Influence of Social Capital, Social Motivation and Functional Competencies of Entrepreneurs on Agritourism Business: Rural Lodges

Abstract

This study is aimed at examining the relationships between social capital, social motivation and functional competencies and their effects on the participation in the development of an agritourism business among Tunisian entrepreneurs who already have rural lodges in the agritourism sector in Tunisia. The authors applied structural modeling of the partial least squares equation to analyze 100 questionnaires completed by participants and test the hypotheses. The results showed positive and direct effects concerning the two variables, namely, the social capital and functional competencies on the participation in the development of a business in agritourism. On the other hand, the mediating role of social motivation between social capital and participation in the development of an agritourism business has shown an insignificant effect. This study creates a distinctive theoretical contribution to the literature on social entrepreneurial factors by analyzing the relationships between social capital, social motivation and functional competencies of an entrepreneur on participation in the development of a business in agritourism. In addition, this study investigates numerous practical implications of these results.

1. Introduction

Today, agritourism offers a major advantage in the international tourism market and has already played a very important economic and social role in the rural development of certain disadvantaged regions [1]. Agritourism is a key element in the multifunctional development of rural areas. In addition, rural development involves a wide variety of new activities, as well as the production of high-quality and region-specific products, nature conservation and landscape management, agritourism and the development of chains local procurement. There are many theories and approaches in scientific studies that present agritourism as an economic, social, cultural and psychological phenomenon [2] where the rural area represents the essential basic resource for the expansion of agritourism that tourist activity was based on the urban community’s need for peace and outdoor space for restoration [3]. However, agritourism is used more predictably for concepts related to touristic products and services, which are directly related to the agricultural environment, products and other forms of farm stay [2]. In fact, agritourism creates significant and continuous benefits for rural tourism sites and for entrepreneurs themselves. As a result, those responsible for the development, promotion and organization of rural touristic areas come together to assist in the development of these areas [4], and to propose and adjust their rural tourism product or service to be compatible with the demands of today’s customers. However, in the agritourism sector, the persistence of personal businesses differs on their co-operation and assistance with their network [5]. This is especially essential for very specific entrepreneurs who are looking for the persistence of their agritourism businesses. For this reason, it is also necessary to better comprehend the distinct backgrounds that lead the participation in the development of an agritourism business before offering the necessary products/services to meet the needs of their clients. As a result, the importance of an entrepreneur’s social motivation and functional competencies and their effect on development have become very important for researchers in order to reduce the risk that an entrepreneur may face before, during or after his business. However, little research has examined the motivational, social and functional competencies that drive entrepreneurs to launch in the development of their agritourism business.

This research’s purpose is to clarify the interrelations between the entrepreneurial social factors: social capital, social motivation and functional competencies in the context of agritourism through the following research question: how do social capital, social motivation and functional competencies affect the reconstruction of participation in the development of an agritourism business? This question probably retraces the contours of a major research issue in the vast field of entrepreneurship where one answer cannot satisfy all the aspects. In addition, the agritourism sector can be constituted as an essential territory to attract a target, which possibly conceals a remarkable experiential potential in the field of agriculture and tourism.

2. Literature Review

2.1. Social Capital

Over the last decade, the notion of social capital has enjoyed a spectacular career, illustrated by the dynamism of the production of academic articles devoted to commenting on it or implementing it in one way or another, and has gained a rarely equal popularity for an academic notion. Indeed, the notion of social capital makes it possible to characterize the interactions of relationships, to analyze them and to manage them. While their definition of familiarize provides a link between competitive advantages and the resources derived from interactions, the use of the concept of social capital makes it possible to extend and complement this approach by identifying the roots of these competitive advantages. In line with the work of Nahapiet and Ghoshal [6], which shows that social capital is a fundamental resource for this type of business compared to other types of organizations. Social capital is the set of resources that individuals can obtain by knowing other individuals, being part of a social network with them, or simply by being recognized by them and having a great reputation [7]. Many definitions have been proposed, but what they all have in common is that the benevolence that others have towards an actor can be a source of value and that the social resources fundamental in relationships can be applied for economic ends [8,9]. Thus, the actors can derive benefits from their membership in social networks. The notion of social capital covers the structure and content of an actor’s social relationships [10], e.g., the network of relationships, but also the volume of the capital of different kinds that it allows to mobilize by proxy. For an actor to benefit from social capital, three conditions must be met: (1) he must have the opportunity to enter social transactions (the connections of the social network); (2) members of the social network must be motivated to act in favor of the actor; (3) they must have the capacity to do so [10]. Moreover, the beneficial effects of social capital generally fall into three categories, which are not mutually exclusive: information and research, coercion–attraction, and influence. First, network members can use their social connections to generate information that is useful for themselves or the group. This phenomenon has been described in research at the individual, group or company level [8,9]. This beneficial effect vis-à-vis information shows the relationships developed for social purposes that can affect the costs of research and access to information. This point has been further investigated by the network theory through the analysis of how social connections can increase the likelihood of an actor finding the right information [8,9]. Second, social relations can also induce normative pressures [7]. However, there are four ways in which social relations can act coercively or attractively on economic actions: recruitment, obligations, surveillance and discipline. For example, recruiting into a network of relationships implicitly uses pressure from network members to ensure the quality of the worker and to discipline him. Likewise, regular social relations allow actors to monitor economic relations and behavior.

Third, through their social relationships a network member can benefit from varying degrees of influence and power [10]. This allows this (or these) actor(s) to make others carry out certain actions and thus achieve their objectives.

These different impacts of social capital have, for example, been observed in studies on entrepreneurs [10,11]. Thus, the individual social capital that an entrepreneur can have to create or develop his business has an impact on his success in achieving his objectives. Alongside these beneficial aspects, there are also negative facets of social capital that are less highlighted in management research but still exist. These negative consequences are mainly four in number: the exclusion of “outsiders” to the social network, excessive demands for solidarity or mutual assistance between the members of the group, a restriction of individual freedom and standards that hinder success and the development of group members. So, the objective of this study was to use the sources of social capital benefits in the development of certain behavioral variables in an entrepreneur.

2.2. Functional Competencies of an Entrepreneur

The knowledge of job competency refers to the existing abilities or natural abilities of a person. The knowledge of professional competency is seen as influencing the success of entrepreneurship as a socially integrated activity where the idea emphasizes the importance of skills and knowledge in relationships with other partners [12]. Knowledge is a factor that sets entrepreneurs apart from their rivals and turns poorly organized businesses into well-regulated businesses. Knowledge is an important resource for organizations. With more knowledge, the entrepreneur who are unsure of their efficacy can learn and notice market changes more quickly. In fact, the role of entrepreneurship is constantly influenced by education acquired experimentally and culturally. Therefore, it was strongly argued that the traditional approach to entrepreneurship should change, and that the importance of entrepreneurial education should be increased. More recently, the concept of entrepreneurship includes more than just starting a business [12]. Instead, it includes developing the competencies needed to grow the business as well as the personal competencies needed to be successful. Empirical evidence shows that companies whose leaders develop their skills and competences are more likely to be profitable and grow more than companies run by entrepreneurs who do not have these characteristics [12]. Research shows that entrepreneurial competence affects organizational performance, and this concept has become an important tool for improving a company’s competitive advantage. A recent study on emerging economies found that business knowledge tends to promote development, especially among rural women entrepreneurs in Bangladesh [13]. Particularly from the point of view of Asnaf entrepreneurs (beneficiaries of zakat), recent research has shown that capital assistance in the form of courses, training and skills is important for Asnaf entrepreneurs to be successful in their business [14]. On the contrary, it was found that a lack of competencies led to the failure of the company [12]. A previous studies suggests a lack of large-scale entrepreneurial expertise [12]. However, the current studies are fragmented in terms of indicators of business information, and most factors focus on the concept of information in the context of entrepreneurial characteristics. Therefore, the development of these competencies needs to be better assessed.

