Sociocultural Sustainability and the Formation of Social Capital from Community-based Tourism

Abstract

Favorable resident perceptions of the development of social capital resulting from hosting community-based tourism is an important issue for the Chinese authorities. This study aimed to develop and test a multidimensional scale to evaluate the perceived social impacts from tourism on social capital from sustainable community-based tourism in China. A questionnaire was distributed to host community residents (430) in Fanhe village, Guangdong Province. Analysis from this survey resulted in the development of a six-factor model incorporating 20 items in the six groups. This allowed the researchers to assess perceived social impacts on social capital: covering collective efficacy, community belonging, traditional social regulations, community cohesion, social networking, and community competence. The study reveals the multidimensional nature of perceived tourism social impacts on social capital in the Chinese tourism community and contributes to a better understanding of how residents view the social capital associated with community-based tourism as part of sustainable development.

Keywords

tourism impact social capital community-based tourism sociocultural sustainability scale development

Introduction

Social capital is an important component of community-based tourism development (Choo and Jamal 2009; Jones 2005; Nunkoo 2017; Ooi, Laing, and Mair 2015). It is a collective and public product that encourages coordination and cooperation among local people to achieve mutual benefits (Li, Zhang, and Zheng 2016; Rastegar 2019). As one of the sustainability indicators of community-based tourism, social capital has the power to bring community members of diverse backgrounds together to engage in meaningful dialogue and socially constructed scenarios (K. Park, Lee, and Lee 2017). China has its own interpretation of social capital based on the specific connotations of Confucian relationships and on the specifics of the country’s social environment (Hwang et al 2009). Social capital in China relates to the interpersonal networks originating from life and work and represents an informal substitute for formal institutions (Zhang, Lee, and Xiong 2019).

Social capital as a component of sustainable community-based tourism in China is composed of the trust, identity, and social connections among community members that allows them to behave rationally to achieve collective goals such as resource preservation and profit sharing (J. Li 2012). These connections are necessary for communities to gain competitive advantage (Lee, Li, and Kim 2007). In China, community-based tourism development has important implications for the sustainability of rural communities (Gao and Wu 2017; Qian et al. 2017; Su, Wall, and Xu 2016). As a concept with a very strong academic potential, social capital provides an important framework for understanding the impacts of tourism development on Chinese society.

Regarding the evaluation of tourism impact on community sustainability, the literature has most often conceptualized those impacts in three categories: economic, environmental and sociocultural (Abukhalifeh and Wondirad 2019; Bhatta and Ohe 2019; Cho, Um, and Lee 2016; Hall and Lew 2009); and they have been assessed using surveys of residents’ perceptions of tourism development (Gursoy et al. 2019; Hadinejad et al. 2019; Nunkoo, Smith, and Ramkissoon 2013) and ethnographic analyses of specific destinations and/or tourism development (Harrison 2007). These studies, while describing the existence and extent of the different impacts, are generally limited with respect to the broader investigation of the noneconomic impacts of hosting community-based tourism, especially social impacts, because of the difficulty in quantifying these. In particular, current research into tourism social impact usually explores how tourism influences the entire community with little concentration on a specific sociocultural aspect.

In the discussions that surround community-based tourism, the capital approach toward the concept of sustainability is conceptualized as maintaining or increasing the stock of social capital, and was proposed by Lehtonen (2004) and Costanza, Graumlich, and Steffen (2007). This approach has been identified as valuable by many scholars, especially when analyzing the concept of social capital within the context of a community’s value systems and traditions, sociological interactions and processes, and its outcomes in terms of sociability (Andereck and Nyuapane 2011; Bennett et al. 2012; Leong 2016; McGehee et al. 2010). This study develops a scale to measure the impacts of tourism on sociocultural sustainability using a social capital perspective.

There has been little research that investigates tourism-related social capital in Chinese culture. The majority of research has been conducted in countries other than China, such as in England (Arcodia and Whitford 2006), South Korea (Choo and Jamal 2009; E. Park, Choi, and Lee 2019; K. Park, Lee, and Lee 2017), Iceland (Jóhannesson, Skaptadóttir, and Benediktsson 2003), the United States (McGehee et al. 2010; Ooi, Laing, and Mair 2015), and Australia (Macbeth, Carson, and Northcote 2004). Also, scales developed to describe social capital in one culture may not be easily transferable to others (Sirakaya-Turk, Ingram, and Harrill 2008). Furthermore, patterns of responses to questions differ across cultures (J. W. Lee et al. 2002). For example, J. W. Lee and colleagues (2002) reported that the Japanese have more difficulty with the scales used in such studies, while the Chinese skip questions more frequently, and both groups are more likely to select the midpoint on a scale than are Americans. Therefore, existing scales for the measurement of tourism-related social capital developed in other cultural settings may have limited applicability in China. The construct validity of the commonly used Likert-type scale measurement items may therefore be restricted to only one culture, requiring researchers to develop scales adapted to a specific culture, even if scales that are transferable to other cultures could also have validity (Sirakaya-Turk, Ingram, and Harrill 2008). Thus, this study aimed to develop and test a scale to measure the impact of social capital on tourism development that is applicable to Chinese culture first and foremost.

