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Abstract

Given the urgent need to investigate factors that influence small agricultural businesses, sustainability is one of the most worldwide priorities in rural areas. This study explores the essential factors influencing small agricultural businesses’ sustainability within this context. The small agricultural businesses’ sustainability factors were identified by doing 41 interviews with small farmers that were analyzed through the Cross-Impact Matrix Multiplication Applied to Classification software (MICMAC) method, which is used to examine the strength of the relationship between small agricultural businesses’ sustainability and significant factors based on their influence and dependence power. We found approximately 44 sustainability factors of small agricultural businesses; the most common are 29 factors/concepts besides sustainability. We employed the collective cross-impact matrix to find the independent, relay, and excluded factors for a more in-depth analysis of the most influential factors. Then, we found that 17 were independent, nine were relay, and three were excluded. The results showed that the very important of these factors, which have strong effects on small agricultural businesses’ sustainability, is determining a percentage of profits for continuous development and improvement, determining crops compatible with the type of farm soil and water, financial transactions documentation, capacity to use loans for expanding the farm, percentage of cultivated land out of farm space, periodic analysis of soil and water, Property ownership, activating the role of associations in providing services, keeping up with renewable and alternative energy innovations, keeping up with government laws and regulations of the agricultural sector, and agricultural associations services for farmers.

Keywords

small agricultural businesses sustainability internal factors external factors cognitive mapping

Introduction

Agricultural economists stress the importance of the agricultural sector as one of the main drivers of economic development. Within numerous developing nations, agriculture not only stands as the largest sector within the economy but also employs the highest number of individuals. Given the substantial size of the agricultural sector, it serves multiple critical purposes: driving economic growth, generating employment opportunities, reducing poverty rates, and enhancing food and nutrition security (Christiaensen, 2019; Christiaensen et al., 2011; Dorward et al., 2004). Over the years, the agricultural sector has experienced remarkable transformations driven by dynamic market dynamics, evolving consumer preferences, and intensified global competition. These changes have presented unique challenges for small agricultural businesses, which frequently operate under resource constraints and face barriers in accessing vital elements such as capital, technology, and markets (Zhang & Diao, 2020). Changing market dynamics, for instance, have significantly impacted small agricultural businesses, introducing new demands for product innovation, quality standards, and marketing strategies to maintain competitiveness. In particular, the rising emphasis on sustainability has reshaped market preferences, requiring businesses to align their practices with the increasing demand for organic, locally sourced, and environmentally friendly products. For small agricultural businesses, adapting to these shifts often necessitates adopting sustainable farming methods and innovative practices, which can impose additional financial and operational pressures (Wang et al., 2022). Limited financial resources further exacerbate these challenges, as many small-scale agricultural enterprises struggle to secure loans due to their perceived riskiness and lack of comprehensive financial records, restricting their ability to invest in modern equipment, infrastructure upgrades, and research and development (Dias et al., 2021; Fan & Rue, 2020). According to Ölkers and Mußhoff (2024), access to formal credit is a critical factor influencing the development of the agricultural sector in developing countries, particularly as many farmers face significant liquidity constraints.

As part of its Vision 2030 plan, the Saudi government has prioritized the establishment of a sustainable and self-sufficient agricultural sector to reduce food import dependency and create new economic opportunities (Al Naimi, 2022). This vision aligns with global Sustainable Development Goals (SDGs), particularly SDG 8, which emphasizes promoting decent work and economic growth. The Saudi Ministry of Environment, Water, and Agriculture (SMEWA) has introduced several initiatives to support agricultural enterprises and ensure the sector’s alignment with national sustainability goals. The agricultural sector’s significance in the Kingdom is underscored by its substantial contribution to the national economy. For instance, in the 43rd session of the UN Food and Agriculture Organization (FAO) General Conference, the deputy minister of SMEWA reported that Saudi Arabia’s agricultural GDP increased by more than 38% in 2022, reaching 100 billion SAR compared to 72.25 billion SAR in 2021. These achievements highlight the potential of agriculture to contribute to Saudi Arabia’s economic diversification efforts. However, despite this progress, the challenges of ensuring the sustainability and continuity of small agricultural businesses remain underexplored, particularly in the context of developing economies such as Saudi Arabia.

