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Article

Post-COVID-19 Family Micro-Business Resources and Agritourism Performance: A Two-Mediated Moderated Quantitative-Based Model with a PLS-SEM Data Analysis Method

by
Ibrahim A. Elshaer
1,2,
Ahmad M. AboAlkhair
3,4,
Sameh Fayyad
2 and
Alaa M. S. Azazz
5,6,*
1
Department of Management, College of Business Administration, King Faisal University, Al-Ahsaa 380, Saudi Arabia
2
Hotel Studies Department, Faculty of Tourism and Hotels, Suez Canal University, Ismailia 41522, Egypt
3
Quantitative Methods Department, College of Business Administration, King Faisal University, Al-Ahsaa 380, Saudi Arabia
4
Department of Applied Statistics and Insurance, Mansoura University, Mansoura 35516, Egypt
5
Department of Tourism and Hospitality, Arts College, King Faisal University, Al-Ahsaa 380, Saudi Arabia
6
Tourism Studies Department, Faculty of Tourism and Hotels, Suez Canal University, Ismailia 41522, Egypt
*
Author to whom correspondence should be addressed.
Mathematics 2023, 11(2), 359; https://doi.org/10.3390/math11020359
Submission received: 24 November 2022 / Revised: 28 December 2022 / Accepted: 6 January 2023 / Published: 10 January 2023
(This article belongs to the Special Issue From COVID-19 to Resilience: Quantitative Methods in Economics and Business)
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Versions Notes

Abstract

:
The global spread of coronavirus (COVID-19) has had a devastating impact on thousands of small businesses. Many businesspeople, especially those who own and run micro-businesses, have been hampered by the unprecedented scale of the lockdown of social activities and the restrictions placed on their freedom of movement. The reciprocity process between small rural businesses and residents is ultimately in the interest of improving agrotourism performance. Integrating the non-zero-sum games theory and the social exchange theory, this study aims to achieve the following: (1) testing the relationship between family micro-businesses resources and agritourism performance; (2) examining the impact of two mediating variables (resident–micro-business interaction and support for agritourism development); and (3) testing the intervention of one moderating variable (personal resident benefit) on the tested relationships. Dyads data was collected from 293 residents/family small businesses operators. Partial least squares-based structural equation modelling (PLS-SEM) with the SmartPLS program was employed to analyze the collected data. Family micro-business resources were found to have a positive and significant impact on agritourism performance, moreover, resident–micro-business interaction and support for agritourism development were found to partially mediate the relationship between family micro-business resources and agritourism performance, and the personal resident benefit significantly moderated the relationship between family micro-business resources and resident–micro-business interaction. Several implications for academics and policymakers were elaborated. The limitations and further study opportunities were also discussed.