This study relies on data collected from 430 residents of Fanhe village located in the Huidong County of Guangdong province. Fanhe is a rural tourism destination with a long history and is characterized by rich cultural and natural resources. With the improvement of the Chinese economy since the 1980s, Fanhe village has become a rich rural place given its trade relations with Hong Kong, abundance of fishing resources, and overseas labor migration. In recent years, both the Huidong county government and the local tourism industry have advocated community-based tourism as a means of increasing tourism revenue, while at the same time allowing greater community participation in tourism development. Fanhe has endeavored to reposition itself from a rural locality to a unique tourism destination, with an emphasis on culture and heritage as the main tourism products provided by local communities.

Literature Review

Social Capital and Sustainable Tourism

The term sustainability is broadly used to indicate programs, initiatives, and actions aimed at the preservation of a particular resource. However, it actually refers to four distinct areas: human, social, economic and environmental—known as the four pillars of sustainability. Among these, social capital is essential as sustainable development can only occur through collective action with an adequate stock of social capital. The power relationships inherent in everyday social interactions between community members enhance the linking ties that increase access to resources outside the community (Bramwell and Lane 2011; Lee and Stanciulescu, 2011) and develop the shared norms, trust, and reciprocity that will foster cooperation for constructive outcomes (T. J. Lee, Riley, and Hampton 2010). Research works by Bourdieu (1985), Coleman (1988), and Putnam (2000) recognize networks and norms as informal social resources necessary for sustainability. In this article, therefore, social capital is defined as informal access to other social norms (including, but not limited to, trust and reciprocity), networks, and resources in particular spaces and structures resulting from social ties.

The existing literature suggests that the three components of social capital are bonding, bridging, and bracing. Putnam (2000, p. 22) describes bonding social capital as the connections that are created among people with similar characteristics such as class, ethnicity, background, and interests, whose networks reinforce exclusive identities and solidarity and focus upon trust and reciprocity that exists within closely knit networks; and bridging social capital refers to the connections between nonsimilar groups, or “people unlike ourselves,” thereby extending linkages to external assets and information diffusion that encourages generalized reciprocity and the creation of broader social identities. Rydin and Holman (2004) proposed an additional type of social capital known as bracing social capital that “braces” the linkages created by bonding and bridging networks and suggests personal connections between various groups through different ties. Kusakabe (2012) argued that bonding social capital builds on effective norms and achieves solidarity within communities, but limits access to various external resources. Bridging social capital helps to extend networks and can maintain information flow but is weak in generating collective action through solidarity creation, while bracing social capital can expedite common problem framing and joint strategy formation by connecting various networks across sectors, scales, and localities, thus making it possible for collective action to occur.

With deep roots in Confucianism, social capital in Chinese society is as abstract as it is concrete (Y. Zhang, Lee, and Xiong 2019), and is highly influenced by the concept of Guanxi. This concept represents particularistic ties based on favor and interdependence in Chinese community, such as kinship, relational demographics between family, marriage, education, and profession (Farh et al. 1998), and is governed by unwritten norms of reciprocity (Hwang et al. 2009). A set of indigenous Chinese guanxi concepts has been identified as constituent dimensions of social capital such as mianzi (face saving), lishangwanglai (reciprocity), renqing (indebtness), ganqing (affection), and xinren (trust) (X. P. Chen and Chen 2004; Kipnis 1997). These dimensions of social capital in the Chinese community indicate the informal nature of the concept relevant to the specific conditions of China (Woolcock and Narayan 2000; Xu, Perkins, and Chow 2010).

According to the capital approach (Costanza, Graumlich, and Steffen 2007), sustainability can be best explained by comparing the “empty world” and “full world” models of economics. In the empty world model, the only capital resources that matter are product (economic) and financial capital, and individual well-being results from the consumption of goods and services, while the goal of economic activity is how to best convert land and labor into goods and services. This model has largely driven the business agenda but has to be changed if sustainability is to be achieved. An alternative to the empty world model is the full world model in which there exists multiple forms of capital, including natural, social, economic, and human capital. Well-being in this alternative model is expanded to include recognition of the need to balance individual and community development, and the goal of economic and government action is to protect and enhance stocks of all forms of capital. Lehtonen (2004) refers to this as the capitals approach to sustainability and defines sustainability as “the maintenance or increase of the total stock of different types of capital” (p. 200). Adapting this approach to tourism suggests that from the destination perspective, sustainable tourism development can be defined as tourism activities that maintain and enhance all forms of capital, including social, cultural, economic, environmental, and natural resources, while recognizing the primary importance of natural capital (Sinclair-Maragh and Gursoy 2017).

The social capital concept has influenced the debates around social sustainability (Macbeth, Carson, and Northcote 2004). As a conceptual tool for examining the sociological interactions and processes associated with tourism, Jones (2005) adopted social capital to examine the social change surrounding the formation of a community-based ecotourism venture in Gambia. The role of social capital in determining tourism entrepreneurship (Karlsson 2005; Nordin and Westlund 2009; Zhao, Ritchie, and Echtner 2011), as well as its importance in developing grassroots cultural tourism initiatives as coping strategies for rural communities (Jóhannesson, Skaptadóttir, and Benediktsson 2003; Kim et al. 2016) has also been the subject of research. McGehee and colleagues (2010) explored the relationship between the length of residence of tourism stakeholders and social capital, and the relationships that exist between the existence of social capital and other forms of capital to gain a better understanding of rural tourism development.