Existing studies have extensively examined the objectives and motivations driving farmers’ agricultural activities (Alvarez & Busenitz, 2001; Windle & Rolfe, 2005). However, research on the continuity of agricultural businesses, particularly at the small business level, remains limited. Most studies on business continuity focus on the performance and sustainability of urban industrial and commercial enterprises. From a management perspective, such research typically emphasizes factors such as market orientation, entrepreneurial orientation, and corporate strategies as key determinants of business performance (Boso et al., 2013; Kajalo & Lindblom, 2015; Mathafena & Msimango-Galawe, 2023). Economic studies, on the other hand, highlight enterprise-level determinants, including human resource management, ownership structures, innovation behavior, financing methods, and external policy and environmental influences such as foreign direct investment (FDI) and property rights protection (Buck et al., 2003; Ferragina & Mazzotta, 2014; Ugur & Vivarelli, 2021; Zhang et al., 2017). While these insights are valuable, they often fail to capture the specific dynamics of agribusiness, particularly in rural or developing regions, where agricultural enterprises face distinct challenges that differ from those of urban businesses.

Agribusinesses operate under a unique set of circumstances that distinguish them from other forms of entrepreneurship. As Pindado and Sánchez (2017) argue, agricultural entrepreneurship requires understanding the particular constraints and opportunities within the sector. These include fluctuating market conditions, seasonal production cycles, and the growing demand for sustainable practices in the face of global environmental challenges. Moreover, agribusinesses must contend with rapid shifts in consumer behavior, food safety regulations, and sustainability standards (Steenis et al., 2017). For instance, consumer demand for organic and environmentally friendly products presents opportunities for differentiation but also imposes costs related to certification, compliance, and production adjustments. Additionally, agricultural businesses in developing countries often face barriers such as inadequate infrastructure, limited access to technology, and weak institutional support, which exacerbate their vulnerability to market and environmental shocks. Consequently, there is a pressing need for research that specifically addresses the continuity and sustainability of agribusinesses. This paper seeks to bridge these gaps by focusing on the sustainability and continuity of small agricultural businesses in Saudi Arabia. By doing so, it contributes to a growing body of literature on agribusiness sustainability while providing insights that are directly applicable to the unique context of Saudi Arabia’s agricultural sector. The study examines internal and external factors influencing the sustainability of small agricultural businesses, employing a novel methodological approach to provide a comprehensive understanding of these dynamics. Internal factors explored include the characteristics of farm owners, such as education, experience, and management practices, as well as business-specific factors, such as operational strategies and resource utilization. External factors include regulatory frameworks, market conditions, and socio-cultural influences that shape the broader operating environment for small agricultural enterprises. By integrating these dimensions, the research offers a holistic perspective on the determinants of agribusiness sustainability in Saudi Arabia.

This study makes several key contributions to small agricultural business sustainability literature. First, it provides a unique methodological contribution by employing the MICMAC (Cross-Impact Matrix Multiplication Applied to Classification) analysis to systematically classify and understand the influence and dependence of sustainability factors, offering a novel approach to structural analysis in agribusiness research. Second, it enriches the empirical literature by identifying 29 critical sustainability factors, including internal, external, and personal dimensions, tailored to the specific context of Saudi Arabia, which has been underexplored in prior studies. Third, the study bridges gaps in the existing literature by highlighting actionable insights for policymakers and practitioners, including strategies to enhance resource management, financial planning, and adopting sustainable technologies. In terms of results, by classifying factors into internal, external, and personal dimensions, the research provides a comprehensive framework for understanding the multifaceted nature of agribusiness sustainability, which can be adapted for use in other contexts or future studies. These contributions advance theoretical understanding and provide practical tools and policy guidance to support the sustainability of small agricultural businesses in comparable regions.

The rest of the paper is structured as follows: The next section reviews the existing literature on the sustainability of small agricultural businesses, focusing on the internal and external factors influencing their performance. This is followed by a detailed description of the methodological framework, including data collection and analysis techniques. The subsequent sections present the study’s findings and discuss their implications for agribusiness practice and policy. The final section summarizes the key results and offers practical and policy recommendations.

Literature Review

A combination of internal and external factors can influence the sustainability of small agricultural businesses. Internal factors are those within the control of the business owner or management, while external factors are those outside of their direct control. Internal factors include human resources management, marketing skills, financial management, lack of capital, strategy, personal characteristics, information technologies, and business plan, whereas external factors include market conditions, government policies and regulations, climate and weather patterns, access to resources, infrastructure and transportation, technological advancements, and socioeconomic factors (Darroch & Clover, 2005; Hove & Tarisai, 2013; Key, 2022; Lekhanya & Mason, 2014; Plana-Farran & Gallizo, 2021; Pliakoura et al., 2023; Stokes & Wilson, 2010).