In the entrepreneurial practice paradigm, dimensions of entrepreneurial knowledge and competencies include self-confidence, education and functional knowledge, especially in the context of small and medium-sized enterprises [12]. The most important elements of entrepreneurial competencies and knowledge are rational/critical reasoning, leadership competencies, and knowledge of business management and organization. Based on the literature review, the current research is an attempt to assess the functional competencies and knowledge between entrepreneurs as a variable that leads to business development in agritourism.

2.3. Motivational Components of Entrepreneurs

Entrepreneurs’ motivation is related to entrepreneurship via entrepreneurial intentions. Indeed, the path companies react to challenges, recognize business-related opportunities and create business plans to invest in them is an intentional behavior strongly affected by entrepreneurial intentions [15]. The major model of entrepreneurial intentions is based on the theory of planned behavior [16] and the idea of the entrepreneurial event [17]. This model recommends which intentions are affected through the seeming viability that is driven by self-efficacy, the individual’s confidence in entrepreneurial defiance, and seeming suitability as the person’s desire to re-engage in connected entrepreneurship tasks [15].

The current motivational approach is generally embedded in economics and psychology but is still struggling. This approach is concentrated on push factors and the incentive approach is concentrated on the pull factors. Therefore, entrepreneurs are motivated by success in their entrepreneurial activities and avoid the risk of failure. There is also the intrinsic motivation that involves intangible motives that endogenously guide an entrepreneur to move (the need for accomplishment, self-realization or reciprocity) and extrinsic motivation that involves external rewards such as acknowledgment and monetary payment.

Empirical analyses reinforce the idea that motivations are a crucial marker of entrepreneurial intentions and interests [15]. Ryan and Deci [18] discover that while the individual’s need for competence, kinship and autonomy is met, intrinsic motivation is the main potential. However, if the above needs are not satisfied, extrinsic motivations become dominant in the behavior. Indeed, the study of Luthje and Franke [19] shows that the personality traits that present themselves as motivational factors have an important effect on entrepreneurial intentions. According to Barba-Sanchez and Atienza-Sahuquillo [20], the need for independence is emerging as a motivation that is closely related to entrepreneurial intentions. For Antonioli et al. [21], the intrinsic motivations are strongly affected by entrepreneurial intentions, contrary to the extrinsic motives that are generally influenced by the position and the environmental work.

In addition, motivations affect behavior through intentions. According to Kozubikova et al. [22], searches on small and medium-sized enterprises (SMEs) have shown that they are more expected to create new products and get involved in innovation. Using multivariate tests on many French start-ups, Gundolf et al. [23] have stated that entrepreneurial motivation is linked to the technique of innovation. An analysis of students founded in Krakow showed that the attitude of risk in business/non-business generally influence entrepreneurial intentions [24]. Using the GUESSS-based data, Sieger et al. [25] suggested that entrepreneurial motivation is related to social identity. They show that there are important differences at the regional level in entrepreneurial identities between Western regions.

2.4. Agritourism in Entrepreneurship Business

Currently, increasing the attractiveness of agritourism and business launch opportunities are a major element of green entrepreneurship in rural areas and help residents in sustainable development [26]. Correspondingly, agritourism entrepreneurship enhances the entrepreneurial features to the agritourism interrelated activities: startling the occasion on the market (many visitors are currently involved in the opportunity of expenditure their vacations on farming milieus), the adjusting of the transformation via an adaptable method (the change from agriculture to agritourism leaning services), affecting the innovation (the practice of the modern technologies in evolving or instigating their businesses) and presumptuous risks of an innovative business project in the rural zone.

Conferring to Bosworth and McElwee [27], ranching has been progressively market concentrated and, in times of economic decline, has prompted farmers to be more flexible to emerge innovative competencies and to renovate themselves from “simple managers” to “entrepreneurs”. Consequently, agritourism entrepreneurship denotes business initiatives founded on agritourism lodging houses, pointed to develop the economic activities in the rural zones, such as a substitute to agriculture, and to respond to a transformation in the customers’ behavior [28], which is more and more fascinated through this kind of expenditure vacations.

Compare to agritourism (which is related to the economic activity), agritourism entrepreneurship (which is based on tourism associated to business initiatives established by entrepreneurs in the rural zones) takes in the entrepreneurial personality and the role of the farm’s worker [29]. Consequently, the economic facets are countered through social and cultural features while assessing agritourism entrepreneurship. The entrepreneurial character is enhanced by the apparent occasion on the market (increasing the number of tourists and national/regional financial funding), the practical and risk-taking initiative by creating an innovative business, within the subsequent challenges related to it, and the sustenance of innovation and technology (while profoundly attached in the rural milieu and local traditions, the agritourism lodging frequently encourage and reserve their services and activities by employing the Internet and social media channels). Hence, the vital trait of agritourism entrepreneurship implies the prospect of the agritourism entrepreneur to attain his/her entrepreneurial objectives alike in the lack of the benefits [30].

3. Research Model and Hypothesis Development

Numerous transcribing works in the postmodern approach favor inductive rather than deductive, and qualitative rather than quantitative currents. For some, they propose to contemplate a “new generation” of qualitative methods better adapted to the field of capital [31]. Notwithstanding, we prefer to take a more mixed method. As a result, we believe that it is possible to consider a framework and research model that integrates approaches. Our work is part of the hypothetic–deductive perspective. Therefore, the next paragraph aims in defining and explaining the variables used for our research model, which should make it possible to study the role played by social entrepreneurial factors in the context of agritourism businesses. Indeed, the next paragraph deals with the clarification of the key variables of our model. As a result, we will focus on the interactions between the variables in our research and the proposed conceptual model.

• Social capital as a social factor on the participation in the development of a business in agritourism

The social capital of an entrepreneur implies their capability to co-operate efficiently with others and to adapt to new situations in order to develop strategic relationships and seize business opportunities. In the same perception, Baron and Markman [7] assert that the social capital of the entrepreneur positively affects the entrepreneurial success.

Hence, based on this observation, the hypotheses already mentioned in the introduction have been developed.

Hypothesis 1 (H1).

The social capital has a strong effect on the entrepreneur to rely on the participation in the development of a business in agritourism.

• Functional competencies as a social factor on the participation in the development of a business in agritourism

Several studies examine the influence of entrepreneurial competencies on the success of their businesses. Chandler and Jansen [32] distinguish three types of competencies: entrepreneurial competencies, technical–functional competencies and managerial competencies. Authors, such as Gupta and Mirchandani [33], admit that these three categories of skills are essential to achieve entrepreneurial success. The experience of the entrepreneur influences the success of the company. Along the same lines, Gupta and Mirchandani [33] have shown that experience is a significant variable in determining success. Having had experience in the same industry as the newly created business increases the likelihood of success and survival. Indeed, they provide practical (organization, team management) and technical competencies that are a success factor for businesses. Several studies suggest that an entrepreneur’s experience working in the same field as their new business has a significant impact on performance. Sajilan and Tehseen [34] find that business experience positively affects the success of the new business. In addition, the effects of past experiences reflect the notion of common sense, and entrepreneurs will be able to do better if they have prior knowledge of buyers and suppliers of operational issues and their environment. Other studies find that the connection between previous experience and entrepreneurial achievement is insignificant [35]. Sapienza et al. [36] explain that the degree of similarity between the new firm and the previous firm can effect negatively the performance. However, the new business builds on the previous competencies without any innovation in entrepreneurial, managerial and technological competencies positively influence success. The study by Aldrich et al. [37] supports these results and shows that good network management (overdraft facilities, support and intervention to manage administrative problems) positively affects the business growth.

Hypothesis 2 (H2).

The functional competencies have a strong effect on the entrepreneur to rely on the participation in the development of a business in agritourism.

For many companies, the social capital of the entrepreneur has a positive impact on entrepreneurial success [38,39]. The majority of companies do not have the knowledge and skills necessary for their activity and must rely on internal and external links to acquire essential information [39]. The functional skills developed based on the network allow entrepreneurs to pave the way for participation in the development of their business. Indeed, based on the training and experience required from the networks, the functional competencies of entrepreneurs can be well developed and acquired [40]. Hence, the following hypothesis is suggested to verify the correlations between the functional competencies of an entrepreneur and social capital:

Hypothesis 3 (H3).

The social capital has a strong effect on the entrepreneur to rely on functional competencies.

• Social motivation as a social factor on the participation in the development of a business in agritourism

The majority of current theoretical approaches, which are based on regional development, agree on the importance of networks, clusters and other forms of social capital which improve the development of businesses and local communities. Precisely, in the tourism sector, the need for collaboration, co-operation and co-ordination between these service providers to produce successful agritourism products suggests that tourism businesses are working together to be successful [41]. In addition, entrepreneurs fostering strong links with tourism stakeholders are more efficient than those doing so individually [42], can generate both personal and social motivations for them. Indeed, agritourism had long ago appeared for farmers as a source to improve their income. However, with the major diversity that the sector has received and the new values that have emerged, the range of motivations of farmers has necessarily widened. The new entrepreneurial motivations are not based only on economic motivations but also on social, environmental and cultural motivations, which take into consideration the community development of the region and sustainability [43]

Hence, the following hypothesis is proposed to verify the mediating role of social motivation between social capital and the participation in the development of a business in agritourism:

Hypothesis 4 (H4).

The social motivation mediates the relationship between the social capital and the participation in the development of a business in agritourism.

All hypotheses were cleared from the literature review are revealed in detail in the theoretical model which is below (Figure 1).

4. Materials and Methods

4.1. Questionnaire Design

Based on the conceptual model developed, an online questionnaire was disseminated. The population is characterized by Tunisian entrepreneurs who owned rural lodgings in Tunisia.

Due to COVID-19, we contacted the respondents via phone and social media so that we could have their agreement to send the questionnaire by email. We were able to collect our data through Google Drive. Respondents were invited to reply to all questions developed in the questionnaire in order to eliminate the problem of missing values. At the end of the three-month period (March, April and June 2020), we received 100 well-completed questionnaires.

The questionnaire used in this study comprises two sections. Firstly, respondents were requested to respond to certain general information about the rural lodging and the time required for the entrepreneur to start their businesses. Secondly, questions were used to measure social capital, social motivation, entrepreneurial functional competencies and participation in the development of an agritourism business. The last part was devoted to answering questions about their sex, age, education and income level in order to determine their demographic characteristics.

4.2. Research Instrument

In order to ensure the right choice of measurement scales and the possibility of their use in the context of this work, we carried out a pre-test of the borrowed scales, considering the difference in the context of our study compared to the context of the origin of the chosen scales. However, the validity criteria, the validation construct and the constructed validity criteria were applied to prove the questionnaire. The apparent validity was confirmed by seeking expert advice on the importance of the measurement items and the defect items for each variable used in the questionnaire. The recommendations of specialists in this area were considered and the definitive version of the questionnaire was arranged, centered on their remarks and recommendations. The correctness of the construction and the validity of the standard for the implants under study have already been demonstrated based on the previous studies. However, an exploratory factor analysis was presented to improve the validity of the construction.

The elements used to measure the social capital were adapted by using ten items from Nahapiet and Ghoshal [6]. The functional competencies were measured by nine items from Lichtenstein and Lyons [44] and Phelan C. [45]. For the social motivation, it was adapted by eleven items from Bartha, et al. [15]. Lastly, the participation on the development of an agritourism business was measured by using thirteen items from Durrande-Moreau et al. [46] (See Appendix A 

Table A1. List of items used to measure the variables.

Variables	Sub-Variables	Items
Social capital	SCS1	For you, the number of social ties with business experience in agritourism is very important.
	SCS2	For you, work experience in the tourism sector is very important.
	SCS3	For you, being a village leaders is very important.
	SCR4	For you, willingness to exchange employment and investment information is very important.
	SCR5	For you, willingness to exchange money and other assets is very important.
	SCR6	For you, confidence in family and friends for strong support in a crisis is very important.
	SCR7	For you, trustworthiness of family and friends is very important.
	SCC8	For you, encouraging young people to become independent by operating a business is very important.
	SCC9	For you, paying close attention to and admiring successful entrepreneurs is very important.
	SCC10	For you, attitude towards employment in tourism/hospitality is very important.
Social motivation	SM1	For you, to start a business in agritourism is to help you make money and become rich.
	SM2	For you, starting a business in agritourism is mainly to achieve financial success.
	SM3	For you, to start a business in agritourism is to advance your career in the business world.
	SM4	For you, to start a business in agritourism is to be able to signal your capabilities to others.
	SM5	For you, to start a business in agritourism is to solve a specific problem for a group of people that you strongly identify with.
	SM6	For you, to start a business in agritourism is to play a proactive role with the companion of guests.
	SM7	For you, to start a business in agritourism is to meet the needs of the leisure that the government encourages with their tax incentives.
	SM8	For you, to start a business in agritourism is to do something that allows you to enact values that are core to who you are.
	SM9	For you, to start a business in agritourism is to help you solve a societal problem that the government encourages with their new programs.
	SM10	For you, to start a business in agritourism is to define an image of the entrepreneur.
	SM11	For you, to start a business in agritourism is to be an entrepreneurial innovator.
Functional competencies	FC1	For you, a business in agritourism helps the ability to take responsibility for solving a problem.
	FC2	For you, a business in agritourism helps the emotional ability to cope with a problem.
	FC3	For you, a business in agritourism helps the ability to think critically.
	FC4	For you, a business in agritourism helps the ability to co-operate with others, networking and utilizing contacts.
	FC5	For you, a business in agritourism helps the ability to reflect and to be introspective.
	FC6	For you, a business in agritourism helps the ability to recognize market gaps and exploit market opportunities.
	FC7	For you, a business in agritourism helps the ability to do business and strategic planning.
	FC8	For you, a business in agritourism helps the ability to set personal goals, reach them and set new ones.
	FC9	For you, a business in agritourism helps the ability to make persuasive communication and negotiation skills.
Participation on the development of an agritourism business	ADOFF1	For you, a business in agritourism helps in the development of off-farm accommodation.
	ADOFF2	For you, a business in agritourism helps in the development of off-farm catering.
	ADOFF3	For you, a business in agritourism helps in the development of off-farm agritourist tours.
	ADOFF4	For you, a business in agritourism helps the sales development of regional off-farm products.
	ADOFF5	For you, a business in agritourism helps the development of visits to regional museums.
	ADOFF6	For you, a business in agritourism helps the development of themed stays.
	ADOF7	For you, a business in agritourism helps the development of regional events.
	ADOFF8	For you, a business in agritourism helps the development of themed routes (cheese road, wine road, etc.).
	ADOFF9	For you, a business in agritourism helps the development of themed trails (hiking, equestrian trails, etc.).
	ADONN1	For you, a business in agritourism helps the development of farm accommodation.
	ADONN2	For you, a business in agritourism helps the development of farm catering.
	ADONN3	For you, a business in agritourism helps the development of farm visits.
	ADONN4	For you, a business in agritourism helps the development of direct farm sales.

). The whole concepts were assessed based on the five-point Likert scale ranging from (1) strongly disagree to (5) strongly disagree. The questionnaire was converted to French and Arabic and later reconverted to English to demonstrate the accuracy of the meaning for every element [47] for the Tunisian entrepreneurs.

4.3. Analytical Methods

As part of this research, the following methods were selected:

• An exploratory factor analysis (EFA) was performed using Cronbach’s alpha with the help of SPSS 26 software.
• A confirmatory factor analysis (CFA) was performed in order to obtain reliable, valid and good psychometric measurement scales.
• A causal analysis of the relational structure of the conceptual model and making it possible to test all the research hypotheses by applying the PLS approach. SmartPLS 3.2 software was used. By comparing the two approaches CB-SEM and PLS-SEM, the CB-SEM approach is based on the analysis of covariances via the LISREL or AMOS software and is interested in the estimation by the maximum likelihood (estimation of coefficients and minimization of the difference between the variance–covariance matrix). Unfortunately, this method has restrictions for certain types of data, resulting in serious estimation errors in addition to its rigidity in terms of sample size. The second PLS-SEM approach is widely used by marketing researchers [48]. It is based on the variance (estimation of the parameters with a multiple regression) and the statistical processing carried out via the SmartPLS software. It completes the method which precedes it as an extension without the same limits by presenting solutions to the problems of estimation by covariance. It should be noted that the estimation of the model is based on partial least squares following an iterative approach which is performed by multiple regressions while maximizing the explained variance. As mentioned by Kumar and Purani [49], PLS-SEM is a more flexible method for researchers who intend to work on small samples with measuring instruments with a low number of elements and data that do not follow the rule of collinearity. Our own justifications for choosing this approach are based essentially on “the complex nature of the structural model comprising several constructs and several indicators”, “the non-normal distribution of the data”, “the exploratory nature of the research”, “the objective prediction constructs that we want to achieve” and “the reduced sample size”.

5. Results and Findings

5.1. Demographics of Participants

The population studied represents Tunisian entrepreneurs who have rural lodges working in the agritourism sector in Tunisia. The demographic characteristics of the respondents (n = 100) are presented in

Table 1. Description of the sample.

Demographic Characteristics	Category	Percent
Gender	Male	61
	Female	39
Age	18–35	15
	36–50	56
	51–65	29
Education	High school	43
	Bachelor’s degree	54
	Postgraduate (+5 years)	2
Income/monthly/person	TND 1300–4000 *	78
	TND 4000<	22

* TND 1 (Tunisian Dinar) = EUR 0.31; EUR 1 = HUF 362.62; TND 1 = HUF 110.45.

. Men (61.0%) were slightly more numerous than women (39.0%). More than half of the respondents (56.0%) were between 36–50 years old, followed by the oldest who were aged between 51–65 years old (29.0%). More than half of the respondents had a bachelor’s degree, which represented 54.0%, and those who had graduated from high school represented 43.0%. The majority of respondents earn between TND 1300–4000 (78.0%).

5.2. Factor Analysis

An EFA was accomplished by applying a principal element analysis and varimax rotation. The minimum factor loading criteria was agreed to 0.50. The communality of the scale, which reveals the amount of variance in each dimension, was also assessed to confirm acceptable levels of explanation. The results demonstrate that all communalities were more than 0.50 excluding one item.

An important step included assessing the overall significance of the correlation matrix through Bartlett’s Test of Sphericity, which requires a measure of the statistical probability that the correlation matrix has significant correlation among some of its components. The results were significant, X² (n = 100) = 410,271 (p < 0.001), which indicates its suitability for factor analysis. The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy, which indicates the appropriateness of the data for factor analysis, was 0.765. Concerning data with KMO values over 0.700 were deemed suitable for factor analysis. Finally, the factor solution stemming from this assessment generated four factors for the scale, which reported 87.692% of the variation in the data.

Nonetheless, in this initial EFA, one item (ADOFFFARM4) declined to load on any dimension significantly. Hence, these items were eliminated from the next assessment. The author restated the EFA without involving these items. The results of this new analysis proved that the four factor’s structure theoretically described in the study (see

Table 2. Reliability of measurement scales.

Variables	Dimensions	Items	Communalities	Rotated Factor Loadings	Cronbach’s Alpha
Social capital of entrepreneur	Structural social capital	SCS1	0.757	0.850	0.845
		SCS2	0.850	0.796
		SCS3	0.868	0.906
	Relational social capital	SCR4	0.702	0.838	0.851
		SCR5	0.736	0.632
		SCR6	0.864	0.807
		SCR7	0.676	0.608
	Cognitive social capital	SCC8	0.774	0.824	0.902
		SCS9	0.862	0.716
		SCC10	0.716	0.602
	SS loadings = 1.031; KMO = 0.882; α of the scale = 0.945; Bartlett’s Test = Significant p < 0.001
	Total variance 78.056%
Social motivation of entrepreneur		SM1	0.729	0.725	0.896
		SM2	0.616	0.775
		SM3	0.962	0.938
		SM4	0.633	0.625
		SM5	0.657	0.609
		SM6	0.806	0.782
		SM7	0.640	0.670
		SM8	0.638	0.789
		SM9	0.833	0.855
		SM10	0.952	0.936
		SM11	0.958	0.937
		SS loadings = 1.267; KMO = 0.812; α of the scale = 0.896; Bartlett’s Test = Significant p < 0.001
	Total variance 76.583%
Functional competencies of entrepreneur		FC1	0.652	0.740	0.701
		FC2	0.738	0.855
		FC3	0.593	0.529
		FC4	0.740	0.825
		FC6	0.881	0.931
		FC8	0.850	0.886
		FC9	0.806	0.877
		SS loadings = 1.073; KMO = 0.669; α of the scale = 0.701; Bartlett’s test = Significant p < 0.001
	Total variance 75.160%
Agritourism development	Agritourism development of farms	ADOFFFARM1	0.706	0.825	0.728
		ADOFFFARM2	0.860	0.904
		ADOFFFARM3	0.977	0.979
		ADOFFFARM5	0.871	0.922
		ADOFFFARM6	0.792	0.816
		ADOFFFARM7	0.805	0.801
		ADOFFFARM8	0.675	0.821
		ADOFFFARM9	0.739	0.832
	Agritourism development on farm	ADONFARM1	0.977	0.975	0.986
		ADONFARM2	0.966	0.972
		ADONFARM3	0.833	0.900
		ADONFARM4	0.974	0.974
	SS loadings = 1.009; KMO = 0.870; α of the scale = 0.896; Bartlett’s test = Significant p < 0.001
	Total variance 84.798%

). The Kaiser–Meyer–Olkin (KMO) was 0.791. the four factors described a total of 88.955% of the variance among the items in the research. The Bartlett’ Test of Sphericity proved to be significant, and all communalities were over the required value of 0.500. The four factors categorized as part of this EFA allied with the theoretical proposal in this research. Factor one contains items SC1 to SC10, indicating social capital (SC). Factor two indicates items SM1 to SM11, referring to social motivation (SM). Factor three comprises items FC1 to FC9, denoting functional competencies (FC). Finally, factor four gathers 12 items from ADONFARM 1 to ADONFARM 4 and ADOFFFARM 1 to ADOFFFARM 9, representing agritourism business development (AG). Factor loadings are presented in Table 2.

5.3. Measurement of Model Applying PLS-SEM

5.3.1. Item Statistics

The central tendency measures that include mean and median as well as of variability measures as standard deviation, kurtosis and skewness were verified to ensure that the data utilized for analysis were good enough. If the skewness and kurtosis values of a data set fall within the range of ±2, the normal univariate distribution of a data set can be proved [50]. Nevertheless, one of the principal advantages of utilizing PLS-SEM is that it does not demand normal distribution of the data being analyzed. However, the item statistics were totally checked to assure that there were no extreme values in the data analyzed. The presence of extreme outliers is not desirable in exploratory studies. The results of measures of the central tendency and variability of the independent variables are bounded as Appendix A 

Table A2. Item statistics of independent variables.