Meanwhile, research on community development has acknowledged the many positive outcomes of social capital such as community capacity, cooperation, the desired enhancement of community attachment and ownership, and the potential for residents to act collectively to achieve mutual goals as the indicators of community sustainability (Gittel and Vidal 1998). As social capital incorporates the distribution and use of resources and the subsequent exercise of power, the ability to illuminate social inequities often exists within collectives, such as social exclusion and the marginalization of individuals resulting from their inability to access resources (Roseland 2000). Additionally, both formal and informal networks and norms and resources emphasize the importance of quality relationships in enabling community members to collaborate and contribute to decision-making processes in a democratic and equitable manner. Therefore, social capital outcomes mirror those associated with sociocultural sustainability and suggests its utility as a conceptual guide for examining the sociocultural dimension of sustainable tourism.

The Social Impact on Social Capital from Tourism

The social impacts of tourism development are important since they may have even more substantial influence on the community (Jiang, Su, and Du 2013; E. Park, Choi, and Lee 2019). Yet they have been commonly assessed as a one-dimensional concept. One possible reason is that sociopsychological attitudes and impacts are correlated and hard to separate completely (Fredline, Jago, and Deery 2003; T. J. Lee, Riley, and Hampton 2010). Moreover, tourism social impacts not only affect local society in negative ways, but also in positive ways. Sustainable tourism requires that the positive impacts of tourism are enhanced, and at the same time the adverse consequences on development (Ooi, Laing, and Mair 2014; Prayag et al. 2013) are minimized.

Reviews of this area of research by Misener and Mason (2006) and Moscardo (2008) have identified several links between hosting tourism activities and social capital. These include community pride and shared values and identity, closer social bonds with family and friends, and the development of networks (both internal and external). Therefore, the positive sociocultural impacts of tourism development include cross-cultural communication, positive changes in values and customs, and cultural exchanges that lead to the formation of harmonious relationships between different individuals and groups. Meanwhile, Kim and Petrick (2005) found that image enhancement and consolidation are the most salient positive impacts of tourism development. In addition, socialization can be developed by tourism coordination through the creation of networks and associations to organize and coordinate tourism activity within a community (Jones 2005; McGehee et al. 2010; Moscardo 2008; Wang and Xiang 2007).

Based on the aforementioned issues, the current study investigates the perceived social impacts of community-based tourism from the social capital perspective through dimensional structures that consist of three initial constructs: (1) community consolidation, (2) community competence, and (3) community visibility and image enhancement. This study contributes to the social impact literature by integrating additional theoretical underpinnings about social capital and by investigating collective efficacy, community cohesion, and social networks. In this way, the article builds on existing findings by adding several previously unmeasured dimensions.

Social Capital in the Chinese Community-based Tourism Context

With deep roots in Confucianism, social capital in Chinese society is as abstract as it is concrete (Y. Li, Zhang, and Zheng 2016) and is largely influenced by the concept of Guanxi. This concept represents ties based on favor and interdependence throughout the Chinese community (P. P. Li 2006), such as kinship, the relational demographics between family, marriage, education, and occupation (Farh et al. 1998; Preston et al. 2017), and is governed by the unwritten norm of reciprocity (Hwang et al. 2009; Zhang, Ding, and Bao 2009). A set of indigenous Chinese guanxi concepts has been identified as the constituent dimensions of social capital: such as mianzi (face saving), lishangwanglai (reciprocity), renqing (human sentiment), ganqing (affection), and xinren (trust) (X. P. Chen and Chen 2004; Kipnis 1997). In the context of Chinese community-based tourism, social capital has been used as an analytical tool to deconstruct the complex social network within and outside rural tourism communities (Adongo, Choe, and Han 2017). Empirical studies reflect this concept’s usefulness and explanatory power in addressing various sustainability issues in tourism. Social capital influences local tourism business success as well as the community’s capacity to resolve problems (Guo, Wang, and Zhu 2015; X. M. Zhang, Ding, and Bao 2009). Hence, investigation of the measurement of social capital in Chinese community-based tourism should incorporate aspects of Chinese social thinking within empirical methods of social analysis (Yang, Ryan, and Zhang 2012).

Methodology

Research Setting

The study was based in Fanhe village, a settlement of Huidong County in the Guangdong province of China. Fanhe has more than 10,000 residents that belong to the 50 different clans of Hoklo and Hakka that migrated from the neighboring Fujian and Guangdong provinces from the end of the Ming Dynasty. Gao, Wang, Guo, and Lin are the top four family names, and shared by around 70% of the village population. Intermarriage between people of different family names creates complex social networks in the village. Agriculture, fishery, salt extraction, and coastal trade are the traditional industries of this village, but tourism is one of the main sectors of the local economy. As the village is made up mainly of migrant residents, their social and cultural doctrines such as familial loyalty, ancestor worship, respect for seniority, and cultivation and reading are derived from the Central Plains of China, and accompanied these migrants as they arrived in Guangdong in search of new survival strategies and seeking to engage in the local social-political system (Knapp 2005). These social and cultural norms are Confucian in origin; thus, traditional social orders and norms of behavior, communication, and daily movement for clan members are present within their life and work (Lowe 2012). The enclosed house group is the representative architecture of accommodation as built by these clans. For security reasons and for ensuring the solidarity of the clans, these house groups can only be opened from the inside. Personal networking is based on the traditional family and clan structure, which is the root of social capital development in a village (Kipnis 1997; Su, Wall, and Xu 2016; X. M. Zhang et al. 2019).