1. Introduction

The perspectives of rural residents toward agritourism enterprises directly influence their behavior in engaging with agritourism enhancement and, thus, are a crucial factor that can determine the resilience ability and the success or failure of the organization [1]. Research has indicated that rural residents might participate in resistance actions that can significantly prevent rural tourism development if they believe that they are responsible for the majority of the rural core tourism attractions while having the least access to those that are useful to tourists [2,3]. They believe tourism developments that do not use local businesses will not provide clear economic benefits such as jobs and higher family incomes [2]; as agritourism’s main players, they will defend their rights and interests.
In developing countries, agritourism micro-businesses are frequently associated with family-related enterprises, such as farming or tourist-related activities on farms [4]. Family-owned agritourism small businesses often do not aim to become large entities and the owners often see themselves as emotionally attached to their communities and businesses [5]. However, micro-business success is predicated not just on the individual ventures’ success but also on the overall contributions each makes to its local community [6]. In the same vein, drawing on the social exchange theory, [7] it can be argued that “local residents are prepared to participate in an exchange with tourists if they believe that it is likely they will obtain benefits without incurring unacceptable costs”. The reciprocity process between family micro-businesses and local residents is ultimately in the interest of improving agrotourism performance.
According to the social exchange theory (SET), economic and socio-emotional resources are exchanged. Economic resources include everything of monetary value that might meet financial needs. Socio-emotional resources include supportiveness, helpfulness, and friendliness [8]. On examination, micro-businesses are frequently perceived as non-‘mainstream’, boosted by the owners’ interests rather than by commercial motivations, offering little opportunity for growth and greater value in promoting social inclusion. Hence, the economic activities of the micro-business are embedded within the broader social and economic relationships of the household [9]. Local residents’ ownership of family micro-businesses is expected to increase resident–micro-business interaction (or client interaction) due to high-quality social exchanges (i.e., economic and socio-emotional relationships) [8]. Furthermore, personal benefits play a significant role in the exchange process for residents’ favorable attitudes toward tourism [10]. Thus, maximizing the residents’ personal benefits will reflect positively on resident–micro-business interaction [11]. Overall, local residents’ involvement in tourism development strengthens their perceptions of tourism’s benefits, increasing their willingness to support agritourism development in their community [12,13].
Based on the arguments mentioned earlier, the current study uses game theory (GT) as a theoretical background to explain the intercorrelations in our study. According to Friedenberg and Keisler [14], the application of the game theory to economic behavior and alliances is extensive. The theory is instrumental in gaining insights into how market players behave and interact in certain situations [15] and provides a way of analyzing both competitor and partner behavior, as well as what is likely to happen if the rules are changed. Game theorists have suggested the notion of a non-zero-sum game (see Figure 1). This is one of the considerable critical assumptions of game theory. The idea proposes that players—i.e., in our study are (player 1) family micro-businesses and (player 2) local residents—may profit from collaboration by revealing their approach beforehand and making an “irrevocable commitment” to it [16].
Zhang et al. described this notion as “the realization of maximizing the interests of both sides, which is a harmonious development with mutual benefits” [17]. Accordingly, this study, depending on the game theory along with the social exchange theory (SET), aims to (1) test the associations between family micro-business resources (FM) and agritourism performance (AP), (2) explore the mediating role of resident–micro-business interaction (RMI) and support for agritourism development (SAD), and finally, (3) test the moderating role of personal resident benefit (PRB) on the proposed relationships.
Previous studies on agritourism were found to have focused on the social, ecological, cultural, authenticity variables [18], and agritourism marketing endeavors [19]. Still, they have not addressed the micro-business as a tool for the success of agritourism enterprises in local rural communities [20]. Furthermore, most agritourism research has been conducted in Western nations, resulting in a need for more awareness of the sector’s condition in less developed countries [21]. Consequently, this study attempts to fill this gap by (1) exploring the role of establishing family micro-businesses in improving agritourism performance and (2) conducting a field study in one of the developing countries (i.e., KSA). To the authors’ best knowledge, this study is one of the first that explores all these direct, moderating, and mediating relationships in one model and in one context using partial least squares-based structural equation modelling (PLS-SEM) as the main data analysis technique.

