model- revised framework of SET. Note: Direct relationships hypotheses are highlighted in black; simple mediating relationships hypotheses are highlighted in green; parallel mediating relationships hypotheses are highlighted in blue; serial mediating relationships hypotheses are highlighted in red.

3.1 Study Site

Goa, a small state on the western coast of India, offers a unique blend of natural beauty, rich cultural heritage, and a relaxed, contemporary lifestyle. The state has long been a magnet for domestic and international tourists with its diverse flora and fauna, pristine beaches, and historical sites. The state’s culture is deeply influenced by its Portuguese colonial past, which adds to its distinctive charm. This strong cultural foundation thrives in cultural tourism, especially as tourists seek destinations that blend history, tradition, and leisure. Goa’s cultural tourism sector is witnessing a shift toward diversifying beyond its well-known beaches, with a growing emphasis on heritage and festival tourism. The potential demand for cultural tourism in Goa is rising as stakeholders push for better utilisation of the state’s rich cultural and historical assets. However, the supply still needs improvement (Gomantak Times 2024c). The government has been promoting cultural tourism through its regenerative tourism initiatives, which aim to protect and preserve Goa’s cultural and natural heritage.

Collaborations with companies like MakeMyTrip help spotlight Goa’s lesser-known inland destinations, highlighting its cultural tapestry and culinary traditions. This reflects a growing demand for experiences beyond the beaches and into Goa’s historical and cultural heart (Gomantak Times 2024a, 2024b). While demand for cultural tourism in Goa is growing, the supply side requires policy support, better infrastructure, and a focus on sustainability to realise its full potential. The supply side of cultural tourism in Goa is expanding, but further development is required to meet growing demand. The Department of Tourism, Goa, has been actively marketing the state’s traditional events, investing in infrastructure to support these cultural experiences. This includes promoting heritage sites and local festivals and setting aside specific budgets to make these festivals more tourist-friendly. There are also plans to expand homestay options in Goa’s rural and inland areas to offer tourists a more immersive cultural experience. This move aims to spread the benefits of tourism beyond the coastal areas and into the hinterlands, where Goa’s rich cultural and religious heritage is most evident (Gomantak Times 2024a).

3.2 Sampling and Data Collection

The data was primarily collected from individual residents in the study area who lived at a particular place for a prolonged period (at least a year to be familiar with it), including officials from the Department of Tourism, Goa, Goa Tourism Development Corporation, tour operators, and Intangible Cultural Heritage (ICH) practitioners and those who follow as well as practices the culture of Goa. The sampling study was directed in two stages. In the first stage, Krejcie and Morgan’s table was used to calculate the required sample size. As the population was known and finite, it was easy to decide on the sample size of the total population. Further, proportionate stratified random sampling techniques were applied to indicate that each stratum sample size is proportionate to the population size of the stratum when observed against the total population (Eslami et al. 2019). Here, each stratum is considered one district of Goa i.e. North-Goa and South-Goa. The total population of Goa is 14, 58, 545 as per the 2011 census, of which, 8, 18, 008 belong to North-Goa, and 6, 40, 537 belong to South-Goa. Therefore, from Krejcie and Morgan’s sample size table, it is understood that if the total known population exceeds 2, 50, 000, a finite and standard sample can be chosen as 384. However, the final sample chosen for the residents is 500, consisting of North Goa (280 residents) and South Goa (220 Residents), based on the stratified sample formula below.

The sample size of the strata = size of the entire sample/ population size × layer size.

In the second stage, the sample distribution was divided proportionately by taluka, with 5%–10 % going to the lower population talukas and 15%–25 % to the highest population talukas. Data was collected between November 2022 and June 2023 using self-administered questionnaires, with researchers personally interviewing respondents for accuracy. In the end, out of 500 questionnaires distributed, 467 were found valid, resulting in a response rate of 93.4 %. The remaining questionnaires were discarded due to missing information and outliers.

3.3 Constructs Measurement

This questionnaire was designed to gather insights from residents on their perceptions and attitudes towards cultural tourism. It focused on six key constructs for understanding the community’s stance on tourism and its cultural impact. These constructs were adapted from prior research to fit the context of the present study, ensuring the use of validated measures (Bhat and Mishra 2020; Çelik and Rasoolimanesh 2021; Lee 2013; López et al. 2018; Martín et al. 2017b; Papastathopoulos et al. 2019; Rasoolimanesh et al. 2015; Szromek, Kruczek, and Walas 2020). The constructs such as ‘residents’ community attachment’, ‘residents’ community involvement’, ‘residents’ perceived cultural impact’, ‘residents’ attitude towards cultural tourism’, and ‘residents’ support for cultural tourism’ were measured by 4 variables each, whereas, ‘residents’ attitude towards cultural tourists’ is measured by 5 variables. Altogether, 25 variables were measured for the study. Each construct was measured using a 7-point Likert scale ranging from (1) strongly disagree to (7) strongly agree. It is a commonly used tool in social science research to capture respondents' agreement levels or disagreement with specific statements.