In 2014, tourism infrastructure in Fanhe village was limited. Roads, tourism maps, and other tourism instruments have been built with funding from local government in the past five years since then. However, the tourism planning and strategies that had been set previously were not put into practice because of conflicts between residents and the local village committee. Some local residents have started family inn businesses, while those who were traditionally involved in fishing activities have become tour guides. As one of the biggest villages in Huidong County, there are 12,600 residents who have local household registration (Hukou) in Fanhe, but only 10% of all residents actually live in the village. Meanwhile, as in other Chinese villages, many of the younger or middle-age residents have moved away to the cities in the past five years, leaving mainly senior residents.

As noted above, tourism development in the village is characterized by conflicts between residents and development over resource sharing and profit distribution. Given that most people choose to keep harmonious links with other family members, clan and neighbors are of ultimate importance. As for their relationship with the external world, irrespective of conflicts, residents display strong identity and belongingness to the village, especially their significant solidarity when faced with external challenges. However, residents also display enthusiastic attitudes toward tourism, although they have expressed concerns about the local village committees’ weak tourism leadership and lack of local participation in tourism development. As a result, despite the potential economic opportunities present in the tourism sector, only around 150 residents are employed by tourism businesses. Moreover, there are no formal institutions to manage tourism development in the village, although recently a public welfare council composed of members from the local communities has started getting involved in the day-to-day management of tourism.

In 2014, the village was added to the List of Historical Famous Villages of China by the Chinese Ancient Village Protection Development Committee in recognition of its unique seaside landscape, rich architectural relics, and the well-preserved ancient village scenery. Community-based tourism featuring folk cultures has developed rapidly in the village and has attracted thousands of visitors over the past few years. Some villagers participate actively in tourism as tour guides, opera performers, and by working in restaurants. The tourism industry has also attracted external investors in the hotel and transportation businesses. External control over tourism development in the village has meant that policy decisions are made by the elites, while the local administrative committee of the village has had little power in tourism policy making.

Scale Development Process

To undertake the analysis, a total of 58 items for measuring the tourism-related social capital in the village, measured on a 5-point Likert-type scale, were derived from the existing literature. A pilot study was also conducted. The pilot questionnaire was distributed to a number of residents of the village. They were asked to provide feedback regarding the layout, wording of the statements, and the ease of understanding of the statements that comprised the measurement scales. Following Babbie (2005), the items were also discussed among experts and professionals of the tourism industry, as well as with community leaders who were asked to comment on the clarity, relevance, and effectiveness of the items. This process resulted in the deletion of 17 items that were considered to poorly measure social capital in tourism development from a conceptual as well as a practical point of view from the scales. The remaining 41 items were tested empirically using a pilot study sample of 60 respondents. Item-to-item correlation and Cronbach’s alpha values were used to further refine the scale items. Four items were further eliminated, resulting in a final scale comprising of 37 items.

These items were assessed by a panel of experts that included two local university tourism professors, two tourism operators from Huidong County, one government official from the tourism bureau of Huidong County, and two Fanhe village committee members. Each participant was asked to comprehensively assess the 37 items and then report their opinions on the relevance, representativeness, clarity, format and wording, and the item content of the questionnaire (Babbie 2005). Based on feedback from this panel, the scale was further modified, revised, and improved to enhance its clarity and face validity. After this panel modification, a pilot study of local residents (n = 60) was undertaken to examine the content validity with the perspectives of the targeted population and so assess the reliability of the developed scales (Ary, Jacobs, and Sorensen 2009). A total of six additional items were eliminated based on Cronbach’s alpha coefficient and related statistics. The modified scale then included 31 items that fell within Cronbach’s alpha value and suggested cut-offs (Lance, Butts, and Michels 2006), which means that it could be used for further analysis. Following the pilot study, the retained questionnaire with these 31 items was deployed.

Data Collection

Data collection took place in Fanhe village from August to November 2014. As the survey was carried out in a Chinese community, the questionnaire was translated from English to Chinese using the procedure established by Nurjannah et al. (2014). First, forward translation was conducted by two bilingual researchers independently. Next, the two versions of the translated questionnaires were thoroughly compared by the two translators to locate any translation errors (i.e., incorrect wording, ambiguous terms, etc.). Finally, back translation was conducted by a bilingual doctoral student who majors in tourism management and English literature. The student was asked to retranslate the questionnaire into the original language (English) so the researcher could compare its accuracy and equivalence.

According to the recommendations of appropriate sample size by Hair et al. (2014) and Kline (2005), the target sample size was at least ten respondents for each item. Following C. C. Chen, Lin, and Petrick (2013), the questionnaire was administered to potential respondents who were approached mainly in selected public areas (i.e., shopping areas and neighborhoods) using a random day/time/site pattern (Bonn, Joseph, and Dai 2005). The sample consisted of adults (older than 18 years) who were permanent residents of Fanhe village and working in the tourism industry. Ten graduate students who were fluent in the local dialects and had the necessary field training carried out the survey. The students provided assistance to the respondents when necessary. Of the more than 600 residents that were approached to complete the survey, 500 agreed to participate. After discarding 70 incomplete questionnaires to avoid statistical bias, 430 usable questionnaires, representing a response rate of 86%, were available for the data analysis.