Regarding the internal factors, Olawale Olufunso and Garwe (2010) argue that the lack of capital impedes the ability of agribusinesses to invest in essential resources, such as seeds, machinery, and sustainable farming practices. This shortage restricts productivity and hinders resilience against market fluctuations and climate variability. Stokes and Wilson (2010) corroborate this by emphasizing that agribusiness’s financial challenges often stem from inadequate capitalization and poor financial management. For small agribusinesses, this issue is compounded by seasonal cash flows and the perishable nature of agricultural products, which require strategic planning to optimize production and processing cycles. Strategic planning is also critical for agribusinesses due to the inherent life-cycle characteristics of agricultural products. Hove and Tarisai (2013) highlighted that successful agribusinesses implement thorough production, processing, and marketing plans tailored to the dynamics of agricultural markets. In the same direction, Hove and Tarisai (2013) conducted a study investigating the factors contributing to the successful growth and survival of small and micro agribusiness firms. Their research identified several key internal factors that significantly influence these enterprises’ growth and survival, including an effective marketing strategy, a well-developed business plan, a clear mission and vision, a thorough SWOT analysis, and adequate financial resources. According to Nieman and Nieuwenhuizen (2009), a business plan is a written presentation that explains a business, including its management team, products or services, and goals. It is a crucial component of formal planning within a company and serves multiple functions. The business plan acts as a living document, helping to reduce the risk of venture failure, serving as a benchmark for assessing internal performance, and functioning as a tool for accessing funds, such as loans or investments. Bidzakin (2009) also underscored that all businesses engage in strategic activities regardless of whether they explicitly acknowledge it. This principle applies to small agriculture businesses, which must make strategic decisions concerning crucial aspects such as operating hours and location. The success of these businesses primarily relies on the choices made by their owners, who play a pivotal role in identifying opportunities, devising strategies, mobilizing resources, and taking proactive measures (Bidzakin, 2009). Personal characteristics of owners and managers also play a pivotal role in agribusiness success. Attributes, such as education level, prior experience, and entrepreneurial orientation directly influence decision-making and resource allocation. Bidzakin (2009) and Westbrooke and Nuthall (2017) demonstrate that higher levels of education and prior professional experience correlate positively with business survival rates in agribusiness. Saghaian et al. extend this perspective by showing that entrepreneurial traits like risk-taking behavior and adaptive decision-making are particularly crucial in agribusiness contexts, where market and environmental uncertainties are prevalent. Moreover, green entrepreneurial orientation has also emerged as a significant determinant of agribusiness sustainability. Guo et al. emphasize the role of green innovations in enhancing performance and sustainability. Their findings suggest that integrating green management practices, product development, and operational processes enables agribusinesses to align with sustainability goals while maintaining competitiveness. These insights are particularly relevant for addressing the dual challenges of economic viability and environmental stewardship.

On the other hand, external factors, while outside the control of agribusinesses, have an equally profound impact on their sustainability. Government policies play a foundational role by establishing the regulatory and economic framework within which agribusinesses operate. Muhammad et al. (2015) and Rantšo (2016) emphasized the importance of direct government support mechanisms, including subsidies, technical assistance programs, and investments in rural infrastructure. Subsidies can reduce production costs, technical assistance can enhance farmers’ skills and access to innovation, and infrastructure investments can improve market connectivity and access to essential resources. These support systems are critical for small agribusinesses that often lack the capacity to independently overcome external challenges. In Saudi Arabia, Li et al. (2023) provided a detailed analysis of how government policies have historically shaped agribusiness practices. The shift from wheat production to fodder crops under sustainability-driven policies demonstrates the impact of policy priorities on resource allocation and production strategies. Such measures, aligned with Vision 2030, also reflect a broader commitment to addressing environmental challenges, such as water scarcity, while maintaining economic productivity. These policy shifts not only influence the types of crops grown but also push for the adoption of sustainable technologies and practices, driving innovation across the sector. Infrastructure and technological advancements further act as enablers of agribusiness development, bridging gaps in efficiency and productivity. For example, Jabbari et al. (2024) highlighted the transformative potential of smart irrigation systems in addressing water scarcity challenges, a critical issue in arid regions like Saudi Arabia. These systems enhance water-use efficiency, reduce operational costs, and enable precise irrigation tailored to crop needs. However, the widespread adoption of such technologies depends on the availability of supporting infrastructure and favorable policy environments. Investment in rural electrification, telecommunications for IoT connectivity, and access to affordable technology are essential to unlocking the potential of these innovations for small and medium-sized agribusinesses. By addressing these external factors, governments, and policymakers can create an enabling environment that fosters resilience and growth in the agribusiness sector. This requires a holistic approach that combines regulatory reforms, strategic investments, and support for technological adoption. Such efforts are essential for ensuring that agribusinesses, particularly small and medium-sized enterprises, can thrive in increasingly complex and competitive agricultural markets.

While studies emphasize the importance of internal factors like financial management, strategic planning, and entrepreneurial orientation, the interplay between these factors and external determinants, such as policy frameworks, market access, and infrastructure development, remains underexplored. Furthermore, there is limited research incorporating local contexts relevant to regions like Saudi Arabia, where unique environmental, economic, and socio-cultural conditions prevail. