Perception of social prosperity in indigenous tourism destinations in Mexico: The mediator effect of competitiveness of the destinations

Abstract

In this study, the relationship between community social capital and social prosperity is analysed, as well as the mediatory effect of competitiveness in indigenous tourism destinations from the perspective of the residents in indigenous communities. The sample was 103 people from 10 communities that are recognised as indigenous communities as affiliates of the Red Indígena de Turismo de México A.C. (RITA) (Indigenous Network of Tourism in Mexico). The analysis of the data and proof of hypothesis was carried out through partial least squares structural equation modelling (PLS-SEM). The discoveries show that the competitiveness of the destinations has a mediatory effect between the community social capital and the perception of social prosperity. It was found that the indigenous people perceive social prosperity through the competitiveness of the destination given that said competitiveness has various effects; more tourists have arrived at the destination, the tourist activities that benefit the local economy have been better managed, the creation of new businesses and jobs, entrepreneurship, investment in infrastructure, improvement in access to public services, and care for the natural resources of the communities. This competitiveness is directly influenced by the community social capital of the indigenous tourism destinations.

Keywords:

• community social capital
• tourism destination competitiveness
• social prosperity
• indigenous tourism
• structural equation modelling

public interest statement

The study presents a relationship analysis between community social capital, competitiveness and social prosperity in indigenous tourist destinations. The results of the study revealed that social capital affects in a positive way the development of competitive management factors. Indigenous tourism destination management is the result of the experience in the management of common goods, such skills in combination with collective actions help communities to be competitive in the tourism market. The benefits derived from the tourist activity are called social prosperity and it is perceived by the increase in wealth distribution, improvement of the quality of life and the management of environmental practices in which communities are involved to maintain and preserve the natural and cultural resources of the destination.

1. Introduction

In indigenous communities, tourism plays an important role. The communities that were previously dedicated to agricultural, agroforestry, and pisciculture activities found a way to diversify their economic activities through tourism (Musavengane & Simatele, 2016; Situmorang, 2018). Ecotourism, community-based tourism, nature-based tourism, and indigenous tourism, have developed as a response to international agreements for the sustainable use and leverage of natural and cultural resources in the name of conservation (Espeso-Molinero & Pastor-Alfonso, 2020; Romão et al., 2021).

For decades, indigenous people have had little access to tourist activities and thus little access to the benefit of the tourism industry (Hinch & Butler, 2009; Pereiro, 2016; Scheyvens et al., 2021). After years of exclusion and exploitation of their culture as a tourist attraction (product), the indigenous communities have become indigenous tourism destinations, where the indigenous residents have direct and collective participation in management activities for tourism development.

Indigenous tourism has been an option for economic development and the cultural and natural revival of indigenous towns (Hinch & Butler, 2009; Hoque et al., 2020; Pereiro, 2016; Ruhanen & Whitford, 2019; Scheyvens et al., 2021). Indigenous communities’ cultural wealth and biodiversity are their main competitive advantage in the tourism industry (Hinch & Butler, 2009; W. Liu et al., 2016). The sustainable development projects for tourism have given indigenous tourism a way to alleviate the poverty in indigenous regions, and empower indigenous people in tourist activities. This is done through entrepreneurship and the creation of small businesses in order to obtain economic income, whilst also utilising and conserving their culture and natural resources (Hoque et al., 2020; Ruhanen & Whitford, 2019; Scheyvens et al., 2021).

This study is developed in the context of indigenous communities in Mexico which are recognised as indigenous tourism destinations following their legal framework in the United Nations Declaration on the Rights of Indigenous Peoples (UN, 2007) which permits the free development of economic, cultural, social, and spiritual activities under a scheme of self-determination. In this context, indigenous communities have shown interest in developing tourism starting many years ago, derived from impositions and restrictions on the use of natural resources, a policy imposed by the Mexican government in 1986. Some communities began the sub-division of their lands in order to convert them into Protected Areas (PA), and utilise them in the context of tourism under legal schemes of associations, cooperatives, and community-based businesses. This was done through forms of organisation of community or collective social capital. Musavengane and Simatele (2016), indicate that the communities that have suffered racial segregation or socio-economic exclusion are more disposed to generating different types of social capital as a means of support in order to advance towards development and sustainability.

This investigation is developed in 10 tourism destinations in indigenous communities pertaining to the Indigenous Network of Tourism in Mexico (RITA). RITA is a civil non-profit organisation made up of 32 organisations from the indigenous movement of Mexico. RITA, along with indigenous communities, seeks to contribute to community development for the sustainable preservation and utilisation of natural and cultural resources in the form of rural and indigenous tourism. The form of the community organisation is one of the attributes of the indigenous communities of Mexico that has contributed to the consolidation of tourist activities in these communities. Nunkoo (2017) and Musavengane and Simatele (2016) refer to the fact that in this type of community, both their governance and social capital play a relevant role in identifying the explicit and implicit values that are developed in the social interaction of indigenous people.

The indigenous communities of Mexico have, throughout the years, tried to promote their community development through tourist activities that utilise their biocultural richness through the collective management of community-based resources. It is known that the development of indigenous tourism contributes to the economy, the conservation of culture, and the natural resources in indigenous communities, and as a consequence, the wellbeing and standard of living of indigenous residents (Chin et al., 2017; Crouch & Ritchie, 1999; Hinch & Butler, 2009; Hoque et al., 2020; Ruhanen & Whitford, 2019; Scheyvens et al., 2021). However, little is known about the competitiveness of indigenous tourism destinations and the social prosperity that has been generated in these indigenous communities from the perspective of indigenous residents, who are the main beneficiaries and/or victims of tourist activity (X. Chen et al., 2020; Ngo & Pham, 2021).

Analysing the competitiveness and social prosperity of the destination from the perspective of the indigenous residents contributes toward understanding how indigenous people have developed capacities and strategies for tourism management in order to administer the benefits that tourism brings to the culture, natural and territorial resources of the destinations (Chin et al., 2017; Crouch & Ritchie, 1999). Chin et al. (2017) indicate that the perception and attitudes of the local communities on the development of tourism influence its success or failure. Thus, the way in which indigenous people collectively think, organise, and manage their natural, cultural, and economic resources is the basis for the development of tourism in the destination (Chin et al., 2017; Ngo & Pham, 2021; Pereiro, 2016; Scheyvens et al., 2021). For Rastrollo-Horrillo and Rivero Díaz (2019), there is an academic gap in the way that the influence of social capital on the innovative behaviour of tourism entrepreneurship is analysed. This is closely related to the competitiveness of the destination, and as a response, the perception of social prosperity (Crouch & Ritchie, 1999; García-Sánchez et al., 2019; Mintchev & Moore, 2017).

Chin et al. (2017) refer to achieving destination competitiveness with the cultural and natural advantage through creating competitive strategies based on the natural and cultural resources in order to attract more visitors, improve the tourism infrastructure, and make the most of the economic performance of indigenous communities. Therefore, the objective of this investigation is to analyse the relationship between community social capital and social prosperity, and the mediatory effect of the competitiveness of indigenous tourism destinations from the perspective of the residents of indigenous communities. This study aims to contribute to the literature on the development of indigenous tourism with a study with a quantitative focus, from the perspective of the residents that is measured through empirical indicators of social capital, competitiveness, and social prosperity of the indigenous tourism destinations. This has been widely studied through different focuses. As such, generating information for the makers of public policy and social promoters that promote the development of indigenous communities and areas through tourism, as well as promoting indigenous and rural areas where industrialisation isn’t an option for economic development. Another aim is to see tourist activities as an alternative for development through the utilisation and management of their biocultural richness and community resources. The rest of the document hereafter is structured thusly: first, with the revision of the literature regarding community social capital, competitiveness of the destination, and social prosperity. An investigation model is constructed, as is a hypothetical model of the study. Then, the methodological design of the investigation is described. Finally, the results, discussions, conclusions and implications of the study are given.

2. Community Social Capital (CSC)

Social capital (CS) is considered to be a multidimensional element that is difficult to define due to the variety of contexts in which it applies. One of the main contributors on CS is Putnam (1993, pp. 1–2) “… it refers to the characteristics of social organisation, such as networks, norms, and confidence that facilitate coordination and cooperation for mutual benefit [in a community]”. The study reconsiders the concept of CSC, now from the economic perspective, as a factor created by residents within a community that has positive effects on obtaining a common result, and that additionally is quantifiable (Ooi et al., 2015; Ramón-Hidalgo & Harris, 2018). It is underlined that this focus can be applied in any context in order to develop activities that are demanded by globalisation in the consequent reduction of poverty (Prayitno et al., 2019; Zhang et al., 2017), social wellbeing (Brownett, 2018; Shoeb-Ur-Rahman et al., 2020), improving quality of life (Rastegar et al., 2017), social prosperity (Hong, 2009; Mintchev & Moore, 2017), innovation, and shared knowledge in the context of tourist clusters for medium and small businesses (Kim & Shim, 2018). This focus has provided empirical evidence of benefits for the entrepreneurs in local communities, as well as in populations that face challenges in improving their basic services and social prosperity (Ali & Yousuf, 2019; Kwon et al., 2013; L. Zhou et al., 2017).

The multidimensionality of CSC is diverse; some investigators mention that confidence and reciprocity, horizontal and vertical networks, shared norms, collective action, community participation, and social cohesion are some of the dimensions that can identify CSC (Coleman, 1988; Mintchev & Moore, 2017; Nunkoo, 2017; Putnam, 1993; Shoeb-Ur-Rahman et al., 2020).

As such, the dimensions of CSC in this theoretical framework refer to the prerequisites that should be considered in order to achieve the objective of community social capital in its descriptive phase of the process, and the mechanisms that help to generate factors that make an indigenous tourism destination competitive and sustainable, as such describing their relationship with social prosperity. Thus, the theoretical perspective of dimensionality is framed by confidence, as mentioned by various authors (Beyer, 2014; Nunkoo, 2017; Thöni et al., 2012), social networks (Hwang & Stewart, 2017; López-Rodríguez & Soloaga, 2012; L. Zhou et al., 2017), community participation (Kieffer, 2018; J. Liu et al., 2014; Musavengane & Simatele, 2016; Prayitno et al., 2019), and norms (Ostrom, 2014; Ramón-Hidalgo & Harris, 2018; Woolcock & Narayan, 2000; Young et al., 2001). From here, it is considered that this kind of community social capital is developed through community cooperation and the participation of indigenous people for the sustainable development of indigenous tourism. This is referring to community social capital that is manifested by both social networks that culminate in the confidence and reciprocity of indigenous residents, and norms that govern communities for the control of their territorial, natural and cultural resources.

3. Tourist Destination Competitiveness (TDC)

Competitiveness is a recurring theme in various industrial and service contexts, as its adaptive characteristic is considered to be a multifaceted and multidimensional focus (C.-M. Chen et al., 2016; Porter & Linde, 1995). These characteristics mean that competitiveness, with all its attributes, can be extrapolated in the context of tourism.

Previously, groups of interest in the destination sought to position themselves in the tourism market through natural or cultural attributes (comparative advantage). However, making these attributes accessible and knowable requires management and cooperation between the interested parties, which is framed by the competitive advantage (Chin et al., 2017; Gratzer & Winiwarter, 2003; Vodeb, 2012). Porter (1990) indicates that management is a focus that finds itself directly related to innovation and, as such, to competitiveness in the industry.

From the context of tourism destinations, one of the models derived from Porter Diamond is the Calgary model, which groups the factors which serve as determinants for TDC (Crouch & Ritchie, 1999; Dwyer & Kim, 2003a; Mazanec et al., 2007). The model groups three large constructs: endowed resources (comparative advantage), destination management (competitive advantage), and the macro and micro environment (moderating factor), which affect the first two constructs. In a similar way, the Integrated Destination Competitiveness Model (Armenski et al., 2017; Dwyer & Kim, 2003b; Dwyer et al., 2014) is one of the models that groups four main determinants of competitiveness: resources (endowed, created and supporting), destination management, demand conditions, and situational conditions (Dwyer et al., 2014).

The tourism competitiveness models generally integrate similar factors, but they depend on the size of the industry (macro or micro) to determine which dimensions are the most adequate for building up the competitiveness of the destination (Cibinskiene & Snieskiene, 2015; Crouch, 2007; Crouch & Ritchie, 1999; Dwyer et al., 2014; Y. Zhou et al., 2015).

The focus on the sustainable tourism destination competitiveness establishes that tourism in natural environments wagers on the natural conservation and improvement of the residents’ well-being without compromising the natural and cultural resources of the present, so that future generations continue to enjoy the benefits and have a better life (Brundtland, 1987; Mika & Scheyvens, 2022). The resources of the communities are their main source of competitive advantage for the development of rural and indigenous tourism, which is why it is important to involve them in its conservation, as is managing the cultural and natural resources to make them attractive destinations to visitors (Aseres & Sira, 2020; Campón-Cerro et al., 2016; Chin et al., 2017). Thus, the performance of the destination will manifest itself through the general satisfaction of visitors, which consequently generates recommendations of the destination and the preference of tourists, which leads to more incomes and better life conditions for the residents (Aseres & Sira, 2020; Campón-Cerro et al., 2016; Chin et al., 2017; Hanafiah et al., 2017).

Thus, the theoretical and empirical relationship on how to make an indigenous tourism destination competitive lies in not only the quality of the natural or cultural resources, but in how they are managed by the indigenous people, how the communities organise themselves, and how they come to understand the target market (Buhalis & Laws, 2001; Mariani et al., 2014; Zehrer & Hallmann, 2015). Following this logic, it is discerned in the literature on competitiveness that the different community management practices largely depend on the context in which they are developed (Mendola & Volo, 2017; Nadalipour et al., 2019).

4. Social Prosperity Of The Tourism Destinations (PROSP)

Social prosperity is a focus that is derived from the predominant economic model and which has been associated with developed economies (Ritchie & Crouch, 2003), which seek, through the business-state relationship, to favour direct foreign investment and the creation of infrastructure, in addition to providing basic services of quality (Fritz & Koch, 2014; Ritchie & Crouch, 2003).

Prosperity is a subject that speaks to the elimination of poverty and hunger, creating material conditions that guarantee a dignified life for the poorest people, in a fairer world (Northrop, 2014). It attempts to eliminate the big differences between the rich and the poor, which generate social conflicts in communities, and that have a dispersion effect on the most vulnerable places in society (op cit).

Social prosperity in tourism has been considered to be a concept that depends on the competitiveness of the tourism destination (Crouch & Ritchie, 1999; García-Sánchez et al., 2019; Goodwin, 2011). This departs from the fact that the competitiveness of the destination is built through factors that modify, develop, create, and reinforce the management of natural and sociocultural resources, public services, and infrastructure, which contribute towards attracting tourists to the destination. Consequently, the competitiveness of the destination influences social prosperity, as it improves economic income, conserves tourism resources, and generates job opportunities, social wellbeing, and quality of life for the residents (Fritz & Koch, 2014; Upadhayaya, 2019).

Some authors mention that the quality of life (Kubickova et al., 2017), social well-being, wealth distribution (Liburd et al., 2012), ecological sustainability, social inclusion (Fritz & Koch, 2014), and sustainable practices in the tourism destination (Nilnoppakun & Ampavat, 2016), are underlying dimensions of the social prosperity.

5. Hypothetical model

The extensive benefits that CS offers to people, communities, and businesses that are involved in the tourism industry have been documented by various authors. For example, Guo et al. (2018) analysed the relationship between social capital and the resilience of two tourism communities in China, Dujiangyan, and the National Park of the Jiuzhai Valley; they found a positive effect between CS and resilience. In another similar context, social capital has served to empower social or gender groups that find themselves disadvantaged when carrying out some economic activities in established markets, leading to the associationism of these groups in the informal product market in tourism destinations (Griffiths et al., 2009; Ooi et al., 2015).

CS positively influences collective entrepreneurship through various forms of CS in order to develop tourist activities and take advantage of the natural, cultural, and created resources in a sustainable way (Nunkoo, 2017; Rastrollo-Horrillo & Rivero Díaz, 2019). Under this perspective, Barba-Sánchez & Molina-Ramirez are situated within the framework of entrepreneurship in indigenous communities in relation with social capital. The contributions are particularly relevant given that recent scholarship indicates that entrepreneurship, including social entrepreneurship, can positively affect the livelihoods of indigenous communities in Mexico. The theory of social capital suggests that emotional support from close networks has been identified as a significant factor that can contribute to the success of indigenous ecotourism businesses. Furthermore, entrepreneurship has been found to function as a survival strategy for these communities, and the mobilization of social capital can enhance the prospects for successful entrepreneurship. Support for social entrepreneurship initiatives can thus play a crucial role in promoting sustainable development and poverty reduction in Mexico, by facilitating the creation and strengthening of social networks that can support these initiatives (Barba-Sánchez & Molina Ramírez, 2015; Barba-Sánchez & Molina-Ramirez, 2016; Barba-Sánchez & Molina-Ramírez, 2014).

Wszendybył-Skulska et al. (2016) study the impact that CS has on the management of TDC in countries in the European Union. They developed a Pearson correlation and regression analysis between the CS elements and the Travel and Tourism Competitiveness Index (TTCI), and showed that a direct and statistically significant linear correlation exists. This means that as social capital is invested in tourism destinations, the capacity to innovate and the management of competitive factors increase. The long-term competitiveness is determined in large part by a balance between cooperation, the competence of businesses or lenders of tourism services (Corte & Aria, 2016; Czernek, 2013; Fehr & Schmidt, 1999), and the capacity to innovate in developing tourism products (Kim & Shim, 2018; Rastrollo-Horrillo & Rivero Díaz, 2019). Additionally, emphasis on the management of tourism from both perspectives (supply and demand) is required in order to shape the future of developing sustainable tourism and obtaining a long-term competitive advantage (Dwyer et al., 2009).

Experience has shown that businesses cannot establish a sustainable tourism industry without cooperation, support, and the participation of stakeholders (J. S. Chen, 2015; Woo et al., 2018). In the current context of tourism, it bears mentioning that CS acts as a factor that facilitates or inhibits the success of planning of tourism destinations (Soulard et al., 2018).

Additionally, from this point of view, if a geographic location has the characteristics to be able to identify as a tourism destination and wishes to gain competitive advantages, this necessitates the development of tourism products with a strong image. They must also be bought by demand, but not only pertain to securing immediate economic profitability, but also to securing that the development of tourism activities, from the perspective of the tourists and residents, be comprised of sustainable practices that result in competition (Genç, 2014; Marzo-Navarro et al., 2015; Nilnoppakun & Ampavat, 2016).

The empirical contributions show that the different types of CS positively support the increase of the perception of social prosperity (Mintchev & Moore, 2017; Prasad Shrestha, 2019), quality of life (Rastegar et al., 2017), and economic development (Ali & Yousuf, 2019; Engbers et al., 2016; Kay, 2006).

Derived from the above, the conceptual hypothetical model (Figure 1) is proposed. It is expected that CSC is positively related to PROSP (${\beta }_2$), in that the relationship between CSC and TDC can have a direct and positive relationship (${\beta }_1$), whilst TDC is positively and directly related with PROSP (${\beta }_3$). Finally, the mediator effect of TDC in the relationship between CSC and PROSP (${\beta }_{\mathit{\text{ind}}}$) is also expected. Thus, hypothetical relationships are proposed in this conceptual research model (Figure 1).

Figure 1. Research conceptual model.

CSC = Community Social Capital, PROSP = Social Prosperity, TDC = Tourism Destination Competitiveness.

6. Methodology

The investigation was quantitative with a transversal and exploratory study type. The data were collected in 10 indigenous communities in Mexico that are renowned as indigenous tourism destinations (Table 1) pertaining to the Red Indígena de Turismo de México (RITA) (Indigenous Network of Tourism in Mexico), which makes up 32 indigenous tourism destinations.

Table 1. Sample location (communities) as indigenous tourism destinations

State	Indigenous tourism destination
Colima	La Becerrera El Carrizalillo
Estado de México	San Juan Teotihuacán
Guerrero	Grutas de Cacahuamilpa
Michoacán	San Juan Nuevo Cherán Isla Yunuén
Morelos	Amatlán de Quetzalcóatl Los Laureles
Oaxaca	Capulalpám
Puebla	Cuetzalan

Source. Self-made with data from RITA.

The sample was composed of 103 indigenous residents who were invited to respond voluntarily to a structured questionnaire through face-to-face interviews with an approximate duration of 45 minutes per questionnaire. The size of the sample was determined for the PLS-SEM data analysis (Hair, Risher, et al., 2019; Willaby et al., 2015) and complies with the minimum requirement (n = 97) for the data analysis with six predictors, a medium effect size, a level of significance of 0.05 and a statistical power of 0.8 (Cohen, 1992; Nitzl et al., 2016). The analysis of the data was performed with Smart-PLS software ver. 3.0 (Ringle et al., 2015) and SPSS Ver 22.

6.1. Sample

The sample locations were 10 indigenous tourist destinations in Mexico. Under this denomination, the communities of 71 current indigenous groups operate in Mexico, and are found in various towns and municipalities of 20 entities of the Mexican Republic (SIC, 2021). The 10 destinations are affiliated with RITA. RITA was selected as the source of information in order to localise the indigenous tourism destinations in Mexico, because it is the only NGO that groups indigenous communities that have activities framed by indigenous and community tourism in their majority. The association (Table 1) promotes the self-management of tourism in the form of said communities assuming the most important role in planning, operating, developing, and supervising their own businesses, which is associated with the preservation and utilisation of their resources (RITA, 2022).

For RITA, indigenous tourism is an inherited manifestation of the traditional customs of indigenous towns, who make use of their rights and bring about good practices in the administration of their community resources in order to develop a sustainable and responsible development model. The mission of the indigenous tourism destinations is to ensure that the residents and visitors of the indigenous communities participate in the conservation of natural, cultural, and human resources that they inhabit (RITA, 2022).

The complete sample is made up of 103 indigenous residents and the size of the sample complies with the minimum required for data analysis with PLS-SEM (Cohen, 1992; Nitzl et al., 2016), furthermore, the selection was made through non-probabilistic snowball sampling technique. The sample selection is made up of indigenous residents that comply with two selection criteria: (1) The ability to perform in tourism activities in the indigenous community, recognised by RITA as an indigenous tourism destination. (2) To be a native resident of the indigenous community as a community local or a shareholder of common land with an indigenous identity (i.e. social recognition from indigenous communities for their native residents with rights to access common-use resources). This last criterion is included in the sample selection as in Mexico, indigenous territories are communal property (common or collective goods). As such, the resident that has the right and participates in taking decisions in developing the community is granted social recognition, which gives them the identity of co-proprietor or shareholder of common land, in accordance with the possession of the land. The demographics data of the respondents is shown in Table 2.

Table 2. Demographics data of the respondents

Gender	Total
Female	54
Male	49
Total	103
Marital Status
Married	71
Single	21
Other	10
Total	103
Education
High School/some college	28
Primary	26
Secondary	22
Bachelor’s Degree	17
Other	10
Total	103

Notes: Self-made with data from survey.

6.2. Measurements

The instrument of measurement was a structured questionnaire in two sections. The first measures latent variables of the study, including its underlying dimensions and its observable variables (items). In the second, the socio-demographic data of the residents and the indigenous tourism destinations were recorded. The scale used to measure the latent variables was a social approach scale called Bogardus from 10 points, where 1 is a low score, and 10 is a high score.

Community social capital (CSC) is defined as the capacity of indigenous people to collectively trust, organise, cooperate, respect, and adapt to the established behavioural patterns by the community to access common-use resources and goods. In order to measure the variable, the indigenous residents were asked how much confidence they have in their neighbours, individuals, and internal and external institutions in their community. Additionally, they were asked about the extent to which they agree with the social and community norms and values shared by the residents of the community, the frequency of establishing contact networks and the cooperation of family members, friends, residents, neighbours, communities, and internal and external organisations in the local community. They were also asked about their disposition towards participating in activities for the sustainable development of their community and of indigenous tourism. The indicators were trust (TRU), norms (NRM), social networks (SNW) and community participation (CMP). Some items of CSC were obtained from the Encuesta Nacional de Capital Social Urbano (ENCASU), (2006) (National Survey of Urban Social Capital) and the Encuesta Nacional de Capital Social (ENCAS) (2011) (National Survey of Social Capital), both of which were developed by the Secretaría de Desarrollo Social and the Programa de Naciones Unidas para el Desarrollo en México (SEDESOL, & PNUD, 2006) (Secretary of Social Development, United Nations Program for the Development of Mexico); which were adapted to the 10-point scale for the standardized measurement of latent variables of this study.

Tourism destination competitiveness (TDC) is defined as the capacity that the indigenous residents and groups have in creating a sustainable offer in the tourism market through the correct link between tangible and intangible resources that indigenous communities possess and control. The determinant indicators of the TDC model (Chin et al., 2017; Crouch & Ritchie, 1999; Dwyer & Kim, 2003a), were the natural resources (NATR), cultural resources (CULR), developed resources (DEVR), tourism destination management (TDM), management of environmental benefits (MoEVB), management of socio-cultural benefits (MoSCB). In order to measure each variable, the indigenous residents were asked about the perception of the quality of their natural, socio-cultural, and created resources, as well as what the destination offers in order to attract tourism to the indigenous community. They were also asked about the prevalence of indigenous groups that are responsible for the operation of the destination, manage resources (natural, cultural, and developed), carry out strategic actions that develop and position the indigenous tourism destination, attract more visitors to the destination, and manage the benefits of tourism for the development of tourism and the indigenous community.

Social Prosperity (PROSP) is defined as the positive perception of indigenous residents regarding the wellbeing and economic, social, and environmental development of the indigenous community that is derived from the development of indigenous tourism in the community. This includes the improvements and benefits received by the local community due to the arrival at and preference of the indigenous tourism destination by tourists. The indicators were distribution of wealth (DoW), quality of life (QoL), and environmental management practices (EVNP). In order to measure the variables, the indigenous residents were asked about their perception regarding the increase and improvements of economic and material well-being that indigenous tourism generates in the local community, as well as in their personal and family life. This includes the increase and improvements of community public services such as drainage, public transport, road infrastructure, drinking water, electricity, and health services. It also includes improvements in the management of natural resources and environmental practices in the community.

6.3. Data Analysis

Exploratory factor analysis (appendix 1) in the SPSS 22 was used to determine the first-order assessment of the constructs, reduce item sets, and explore the underlying theoretical structure of the latent variables. The loading items ≥ 0.6 defined the constructs of the first order. Skewness and kurtosis were measured to analyse data distribution. The skewness values of data distribution were negative CSC = −0.630; TDC = −1.455; PROSP = −0.944), were skewed left relative to an arithmetic mean (appendix 1), and high/low kurtosis (CSC = 0.258; TDC = 2.000; PROSP = 0.510), indicating that the data set is asymmetric and heavy-tailed. So, the data set does not show a normal distribution. However, the negative skewness value between −1 and + 1 is considered excellent, and the positive value of the kurtosis is close to zero and is not greater than + 2; according to PLS-SEM the data sets have a normal distribution for analysis (Hair, Hult, et al., 2019). So, PLS-SEM was used to determine the confirmatory factor analysis of the second order of the CSC, TDC, and PROSP variables. The data analysis was done by evaluating the measurement and structural models, the total effects, and the predictive relevance of the model.

7. Results

7.1. Evaluation of the measurement model

For the evaluation of the reflective measurement model, the PLS algorithm was used. The lost values were identified as −0.99 and were replaced by the average. The elements of the PLS algorithm that were occupied for the Weighting Scheme were: Path Weighting Scheme; Data Metric, Mean 0, Var 1. The iteration maximum was 5000, which were adjusted at the recommendation of Hair, Hult, et al. (2019). In the first evolution of the model, the constructs with loads lower than 0.6 were eliminated from the model (Figure 2): SNW (.0438), CULR (0.465), DEVR (0.521) and NATR (0.454). The model was assessed again (Figure 3), and the indicators of CSC (TRU, NRM, CMP); TDC (MoEVB, MoSCB, TDM); and PROSP (QoL, DoW, ENP) had load factors ≥ 0.6.

Figure 2. First reflective model without discriminating items.

*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001. Source: Self-made, results of SmartPLS 3.

Figure 3. Adjusted measurement model.

*p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001. Source: Self-made, results of SmartPLS 3.

7.2. Reliability and validity

The reliability analysis of the constructs was done through Cronbach’s alpha, composite reliability (Pc), and rho A, with values > 0.7. The convergent validity (AVE) was greater than 0.5, as such complying with the criteria for measurement analysis (Table 3).

Table 3. Reliability and validity indexes

Latent variable	Internal Consistency Reliability		Convergent Validity		Average reliability of construct between Alpha and Pc
	Cronbach’s Alpha	rho_A	Ρс	AVE	%
CSC	0.719	0.725	0.842	0.639	0.791
PROSP	0.722	0.756	0.838	0.634	0.787
TDC	0.817	0.821	0.891	0.732	0.878

Notes: AVE (Average Variance Extracted), Ρс (Compound Reliability); rho_A,

% (average reliability).

The average reliability between Cronbach’s alpha and composite reliability were acceptable values for each construct (Hair, Hult, et al., 2019). The evaluation of discriminant validity was made through crossed loads (Table 4).

Table 4. Crossed loads on the constructs with their observable variables

	CSC	PROSP	TDC
TRU	0.780
NRM	0.837
PoC	0.781
QoL		.854
DoW		.713
EVNP		.816
MoEVB			0.870
MoSCB			0.869
TDM			0.826

Notes: Self-made with results of SmartPLS analysis.