4.1 Analysis of the Description of the Demographic Profile of the Residents

The analysis in Table 1 provides a glimpse into the demographic profiles of residents.

4.2 Analysis of the Measurement Model

Before constructing the measurement model, we assessed the summary statistics based on mean and standard deviation and normality tests based on skewness and kurtosis. The mean ranges from 3.548 to 5.34, whereas the standard deviation value ranges from 1.386 to 1.851. Further, the kurtosis and skewness values lie between −0.285 and 0.930, and skewness ranges between −1.072 and 0.308. This shows the values are within the threshold limit of −2 to +2 (George and Mallery 2010). Hence, it proved to be acceptable for further analysis. A multicollinearity test based on the VIF value was also tested. The VIF value of all the variables is in the bracket of 1.424 (CI1) to 3.999 (CI3), which shows that the variables do not have any issue of multicollinearity, as the VIF values are within or equal to 5. Further, the dimension reduction technique under the Harman Single Factor method evaluated all the variables under a single factor to check for any bias in the data. Under this method, if the value exceeds 50 %, it is assumed to be the presence of data biasedness. However, the evaluation shows that the value is 41.638 %, confirming that they represent their corresponding factor and unbiased data. Ultimately, this study conducted Partial Least Square-Structural Equation Modeling (PLS-SEM) analysis by testing the reliability and validity of the measurement model and assessing the structural equation model using path coefficient, and mediation analysis in Smart PLS 4.

The reliability and validity of the measurement model in Tables 2–4, were estimated. The results of the model’s reliability and convergent validity tests are presented in Table 2, which shows that all the CA presented surpassed the recommendation of 0.70 (Cronbach 1951), as the values of CA range from 0.855 (CI) to 0.906 (ATCT). The CR indicators denote the mutual variance of a group of observed variables by assessing a specific construct (Fornell and Larcker 1981). Generally, a CR of a minimum of 0.60 is estimated to be appropriate (Bagozzi and Yi 1988). In exploratory research, the threshold limit is 0.70 (Hair, Ringle, and Sarstedt 2011, 2013, 2014). Each construct’s CR exceeds the threshold of 0.70 (Hair, Ringle, and Sarstedt 2013). Thus, the measurement model has satisfactory internal consistency reliability as the CR for the constructs ranges between 0.856 (CI) and 0.909 (ATCT), which is above the recommended threshold of 0.70 (Hair et al. 2012, 2013). Furthermore, the AVE was estimated for every construct. The AVE should be higher than 0.50 (Fornell and Larcker 1981). Table 2, also shows that all the constructs have substantial AVE scores ranging from 0.698 (CI) to 0.760 (CA), which is within the thumb rule of ≥ 0.50 (Hair, Ringle, and Sarstedt 2013). As evidence of convergent validity, the findings revealed that all variables were meaningfully linked to their hypothesised variables, and the size of every standardised loading was above 0.70 (Anderson, Kellogg, and Gerbing 1988).

The discriminant validity is examined in Tables 3 and 4, which shows that the shared variance between pairs of constructs was lower than the linked AVE (Fornell and Larcker 1981). The findings of the intercorrelation matrix suggest adequate discriminant validity of the measurement model as the square root of AVE of a specific construct exceeds the intercorrelations score of its corresponding constructs (Fornell and Larcker 1981), as shown in Table 3.

The HTMT ratio method recently proposed by Henseler, Ringle, and Sarstedt (2015), shown in Table 4, was also applied to assess discriminant validity. In this case, every ratio should be lower than 0.85. Since every ratio was lower than 0.85, no problems resulted. The analysis found the maximum HTMT ratio of correlation value of 0.747, below the most conservative critical HTMT value of 0.85. The study also assessed discriminant validity at the variable level, examining the cross-loadings matrix. All variables demonstrated substantial discriminant validity as the loading of the individual variable within a construct was more significant than their cross-loadings. The study results suggested substantial discriminant validity, both at the variable and construct levels of the model. Therefore, it was concluded that the proposed model offered appropriate discriminant validity evidence. Thus, our findings confirmed the validity and reliability of the measurement model.

4.3 Results of Path Analysis

The Partial Least Square Equation Modelling (PLS-SEM) bootstrapping procedure was assessed with 5,000 iterations to determine the path relationships in the structural model. This study estimated the explanatory power of the exogenous latent constructs in the study model. The R² values of residents’ attitude toward cultural tourism (0.339), residents’ attitude towards cultural tourists (0.359), residents’ perceived cultural impact (0.392), and residents’ support for cultural tourism (0.590) suggest the satisfactory predictive ability of the research model (refer Figure 2). The findings of the analysis presented in Table 5 show that residents’ community attachment (H₁; p < 0.05; β = 0.338) and residents’ community involvement (H₃; p < 0.05; β = 0.377;) significantly influence the residents’ perceived cultural impact. Further, residents’ community attachment (H₂; p < 0.05; β = 0.134), residents’ community involvement (H₄; p < 0.05; β = 0.106), residents’ attitude toward cultural tourism (H₈; p < 0.05; β = 0.295), residents’ attitude towards cultural tourists (H₉; p < 0.05; β = 0.338;), has positively and significantly influenced the resident’s support for cultural tourism.

Figure 2:

Results of PLS-SEM analysis.

It can also be noted that residents’ community attachment and involvement are more influenced by residents’ perceived cultural impact than residents’ support for cultural tourism. In this regard, it is reasonable that these residents who have recently felt involved in cultural-related activities have perceived a positive impact from this sector. However, residents’ perceived cultural impact (H₅; p > 0.05; β = 0.053) indicates that the p-value is not statistically significant. It is noted that residents’ attitude towards cultural tourists more significantly influences the support for cultural tourism than residents’ community attachments, involvement, perceived cultural impact, and attitude towards cultural tourism. Moreover, residents’ perceived cultural impact was found to influence the residents’ attitude toward cultural tourism significantly (H₆; p < 0.05; β = 0.582) and residents’ attitude towards cultural tourists (H₇; p < 0.05; β = 0.600).

4.4 Results of Mediation Analysis

Table 6 shows the simple mediating effect of residents’ perceived cultural impact between residents’ community attachment and residents’ support for cultural tourism and between residents’ community involvement and residents’ support for cultural tourism. It is noted that the direct effect of residents’ community attachment on residents’ support for cultural tourism is significant (p < 0.001; β = 0.134). However, the mediating effect of residents’ perceived cultural impact on this relationship is insignificant (p = 0.311; β = 0.018). Hence, H₁₀ is unsupported.

Similarly, the direct effect of residents’ community involvement on residents’ support for cultural tourism is found significant (p < 0.001; β = 0.106), and the indirect effect of a perceived cultural impact is insignificant (p = 0.311; β = 0.020). This indicates that although there exists a direct relationship between the construct, there is no mediating effect of residents’ perceived cultural impact as the p value of the specific indirect effect is below the significance level of 0.05. Hence, H₁₁ is unsupported.

The parallel mediating effect of residents’ attitudes toward cultural tourism and residents’ attitudes toward cultural tourists is observed in Table 7. The direct effect of residents’ perceived cultural impact on residents’ support for cultural tourism (p = 0.297; β = 0.053), and the indirect effect of residents’ attitude towards cultural tourism (p < 0.001; β = 0.172) is significant. The total effect is (p < 0.001; β = 0.427). The VAF value is 40.28 %, indicating a partial mediating effect of residents’ attitude towards cultural tourism, thus, proving H₁₂.

In the case of H₁₃, the direct effect between perceived cultural impact and support for cultural tourism is found significant (p = 0.297; β = 0.053), and the indirect effect of attitude towards cultural tourists is also found significant (p < 0.001; β = 0.202). Therefore, the total effect reaches (p < 0.001; β = 0.427). The VAF value is 47.30 %, closer to 50 %, depicting a partial mediating effect of residents’ attitudes towards cultural tourists. Overall, the result indicates that even though residents’ perceived cultural impact does not directly influence the residents’ support for cultural tourism, there exists a parallel mediating effect of residents’ attitude towards cultural tourism and cultural tourists between the residents’ perceived cultural impact and residents’ support for cultural tourism. Therefore, H₁₂ and H₁₃ are supported.

The analysis also checks for any serial mediation effect between the constructs in Table 8. The H₁₄ and H₁₅ test the direct and indirect relationship between residents’ community attachment and residents’ support for cultural tourism. It is noted that residents’ perceived cultural impact and residents’ attitudes towards cultural tourism have a significant direct effect (p = < 0.001; β = 0.134), and indirect effect (p < 0.001; β = 0.058), with a VAF value of 20.78 %. The residents’ perceived cultural impact and residents’ attitudes towards cultural tourists have significant direct effects (p < 0.001; β = 0.134), and indirect effects (p < 0.001; β = 0.068), with a VAF value of 24.37 %. Therefore, the total effect implies (p < 0.001; β = 0.279). This means that H₁₄ and H₁₅ are supported and concluded that there is a serially partial mediation effect of residents’ perceived cultural impact and residents’ attitude towards cultural tourism between residents’ community attachment and residents’ support for cultural tourism.

On the other hand, H₁₆ and H₁₇ test the direct and indirect relationships between residents’ community involvement and residents’ support for cultural tourism. It is found that the residents’ perceived cultural impact and residents’ attitude towards cultural tourism have a significant direct effect (p < 0.001; β = 0.106), and an indirect effect (p < 0.001; β = 0.065), with a VAF value of 24.34 %.

Similarly, residents’ perceived cultural impact and residents’ attitude towards cultural tourists have significant direct effects (p < 0.001; β = 0.106), and indirect effects (p < 0.001; β = 0.076), with a VAF value of 28.46 %. Thus, the total effect implied between the constructs is significant (p < 0.001; β = 0.267). This concludes that H₁₆ and H₁₇ are supported, indicating a serially partial mediation effect of residents’ perceived cultural impact, residents’ attitudes toward cultural tourism, and residents’ attitudes toward cultural tourists between residents’ community attachment, residents’ community involvement, and support for cultural tourism.