2. Literature Review and Development of Hypotheses

2.1. The Mediating Role of Resident–Micro-Business Interaction (RMI) and Support for Agritourism Development (SAD)

Traditional agricultural production methods are becoming less feasible, especially in developing countries, and farming residents have faced economic and social problems due to lower farming revenues. Hence, farmers have resorted to agritourism activities [22]. Agritourism promotes local economic development by revitalizing traditional industries, farming-related tourist activities, and older styles of life that react to the post-modern customers’ pursuit of authenticity [23]. Thus, it generates services and employment chances and provides additional foreign sources of income. Therefore, agritourism is increasingly regarded as a tool for enhancing the economic and social circumstances for local residents [24,25].
Agritourism operators (agritourism practices include on-farm direct sales, accommodation/lodging, leisure/special events, open-air recreation, and educational activities) are often smaller, family-owned businesses originating in the host community and frequently showcase host agricultural goods and cultural practices [26]. These micro-businesses employ 10 or fewer employees and have progressively more significant roles in local economic growth [27] by creating entrepreneurship chances for women [28], and family groups [29]. Employing the resource-based view (RBV) approach [30], family micro-business resources (FM) can be categorized as business-based resources and structural resources, where “business resources are those created and possessed by individual business owners”. While structural resources are considered externally based in nature “… that owners may benefit from or contribute to but do not possess individually”. Business-based resources—that include small business orientation, social capital, and social networking links—for family micro-businesses are critical strategic resources for competitive advantage. These resources are valuable, rare, hard to imitate, and hard to substitute [31] as they are based on culture, community environment, and family-entrepreneurship processes [32].
Family micro-businesses that operate a small business orientation are “any business that is independently owned and operated, not dominant in its field, and does not engage in any new marketing or innovative practices” [33]. The limited size of agritourism markets may be unattractive to large businesses. Thus, small family agritourism firms may be more stable and prosperous in niches with less competition [34]. Social capital as a business resource is a core resource or group of social assets that performers utilize to track their interests through the membership of social networks/structures [35], which can facilitate mutual collaboration between individuals [36]. Based on the social capital theory, family micro-businesses can benefit from social capital in sharing information, working toward joint goals with the community, and creating trust among group members [20]. On the other hand, as the third business resource, social network ties may be a precursor to forming possible social capital, yet “they are not equivalent or interchangeable terms” [37]. These social network ties are more significant to micro-businesses and those in the difficult conditions seen in rural areas [38]. Based on SET, we argue that the business-based resources of family micro-businesses (social network ties, small business orientation, and social capital) involve many economic and socio-emotional resource exchanges between micro-businesses and the community. Therefore, they are vital to boosting these micro-businesses’ success in particular, and the agritourism performance in general [39]. Thus, we can propose the below hypothesis:
Hypothesis 1 (H1). 
Family micro-business resources have a relationship with agritourism performance.
Contact in tourism occurs between tourists and hosts, other guests, service providers, and fellow tourists [40]. Positive communication between service providers and their guests or residents is the most important of these contacts and can boost friendly attitudes and good behaviors, which are essential for the success of any tourism business [41,42]. In the agritourism sector, farm owners themselves are the owners of agritourism businesses in many cases [43]. Thus, the residents feel psychological ownership of these businesses. According to the affective events theory (AET), when locals experience psychological ownership of the family micro-businesses, they support them and express their loyalty. This is because of their psychological connection with the businesses [44,45]. Given the nature of the resources on which family micro-businesses depend and which require a lot of exchanges of interests between these businesses and the residents, resident–micro-business interaction has become significant [40]. Therefore, we introduce the below hypothesis:
Hypothesis 2 (H2). 
Family micro-business resources have a relationship with resident–micro-business interaction.
The positive social contact and interactions inherent in agritourism between agritourism operators and local residents associate strongly and positively with profitability and successful agritourism endeavors [46]. In the same vein, such interactions can succeed in the mutual objectives of exchanging economic and socio-emotional resources among agritourism entrepreneurs and local communities and reinforce collaborative dual partnerships between agritourism companies [47]. Aiming to assess the contribution of resident–micro-business interaction to enhancing agritourism performance, we hypothesize that:
Hypothesis 3 (H3). 
Resident–micro-business interactions have a relationship with agritourism performance.
Local communities’ perceptions of tourism benefits affect their support for tourism development [48]. Furthermore, locals dependent on the tourist business or perceiving a more significant economic benefit have a more favorable impression of tourism’s economic influence than other residents [49]. Although economic benefits were a crucial indicator, social and emotional factors better predicted local residents’ support for tourism development [50]. Hence, we argue that resident–micro-business interaction, besides the participation of the residents in tourism development, demonstrates the economic, social, and emotional benefits of agritourism development, thus increasing societal support for agritourism and improving its performance. On this basis, the following two hypotheses were derived (as seen in Figure 2).
Hypothesis 4 (H4). 
Resident–micro-business interactions have a relationship with residents’support for agritourism development.
Hypothesis 5 (H5). 
Residents’ support for agritourism development has a relationship with agritourism performance.
Based on the non-zero-sum games theory and combining prior pieces of evidence, and drawing on the previous justifications of the proposed five hypotheses, we suggested the following hypotheses for mediation relationships:
Hypothesis 6 (H6). 
Resident–micro-business interaction mediates the association between family micro-business resources and agritourism performance.
Hypothesis 7 (H7). 
Resident–micro-business interaction and residents’ support for agritourism development mediate the relationship between family micro-business resources and agritourism performance.

2.2. The Moderating Role of Personal Resident Benefit (PRB)

The level of residents’ perception of tourism benefits shifts from a macro to a micro perspective, when treating it as a personal benefit [51]. According to the rationality theory, people’s motivation to join in some economic actions is defined by their surface appearance and formal rationality. Formal rationality focuses on financial incentives, while substantive (surface appearance) rationality concentrates on non-financial stimuli, such as morals, philosophy, and psychological dimensions [52]. As a consequence of this, when locals base their decisions regarding whether or not to support tourism on their perceptions of justice (substantive rationality), they take into consideration the personal and material rewards that might be gained from tourism (formal rationality) [53]. Thus, the host’s perception of the unique personal benefits from tourism is also essential in the context of residents’ interaction with agritourism operators [7]. Therefore, personal resident benefits significantly affect the link between family micro-business resources and resident–micro-business interaction. Thus, we developed the hypothesis:
Hypothesis 8 (H8). 
Personal resident benefit moderates the impact of family micro-business resources on resident–micro-business interaction (the association will be more robust when the personal resident benefit is high).

3. Methods

This paper aims to give answers that explain and test the impact of building family micro-businesses and the performance of agritourism through two mediating variables: resident–micro-business interaction and support for agritourism development. Moreover, the paper tested the moderating role of personal resident benefit in the tested relationships. A quantitative-based research methodology was considered to attain and accomplish the assumed aims by employing a self- structured survey to gather the dyadic data (from residents and micro-businesses). PLS-SEM was utilized as the main data analysis procedure. PLS-SEM is a proper approach for investigating and approving the early levels of theory development [54]. PLS-SEM was conducted to calculate the measurement and structural models’ validity due to its multivariate nature and predictive power with a small sample size. Furthermore, 5000 bootstraps repeats of 293 dyadic data (total of 686) samples were run to assess the significance (p) level of all path coefficients.

3.1. Scale and Measure Development

An extensive review of the related previous studies was conducted to develop the study scale and create the questionnaire items. This process yielded five significant measures that could be employed as the study scale. The FM (family microbusinesses’ business-based resources variable)—as we explained previously, business-based resources were selected for their importance in agritourism—was tested by 13 items derived from Campbell and Kubickova [20], three variables to measure small business orientation (SMO), six items for social capital (SC), and four variables for social networking ties (SNT). At the same time, agritourism performance (AP) was operationalized by the eight-item scale suggested by Domi and Belletti [55]. Five items from Reimer et al. [56] were employed to measure resident–micro-business interaction (RMI). The SAD (support for agritourism development) was measured by three items created by Wang et al. [53]. Finally, the PRB (personal resident benefit) was measured using the eight-item scale proposed by Vukovic et al. [7]. A Likert scale of 1 (strongly disagree) to 5 (strongly agree) was employed. Eight academics and eight professionals in the field area tested the instrument. The text was transcribed and clarified. The scale content was retained and employed with no changes.

3.2. Participants and Collection of the Study Data

Family micro-businesses in rural destinations in Saudi Arabia’s eastern province (Al Ahsa governance) were selected to participate in the field study. Data collection was achieved via the drop-and-collect method. The survey was split into two sequential phases. Residents were asked to answer and provide the information necessary for the PRB and SAD variables in the first phase. One month after, family micro-businesses operators and employees within the same rural area were asked to complete the FM, AP, and RMI questionnaire items. In the two phases, 400 questionnaires were disseminated. After removing all the unqualified and irrelevant questionnaires, we were left with 293 residents/family micro-businesses operators and employees whose dyads data were tested, with an effective recovery rate of 73.25%. The data was collected in September and October 2022, post COVID-19 pandemic, when the small businesses in these rural places had returned back to their normal operation. The final residents sample included 224 males (76.5%) and 69 females (23.5%). Most of them were between the ages of 26 and 45. For family micro-business operators and employees, the final family micro-business operators and employees sample comprised 246 males, accounting for 84% of the total, and 43 women (16%). Most of them were between the ages of 28 and 53, and the vast majority held university degrees (91.5%).

4. Findings of the Data Analysis

The SmartPLS-4.0 program was used to test the previously justified research hypotheses using SEM (structural equation modeling) via “Partial least squares PLS 4”. The proposed theoretical model was tested in two sequential stages [57].

4.1. Evaluation of the Outer Model (Validity Assessment)

Following the suggestions of [57,58,59], the scale validity (discriminant and convergent) and reliability were assessed through several criteria. First, for reliability, Cronbach’s alpha (α) and composite reliability (C_R) were used, as shown in Table 1. All values exceeded the threshold of 0.7, which gives a signal of a proper level of reliability.
Second, the standardized factor loading for all reflective items was higher than 0.7, further supporting the scale’s convergent validity. Furthermore, the average variance extracted (AVE) values exceeded the value of 0.50, which approves convergent validity [54]. Finally, three main indices were checked to test discriminant validity: (1) cross-loading, (2) the Fronell-Larcker index, and (3) the heterotrait-monotrait value (HTMT). As revealed in Table 2, the outer loading for the latent variables (bolded) exceeded the cross-loading with other items.
Table 3 shows bolded AVEs which are higher than the correlation coefficient between variables. Hair Jr et al. [54] suggested that the readings on the HTMT should be less than 0.90, as the rule stated. In the study, the levels of HTMT were significantly lower than this. Based on the findings, it is clear that the model structure possesses the necessary discriminant validity. As a direct consequence of this, the outputs of the outer measurement model were considered adequate to move forward with the evaluation of the structural model.

4.2. Structural Model Evaluation (Hypotheses Testing)

The model should possess adequate predictive and explanatory power before testing the path coefficient [58]. Furthermore, the multicollinearity test should show adequate results based on the VIF values not exceeding 5. The VIF values in our model ranged between 1.421 and 4.659 (<5.0), which supports the nonexistence of multicollinearity in the model. Furthermore, the lower level of R2 values is 0.10 for a good model fit [58]. Consequently, the R2 values for the study variables—AP (R2 = 0.745), RMI (R2 = 0.591), and SAD (R2 = 0.408)—are appropriate (Table 4). Likewise, the Stone–Geisser (Q2) index revealed the AP, RMI, and SAD values to be higher than zero (Table 4), suggesting the sufficient predictive validity of our model [59]. As a direct result of this, an adequate level of predictive validity was also demonstrated for the structural model.
A bootstrapping method was used to conduct the final analysis, which consisted of a path coefficient and t-value analysis of the hypothesized paths. The results of the hypothesis test are displayed below in Table 5, along with Figure 3, which includes the path coefficient values and their relevant significance. FM was found to be in positive and significant correlation with AP (β = 0.632) and RMI (β = 0.299), hence, we can accept hypothesis one (H1) and hypothesis two (H2). The results also demonstrated that RMI has a significant (p < 0.001) and positive association with AP (β = 0.150) and SAD (β = 0.639), which led us to support hypothesis three (H3) and hypothesis four (H4). Hypothesis five (H5) was supported as well due to the correlation between SAD and AP being positive and significant (β = 0.508). The mediation impact of RMI in the link between FM-AP was supported with a significant effect size of β = 0.095. Thus hypothesis six (H6) was accepted. Similarly, the sequential mediation effect of RMI and SAD in the link between FM and AP showed a significant effect size of β = 0.205, which leads us to support hypothesis (H7). Lastly, the findings supported the positive moderation impact of PRB on the link between FM and RMI at a significant path coefficient value of β = 0.287, which confirms hypothesis (H8).

5. Discussion and Implications

5.1. Family Microbusiness Resources, Agritourism Performance, Resident–Micro-Business Interaction and Support for Agritourism Development (Direct Relationship)

This study revealed a direct, significant, and positive association between FM and AP (H1). This result is consistent with the studies of Kangasharju [27] and Tamilmani [29]. Given the features of the limited agritourism market and the nature of the resources on which micro-businesses depend in rural destinations, especially business-based resources (small business orientation, social capital, and social networking links), we find that it is a favorable environment for improving agritourism performance in general and achieving profitability for agritourism operators [34,39]. This study confirms that FM is an antecedent facet in RMI practice implementation (H2). In most rural destinations, the owners of agritourism businesses themselves are farm owners in many cases [43]. Thus, the contact between rural micro-business operators and their guests or residents is rational and practical and boosts friendly attitudes and good behaviors [42].
Furthermore, our findings assist in verifying the positive effect of RMI on AP (H3). In line with this result, Li and Barbieri [46] pointed out that the positive interaction inherent in the agritourism field between agritourism operators and their guests, residents, and agritourism operators themselves correlates strongly and positively with profitability and successful agritourism efforts. It follows from the results obtained that RMI positively influences the SAD achieved (H4). In explanation of this result, the residents’ perceptions of tourism’s benefits increase due to positive resident–micro-business interactions. Thus, the greater the positive resident–micro-business interaction, the more the residents understand and perceive the benefits of tourism. Therefore, the residents’ support for tourism development in their rural destinations is increasing [49]. The final direct relationship in our study is the positive influence of SAD on AP (H5). In an agritourism business environment, business owners need the support of the local community as it is a crucial determinant of the success or failure of such businesses and ensures that they avoid any resistance from them to tourism development [1].

5.2. Results of the Moderating Effect

The empirical results supported the moderation effects of the PRB on the link between FM and RMI (H6). In other words, according to the interaction plot in Figure 4, PRB made the connection between FM and RMI strengthen. This result can be justified based on the SET and the non-zero-sum games theory. When an individual in the community realizes the personal benefit generated by the agritourism development business, he will enhance his positive interaction with them to improve personal benefit and respect for the principle of reciprocity.

5.3. The Mediating Effect of RMI and SAD in the Tested Model

One of the paper’s basic purposes was to evaluate the mediating effects of RMI and SAD on the link between FM and AP. Concerning H7, the results prove that the impact of RMI as a single mediating variable in the link between FM and AP is significant and positive. Finally, the empirical evidence obtained allows us to confirm that the sequential mediation exerted by the RMI and SAD variables indirectly influences the relationship between FM and AP (H8). Based on the SET and the non-zero-sum games theory, the significance of mediation can be justified, whether single or sequential. Given the residents’ sense of psychological ownership of family micro-businesses in rural destinations, we assert that the resident–micro-business interaction is effective and supports the development and performance of agritourism (single mediation) [45]. Regarding sequential mediation, with the positive interaction and mutual interaction between residents and family micro-businesses, the individual’s perception of the personal and societal benefits resulting from the development of tourism in rural destinations increases, and thus their support for agritourism increases, reflected in improving the agritourism performance [7,50].
By comparing the single and sequential mediations, we find that the indirect impact of the sequential mediation of RMI and SAD variables between FM and AP (β = 0.205, p < 0.000) was more significant than the single mediation effect of RMI (β = 0.095, p < 0.023) in the same relationship. In both cases, the mediation was partial. Hence, the resident–micro-business interaction must generate outcomes (economic and socio-emotional) that motivate the residents and communities to support tourism development to boost agritourism performance. This literature review offers direct theoretical and practical implications. Concerning the theoretical implications, this examination promotes the comprehension of the micro-businesses economy and adds a unique role to this economy in rural destinations by exploiting family micro-businesses’ features and benefits to support local rural communities via developing agritourism. Regarding the practical implications, this article provides a valuable synthesis of micro-businesses’ economic role and family micro-businesses’ local community exchange connections that should be beneficial to both. Supporting this type of micro-business makes it feasible to build local economies to protect farmers from economic and social problems caused by lower farming revenues from unfeasible traditional agricultural production methods, especially in developing countries.

6. Conclusions and Avenues for Further Research

Rural local hosts may resist rural tourism development if they believe they are responsible for most of the key attractions but have the least access to those helpful to tourists. Dyadic data were gathered targeting 400 residents—owners and employees in family micro-businesses. A total of 293 valid responses were prepared for further analysis with PLS-SEM. After ensuring that the study scale possesses adequate convergent and discriminant validity, the proposed hypotheses were tested. The results supported the direct association between family micro-business resources (small business orientation, social capital, and social network ties) and agritourism performance. Additionally, the results highlighted the critical mediating roles of resident–micro-business interaction and support for agritourism development in improving the tested direct relationships. Furthermore, the PLS-SEM result supported the moderating role of personal resident benefit in strengthening the tested interrelationships. These results are consistent with different previous study results, but the main contribution of our study is that it tested all of these relationships (direct, mediating, and moderating), for the first time, in one model employing a sophisticated data analysis technique (PLS-SEM), in one context (family micro-businesses in KSA), post COVID-19 pandemic. Future studies could employ a qualitative research design to improve and extend our understanding of how to enhance agritourism performance. Moreover, in future studies, other mediating dimensions (i.e., tourist satisfaction, resident satisfaction) can be explored to decide whether they can act as mediators in the relationship between FM and AP. In conclusion, it should be noted that this research was only conducted using a cross-sectional research strategy, and the results do not allow for the inference of a causal relationship. It would be beneficial to undertake longitudinal research in order to support or disprove the outcomes of the study.

Author Contributions

Methodology, S.F. and A.M.S.A.; Software, A.M.A.; Writing—original draft, I.A.E.; Writing—review & editing, I.A.E., S.F. and A.M.S.A.; Supervision, I.A.E.; Funding acquisition, I.A.E. and A.M.S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Grant No. 2012).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the deanship of the scientific research ethical committee, King Faisal University (project number: GRANT2012, date of approval: 1 August 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is available upon request from researchers who meet the eligibility criteria. Kindly contact the first author privately by e-mail.

Acknowledgments

We thank for the support by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia (Grant No. 2012).

Conflicts of Interest

The authors declare no conflict of interest.