7.3. Evaluation of the structural model

For the evaluation of the structural model in PLS-SEM, the evaluation criteria are taken into account, which are: the determination coefficient (R²), predictive relevance (Q²), magnitude and significance of the beta coefficients (path), sizes of the effects f², sizes of the effects q² (Hair, Hult, et al., 2019). According to Hair, Hult, et al. (2019), after examining the validity and reliability of the constructs, the next step is to verify that collinearity is within the established limit, otherwise, the model has a high correlation between the constructs. Variance Inflation Factor (VIF) is used for this test, and values < 0.2 and > 5 indicate high collinearity. The VIF values of constructs were 1.0 and 1.84, and there are no multicollinearity problems between constructs (Table 5).

Table 5. Test of hypothetical relationship

Hypothetical Relationship	Β	t	f2	VIF	P-value	Hypotheses Supported
β1: CSC—TDC	0.676	2.957**	0.841	1.000	.003	Yes
β2: CSC—PROSP	−0.151	0.736ns	0.029	1.841	.4	No
β3: TDC—PROSP	0.849	2.846**	0.910	1.841	.005	Yes
Βind: CSC—TDC – PROSP	0.574	7.275**	-	-	.000	Yes

Notes: **p ≤ 0.01, ns: not significant, β- path coefficient, t- t value, p- p value, f2- effect size, VIF- variance inflation factor. Source: Self-made with results from SmartPLS 3.

The validation of the structural model was done through bootstrap estimation sample reuse (500) to obtain loads of the constructs (R² ≥0.1), the path coefficients (β≥0.2), and the statistical “t” for proving the significance (p ≤ 0.05). These were all determined to test relationships between variables of the conceptual research model.

The results show that the β₁ coefficient indicates a positive and significant relationship between CSC and TDC (β₁ = 0.676, p = 0.03). The β2 coefficient indicates a negative and non-significant effect between CSC and PROSP (β2= −0.151, p = 0.095), while β3indicates that there is a positive and significant effect between TDC and PROSP (β3 = 0.849, p = 0.005). As endogenous constructs, TDC’s determination coefficient (R2) was 0.451, while PROSP was 0.561 (Figure 2). As such, hypothetical relationships between CSC and TDC (β1) and TDC and PROSP (β3) are supported, and the relationship between CSC and PROSP (β3) is rejected (Table 5).

Through the omitted results for the hypothetical measurement mediation of CSC-TDC-PROSP (β_ind), it was found that the mediator effect of TDC is positive and significant (β_ind = 0.517, p ≤ 0.01), and as such β_ind was supported (Table 5).

7.4. Evaluation of the total effects (f²)

The total effects (f²) allow the evaluation of the strength that each exogenous effect (CSC, TDC) exercises over the endogenous variable (PROSP) in a direct way (CSC) and through the mediatory variable (TDC). The relationship between CSC and PROSP has a moderate but not significant effect (0.422). The effect of the relationship between TDC and PROSP (0.849), and that of CSC and TDC (0.676) were significant and of great size (Hair, Hult, et al., 2019).

7.5. Predictive relevance of the model (Ǫ² y q²)

The predictive relevance of the model (Ǫ² y q²) indicates to what extent the model has predictive relevance for a reflective endogenous latent variable. Values of Ǫ² >0 indicate predictive relevance (Hair, Hult, et al., 2019, p. 266).

To determine Ǫ², the Blindfolding technique was used. This is a “sample reuse technique that omits every data point in the endogenous construct’s indicators and estimates the parameters with the remaining data points” (Hair, Hult, et al., 2019, p. 266). According to Hair, Hult, et al. (2019), estimated values of predictive relevance from the model of each endogenous construct are shown with the table of the construct cross validated redundancy and communality (CCR) results (Table 4), and the indexes are obtained, the squared observations (SSO) are summed, the squared prediction errors are summed, as is the final Ǫ² value (1-SSE/SSO). The results report that Ǫ² >0 for both endogenous constructs (PROSP and TDC). This indicates an average predictive relevance with Ǫ² >0.25 and Ǫ² <0.50 (Hair, Hult, et al., 2019).

On a different note, the final evolution of the model is assessed through the q² index, which shows the size of the Q² effects. Firstly, the relationship between CSC and PROSP was calculated in order to obtain the includedQ² and excludedQ² values of an endogenous latent variable (PROSP). The values of the first blindfolding analysis of the CCR table were taken, which represent (1-SSE/SSO) to includedQ² (Table 6).

Table 6. Values of Ǫ2 included

Total	SSO	SSE	Q2(1-SSE/SSO)
PROSP	166	98.838	0.404
TDC	249	167.547	0.327

Notes: Source: Self-made with results from the Blindfolding analysis with SmartPLS 3.

To obtain the excluded Q², according to Hair, Hult, et al. (2019, p. 264), a “model reestimation after deleting a specific predecessor of that endogenous latent variable” is performed. This is to say that for the PROSP variable, which has a score of (0.404) from the first blindfolding analysis, CSC was erased from the model in order to obtain the excludedQ² before calculating the model once again. For obtaining excluded Q² from TDC for PROSP, the same procedure of variable elimination and recalculation of the model was followed (Table 7). These values are considered to be the inputs for calculating the sizes of the q² effect.

Table 7. Excluded Q 2 values

Total	SSO	SSE	1-SSE/SSO
TDC—PROSP	288	264.681338	0.080968
CSC—PROSP	255	161.64966	0.36608

Notes: Source: Self-made with results from the Blindfolding analysis with SmartPLS 3.

In order to obtain the q² values, the following formulas were employed, and were calculated manually. In this case, CSC acted only as an exogenous latent variable, whilst TDC served as both an endogenous and exogenous latent variable at the same time.

$q^2=\frac{\mathrm{i}\mathit{\text{ncluded}}{Q}^2-\mathit{\text{excluded}}{Q}^2}{1-\mathrm{i}\mathit{\text{ncluded}}{Q}^2}$

$q^2\mathit{\text{CSC}}\to \mathit{\text{PROSP}}=\frac{\mathrm{i}\mathit{\text{ncluded}}{Q}^2-\mathit{\text{excluded}}{Q}^2}{1-\mathrm{i}\mathit{\text{ncluded}}{Q}^2}$

$q^2\mathit{\text{CSC}}\to \mathit{\text{PROSP}}=\frac{0.404-0.366}{1-0.404}=0.063$

The excluded value of TDC was calculated:

$q^2\mathit{\text{TDC}}\to \mathit{\text{PROSP}}=\frac{\mathrm{i}\mathit{\text{ncluded}}{Q}^2-\mathit{\text{excluded}}{Q}^2}{1-\mathrm{i}\mathit{\text{ncluded}}{Q}^2}$

$q^2\mathit{\text{TDC}}\to \mathit{\text{PROSP}}=\frac{0.404-0.081}{1-0.404}=0.541$

In accordance with the results of the size of the effects, and following the practical rules derived from the bibliographical revision, it was observed that the $q^2\mathit{\text{CSC}}\to \mathit{\text{PROSP}}$ = 0.063 effect shows a small effect. The following effect, $q^2\mathit{\text{TDC}}\to \mathit{\text{PROSP}}$ = 0.541, shows a big effect.

8. Discusions

The theoretical concepts of CSC and TDC were used to describe how the community residents of indigenous tourism destinations perceive social prosperity. Especially in Mexico, many indigenous communities face challenges in improving the perception of prosperity and bridging the poverty gap. In indigenous tourism destinations, the natural and cultural resources are managed from the principles of the common or collective goods; indigenous communities manage tourism activities and the benefits they get from them. The collective actions on community-based resource management help preserve and take advantage of natural and cultural resources sustainability and contribute to attracting tourism and generating socio-economic benefits for the residents. Indigenous entrepreneurs create products, services and/or small businesses taking advantage of collective and common resources. They operate from social and community rules and norms and must contribute to community development and sustainability. The findings refer that indigenous communities managed their entry into the tourism market as an alternative to obtaining an economic income; they took decisions on this tourism project through community participation (collective action). They have an organisational structure based on values, implicit and explicit social norms that come from trusted social relationships, and reciprocity among community residents, which leads to community participation in tourism activities for the benefit of the population. Residents are organized to conserve and take care of natural and cultural resources, from living to public places, through environmental and social practices, like waste classification, conserving water, and preserving indigenous culture, language, and traditions.

In this study, the indigenous tourism destinations have an infrastructure for access to provide tourism and hospitality services. In these destinations, due to the internal policies of the indigenous communities, the introduction of transnational businesses that offer tourism or hospitality services is prohibited. These aim to protect the local culture, natural resources, and economy. The infrastructure of basic services has been constructed with the government’s and indigenous residents’ economic contributions. Destinations promote strategies for community participation through networks with governmental and non-governmental organizations to improve community quality of life and tourism development.

The networks that have come about outside, with other member communities and with associations like RITA, have been able to establish contacts and generate faith in asking for financial and technical support. This aids in the acquisition of specialised equipment or the construction of cabins and restaurant services in order to offer hospitality and food services to tourists. The technical support offers training and certifications in the management and conservation of natural and cultural resources for tourism activities. For example, they have created well established routes and itineraries which reduce the impact brought about by a tourism overload, in addition to policing and prohibiting the extraction of flora and fauna.

Tourism destination competitiveness has a mediator effect between CSC and PROSP in the context of indigenous tourism destinations associated with RITA. CSC positively influences developing capacities management to adopt collective strategies for tourism management and natural and cultural benefits that make a destination competitive. Community confidence, norms, and participation strengthen a community. Developing internal policies can lead to control, protection, and preservation of the economy and cultural and natural resources and increase confidence and reciprocity among residents. Efficient management of these community-based resources generates destination competitiveness. Thus the increase of the perceived benefits of management and supporting social prosperity in indigenous communities. These findings agree with Chin et al. (2017; Mendola and Volo (2017), and Nadalipour et al. (2019).

The perception of social prosperity depends on the mediation effect of TDC between CSC and PROSP. When the residents generate community confidence, norms, and participation in direct relation to the management of tourism activities, they perceive an increase in the quality of life due to the actions, arrangements, and management that are developed for the benefit of the local community, for the tourism development. An example would be the distribution of public services that tourists use in some form. Wealth distribution is also perceived due to the increase in income and the creation of job opportunities that arise due to tourism activities. It was also perceived that the quality of life has gradually improved and that the involvement of conservation practices and the utilisation of natural resources provides a positive perception of social prosperity. CSC’s direct effect on PROSP was not significant, contrasting with the reviewed literature. RITA’ indigenous tourism destinations, the community social capital by itself does not increase residents’ perception of the social prosperity of indigenous communities. The management of tourism destination resources is required; they must be efficiently managed to achieve competitiveness for residents to perceive social prosperity. This finding differs from the results of Mintchev and Moore (2017), Prasad Shrestha (2019), Rastegar et al. (2017).

9. Conclusions, implications, and limitations of the study

Tourism destination competitiveness plays an essential role in that the residents perceive the benefits of the tourist activities developed in their communities. Community social capital is critical to indigenous tourism destination competitiveness. Trust, reciprocity between residents, and community participation for tourism management, conservation, and efficient use of cultural and natural resources influence the generation of collective strategies to get competitiveness. The basis of tourism development in indigenous communities is community social capital and the collective action system to manage common resources. The norms and internal community policies regulate the behaviour of unsustainable tourism practices in destinations. Networks outside the community strengthen management capacities for tourism development, competitiveness, and sustainable benefits for indigenous communities.

Sustainable tourism development in indigenous communities is an alternative to reducing poverty levels. The arrival of visitors to indigenous tourism destinations generates local economic benefits, promotes entrepreneurship, jobs, and investment in tourism infrastructure that benefits the community, and improves access to public services (public transportation, energy, water supply, public health, infrastructure transportation, recreational facilities, among others) and ensures the protection of natural and cultural resources in communities. Management practices and transparency for managing resources and benefits of indigenous tourism increase the positive perception of social prosperity. In indigenous tourism destinations, residents perceive an improved quality of life, income, and access to public services and sustainable practices.