Statistical Techniques

The sample (N = 430) was randomly split into two. The first half of the sample (n = 215) was subject to an exploratory factor analysis (EFA) using principal components analysis and varimax rotation with the purpose of obtaining valid factor structures (V. W. Mitchell and Greatorex 1993). Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin measure of sampling adequacy were used to determine the appropriateness of the data for EFA (Kaiser 1974). In addition to the statistical results, it was also ensured that the factors retrieved could be theoretically interpreted. The second half of the data (n = 215) was used for a confirmatory factor analysis (CFA) using the following five steps recommended by Tabachnick and Fidell (2001): (1) model specification; (2) model identification; (3) model estimation; (4) testing model fit; and (5) model respecification. The model was evaluated using a number of fit indices: chi-square statistic (χ²), the normed chi-square (χ²/df), the root mean square residual (RMR), the root mean square error of approximation (RMSEA), the normed fit index (NFI), and the comparative fit index (CFI). The model was also tested for its reliability and validity (Nunkoo and Ramkissoon 2012; Nunkoo, Ramkissoon, and Gursoy 2013).

Results

Profile of Respondents

The profile of the respondents is presented in Table 1. Slightly more than half of the respondents were male (54%), while the remaining were female (46%). The majority of the respondents were aged between 31 and 50 years. The oldest and youngest respondents were 74 and 18 years old, respectively. More than two-thirds of the sample (66%) were married. Around 35% of them had more than one child younger than 18 years. Most of the respondents (82.6%) had resided in the village for more than 20 years. Respondents had a fairly low level of education.

Table 1.

The Demographic Profile of Respondents (n=430).

Item/Category	Percentage
Gender
Male	54.0
Female	46.0
Household annual income, US$
<5,000	21.4
5,001–10,000	40.5
10,001–15,000	25.6
>15,000	12.6
Age, years
18–20	6.0
21–30	19.3
31–40	25.6
41–50	23.7
51–60	16.4
61 or older	8.8
Marital status
Married with child(ren)	35
Married without a child	31
Single with child(ren)	14
Single	20
Education level
Primary school or lower	25.6
Middle school	44.2
High school	20.0
Bachelor’s degree	10.5
Master’s degree or higher	0.0
Period of residence
≥5 years	0.0
6–10 years	3.7
11–15 years	5.4
16–20 years	8.3
>20 years	82.6

The 31 items had a mean score of between 3.06 and 4.08 (Table 2), indicating that respondents had a strong perception of the impacts of tourism development on social capital. They displayed strong opinions about the influence of tourism development on traditional moral rules within the community. However, respondents also felt that they did not have enough power to influence tourism development.

Table 2.

Mean Value Analysis for Social Capital Variables (n=430).

Variable	Mean	SD
S6. Reinforced community spirit	4.08	0.795
S1. Enhanced bonding between neighborhoods	3.97	0.573
S2. Take much more pleasure to help in the neighborhood	3.96	0.593
S5. Increased kin and clan reunion events and more participants	3.96	0.795
S3. Increased trust between neighborhoods	3.93	0.506
S19. Care more about community image	3.88	0.680
S4. More respect for the seniors and cherishing the young as traditional virtues	3.88	0.644
S13. More concern about opinions of the neighborhood	3.86	0.778
S14. More interested in what happens in the community	3.86	0.849
S18. Better destination image of the community	3.84	0.648
S25. Have a stronger sense of belonging to the community	3.83	0.559
S15. Enhanced trust in the leadership of the village committee	3.83	0.648
S20. Improved interpersonal relationship in the community	3.83	0.673
S11. More frequently exchange opinions within one’s neighborhood	3.83	0.615
S30. Compared to others, residents are more satisfied with service in this village	3.82	0.731
S21. Enhanced public order and good custom in the community	3.74	0.659
S26. Residents are more likely to achieve consensus when they have differing opinions	3.73	0.764
S9. Enhanced friendship between residents in the community	3.73	0.575
S22. Increased attachment toward the community	3.72	0.640
S10. Feel more like the community is home	3.71	0.636
S16. Community has stronger capacity to resolve problems	3.71	0.710
S31. More spontaneous contact with the village committee through telephone/post/e-mails	3.66	0.639
S29. Identify more closely with community issues	3.62	0.788
S23. Enhanced social support in the community	3.61	0.578
S12. Feel being a more important part of this community	3.57	0.893
S7. Increased responsibility for this community as its member	3.54	0.622
S17. Increased influence on improving community image	3.46	0.830
S24. Reinforced social contact network	3.44	0.637
S8. Increased intention to participate in local organizations	3.29	0.712
S27. Has more influence on issues outside of the community	3.08	0.698
S28. Has more influence on issues within the community	3.06	0.786

Note: SD = standard deviation.

Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA)

EFA

Two separate sets of EFA were conducted to identify and refine the latent factor structure. Results from the Kaiser–Meyer–Olkin measure of sampling adequacy (0.768) and Bartlett’s test of sphericity (2448.027, p < .001) suggested that the data were suitable for an EFA. As a result of principal axis factoring (PAF) with varimax rotation, nine factors within the 31 items were identified, explaining 55.27% of the variance. However, three of the nine factors only had two items. Following the recommendations of Raubenheimer (2004) that a reliable factor must have at least three items, the three factors were removed from any further analysis. The second factor analysis of the remaining 25 items indicated that six factors could be identified, and these explained 62.35% of the variance. Item S31 was deleted as it loaded on more than one factor and displayed the same load score (Wu, Qiu, and Wang 2005). A scree plot indicated that the six factors were warranted. The six factors extracted from the EFA were as follows: collective efficacy (five items), community belonging (five items), traditional social regulation (three items), community cohesion (three items), social network (four items), and community competence (four items).

CFA

The second half of the data set (N=215) was used to conduct a CFA using the recommendations of Tabachnick and Fidell (2001). The six-factor model consisting of 24 items was subjected to a CFA to aid in its specification. However, the model did not display a good fit. The RMSEA indicated an unreasonable fit for the six-factor model (RMSEA = 0.117), which was above the recommended cutoff value of less than 0.08 (Loehlin 2004). The RMR (0.062) was beyond the acceptable fit range (<0.05; Kline 2005). The CFI (0.715) was below the cutoff value (>0.90) and, lastly, the NFI (0.660) was also below the suggested cutoff value (>0.90). Therefore, the model had to be respecified to be improved (Meyers, Gamst, and Guarino 2017). During model respecification, in order to enhance convergent validity, four items (S3, S7, S25, and S26) were removed because they had factor loadings ranging from 0.37 to 0.48, lower than the recommended minimum value of 0.50 (Anderson and Gerbing 1988). The remaining six-factor model with 20 items was subjected to a CFA, but the goodness-of-fit indices produced by the six-factor modified model with 20 items did not fit the data either. The normed chi-square value (χ²/df = 3.76) was greater than the recommended cutoff value of less than 3.0 (Bollen 1989). In addition, the RMSEA value (0.11) showed an unreasonable fit. Thus, the model had to be further refined.

To do this, the correlation of error terms based on the modification indices were analyzed to improve the model fit (Wu, Qiu, and Wang 2005). The researchers also considered the possibility that correlations that have no theoretical support may result in a lower interpretability of the retained model (Bollen 1989). Therefore, the researchers carefully assessed the model using modification indices, interfactor correlations, and indicator loadings and also considered its theoretical foundation. As a result, S15 was correlated with S16 within the retained 20 items based on the theoretical rationale that developing trust and social capital through tourism development will achieve the required collective action and finally gain the common target (Narayan and Cassidy 2001). The MI was 69.88, which is much higher than 5. S13 (more concern about opinions of the neighborhood) and was connected with S14 (more interested in what happens in the community), given a relatively higher MI (=29.09) as they are both elements which represent residents’ sense of community (Prince et al. 2019).

The remaining six-factor model with 20 items were reevaluated using CFA. The results indicated a better model with an improved fit (χ² = 448.34, p < .001). The normed chi-square (χ²/df =2.93) was lower than the recommended 3.0 value (Bollen 1989). The RMSEA indicated that the current model recorded a good fit (RMSEA = 0.092), and the RMR value (0.040) was less than the cutoff value of 0.05 (Kline 2005). The CFI value (0.864) and the NFI (0.810) were within an acceptable range, indicating an adequate fit (Hu and Bentler 1999). Table 3 presents the model fit comparison of the examined models.

Table 3.

Model Fit Comparison for the Second Data Set (n=215).

Model	χ²	χ²/df	RMR	RMSEA	GFI	NFI	CFI
6 factors, 24 items	985.458	4.158	0.062	0.117	0.732	0.660	0.715
6 factors, 20 items(Removed S3, S7, S25, and S26)	582.791	3.760	0.42	0.110	0.783	0.769	0.827
6 factors, 20 items(Linked S15, S16, S13, and S14)	448.340	2.930	0.040	0.092	0.837	0.810	0.864

Reliability for the perceived tourism social impact on social capital was examined by assessing standardized regression weights (SRWs), Cronbach’s alpha coefficients (α), construct reliability (CR), and average variance extracted (AVE) values (Table 4). The Cronbach’s alpha values were above 0.70, which is the recommended threshold (Hair et al. 2014), while the factor “social network” had a relatively lower value (α = 0.668). According to Nunnally (1978), a coefficient α value in the range from 0.6 to 0.7 should be the minimum acceptable level of reliability. Therefore, we retained this factor in the scale. The CR values for all factors were well above the threshold of 0.70 (Byrne 2010). The AVE value for these factors were from 0.42 to 0.72. However, “collective efficacy” (0.42) and “social network” (0.45) had AVE values that were below the recommended 0.50 threshold (Schumacker and Lomax 2010). According to Hatcher (1994), when construct reliability is acceptable, a marginally low value of the AVE can be accepted. Thus, these factors were retained in the model.

Table 4.

Reliability test results (n=215).

Factors	SRW	A	CR	AVE
Collective Efficacy (4 items)		0.778	0.74	0.42
S15. Enhanced trust in the leadership of the village committee	0.54
S16. Community has stronger capacity to solve problems	0.54
S18. Better destination image of the community	0.77
S20. Improved interpersonal relationship in the community	0.72

Community Belonging (5 items)		0.841	0.84	0.51
S13. More concern about opinions of the neighborhood	0.63
S14. More interested in what happens in the community	0.66
S21. Enhanced public order and good custom in the community	0.61
S22. Increased attachment toward the community	0.87
S7. Increased responsibility for this community as its member	0.79

Traditional Social Regulation (3 items)		0.806	0.81	0.59
S4. Respect the seniors and cherish the young as traditional virtues	0.71
S5. Increased kin and clan reunion events and more participants	0.83
S6. Reinforced community spirit	0.77

Community Cohesion (2 items)		0.703	0.84	0.72
S23. Enhanced social support in the community	0.72
S24. Reinforced social contact network	0.97

Social Network (3 items)		0.668	0.71	0.45
S8. Increased intention to participate in local organizations	0.57
S9. Enhanced friendship between residents in the community	0.63
S10. Feel more like the community is home	0.81

Community Competency (3 items)		0.808	0.85	0.66
S17. Increased influence on improving community image	0.82
S27. Has more influence on issues outside of the community	0.91
S28. Has more influence on issues within the community	0.71

In addition, discriminant validity was examined by analyzing the interfactor correlation values (Table 5). The results indicated that all interfactor loadings were sufficiently below the recommended threshold (0.85) of Kline (2005); ranging from 0.019 (traditional social regulation) to 0.769 (community belonging). Therefore, the model achieved discriminant validity.

Table 5.

Interfactor Correlations from the Confirmatory Factor Analysis (n=215).

	Community efficacy	Community belonging	Traditional social regulation	Community cohesion	Social networks	Community competence
Community efficacy	1.0
Community belonging	0.769	1.0
Traditional social regulation	0.231	0.019	1.0
Community cohesion	0.180	0.050	0.037	1.0
Social networks	0.380	0.260	0.578	0.138	1.0
Community competence	0.291	0.297	0.095	0.402	0.066	1.0

Discussion and Conclusion

Discussion

The study validated the psychometric properties of the impact of community-based tourism on social capital in a Chinese community. When the results are interpreted in the light of existing theoretical perspectives on social capital and the unique features of the Chinese culture, the study provides a clear understanding of the impact of tourism development on social capital in such a culture. The dimensions extracted from the study are mostly congruent with earlier research results; however, each of the six dimensions of social capital must be interpreted from the perspective of the Chinese sociocultural environment to understand the role of tourism development and sociocultural sustainability in that country. The construction of factors illustrates that in communities like Fanhe, tourism’s social impact mainly affects traditional values, responsibilities, and obligations as these are the key elements of social capital. These are based on family structure and are centered on the family and then extended to community and other relationships. This is a major difference compared to the social order, philosophy, and worldviews of other countries. Social relationships within the community are the effect targets as well since they are based on the extended-family type of network. Thus, official leadership is both trusted and respected, and regarded as a patriarch of the whole community. This could be positive for community-based tourism development as community members care for and matter to each other and will share the resources and benefits derived from the industry.

The significant merit of social capital for community-based tourism has been widely acknowledged in the literature. It facilitates the sustainable development and good governance of the tourism sector by fostering cooperation between individuals and groups (I. S. Lee, Lee, and Arcodia 2014; Nunkoo 2017). Social capital enables the creation of tourism business clusters, bridges social inequality between communities, develops a sense of identity and common purpose among community members, and creates solidarity within tourism networks (Nunkoo 2017; Woolcock and Narayan 2000). Despite the various benefits of social capital for sustainable tourism, the literature has failed to analyze the distinctive features of social capital in community-based tourism in Chinese culture that have unique sociocultural traditions and economical-political conditions (P. P. Li 2006; Lin 2002; Meyer 2006). The majority of studies on the topic have been carried out in countries other than China (e.g., Arcodia and Whitford 2006; Choo and Jamal 2009, Jóhannesson, Skaptadóttir, and Benediktsson 2003; Macbeth, Carson, and Northcote 2004; McGehee et al. 2010; Ooi, Laing, and Mair 2015; E. Park, Choi, and Lee 2019; K. Park, Lee, and Lee 2017).

Theoretical Contribution

The findings and theoretical perspectives that existing studies provide have not been sufficient to explain the relationship between tourism development and social capital in Chinese community-based tourism ventures. This study therefore contributes to the literature by testing and validating a scale to measure the influence of community-based tourism development on social capital in a Chinese tourism community destination, Fanhe village. In doing so, it identifies and establishes the impact of community-based tourism development on social capital in China. The results confirm and validate a six-factor model that conceptualizes the impact of community-based tourism development on social capital. The model includes the following dimensions of social capital: collective efficacy, community belongingness, traditional social regulations, community cohesion, social network, and community competency.

The study identifies the influence of community-based tourism on community cohesion, as development works to enhance social support among community members and reinforce social networks among local residents. In other cases, tourism development has led to an improvement of community cohesion in China by providing opportunities for local residents and families to work together to build successful tourism businesses (Y. Zhang, Lee, and Xiong 2019). Our results also suggest the influence of community-based tourism development on community efficacy. Previous studies suggest that collective efficacy has a range of positive behavioral outcomes, with implications for sustainability (M. F. Chen 2015; Doran, Hanss, and Larsen 2017; Jugert et al. 2016).

Our study suggests that community-based tourism development has some influence on community belongingness as an important dimension of social capital. Development of tourism in Fahne village improves residents’ interests in community issues and their concerns for others, improves their attachment to the community, promotes social order, and increases responsibility and accountability vis-à-vis their community. Community belongingness as a component of social capital has also been emphasized by studies outside the tourism field (Carpiano and Hystad 2011; Xu, Perkins, and Chow 2010). In addition, our study finds that community competency is an important internal dimension of the social capital affected by community-based tourism in the village, although some theorists consider community competency as an outcome of investment in social capital. Community competency refers to the problem-solving ability of local residents that arise through collective efforts (Lochner, Kawachi, and Kennedy 1999). Our study suggests that tourism improves community competency by empowering local residents to influence development within and outside their community.

Community-based tourism influences social capital via its influence on traditional social regulation. Such a consequence of tourism development may be more relevant to the Chinese culture because of its Confucian-based traditions. Confucian philosophy had an enormous influence on Chinese culture and emphasized a number of important values underpinning relationships and interactions among people (Fan, Zhang, and Wang 2008). Confucian principles are based on three aspects: ren—the ability of individuals to extend generosity and compassion to others; li—proper social behavior; and Hsiao—the love and respect for one’s family and extending this love and respect to others (Arcodia 2003). The Confucian values prevailing in Chinese culture can explain our findings pertaining to the influence of community-based tourism on traditional social regulation in the study setting. We found in this study that community-based tourism development led to more respect among youngsters for the older residents in the community, while the latter were more receptive of the formers’ values and ways of living. Tourism development also improves ties between kin and clan, reinforcing social relationships among community members.

Practical Implications

The results suggested that traditional Chinese thinking about social capital plays an important role in community-based tourism ventures by treating all members of the society as part of a wider family and by maintaining traditional social order based on trust, reciprocity, family, and clan. However, some residents have insufficient influence on decision making within and outside of the community. For tourism industry practitioners, some critical implications follow from this: first, the positive elements of tourism social impact on traditional social capital, in essence, are an illustration of social cultural sustainability, which needs to be preserved and promoted for it to foster a sense of community and help to establish collective actions to identify and achieve common goals; second, residents who “stock” this social capital and who are not involved in local tourism management should be encouraged and empowered to make use of these resources in advancing community-based tourism and its sustainable development.

Enhanced solidarity between community members is one of the important dimensions of social capital and requires that tourism managers guide and use this positive attribute of social capital in the management of development in the village. In this way, conflicts over shared resources and benefits will be reduced, a collective identity can be fostered, and common targets and action through community developments can be achieved. In the case of Fanhe village, enclosed houses, which are shared by different clans, could be operated through clan alliances, based on their high trust in each other. In addition, developing strategies that enhance local residents’ decision-making rights in community development issues and stimulate their participation in the tourism industry can be encouraged. This may help managers and government officers achieve greater positive integration within the local community and a better understanding of residents’ concerns over tourism development, especially those that stem from the local wisdom that is an outcome of social capital over time. As for the destination management system, encouraging residents to engage with and support formal institutions should be a preferred option as well.

Limitations and Further Research

Future studies should evaluate the possible modifications to and validation of the scale of tourism impacts on social capital based on qualitative data, so that the final scale of tourism impacts on social capital can illustrate a deeper theoretical interpretation of residents’ inner thinking. Secondly, participants were from one single place and from a limited sampling frame given the financial and resource limitations of the study. This may mean that the scale in this study might not be appropriate to other contexts and populations. For future research, it would be valuable to assess the response for other types of Chinese communities, across other ethnicities and villages, and those that are in a different life cycle period, to provide better managerial insights based on a more comprehensive understanding of tourism impact and community-based tourism.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Timothy J. Lee

Robin Nunkoo

Author Biographies

Yang Zhang is an Associate Professor in the Faculty of Hospitality and Tourism Management at the Macau University of Science and Technology. Her research interests include cultural issues in the tourism and hospitality field, sustainable tourism, and tourism migration.

Yu Xiong is a Lecturer in School of Innovation and Entrepreneurship Education at East China University of Technology. She was awarded her doctoral degree with Magna cum laude at the Macau University of Science and Technology. Her main research interests are tourist behavior, tourism marketing, and tourist behavior. She has published many research articles and conference proceedings.

Timothy J. Lee is the Founding Director of the APRI-HOTH (Asia Pacific Research Institute for Health-Oriented Tourism & Hospitality) and GLOSITH (Global Congress of Special Interest Tourism & Hospitality). He serves as the Editor-in-Chief of International Journal of Tourism Sciences. His research interests include wellness/health tourism, cultural heritage tourism, and tourism development that incorporates East Asian values. He has published more than 200 research articles including 65 in the SSCI-indexed journals. His personal website is .

Min Ye is an Associate Lecturer in the Faculty of Tourism Management at Huizhou Economics and Polytechnic College in China. She holds a MTA from the Macau University of Science and Technology, and has interests in quantitative research methods, social capital, and sustainable tourism.

Robin Nunkoo is an Associate Professor in the Faculty of Law and Management at the University of Mauritius; a Visiting Senior Research Fellow in Faculty of Management at the University of Johannesburg, South Africa; an Adjunct Professor at Griffith Institute for Tourism, Griffith University, Australia. He holds a PhD from the University of Waterloo, Canada and has research interests in quantitative methods, sociology of knowledge, and sustainable tourism.

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