Academy of Strategic Management Journal (Print ISSN: 1544-1458; Online ISSN: 1939-6104)

Research Article: 2021 Vol: 20 Issue: 3

Understanding Tourism Business Venture in Rural Communities and the Contribution of Social Capital to Its Performance: A Case Study of the Cotacachi-Cayapas Reserve in Ecuador

Wendy Anzules-Falcones, Universidad de las Américas

Diana Caamana, Universidad de las Américas

Xavier Dávalos, Universidad Técnica del Norte

Abstract

This study presents the relationships between business management and market dynamism, social capital and market dynamism and social capital and resource exploitation. We use data from a sample of 72 community tourism establishments located in the Cotacachi-Cayapas reserve in Ecuador, a place that is home to great biodiversity and ethnic groups who maintain their traditions. We model structural equations and, through non-linear regression analysis, find that increased market dynamism encourages small tourism enterprises to improve their business management, that although social capital exists, the resources generated from networks are not sufficiently exploited and that a sustained increase in market dynamics puts pressure on businesses to improve their social capital by increasing cohesion and strong and diverse ties. It is recommended that tourism business venture develops market strategies and capacity building programmes to cope with market dynamism, as well as formulate strategies to better exploit resources from networks.

Keywords

Tourism Business Venture, Market Dynamism, Social Capital, Closed Ties, Diverse Ties, Resource Exploitation.

Introduction

Some studies affirm that the dynamism of an environment is a critical determinant of a company’s strategy. Therefore, it is necessary for companies to investigate and identify changes in the environment in order to formulate a coherent strategy to deal with this dynamism. Market dynamism considers the changes in consumers’ tastes and needs in an accelerated manner (Jaworski & Kohli, 1993), i.e. consumers do not remain static, they are always demanding more and the company must be prepared to respond quickly. In the tourism sector, companies currently compete in a global market where consumer behaviour is highly changeable and unstable because new needs are constantly appearing (Aarstad et al., 2015).

In this context of turbulence, tourism enterprises must improve their internal processes and management in the areas of administration, strategy, marketing and finance in order to cope with changes in tourists’ preferences. Additionally, these tourism organisations must constantly employ new strategies (Di-Clemente et al., 2020) and strengthen their competitive advantage so that it is sustainable and allows them to meet the requirements of their customers who will perceive the service as a unique experience.

In general, rural tourism ventures are small and are affected by factors derived from their remote locations, labor and dispersed commercial networks (Cunha et al., 2020). For Dinis (2006) the scenarios for entrepreneurship in these regions are complex and difficult because of the demographic and institutional context and indolence among actors.

These types of entrepreneurship do not use defined marketing and management strategies to ensure long-term and profitable business outcomes (Pato & Kastenholz, 2017). The overarching business strategies that stimulate growth are human capital needs, strategies and incubation programmes and - to a lesser extent - the regulatory framework. Focusing on these strategies can bolster tourism business venture (Moyle et al., 2020).

On the other hand, the resource-based approach (Barney, 1991; David, 2017; Grant, 1991; Hill et al., 2019) asserts that organizational performance is primarily determined by an organization’s internal resources, which are important for gaining and retaining competitive advantage. Strategical management with the resource-based approach involves developing and exploiting and strengthening an organization’s resources and capabilities to the fullest. However, given the highly competitive environment, obtaining “external” resources in the open market is proving increasingly difficult for small and medium-sized enterprises compared to larger companies or those with multiple locations. This is of particular concern for rural entrepreneurs, understood as individuals starting and running their own business in a rural area (Stam et al., 2014; Zhao et al., 2010).

In this context of competitive disadvantage, networks of relationships can be a particularly valuable asset for entrepreneurs, as they provide access to strategic resources and offer entrepreneurs the opportunity to improve their performance (Cousins et al., 2006; Davidsson & Honig, 2003; Pirolo & Presutti, 2010).

Literature Review

Market Dynamism and Business Effectiveness

Over the past decade, tourists’ preferences and behaviour have been constantly changing, which leads to a high level of market uncertainty (Aarstad et al., 2015; Pavlovich, 2014).

In a context of highly dynamic markets, continuous change provides companies with opportunities and success so long as they have the ability to develop and bring new products to the market faster than their competitors.

However, when changes in demand become more rapid, a trailing strategy is not the best option for firms aiming to be competitive and survive in the long run. Such dynamism shortens the product life cycle, thus pushing firms to move faster to harvest these opportunities and consolidate their market (Tuppura et al., 2010). As a result, firms develop routines to better detect and take advantage of opportunities arising from changes in demand, which reduce adaptation costs and stabilise adverse effects. These require efficient administrative, marketing and financial management.

In addition, the tourism service chain faces challenges arising from a combination of elements including unexpected competition across traditional industry boundaries, contextual change initiated or intensified by technological progress, changing tourism behaviour, regulations and economic conditions, and market structures that are outdated in regards to beliefs, practices and solutions of how to meet tourists’ needs in an economically sustainable way. This creates the need for the tourism sector to seek to update and change the way its stakeholders create, capture and disseminate value (Reinhold et al., 2017).

The potential of a tourism product depends on a wide range of factors including location, market demand, marketing, the presence of tour operators and destination infrastructure (Spenceley et al., 2019). Tourism management depends on the staff, the adoption of effective management strategies, the resources available for the management itself and the legal and political environment.

Moreover, optimal management in SMEs allows for competitive advantage and this is determined by a company’s ability to react to market intelligence, innovate their products to take advantage of market opportunities and offer reasonable prices (Falahat et al., 2020). Considering this discussion, the following hypothesis is proposed:

H1 Business effectiveness increases exponentially when market dynamism increases.

Social Capital

Social capital supports knowledge management by helping firms achieve sustained superior performance in turbulent markets. Other studies also extensively explore how social capital affects knowledge creation from an individual perspective. Knowledge creation can be seen as a dynamic process that occurs through social interactions between an organisation and its partners (Chen et al., 2016). Organisational social networks function as channels in which fragmented information and knowledge can be rapidly transmitted and integrated (Vannoy & Medlin, 2012). In the context of social capital, Vannoy & Medlin (2012) confirmed that an organisation’s social networks play a key role in optimising collective knowledge of market fluctuations by providing powerful stations for firms to share and create new pieces of knowledge in dynamically complex domains.

Market Dynamism and Closed Ties

Closed ties rarely provide new pieces of knowledge to be used with originality in a tourism destination (Zach & Hill, 2017), but instead provide redundant knowledge. Thus, when demand is continuously changing, information available to firms through closed links may not arrive in time and may not be sufficient to address those changes, making it even more difficult to detect changes in customer needs in dynamic environments, thus increasing adaptation costs. Therefore, it is better to develop strong and open ties.

When market dynamism is high, tourism enterprises located in a cluster with closer ties are not able to reduce the time they need to adapt to rapid market changes through a proactive attitude, as these closed ties make it difficult to identify new consumer demands and exploit emerging opportunities (Esposito Vinzi et al., 2010 Expósito-Langa & Molina-Morales, 2010). This theory confirms that strong and open ties contribute to a better adaptation to market dynamism.

When tourism enterprises have high levels of closed ties in highly dynamic markets, the costs of adapting to the new market situation increase. Thus, strong ties will amplify the disadvantages of market dynamism (García-Villaverde et al., 2020).

Market Dynamism and Diverse Ties

Studies underline that relationships with diverse actors help tourism enterprises to keep up-to-date by accessing external and novel market information (Hemphälä & Magnusson, 2012). The structural differentiation of a network of relationships composed of firms with different routines and competency levels enriches the information content of the network and enables firms to overcome problems that may arise when identifying changes in consumer demands (Neffke et al., 2018).

Under conditions of high market dynamism, proactively tapping into complementary information from diverse ties will facilitate appropriate offerings of new products and services by meeting new customer needs and providing rapid entry into new markets and segments (Sarkar et al., 2001). From there, firms with high diversity ties will reduce the cost of adapting themselves to constant market challenges through a pioneering attitude, as they will be better positioned to learn quickly and efficiently to develop responses to industry trends (Zaheer & Bell, 2005). These theories lead to the following hypothesis:

H2 Social capital increases exponentially when market dynamism increases.

Diverse Ties and Resource Exploitation

It is clear that network diversity enriches resources, at least in terms of variety. A broader network would provide entrepreneurs with more valuable resources, as it allows for a wider range of diverse relationships. The literature has shown the positive effect of network diversity on individuals’ access to resources, skills and opportunities. Managers and workers who have more diverse professional relationships have been shown to gain more economic resources and develop a greater capacity to generate new ideas (Burt, 2004; Sabatini, 2009). This positive effect of diversity has also observed in networks containing structural holes (Granovetter, 1973), which serve as a bridge between individuals who would otherwise not be linked, mainly because they belong to different, unconnected groups. In an industrial network, firms that have structural holes (i.e. those that have a wider range of contacts with various firms and institutions) achieve better performance, as they are able to enhance their resources and capability to innovate (Batt & Purchase, 2004; Capaldo, 2007; Lee, 2007), as well as their capability for teamwork (Auh & Menguc, 2005; Nahapiet & Ghoshal, 1998). Based on these theories, the following hypothesis is proposed:

H3 The diversity of a tourism entrepreneur’s network favours the effective exploitation of resources.

Network Cohesion and Resource Exploitation

Network cohesion facilitates interpersonal contacts and exchange. It thus promotes people’s effective access to the resources available in the network (Burt, 2004; Granovetter, 1973). According to Burt (2000), close-knit networks encourage collective action and resource sharing within the group. The positive effect of cohesion on access to resources has been empirically evidenced in the field of industrial relations in regards to employees (Brass, 1984), managers (Björkman & Kock, 1995) and work teams (Nahapiet & Ghoshal, 1998; Tsai & Ghoshal, 1998), and in the fields of industrial networks and strategic alliances (Andersson et al., 2007; Chetty & Wilson, 2003; Sasi & Arenius, 2008). The presence of close-knit, non-unified networks in a given area has been linked to higher levels of socio-economic development (Landman, 2004). Considering this literature review, the following hypothesis is proposed (Figure 1):

Figure 1 Theoretical Model

H4 The cohesion of a tourism entrepreneur’s network favours the effective exploitation of resources.

Community-based Tourism Business Venture

In recent decades, the tourism sector has incorporated the participation of local communities through community-based tourism business venture, the main objective of which is to improve the quality of life of the communities involved. Therefore, it is imperative to understand the concept of community-based tourism and the challenges it entails. For Maldonado et al. (2020), community-based tourism refers to a type of tourism that aims to satisfy the current needs of tourists, the tourism industry and local communities without compromising one’s ability to meet the needs of future generations. Cañada (2013) explains community-based tourism as a type of tourism developed in rural areas in which the local population (indigenous people) exercise a preponderant role in the control of its design, execution, management and distribution of benefits through their different organisational structures of collective character.

Sustainable tourism business venture faces three major challenges: firstly, finding business proposals and offers that can guarantee a long-term competitive advantage; the second being the development of a sustainable model through specific sustainability-oriented practices, capacities and resources; and the third being related to capturing the value of a sustainable business model through technological, organisational and social innovation factors (Battistella et al., 2018).

Tourism in the Cotacachi-Cayapas Reserve

Ecuador is a country with a lot of tourism potential to exploit due to its biodiversity. Indeed, in 2019, 1,500,708 tourists entered the country (Ministerio de Turismo de Ecuador, 2020). It has protected areas, the most important of which are: the Galapagos Marine Reserve, Galapagos National Park, Yasuní National Park, Cuyabeno Wildlife and Production Reserve, and Sangay National Park (Sistema Nacional de Indicadores Ambientales y Sostenibilidad, 2019). The most visited common reserve for both nationals and foreigners is the Cotacachi-Cayapas National Park (PNCC) with a total of 211,628 visits during 2019 (Sistema Nacional de Indicadores Ambientales y Sostenibilidad, 2019). It is located in the provinces of Imbabura and Esmeraldas, with a surface area of 243,638 hectares.

In its beginnings, community-based tourism in Ecuador faced great challenges, such as the prototyping of ancestral peoples’ cosmovision and sacred customs as well as the description of indigenous communities as cheap labour by national and foreign private tourism companies (Maldonado et al., 2020). There are a variety of factors that prevent community-based tourism ventures from strengthening in Ecuador. The high-quality standards imposed by the Ecuadorian Ministry of Tourism (MINTUR) make it nigh-on impossible for all existing ventures to qualify as Community Tourism Centres (CTC) (Maldonado et al., 2020). According to Polanco et al. (2020), external issues such as a lack of investment and knowledge in the area and mainly the fear of failure prevent ventures from gaining a foothold in a global and competitive market (Polanco et al., 2020).

For Pantoja et al. (2014), amongst the existing weaknesses in this type of entrepreneurship in the province of Imbabura is the lack of staff training, control tools, defined objectives and competitive strategies, along with an absence of risk assessment in projects, poor facilities, weak market positioning and an absence of quality products at low prices. In the same study, the threats faced by small tourism enterprises were highlighted, including a lack of technical support in projects, unfair competition, lack of attention in public works, poor tourism promotion and low awareness of local gastronomy amongst tourists (Burbano & Paspuel, 2014).

According to Jaramillo-Moreno et al. (2020), community-based tourism enterprises, despite being certified by the Ministry of Tourism, “have not implemented important administrative and financial processes such as strategic plan, operational plan, market research, cost analysis, process manual, market plan, initial situation, profit and loss statement, final statement or financial indicators. Therefore, in the long run, this leads to mismanagement of business resources, which can result in the closure of these enterprises” (Jaramillo-Moreno et al., 2020). This demonstrates the importance of the different areas in companies and the impact they come to have on whether better performance is achieved.

Methodology

Context of Study and Data Collection

The empirical analysis focuses on the tourism industry and was conducted on a sample of small Ecuadorian enterprises. The data collection was carried out from October to December 2020 through face-to-face surveys of representatives of the tourism business ventures defined in the sample and located in the Cotacachi-Cayapas reserve.

Due to the pandemic, it was not possible to carry out research in the province of Esmeraldas, so for the purposes of this research, only tourism within both the Cotacachi-Cayapas National Park and the province of Imbabura was considered. In this province, there are various Community Tourism initiatives undertaken by different peoples and nationalities affiliated to the Plurinational Federation of Community Tourism of Ecuador (FEPTCE).

The database was obtained from the cadastre at the Ibarra town council in the province of Imbabura, which was last updated in March 2020. The cadastre contained 581 establishments including accommodation ventures, tour operators, transport operators, recreation services, and food and beverage services. It should be noted that the tourism sector has inevitably been one of the sectors most affected by the pandemic. It has seen the closure of many establishments and large economic losses for those who were able to reopen in October 2020. In addition, tourism small enterprises located in the Cotacachi-Cayapas reserve are not easily accessible due to their geographical location in rural areas with poorly developed roads.

For these reasons, the authors decided to treat the problem of sample size as a case of unknown population. For the sampling, an allocation by quotas was made in the different parishes that make up Imbabura; this allocation was based on the information and experience of an expert on the population under study. This type of sampling is appropriate when the sample size is relatively small and even more so when the places are difficult to access.

After reviewing the data collected and eliminating those records with inconsistencies, the field researchers were able to complete 72 surveys, hence the sampling error with 90% confidence is 9.69%.

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The questionnaire was divided into sub-sections, whereby the first section contained questions on the management, strategy, marketing and financial running of the small enterprises and the second contained questions related to social capital, cohesion, strong ties and diverse ties, and was based on the proposals by Cousins et al. (2006).

In order to measure market dynamism, we used the three-item scale, which is an adaptation of the scale designed by Jaworski & Kohli (1993). The scale measures the managers’ perceptions about the speed of changes in demand, specifically changes in customers’ preferences, and also the entrance of new customers to the market. The constructs and measurement items are shown in Table 1.

Table 1 Constructs and Measurement Items
Construct Code Measurement items
Management and Strategy S1 Strategies consistent with the mission, vision and values
S2 Strategic objectives
S3 Adaptation to change and new ways of learning through innovation.
S4 Key processes involving people, suppliers, partners and customers in process improvement.
S5 Training programmes for the company’s staff members
Marketing M1 Innovative business and marketing practices
M2 Market research
M3 Geographical location
M4 Promotional strategies to customers: promotion and advertising through digital media
M5 Promotional strategies to customers: promotion and advertising through conventional media
M6 Impact of the marketing strategies
Finance F1 Management of economic and financial resources
F2 Use of financial management to support the organisation’s strategy
F3 Allocation of financial resources
Cohesion C1 Exchange of resources and information
C2 People in the network who know each other
C3 Close interactions in the network
Diverse ties DT1 Different people in terms of socio-economic level, education, ideologies and religion
DT2 People from different countries with different languages
DT3 Freedom to freely express opinions
DT4 Complementary skills and abilities of members in the network
Strong Ties ST1 Contact with the professional network
ST2 Members of the professional network who are known on a personal level.
ST3 Close social relationships with members of the network
Market Dynamism D1 Rapidly changing customer demands and product preferences.
D2 New customers tend to have product needs that are considerably different from the needs of existing customers.
D3 Customers tend to be constantly on the lookout for new products.
Resource Explotaition R1 The professional network has contributed to the area of administration.
R2 The professional network has contributed to the area of marketing.
R3 The professional network has contributed to the area of finance.

Structural Equation Modelling

The data were analysed using SEM, a technique that has received great attention in recent years, especially in the area of health and social sciences, one of the reasons being that SEM estimates multiple and interrelated dependence in a single analysis (Esposito Vinzi et al., 2010; Henseler et al., 2009).

According to the literature on market dynamism, it is known that business effectiveness influences market dynamism and is determined by a company’s ability to react to market intelligence and take advantage of opportunities (Falahat et al., 2020). Therefore, the variables that describe organisational behaviour (Management and Strategy, and Marketing and Finance) are considered as latent variables that describe business effectiveness, so a model was proposed in which we studied the correlation between this variable and market dynamism.

On the other hand, social capital also influences the way the market behaves. In the face of great dynamism and taking advantage of the existence of ties, it manages to satisfy customers’ needs, even expanding to new markets (Hemphälä & Magnusson, 2012; Sarkar et al., 2001), so that the variables of strong and diverse ties, as well as the cohesion of the network of small enterprises, are considered as latent variables that describe social capital, and a model was proposed in which we studied the correlation between social capital and market dynamism.

Finally, it is known that tourism companies are strongly linked, thus the study of social capital and networks is an appropriate approach when dealing with the tourism industry, as it is necessary to develop networks not only locally but also globally (Erku?-Öztürk, 2009). Companies that have social capital and consolidated networks are expected to be able to exploit resources more effectively. For that reason, a model was proposed in which we studied the correlation between social capital and resource exploitation.

Non-linear Regression Analysis

In various studies on market dynamism and pioneering or innovative firms, a U-shape relationship has been established. The relationship between competition and innovation is non-linear and depends crucially on the efficient use of inputs for production (De Bettignies, 2018; Peroni & Ferreira, 2012). Following the same reasoning, we ask ourselves: how is market dynamism related to the preparation that organisations should have to face this dynamism? Figure 2 illustrates the expected behaviour of both variables.

Figure 2 Relationship Between Business Effectiveness and Market Dynamism

In markets with low dynamism, the organisation’s preparedness will generally be low, whilst as market dynamism increases, firms are forced to improve management practices, and it is atypical for there to be high preparedness in markets with low dynamism and low preparedness in a market with high dynamism.

In this sense, it is important to consider both linear and non-linear regression analyses (Ritz & Streibig, 2008) in order to corroborate that there is a sufficiently strong correlation, which allows us to verify the hypotheses put forward. Linear regression analysis is one of the most important tools of quantitative analysis, especially when we want to predict - or explain - a dependent variable based on one (simple linear) or more independent variables (multi-linear). Linear model fitting seeks to find a function - in a mathematical sense - that allows us to express a variable from other variables.

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Where the coefficients a_1,…,a_n, E are to be estimated. In the case of non-linear fits, a model of the following form is appropriate.

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Where f represents a function that is not necessarily linear

Results

The data were processed and ordered with Microsoft Excel (2012) and then the R software package (Rosseel, 2012). This provides an analysis of the SEM with a friendly syntax when running the models and the R package (Fox & Weisberg, 2018), which provides a proper approach for regression analysis. In order to perform the quantitative analyses, the data were transformed into a scale from 0 to 4, where 0 represents not at all and 4 completely. Cronbach’s alpha was calculated to measure the reliability of the applied questionnaire, resulting in 0.9418922. This indicates that the measurement instrument is reliable. Table 2 shows a statistical summary of the results obtained.

Table 2 Statistical Summary
Latent Variables Abbreviation Mean std.dev coef.var
Management and Strategy S1 2.60 1.33 0.51
S2 2.47 1.30 0.53
S3 3.07 1.21 0.40
S4 3.13 1.03 0.33
S5 2.44 1.49 0.61
Marketing M1 2.04 1.39 0.68
M2 1.65 1.40 0.84
M3 3.22 1.10 0.34
M4 2.58 1.49 0.58
M5 0.99 1.12 1.14
M6 1.90 1.51 0.79
Finance F1 2.97 1.14 0.38
F2 2.93 1.17 0.40
F3 2.83 1.22 0.43
Cohesion C1 2.57 1.38 0.54
C2 2.60 1.40 0.54
C3 2.60 1.31 0.50
Diverse ties DT1 2.94 1.06 0.36
DT2 3.17 1.29 0.41
DT3 2.82 1.44 0.51
Strong ties ST1 3.10 1.20 0.39
ST2 2.68 1.30 0.48
ST3 2.74 1.36 0.50
Marketing dynamism D1 2.40 1.29 0.53
D2 2.56 1.28 0.50
D3 2.58 1.39 0.54
Resource explotaition R1 1.49 0.99 0.67
R2 1.38 1.03 0.75
R3 1.43 1.05 0.73
 

Structural Equation Models

The first model we studied is given by the relationship between organisational effectiveness and market dynamism. Figure 3 shows the SEM diagram we considered in order to study this relationship.

Figure 3 Model 1: Relationship Between Business Effectiveness and Market Dynamism

The Comparative Fit Index (CFI) indicates a good fit (>0.9) as does the Root Mean Square Error of Approximation (RMSEA) (<0.08) and Parsimonious fit (<3.0). Therefore, it can be concluded from the model that organisational effectiveness is correlated with market dynamism. However, both the Goodness fit index (GFI) and the Normed fit index (NFI) - which explain the variance of the model - are below what is expected (>0.9). This could occur because the predictors of organisational effectiveness do influence market dynamism, but there might be other factors to consider, such as non-linearity.

In this case, the model proposes a correlation between market dynamism and social capital. It should be noted that cohesion is correlated with the diversity of the network, and therefore influences social capital directly and indirectly.

The results for the CFI (>0.9) and Parsimonious fit (<3.0) indicate a good fit. Thus, it can be concluded from the model that social capital correlates with market dynamism; however, the RMSEA, GFI and NFI do not have ideal values, so again, we see the influence of social capital. Nevertheless, this influence is not linear, hence other factors must be considered.

Finally, in the third model, the interaction between the social capital of the companies and how this influences the benefit of resource exploitation is discussed (Figure 4 & Figure 5).

Figure 4 Model 2: Relationship Between Social Capital and Market Dynamism

Figure 5 Model 3: Relationship Between Social Capital and Resource Exploitation

This model takes into consideration the correlation between network cohesion and diversity. It correlates social capital and resource exploitation, and the most relevant fit indices are shown in Table 3.

Table 3 The Comparative Summarised Table of Model fit Indices
Models Df x2 Parsimonious Fit P-value RMSEA CFI SRMR GFI NFI
Model 1 115 165.678 14.407 0.001 0.078 0.911 0.089 0.791 0.765
Model 2 49 78.655 16.052 0.005 0.092 0.895 0.096 0.837 0.774
Model 3 83 104.02 1.253 0.059 0.059 0.952 0.083 0.834 0.809

In this case, all the indices indicate that the fit of this model is very good. The p-value is 0.059 >0.05, the CFI is >0.9, the Parsimonious fit is <3.0, the RMSEA is <0. 08, the GFI is >0.8 and the NFI is >0.8. It can be concluded that social capital has a determining influence on resource exploitation.

Non-linear Regression

The results obtained for Models 1 and 2, which relate market dynamism to business effectiveness and social capital respectively, and what has been discussed about how prepared a company should be to deal with market dynamism lead us to consider that the existing relationship between the variables is non-linear, which is why the adjustment indices for both models have not reached all the optimal acceptance values.

In our case, based on the data collected, we consider the variable of business effectiveness, related to the degree of coherence between the objectives of an organisation and the results achieved. In our study, we have contemplated the degree of management and training that tourism establishments have in the areas of administration, marketing and finance. This corresponds to the components that have to do with the managerial aspects of the organisation. Social capital, which results from the average of cohesion and strong and diverse ties, corresponds to the links and networks that the organisation possesses.

The adjusted model we propose that relates market dynamism and business effectiveness is given by:

Model 4

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The model for the case of market dynamism and social capital is given.

Model 5

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A regression analysis was performed between business effectiveness and social capital, considering that market dynamism has an exponential influence, and a joint scatter plot between both variables is shown in Figure 6.

Figure 6 Scatterplot of the Relationship Between Market Dynamism and (A) Business Effectiveness, and (B) Social Capital, Showing the line of Exponential Fit

Table 4 shows the results of the adjustment for the correlation between market dynamism and business effectiveness (Model 4), and market dynamism and social capital (Model 5).

Table 4 Summary Fit Statistics for Correlation Models
Model DF F-statistic Residual Std. error p-value Adjusted Multiple
R-squared R-squared
Model 4 68 8689 0.9151 2.20E-16 0.9973 0.9974
Model 5 68 7596 0.9734 2.20E-16 0.9969 0.997

Finally, the two non-linear models describing market dynamism represent two sides of the same phenomenon- organisational effectiveness and social capital. For that reason, we analysed the correlation between the two variables. The joint scatter plot is shown in Figure 7.

Figure 7 Scatterplot of the Relationship between Business Effectiveness and Social Capital, Showing the Fitted Line

Table 5 shows the results for the linear estimation model between business effectiveness and social capital.

Table 5 Summary Statistics for the Linear Estimation Model Between Business Effectiveness and Social Captial
  Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.370024 0.153932 2.404 0.0189
Business Effectiveness 0.993716 0.005395 184.198 <2e-16
Df F-statistic Residual Std. Error p-value Adjusted
R-squared
Multiple
R-squared
70 3.39E+04 0.7981 2.20E-16 0.9979 0.9979

Discussion

The responses obtained for Management and Strategy are relatively high, and there is no major variation between the items in this category. Only question S5, which has to do with the implementation of training programmes, shows a greater dispersion, which suggests that the training processes between the establishments differ greatly.

In the case of marketing, it can be noted that the responses to questions M2, M5 and M6 related to market research, promotion and evaluation of advertising and marketing strategies were particularly low, showing that most of the establishments do not have any type of marketing strategies, which is considered a weakness in this type of tourism business.

The results for financial management are fairly homogeneous and relatively high, indicating that most of the establishments have a positive perception of their financial management strategies.

Regarding social capital, it can be observed that the results for cohesion, diverse ties and strong ties are relatively high and the dispersion between them is similar to the results obtained in question DT1 regarding the presence of family members within the professional network, which presents the lowest dispersion, suggesting that most establishments have a strong family component.

The results for market dynamism are homogeneous, placing it at around 2.5 out of 4, which indicate that, in general, the establishments perceive that there is dynamism in how customers change their preferences and demand new products, but this dynamism is not particularly high, i.e. the change in preferences tends to be slow.

As for the exploitation of resources, the results are low (at around 1.43) and there is little variation, so it can be concluded that the establishments are not making optimal use of the resources that can be obtained through the professional networks. This contrasts with the results obtained for social capital, where professional networks do exist and with the results obtained in Table 5 for the adjustment indices of Model 3, which prove hypotheses H3 and H4 put forward in this study. These hypotheses assume that the diversity and cohesion of a tourism enterprise’s network favour the effective exploitation of resources; therefore, the professional networks are not fully exploited for the benefit of the establishments.

The results obtained for Model 4 show a good fit for this model, with an adjusted R-squared value of 0.9973. This confirms that there is an exponential fit between market dynamism and business effectiveness. This exponential behaviour indicates that in a market with low dynamism, business effectiveness can also be at very low values even if dynamism increases slightly. Nonetheless, there comes a point where the increase in market dynamism will result in establishments having to increase greatly in business effectiveness in order to cope with this increase in dynamics. This aligns with the assertions of Spenceley et al. (2019) and Falahat et al. (2020), who found that the potential of a tourism product depends on a wide range of factors and that the competitive advantage of SMEs results from excellent management demonstrated in their ability to react to market changes and take advantage of the opportunities that arise. It is also in line with Anzules-Falcones et al. (2020), who affirm that SMEs in the tourism sector have an opportunity in terms of innovation to redesign their strategies, processes and marketing to permit them to innovate their business model according to the new reality and market needs (Anzules-Falcones et al., 2020). This proves H1 rose in this study: Business effectiveness increases exponentially when market dynamism increases.

Similarly, the results for Model 5 show an adjusted R-squared value of 0.9969, which confirms that there is an exponential fit between market dynamism and social capital. In the same way, this exponential behaviour implies that a low valuation in social capital may be sufficient to face a market with low dynamics, and may remain low for a while, but eventually, the sustained increase in market dynamics will force establishments to increase greatly in the creation of social capital in order to keep up with a highly dynamic market. These results are in line with those presented by Hemphälä & Magnusson (2012) that indicate that relationships with diverse stakeholders allow tourism businesses to stay up-to-date through access to external and novel market information. They are also in line with Neffke et al. (2018), who state that the structural differentiation of a network of relationships composed of firms with different levels of competency nurtures the network’s information content and helps to overcome problems that may originate from identifying changes in consumer needs. Lastly, managers should strengthen their closed ties when market dynamism is high and their diverse ties when the first changes in the market emerge. Therefore, we can accept H2, which indicates that social capital increases exponentially when market dynamism increases.

Finally, in the table that relates the variables of business effectiveness and social capital, we observed an adjusted R-squared value of 0.9979, which indicates that the linear fit between them is good. This interesting finding demonstrates that when there is better business effectiveness, an improvement in social capital to the same extent will be evident.

Conclusion

In this research, we first conducted a literature review to theoretically explain the elements of market dynamism and social capital. Subsequently, we developed the methodology to build the models corresponding to the study, obtaining results that were discussed and contrasted with the theories investigated.

We highlighted the challenges faced by tourism enterprises in developing a business model that takes advantage of sustainable resources and capacities and identifies the ever-changing needs of demand. In addition, these establishments face obstacles, for instance: a lack of economic resources, infrastructure and strategies, limited knowledge and tourism promotion, and poor staff training.

The Cotacachi-Cayapas Reserve has rich biodiversity and many natural tourist attractions, as well as a cultural richness with the presence of ethnic groups and communities who are highly valued by tourists who visit it, but it is poorly promoted.

In terms of practical implications, it is recommended that small tourism enterprises review their internal processes related to management, marketing and finance, with special emphasis on training programmes and the development of marketing, promotion and advertising strategies. They must conduct market research to understand fluctuations in demand and determine opportunities resulting from market dynamism. It is important to note that a large increase in market dynamism will push establishments to greatly increase their business effectiveness, which would even require them to adjust their strategy.

This study shows that although networks exist, small tourism enterprises are not sufficiently exploiting the resources and capacities generated from strong links, diverse links and cohesion, a situation that needs to be analysed by the tourism business ventures in order to benefit from existing social capital networks.

The results obtained in this research allow us to suggest several lines of future research, for example applying this study to other types of tourism, as well as incorporating other elements of social capital related to the size of the network, the quality of the network in terms of trust and cooperation as well as environmental conditions.

After obtaining these results, the research team carried out a series of training programmes related to marketing, management and tourism management focused on a sustainable tourism business model. The training was aimed at tourism entrepreneurs and the community in general in the Cotachi-Cayapas Reserve. Its objective was to contribute to the improvement of their business performance and therefore to improve their strategies in the face of market dynamism and the adequate exploitation of resources with the existing social capital.

Acknowledgment 

The authors acknowledge financial support for this project provided by CEDIACorporación Ecuatoriana para el Desarrollo de la Investigación y la Academia, by the project Gestión Integral del Turismo en las Comunidades del Parque Nacional Cotacachi Cayapas,winner of the Ecuadorian contest of Projects CEPRA in 2019.

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