The study’s implications are directed toward the literature on indigenous tourism and tourism destination competitiveness, public policy, and practitioners. Tourism development in indigenous communities is based on confidence and reciprocity between residents, internal and external networks, and community participation to manage destination resources, which are crucial to a sustainable community. Destination competitiveness plays an essential role between confidence and perception of social prosperity. The quantitative measurement from primary sources statistically validated this relationship in the context of indigenous tourism. The management of environmental benefits, the management of cultural benefits, and the management of the destination are components of TDC. For policymakers, indigenous tourism development is a strategy for the sustainable well-being of communities with natural and/or cultural resources as a source of comparative advantage. They require support and management to develop infrastructures that attract and facilitate the arrival of visitors and contribute to community development. Community participation in the management of collective and common goods is vital to control and protect the rights and autonomy of indigenous communities. Practitioners must know about community social capital before entrepreneurship in indigenous tourism development projects.

It is noteworthy to highlight that prevalent forms of entrepreneurship encompass a range of activities, including fod services, the trade of handicrafts, the desing and marketing of environmentally-friendly or sustainable properties, the production and distribution of food products (both locally and internationally), and the provision of adventure tourism experiences such as zip-lining, rappeling and rock climbing. Consequently, these entrepreneurial initiatives necessitate a variety of certifications, which are administered by governmental bodies within the Mexican State, notably the Ministry of Tourism and the National Institute of Indigenous People.

The limitations of this study are on the sample technique, which was limited to indigenous tourism destinations associated with the RITA network that manage collective or common resources, this technique does not seek representation or statistical inference to the population. We would like to highlight that our study did not gather specific information regarding the various activities undertaken in these destinations. Our focus was exclusively on collecting data necessary for the construction of relevant variables within the framework of the research. For future research, we suggested exploring destinations with both public and private resources, and/or outside the RITA network, with large sample sizes to eliminate selection bias and contribute to the knowledge generation on the mediatory effect of the destination competitiveness in indigenous tourism development.

Acknowledgments

We are grateful to the Red Indígena de Turismo de México (RITA), and the communities that participated in the study, for the support provided to conclude this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Jorge Luis Ramos-García

Jorge L. Ramos-García is an independent researcher with a doctorate in Tourism Management by Universidad Autónoma de Occidente and a master’s degree at Instituto Politécnico Nacional in México. His research topics are tourism destination competitiveness, community social capital, social prosperity perception and sustainable tourism management. Passionate on finding different ways to support the tourism development of indigenous communities.

Delfino Vargas-Chanes

Delfino Vargas-Chanes Researcher-Professor at Programa Universitario en Estudios del Desarrollo (UNAM). Has a doctorate degree in sociology from the Iowa State University, with master’s degrees in Sociology and Statistics (UNAM). Its substantive areas are the study of inequality, poverty, and advanced methodologies for social research.

Arcelia Toledo-López

Arcelia Toledo-López Researcher-Professor at Instituto Politécnico Nacional, México. Her research interests are business strategies and organizational behaviour of Micro, Small and Medium Enterprises (MSMEs) in Latin American context, with an emphasis on understanding and explaining the organizational behaviour and results of MSMEs that operate in subsistence markets and fragmented industries.

Appendix 1.

Exploratory Factor Analysis (EFA)

Table

Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)		Social Prosperity (PROSP)
Skewness	−0.630	−1.455 2.000		−0.944 0.510
Kurtosis	0.285
Media	7.575	7.92		7.656
Variance	1.246	1.347		1.687
TRUS	α = 0.837	NATR	α = 0.842	DoW	α = 0.840
λ1	0.555	λ36	0.446	λ76	0.801
λ2	0.812	λ37	0.652	λ77	0.794
λ3	0.530	λ38	0.767	λ78	0.602
λ4	0.734	λ39	0.82	λ79	0.512
λ5	0.794	λ40	0.768	QoL	α = 0.901
λ6	0.570	CULR	α = 0.672	λ80	0.547
λ7	0.524	λ41	0.475	λ81	0.546
λ8	0.440	λ42	0.698	λ82	0.684
λ9	0.451	λ43	0.656	λ83	0.742
NRMS	α = 0.845	λ44	0.384	λ84	0.783
λ10	0.670	λ45	0.493	λ85	0.373
λ11	0.633	DEVR	α = 0.791	λ86	0.658
λ12	0.762	λ46	0.378	λ87	0.729
λ13	0.718	λ47	0.507	λ88	0.479
λ14	0.604	λ48	0.480	EVNP	α = 0.792
λ15	0.599	λ49	0.548	λ89	0.568
λ16	0.690	λ50	0.701	λ90	0.655
SNW	α = 0.854	λ51	0.843	λ91	0.844
λ17	0.723	λ52	0.627	λ92	0.812
λ18	0.752	λ53	0.385
Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)
λ19	0.554	TDM	α = 0.893
λ20	0.569	λ54	0.708
λ21	0.356	λ55	0.687
λ22	0.771	λ56	0.619
λ23	0.772	λ57	0.773
λ24	0.360	λ58	0.691
λ25	0.593	λ59	0.772
λ26	0.517	λ60	0.791
λ27	0.276	λ61	0.698
PoC	α = 0.806	λ62	0.708
λ28	0.547	λ63	0.391
λ29	0.702	MoEVB	α = 0.775
λ30	0.509	λ64	0.238
λ31	0.653	λ65	0.384
λ32	0.317	λ66	0.403
Community Social Capital (CSC)		Tourism Destination Competitiveness (TDC)
λ33	0.661	λ67	0.784
λ34	0.053	λ68	0.749
λ35	0.361	λ69	0.621
		MoSCB	α = 0.834
		λ70	0.696
		λ71	0.611
		λ72	0.610
		λ73	0.753
		λ74	0.730
		λ75	0.739

Note: α= Cronbach´s alpha coefficient. Extraction Method: maximum likelihood; Rotation Method: Varimax with Kaiser Normalization. It used SPSS ver. 22.