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Mathematics 11 00359 g001 550
Figure 1. Non-zero game theory.
Figure 1. Non-zero game theory.
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Figure 2. The proposed conceptual framework and hypotheses. FM: family micro-business resources, AP: agritourism performance, RMI: resident–micro-business interaction, SAD: support for agritourism development, PRB: personal resident benefit, SBO: small business orientation, SC: social capital, SNY: social network ties.
Figure 2. The proposed conceptual framework and hypotheses. FM: family micro-business resources, AP: agritourism performance, RMI: resident–micro-business interaction, SAD: support for agritourism development, PRB: personal resident benefit, SBO: small business orientation, SC: social capital, SNY: social network ties.
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Figure 3. The tested structural and measurement model. FM: family micro-business resources, AP: agritourism performance, RMI: resident–micro-business interaction, SAD: support for agritourism development, PRB: personal resident benefit, SBO: small business orientation, SC: social capital, SNT: social network ties.
Figure 3. The tested structural and measurement model. FM: family micro-business resources, AP: agritourism performance, RMI: resident–micro-business interaction, SAD: support for agritourism development, PRB: personal resident benefit, SBO: small business orientation, SC: social capital, SNT: social network ties.
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Figure 4. Interaction plot for the PRB moderation effect on FM towards RMI.
Figure 4. Interaction plot for the PRB moderation effect on FM towards RMI.
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Table
Table 1. Assessment of the outer model validity.
Table 1. Assessment of the outer model validity.
AbbreviationItemsLoadingαC_RAVEVIF
FM 0.9480.9540.617
SBO 0.9000.9380.834
SBO_1I established this business/farm because it fit my personal life better than working for others.0.931 4.659
SBO_2I love my business/farm.0.907 2.543
SBO_3I have plans to expand this business/farm in size/sales revenue.0.901 3.116
SC 0.8970.9210.661
SC_1Others would say I am trustworthy.0.766 3.940
SC_2I can be trusted by others not to take advantage of them.0.820 3.472
SC_3Others are generally fair in dealing with me.0.839 4.185
SC_4Others visit my business because I support the community.0.826 2.927
SC_5Others share the same ambitions and visions for our community.0.785 2.542
SC_6Others like to work toward achieving community goals.0.841 3.012
SNT 0.8630.9080.713
SNT_1We in the community know each other by name.0.894 3.380
SNT_2We in the community talk to each other regularly about business/farming issues.0.874 3.064
SNT_3I am similar to these people in terms of my business/community/farm philosophy.0.884 2.506
SNT_4I am similar to these people in terms of my values and beliefs.0.712 3.360
AP 0.9390.9490.701
AP_1Through agritourism we have achieved revenue targets.0.827 3.058
AP_2Through the farm we have achieved profit goals.0.796 2.504
AP_3Through the farm we have achieved a good stabilisation of income.0.847 3.302
AP_4Through the farm we have generated out-of-season income.0.859 3.641
AP_5Through the farm we have made better use of the company’s human resources.0.867 3.934
AP_6We have improved the way in which products are sold.0.815 3.472
AP_7We have improved the loyalty of existing customers.0.843 4.055
AP_8We have attracted a significant number of new customers.0.843 3.448
RMI 0.9260.9440.773
RMI_1How often did you experience being supported in contact with local residents?0.858 1.421
RMI_2How often did you experience being helped in contact with local residents?0.865 2.811
RMI_3How often did you experience being complimented in contact with local residents?0.892 3.642
RMI_4How often did you experience being befriended in contact with local residents?0.907 3.986
RMI_5How often did you experience being welcomed in contact with local residents?0.873 3.164
SAD 0.9000.9380.834
SAD_1I welcome tourists to visit our village.0.917 3.166
SAD_2I intend to support rural tourism development.0.941 4.005
SAD_3I intend to support the local government’s tourism decisions.0.880 2.362
PRB 0.9600.9650.777
PRB_1My understanding of other cultures has increased.0.826 2.945
PRB_2The quality of my personal life has improved.0.859 3.397
PRB_3My property value has increased.0.884 3.910
PRB_4I got in touch with others and expanded my business.0.889 3.920
PRB_5My children will stay in the countryside to work.0.915 4.080
PRB_6I care more about my community’s cultural resources.0.897 4.172
PRB_7I care more about my community’s natural resources.0.899 3.765
PRB_8I feel my community is better place to live.0.880 3.711
SBO (small business orientation), SC (social capital), and SNT (social networking) are the components of family micro-business resources.
Table
Table 2. Cross-loading output.
Table 2. Cross-loading output.
SBOSCSNTRMISADAPPRB
SBO_10.9310.7450.7260.6590.5790.700−0.337
SBO_20.9070.6950.6290.5390.5090.701−0.346
SBO_30.9010.7710.6560.5950.5000.545−0.265
SC_10.6750.7660.5680.5630.4140.480−0.252
SC_20.7500.8200.6420.5870.4560.559−0.266
SC_30.6290.8390.5980.4770.5240.536−0.223
SC_40.6410.8260.6950.5520.5860.585−0.264
SC_50.5510.7850.6270.4770.5150.532−0.305
SC_60.6880.8410.7630.5980.6540.666−0.341
SNT_10.6500.7140.8940.6790.5280.572−0.245
SNT_20.6670.6730.8740.6100.5750.544−0.257
SNT_30.6020.6990.8840.7280.6750.707−0.302
SNT_40.5590.6130.7120.4600.5700.646−0.237
RMI_10.6790.6730.7030.8580.5770.644−0.222
RMI_20.5830.5820.6230.8650.5760.634−0.234
RMI_30.4990.5660.6580.8920.5910.636−0.174
RMI_40.5480.5600.6470.9070.5670.581−0.177
RMI_50.5640.5460.6070.8730.4860.555−0.048
SAD_10.5580.6260.6570.6270.9170.776−0.270
SAD_20.5500.5810.6240.5450.9410.749−0.406
SAD_30.4780.5650.6170.5730.8800.696−0.356
AP_10.6660.6770.6340.5570.7140.827−0.306
AP_20.6200.5280.6270.5170.6060.796−0.271
AP_30.5690.5890.6680.7220.6990.847−0.259
AP_40.6110.5960.6900.6700.7320.859−0.354
AP_50.6010.5560.5670.6570.7000.867−0.354
AP_60.5340.4670.5120.5190.6360.815−0.323
AP_70.5360.5460.5370.4530.6430.843−0.288
AP_80.6070.6460.6200.5360.6920.843−0.266
PRB_1−0.270−0.219−0.207−0.098−0.232−0.3000.826
PRB_2−0.263−0.245−0.189−0.121−0.292−0.2410.859
PRB_3−0.325−0.300−0.236−0.160−0.293−0.2970.884
PRB_4−0.262−0.242−0.234−0.143−0.317−0.2950.889
PRB_5−0.354−0.409−0.399−0.243−0.413−0.3980.915
PRB_6−0.301−0.278−0.273−0.155−0.334−0.3250.897
PRB_7−0.327−0.332−0.308−0.236−0.369−0.3480.899
PRB_8−0.285−0.248−0.194−0.128−0.290−0.2690.880
Table
Table 3. AVE values and HTMT results.
Table 3. AVE values and HTMT results.
AVE ValuesHTMT
FMAPRMIPRBSADFMAPRMIPRBSAD
FM0.786
AP0.7630.837 0.805
RMI0.7410.6960.879 0.7850.738
PRB−0.358−0.362−0.1980.881 0.3570.3690.194
SAD0.6950.8120.639−0.3750.9130.7510.8790.6960.390
Table
Table 4. Model goodness-of-fit R2 and Q2 values.
Table 4. Model goodness-of-fit R2 and Q2 values.
Endogenous Variables(R2)(Q2)
AP0.7450.485
RMI0.5910.420
SAD0.4080.320
Table
Table 5. The structural inner model findings.
Table 5. The structural inner model findings.
HypothesesBeta
(β)		(T-Value)p ValuesResults of
Hypotheses
H1FM → AP0.2993.5180.000Supported
H2FM → RMI0.63211.5680.000Supported
H3RMI → AP0.1502.5360.012Supported
H4RMI → SAD0.63915.0750.000Supported
H5SAD → AP0.5086.9060.000Supported
H6FM → RMI →AP0.0952.2850.023Supported
H7FM → RMI → SAD → AP0.2055.6250.000Supported
H8Moderating imapct 1(FM × PRB) → RMI0.2873.2900.001Supported
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Elshaer, I.A.; AboAlkhair, A.M.; Fayyad, S.; Azazz, A.M.S. Post-COVID-19 Family Micro-Business Resources and Agritourism Performance: A Two-Mediated Moderated Quantitative-Based Model with a PLS-SEM Data Analysis Method. Mathematics 2023, 11, 359. https://doi.org/10.3390/math11020359

AMA Style

Elshaer IA, AboAlkhair AM, Fayyad S, Azazz AMS. Post-COVID-19 Family Micro-Business Resources and Agritourism Performance: A Two-Mediated Moderated Quantitative-Based Model with a PLS-SEM Data Analysis Method. Mathematics. 2023; 11(2):359. https://doi.org/10.3390/math11020359

Chicago/Turabian Style

Elshaer, Ibrahim A., Ahmad M. AboAlkhair, Sameh Fayyad, and Alaa M. S. Azazz. 2023. "Post-COVID-19 Family Micro-Business Resources and Agritourism Performance: A Two-Mediated Moderated Quantitative-Based Model with a PLS-SEM Data Analysis Method" Mathematics 11, no. 2: 359. https://doi.org/10.3390/math11020359

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