Items	Mean	Median	Standard Deviation	Excess Kurtosis	Skewness
SCS1	4.200	4	1.030	1.849	−1.529
SCS2	4.210	4	0.875	1.472	−1.336
SCS3	4.290	4	0.864	1.459	−1.361
SCR4	4.410	4	0.602	2.884	−1.045
SCR5	4.170	4	0.917	0.640	−1.137
SCR6	4.240	4	0.885	1.488	−1.375
SCR7	4.120	4	0.952	0.023	−0.952
SCC8	4.260	4	0.844	1.615	−1.339
SCC9	4.110	4	0.871	1.011	−1.141
SCC10	4.220	4	0.832	0.846	−1.141
SM1	3.690	4	1.270	−1.235	−0.435
SM2	4.430	5	0.738	3.327	−1.647
SM3	4.010	4	0.922	0.640	−1.109
SM4	3.460	4	1.203	−0.926	−0.603
SM5	3.780	4	1.035	0.527	−0.972
SM6	3.360	4	1.179	−1.491	−0.104
SM7	3.320	4	1.067	−1.403	−0.071
SM8	3.890	4	0.882	0.085	−0.758
SM9	3.940	4	1.094	−0.552	−0.764
SM10	4.000	4	0.917	0.664	−1.108
SM11	4.010	4	0.922	0.640	−1.109
FC1	3.890	4	1.067	0.160	−1.031
FC2	3.990	4	1.063	0.462	−1.146
FC3	4.190	4	0.966	1.237	−1.338
FC4	4.090	4	0.960	0.527	−1.147
FC5	4.410	4	0.585	−0.689	−0.404
FC6	4.140	4	0.762	1.150	−0.933
FC7	4.380	5	0.881	4.430	−1.990
FC8	3.780	4	1.293	−1.177	−0.567
FC9	3.840	4	1.138	−1.076	−0.589
ADOFF1	4.050	4	0.973	0.345	−1.092
ADOFF2	3.380	4	1.198	−1.513	−0.101
ADOFF3	3.950	4	1.071	−0.443	−0.890
ADOFF4	3.890	4	1.224	−1.172	−0.684
ADOFF5	3.990	4	1.034	−0.164	−0.971
ADOFF6	3.730	4	1.121	−0.407	−0.787
ADOF7	3.030	3	1.382	−1.355	0.246
ADOFF8	4.080	4	0.987	0.325	−1.114
ADOFF9	4.110	4	0.968	0.518	−1.163
ADONN1	3.950	4	1.071	−0.443	−0.890
ADONN2	3.930	4	1.061	−0.428	−0.879
ADONN3	3.910	4	1.050	0.349	−1.081
ADONN4	3.960	4	1.076	−0.449	−0.897

.

5.3.2. Evaluation of Measurement Model

In order to evaluate internal reliability, we started by checking the composite reliability, the reliability of the indicators (items reliability) as well as the Cronbach’s alpha index based on the suggestions of Hair et al. [51] through the software SmartPLS3 and its PLS algorithm calculation commands. Indeed, the indicator verifying internal consistency, namely, the coefficient of composite reliability that represents the construct recognizing the correlation of its items, must mostly be more than (0.7) and fewer than (0.95), including the tolerance of the lowest level of (0.6) [51]. Likewise, the value of Cronbach’s alpha that is involved in the connection between items and their representativeness of the similar construct must be bigger than (0.7). The reliability of the indicators is determined by the construct’s items and is confirmable across the external loads (outer loading). Concurring to the recommendations of Hair et al. [51], items with low loading factor values should be eliminated (factor loading < 0.4). A minimum item of (0.4) is tolerated, while the removal of items that loadings are between (0.4) and (0.7) should be performed by verifying its effect on the upgrading of the indicators (CR) and the average of the extracted variance (AVE). The assessment of the loading of the indicators allowed to identify some items that have a low loading value (<0.5). Based on the suggestions of Hair et al. [51], we ensued by removing the items that had a lower loading score, starting with the item that exemplifies the lowest factor loading value and verifying its effect on the scale reliability. The removal of seven items (SM2, SM8, FC3, FC6, ADOFFFARM2, ADOFFFARM6, ADOFFFARM7) allowed the improvement of the reliability of the CR and AVE. After the purification of the model, the proof of the loading and the indices of CR and AVE exposed a respectable reliability of the indicators, which all of them had good loadings (more than 0.7) and that the scales measurement showed a respectable internal consistency with values of CR greater than (0.6) and less than (0.95).

The rho_A used in the PLS-SEM models is one of the vital measures of reliability. It provides an estimate for the squared correlation of the construct score with the score that is undetermined or the true construct score. The minimum score to be reached for rho_A is 0.7 [52]. All results of the reflective measurement model are represented in the

Table 3. PLS-SEM assessment results of the reflective measurement model.

Constructs	Dimensions	Indicators	Loadings	Cronbach’s Alpha	Rho_A	Composite Reliability
Social capital				0.945	0.952	0.954
	Structural capital	SCS1	0.887	0.847	0.848	0.908
		SCS2	0.802
		SCS3	0.735
	Relational capital	SCR1	0.585	0.851	0.876	0.900
		SCR2	0.850
		SCR3	0.891
		SCR4	0.831
	Cognitive capital	SCC1	0.819	0.902	0.907	0.939
		SCC2	0.929
		SCC3	0.842
Social motivation		SM1	0.743	0.914	0.944	0.929
		SM3	0.893
		SM4	0.746
		SM5	0.770
		SM6	0.743
		SM9	0.714
		SM10	0.888
		SM11	0.891
Functional competencies of entrepreneur		FC1	0.827	0.788	0.847	0.847
		FC2	0.775
		FC4	0.828
		FC8	0.642
		FC9	0.560
Agritourism development				0.977	0.980	0.981
	Agritourism on farm	ADONFARM1	0.987	0.986	0.988	0.990
		ADONFARM2	0.983
		ADONFARM3	0.909
		ADONFARM4	0.986
	Agritourism off farm	ADOFFFARM1	0.839	0.938	0.945	0.954
		ADOFFFARM3	0.988
		ADOFFFARM5	0.933
		ADOFFFARM8	0.815
		ADOFFFARM9	0.842

.

For a more in-depth assessment, the extracted mean variance (AVE) was explored to investigate the convergent validity, which provides and reveals the manner that the underlying construct clarifies more than half of the variance in its elements, indicating that the construct converges to its indicators [51]. In this effect, the AVE values of the studied compositions were better than the proposed value of 0.50 suggesting that the construct describes more than 50% of the variance of indices (elements). Thus, the converge validity is successfully acquired.

Then, it was opted to utilize the criterion of Fornell and Larcker [53] to assess the discriminant validity of the permutations analyzed that should be required in the model, such as the empirical distinction from other interpretations more accurately than the less accurate cross-loading approach [51]. The criterion of Fornell and Larcker [53] assumes that the correlation values of each construct must be less than the square root of the AVE. As part of our research and for analysis, we have summarized in the table below the different results, which highlight and reveal that all the square roots of the AVE values of the reflective constructions studied (e.g., the diagonal values) are higher structural correlations (e.g., diagonal off-matrix values), indicating that the single specified construct has no covariance with any other construct greater than its AVE value, confirming and demonstrating the distinction of the proof of validity (See

Table 4. Discriminant validity test.

	AGOFF_AG	AGONN_AG	SCC_SC	SCR_SC	SCS_SC	FC	AG	SC	SM
ADOFF_AG	0.949	-	-	-	-	-	-	-	-
ADONN_AG	0.897	0.980	-	-	-	-	-	-	-
SCC_SC	0.486	0.439	0.914	-	-	-	-	-	-
SCR_SC	0.405	0.342	0.843	0.840	-	-	-	-	-
SCS_SC	0.331	0.325	0.847	0.834	0.876	-	-	-	-
FC	0.910	0.893	0.464	0.413	0.335	0.731	-	-	-
AG	0.988	0.987	0.470	0.379	0.333	0.614	0.923	-	-
SC	0.435	0.392	0.947	0.952	0.939	0.432	0.420	0.823	-
SM	0.465	0.428	0.490	0.636	0.479	0.529	0.453	0.575	0.773

Note: The bold numbers in diagonal are the square root of AVE of each construct, and the other numbers are the correlation between constructs.

).

Once reliability and convergent validity have been verified, discriminant validity is investigated. Discriminant validity must be trained to prove the difference between concepts. In this perspective, several criteria can be requested for the assessment of discriminant validity [51]. Corresponding to the current literature, the two most fundamentalist methods to assess discriminant validity are the heterotrait–monotrait ratio (HTMT) and the Fornell–Larcker criterion [53]. Therefore, we used both methods to assess discriminant validity in this research paper. The HTMT value for the whole concept must be less than 0.9 to confirm the discriminant validity based on the HTMT approach [51]. Moreover, to determine the discriminant validity based on the Fornell–Larcker criterion, the square root of the AVE of each construct must be greater than its correlation with the other constructs of the model [51]. The results presented in Table 4 demonstrate adequate discriminant validity based on the two approaches. In the second step, we recognized the values of social capital and the participation in the development of a business in agritourism as second-order formative constructs by applying the score of their correlated dimensions from the first step [51]. Structural social capital, relational social capital and cognitive social capital established social capital [6], while on-farm agritourism and off-farm agritourism established the concept of the participation in the development of business in second order agritourism [46]. Therefore, in the second step, the context of this research contains reflective constructs.

5.3.3. Evaluation of the Structural Model

After having checked the required psychometric properties and the estimation of the measurement model indicating that the quality of the measurement model is acceptable, we proceeded to the evaluation of the structural model (internal model) and to test whether the relations hypotheses between the constructs studied are significant and meaningful. For this purpose, an initial assessment of the structural model and corresponding statistics relating to the quality of the model were established based on the following criteria: coefficient of determination (R²), cross-validated redundancy (Q²) and path coefficients [51].

A prior assessment of the structural model for potential collinearity between construction indicators was examined. The values of the VIF indicator must be greater than (5) (tolerance threshold 0.20) and the variables as well as the indicators must be less than (0.5). Hair et al. [51] propose solutions for these collinearity problems by inviting the elimination of the problematic construct or the merger of the independent variables into a single variable or the transformation of a higher order variable. In our model, the constructs are reflective in nature which have the property of being interchangeable and the values of the VIF confirmed this by displaying values less than three (See

Table 5. The VIF test.

	Agritourism Development	Functional Competencies	Social Capital	Social Motivation
Agritourism development	-	-	-	-
Functional competencies	2.368	-	-	1.237
Social capital	1.642	1.000	-	1.237
Social motivation	1.844	-	-	-

). Thus, we kept our same constructs without bringing any transformation.

The calculation and assessment of the path coefficient is the essential part of the analysis model by which the hypotheses will be accepted or denied from the research.

The criteria mostly utilized to prove that the coefficient of path in two-followed tests is 1.65 at 10%, and 1.96 at a 5% two-tail significance level. Examining the results based on the table below (

Table 6. The path of coefficient.

	Original Sample (O)	Sample Mean (M)	p-Value	5.0%	95.0%
Functional competencies → participation in the development of an agritourism business	0.923	0.032	0.000	0.928	0.999
Social capital → functional competencies	0.161	0.093	0.083	0.286	0.697
Social capital → participation in the development of an agritourism business	0.064	0.037	0.081	0.272	0.608
Social motivation → participation in the development of an agritourism business	−0.072	0.058	0.214	0.310	0.608
Social capital → social motivation	0.586	0.063	0.000	0.440	0.711

), it is noticeable that the paths functional competencies → participation in the development of an agritourism business, social capital → functional competencies, social capital → participation in the development of an agritourism business, and social capital → social motivation were significant, but in one case, social motivation → participation in the development of an agritourism business had proven an insignificant effect.

By examining the output of the statistical blindfolding processing by the PLS-SEM software in order to assess the predictive relevance of the model, we notice that the values associated with the endogenous constructs are all different from zero and quite high. For the exogenous variables representing an antecedent to the endogenous variable “participation in the development of business agritourism”, the value of Q² shows that it has a strong predictive power (0.707). Overall, for the remainder of the antecedents of endogenous variables, all exogenous variables have moderate explanatory predictive power. These results clearly testify to the predictive relevance of the model regarding endogenous latent variables.

The coefficients of the size effect confirm the strong relationship that exists between the constructs whose predictive quality of their antecedents is strong. Indeed, the re-estimation of the model for the construct “participation in the development of business agritourism“ after the removal of its antecedent “functional competencies” shows that the value of Q² has fallen from (0.707) to (0.217), thus showing the strong predictive value of a size effect q² of value (1.672). It is the same for the endogenous variable “functional competencies” whose fall in the value of its coefficient of determination, which went from (0.226) to (0.099), testifies to the consequent explanatory power of the variable “functional competencies” (q² = 0.164). Concerning the variable “social motivation” and its relationship with the “participation in the development of business agritourism “, the variations in the coefficient of determination (from 0.707 to 0.705) are supported by the size effect, which attests to its average predictive prediction (q² = 0.006). Contrary to the relation “social capital” and “participation in the development of business agritourism “, the effect of size q² is very weak (0.003), which can be explained by the existence of other antecedents which could have a stronger prediction quality for this construct. The same is true for the relationship between “social capital” and “functional competencies” which displays a very small size effect. All the results are combined in the table below (

Table 7. Predictive relevance of Q² and size effect of q².

Relationship/Constructs	Q2 Includes (Predictive Importance)	Q2 Excluded	q2 (Size Effect)	Quality of the Size Effect
Social capital → functional competencies	0.226	0.000	0.291	Strong
Social motivation → participation in the development of business agritourism	0.707	0.705	0.006	Weak
Functional competencies → participation in the development of business agritourism	0.707	0.217	1.672	Strong
Social capital → participation in the development of business agritourism	0.707	0.706	0.003	Weak

).

The outputs of the PLS treatment indicated that the variable “functional competencies” contributes strongly to the explanation of the variance of “participation in the development of business agritourism” with a strong effect of size (f² = 1.607 > 0.35). Thus, the functional competencies of entrepreneurs have a large size effect for the participation in the development of business agritourism of entrepreneurs with a strong causal relationship. Regarding “social capital”, it has a moderate effect on “social motivation” with (f² = 0.214 < 0.35). This leads to the social capital of the entrepreneur contributing moderately to explaining the variance of their social motivation. By examining the value of the size effect relative to “social capital” (f² = 0.237 < 0.35), it shows a weak size effect on an “entrepreneur’s functional competencies”. We thus deduce that social capital contributes strongly to the explanation of the variation of functional competencies of the entrepreneur. For its part, “social motivation” has a small effect (f² = 0.009 < 0.35). Based on these values, social motivation could contribute weakly to explaining variation in their social capital and strongly in explaining variation in agritourism development of businesses (See

Table 8. Effect sizes of the exogenous constructs on the model’s predictive accuracy and relevance.

	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	t-Statistics (|O/STDEV|)	p-Values	Effect Size
FC → AG	1.607	1.785	0.676	2.379	0.017	Large
FC → SM	0.237	0.253	0.125	1.892	0.059	Medium
SC → AG	0.001	0.008	0.013	0.045	0.964	Small
SC → FC	0.237	0.294	0.190	1.248	0.212	Medium
SC → SM	0.214	0.231	0.092	2.330	0.020	Medium
SM → AG	0.009	0.026	0.038	0.236	0.813	Small

).

Based on these data, we can presume that the latent variables of the model have a good relationship between them since the indicator of the size effect is linked to the significance of the causal relationships.

Based on our results, the RMS theta indicator (0.129) reveals a result marginally superior to the level that is suitable. As a conclusion found in the table below (

Table 9. FIT model goodness-of-fit index (SRMR).

SRMR Saturated	Estimated SRMR	RMSTheta
0.107	0.110	0.129

), the model showed an appropriate predictive relevance.

To conclude, our findings provide for the hypotheses on the significance of social capital and functional competencies on participation in the development of business agritourism. These facts prove the H1 and H2 hypotheses. The results of this research provide for the direct impacts of social capital on functional competencies (H3).

5.3.4. Verification of the Mediating Effect of Social Motivation

The results of the statistical analyses of the Bootstrap treatment of PLS relating to the verification of the mediating effect of social motivation in the relationship between social capital and participation in the development of an agritourism business showed, on the one hand, that the indirect effect of social capital on participation in the development of an agritourism business through social motivation is not significant. On the other hand, the direct effect of social capital on participation in the development of an agritourism business is significant. A summary of the direct and indirect effect of social motivation is presented in

Table 10. A summary of the direct and indirect effect of the mediation relationship (social motivation).

Total Effect (SC → AD)		Direct Effect (SC → AD)		Indirect Effects (SC → AD)						Results
Coefficient	p-Value	Coefficient	p-Value		Coefficient	SD	t-Value	p-Value	BI (5%, 95%)	Rejected
0.424	0.000	0.064	0.081	H: SC → >SM → AD	−0.042	−0.040	1.142	0.253	−0.111, 0.009

.

By verifying the type of mediation, we see that the direct effect between “social capital” and “participation in the development of an agritourism business” has a positive sign contrary to the sign of the indirect effect, which lets us conclude the negative sign of the product of the indirect effect. These results allow us to see that there is no mediation (See

Table 11. Summary of the results of the type of mediation (social motivation).

Direct Effect Sign	Indirect Effect Sign	Product Sign (Direct Effect × Indirect Effect)	Type of Mediation
+0.064	−0.042	−1.523	Not complementary

). Based on these observations, we can deduce that “social motivation” did not play a mediating role between “social capital” and “participation in the development of an agritourism business”. Hypothesis four has not been proven. A plausible explanation might be found in the field of the agritourism. However, the agritourism business seems to be a good generator of income for entrepreneurs but the loss of government support which minimizes entrepreneurs to overcome the difficulties of approval and authorization to operate, which are not the sole responsibility of the tourism ministry, and which hardly fit into the framework of administrative procedures. Moreover, the information is not always up to date; the lack of signage, the absence of landscaped panoramic points and the lack of accommodation infrastructure on the sites are major shortcomings in the agritourism sector. These difficulties appear as demotivating factors for agritourism entrepreneurs to develop this sector. Therefore, we must also take into consideration some other factors that may promote the sector and motivate entrepreneurs to develop it, such as the combination of macroeconomic measures and regional and local arrangements.

5.4. Discussion and Implications

The research study explored the direct impacts of the social capital and functional competencies on the participation in the development of an agritourism business (H1–H2), and the direct effect of social capital on functional competencies (H3).

The results of the analysis of the social capital effect on participation in the development of an agritourism business through the estimation of the structural model show that the relationship is strictly positive with the value (β = 0.064). Bootstrap processing shows that the direct relationship is not significant at the 5% level with the value of t-statistic (1.743). These results demonstrate the importance of social capital on participation in the development of an agritourism business which the social capital is a vector of rapprochement between the different actors and the entrepreneur. At the end of these observations, we can say that the hypothesis is validated.

The functional competencies have a positive effect on participation in business development in agritourism. This hypothesis supports the idea that participation in the development of an agritourism business is stimulated by the functional competencies of an entrepreneur. By statistically analyzing this link, it turns out that functional competencies have a strong positive and significant coefficient (β = 0.923, t-statistic = 28.466). The sub-hypothesis is thus validated. Indeed, the functional competencies have a positive and significant effect on the participation on-farm variant (β = 0.906, t-statistic = 21.036). This is a validated sub-hypothesis. Thus, functional competencies have a positive and significant effect on the off-farm participation variant (β = 0.884, t-statistic = 18.728). With the importance of the functional competencies that an entrepreneur must have, the latter is encouraged to participate in the development of an agritourism business whether on-farm or off-farm.

To assist the significance of the structural links between the second-order constructs of social capital and functional competencies among entrepreneurs, we first evaluated the model according to the repeated indicator approach, and then we evaluated the model containing only the first-order constructs in order to test the significance of the sub-hypotheses and to conclude on the overall significance of the hypothesis. We underline that this procedure was adopted for the test of all the structural links of the model, which will lead us each time to justify our hypotheses and under hypothesis by crossing the data of the two adopted methods. The results of the analysis of the influence of social capital on functional competencies of the entrepreneur, by estimating the structural model, show that the relationship is positive (β = 0.161). Continuing the analysis by the Bootstrap treatment, the direct relationship was found to be significant at the 5% level with a statistic t-value (1.732). More specifically, the table shows that relational social capital and cognitive social capital have a positive influence on the functional competencies of entrepreneurs (β = 0.278, t-statistics = 2.678) and (β = 0.246, t-statistics = 2.259), while structural social capital negatively affects the functional competencies of entrepreneurs (β = −0.421, t-statistics = 3.439) at the 5% level. An explanation could be that sometimes the close ties forged within the immediate local environment do not necessarily affect the functional competencies of an agritourism entrepreneur. As a result, rural entrepreneurs can benefit most from the strong links of social capital, which opens opportunities outside the immediate environment, and to develop their functional competencies in relation to their businesses.

The logic of these results is that the emergence of feelings in relationships between individuals facilitates the exchange of knowledge and tends to engage entrepreneurs in their relationships. In addition, the mutual knowledge that allows entrepreneurs to freely express their knowledge, tends to increase the opportunities for understanding between members. If the social relationships connected to the network are poorly managed, they risk to negatively influence the functional competencies of the entrepreneur and risk to no longer offer information channels, which reduce the time and effort needed to collect necessary information.

This research requires theoretical and practical contributions. This study examined the entrepreneurial behavior to participate in the development of an agritourism business and established a model to help entrepreneurs in this sector that suffered from an economic crisis after COVID-19 and after revolution. Starting with examining the determinants that affect the entrepreneurial behavior to participate in the development of an agritourism business, the research has led to a conceptual model that can be used to incentivize entrepreneurs to develop their entrepreneurial social factors in the development of their businesses in the agritourism sector. The results of this research can make a significant contribution to entrepreneurs in the agritourism sector especially, with the multiple consequences of the coronavirus epidemic that companies are experiencing in their offer, their economic model and their management methods ultimately change the experience they want and can provide to each of their visitors. Through our growing understanding of the importance of employing social factors of entrepreneurs in the development of a business, these results can inform the development of an agritourism business, especially in a crisis. Moreover, this research can aid the development of the entrepreneurial marketing communication and enable more effective campaigns to influence visits and stays in rural lodges.

One of the objectives of this study was to analyze the social capital in entrepreneurial development. Social capital is often seen as an essential element in entrepreneurial development. However, studies relating to this subject are fragmented, dispersed and suffer from the lack of an integrative model that considers both the multidimensional aspect of social capital and the results of entrepreneurial development models. The measurement of social capital has generally been carried out in terms of the relative position of the entrepreneur in his social network and the properties that derive from it, which reduces social capital to one dimension and distances other aspects. It is suggested in this work that the three dimensions of social capital (structural, relational and cognitive) are linked and studied in more detail to capture all the properties of this concept and its effects on the entrepreneurial development of entrepreneurs. The contribution of this work compared to previous research is the consideration of the effect of social capital on entrepreneurial development. It aims to show the importance of this concept as an analytical framework for integrating the social aspect into entrepreneurial behavior. However, contrary to other conclusions of the study, the results show that the three dimensions of social capital do not have a direct impact on the participation in the development of an agritourism business, on the other hand an indirect effect improves the relationship between the two variables. Indeed, the tourism economy and more specifically, in our study, the agritourism sector has been severely affected by the coronavirus pandemic and by the measures that have been adopted to limit the spread of the virus. As a result, the recovery will take time on the demand side, given the entanglement of the consequences of the economic and health crises and the gradual lifting of travel restrictions. At the same time, the confidence of travel consumers will be even more affected as the pandemic continues. This perception will certainly change once agritourism entrepreneurs find other more promising avenues, such as improving strategic knowledge on the impacts resulting from the COVID-19 crisis according to different dimensions of the visitor experience, thanks to a structured approach based on international research; moreover, prioritize their initiatives and actions aimed at equipping businesses in the various tourism sectors with concrete avenues. In addition, validate the development potential of a collective support tool that can be quickly applied by touristic companies, regardless of their size or activity. In the short term, entrepreneurs must contribute to the post-COVID-19 recovery, and in the medium term to drive continuous improvement in companies.

The second contribution lies in the linking of variables which until now have not been presented in the same study before, and which have succeeded in empirically validating the effects that we wanted to measure and in explaining in a significant way the participation in the development of an agritourism business in the field of entrepreneurship that we were interested in modeling. The study of entrepreneurial social factors contained by the theoretical background of the logic of entrepreneurial participation in the development of an agritourism business and its mix with social variables is an enrichment to the work of the entrepreneurial literature. Indeed, the proposal of a conceptual framework linking entrepreneurial social factors (social capital, functional competencies, social identity and social motivation) has made it possible to identify the most determining variables in the participation in the development of an agritourism business among the entrepreneur and to determine their possible effects by validating it empirically in an entrepreneurial framework.

Concerning the managerial contributions, this research could help entrepreneurship professionals as well as entrepreneurs in their participation in the development of their businesses in the agritourism sector. There are several recommendations that we take the liberty of proposing in this direction. Particularly, managers of rural lodges must pay attention during the development of their businesses by adopting a social approach. The social entrepreneurial factors have become a necessity for the success of businesses, which are more and more expected on the social entrepreneurial for better development and pursuit of the business.

Another managerial contribution lies in the identification of new forms of agritourism for entrepreneurs and also for tourists, which lead the approach to this type of tourism. However, this approach makes it possible to see agritourism in a new form based on a better consideration of realities. It should allow the agritourism entrepreneur to better develop their business and the activities that they offer to tourists and visitors. In addition, it must take into consideration the value of business in agritourism.

The products of the land and agriculture interest the public and can constitute a tourist resource. However, consumers are curious about locally produced foods, how they are made and the cultural elements that surround them. They love to explore them, taste them and bring them back as a souvenir. They appreciate the unique experience of being immersed in the agricultural world. It is important for them to have proof that what they are eating really comes from the place they are visiting. A study of brochures and websites shows that territories often highlight their natural (e.g., hiking sheets) and cultural sides (e.g., castles, churches), but rarely the heritage side from the agricultural area. As an example, some tourist portals offer “flavor” or “terroir” which present regional food products, or “accommodation” which relay to farm inns. Consequently, it is preferable that the entrepreneur develop his business. Similarly, this study helps the entrepreneur to integrate these agritourism offers within the territory to have a good positioning. The agritourism is to create contact between the visitor and the farmer. Consequently, this activity has the potential to renew and diversify social representations of agriculture. To ensure this consistency, which must be built as the projects develop, territorial marketing can be a path that an entrepreneur can follow. For areas keen to develop agritourism, this study shows the need of entrepreneurs for agritourism mediator training. If they want to develop agritourism, the territories can also act in the long term through vocational training. Today’s tourists are increasingly looking to go green during their holidays to escape a stressful daily life while recharging their batteries in vast natural spaces. They are also looking for authentic stays during which they have the opportunity to interact with locals and learn new things. Agritourism meets all these expectations. Rural areas thus benefit from significant economic benefits and this type of tourism increases the number of tourists visiting these areas. Therefore, this business represents a real opportunity for farmers who wish to get into agritourism or who have already embarked on the adventure. So, the entrepreneurs in the agritourism should learn more about their target to attract them especially with the development accelerated by the health crisis, which has awakened in tourists a desire to reconnect with nature.

6. Conclusions

The main objective of this research was to examine and deepen the awareness of agritourism businesses and to assess their ability as a model for an important development in rural areas. In this way, to understand the role of entrepreneurial social factors to encourage agritourism entrepreneurship. Linked to the general objective, the study has specific objectives: First, to examine what agritourism entrepreneurship is and to comprehend the connection between progress, preparation and tourism with the intention to identify the principal features of the agritourism concept. Second, to explore and examine the important role of entrepreneurship social variables on agritourism Tunisian business development. Furthermore, the main goal of this paper was to explain how different factors influence the behavior of an entrepreneur in the development of an agritourism business, and to conceptualize, test and validate a research model that explains the entrepreneurial social factors of a Tunisian entrepreneur within the framework of his participation in the development of an agritourism business. To accomplish these goals, a research model was created, and a questionnaire was established and dispersed to Tunisian entrepreneurs to understand the structure of their entrepreneurial behavior. After assessing the collected questionnaire, only 100 questionnaires were valid and utilized for the analysis part. The data were analyzed using the SPSS 26 and SmartPLS 3.0 programs, and the various statistical tests were applied focusing on the analysis of the modeling of structural equations. The results of this research showed the following most important assumptions:

• Social capital positively affects the functional skills of the entrepreneur. If social relationships connected to the network are poorly managed, they risk negatively influencing the functional skills of the entrepreneur and risk no longer providing information channels that reduce the time and effort required to collect information.
• An entrepreneur who holds an important base of social capital, and more especially a base of relational capital, tends to be socially motivated. Their behaviors and interactions with social capital and networking reveal the motivation of socialization for them to move forward in business.
• The results showed that entrepreneurs are not motivated to improve and develop businesses in agritourism. We can deduce that perhaps because of the current situation that the whole world is living in during this period of a pandemic. COVID-19 has prevented the mobility of tourists to travel and canceled their activities that reflect on the businesses of agritourist entrepreneurs [47].
• With the importance of the functional competencies that an entrepreneur must have, the latter is encouraged to participate in the development of an agritourism business whether on-farm or off-farm.
• The social capital effect on participation in the development of an agritourism business.
• Unlike social motivation, it does not contribute to mediate the relationship between social capital and participation in the development of an agritourism business.

This paper is one among the studies that can serve as a benchmark for the future activity of researchers in the field. More crucially, the results of this research can provide important information for entrepreneurs in the agricultural and tourism sector who plan to fully understand the behavior of an agritourism entrepreneur before offering an appropriate product or service to consumers. Those results can be applied by the territorial managers and the managers of the rural lodges or the managers of the agritourism sector interested to improve their strategies and policies regarding this sector. In addition, agritourism entrepreneurs can use the results of this study to develop more competitive communication strategies and provide them with an improved awareness of the major variables that could influence the behavior of their entrepreneurs to fully understand the behavior of their consumers.

7. Limitations

The researchers recognized challenges during the research period. Fortunately, these challenges did not impact the expected results of the study. The researchers concluded that there is a lack of relevant studies in the context of agritourism in Tunisia. In addition, there is a lack of organization between the various organizations concerned in this sector, entrepreneurs and the community.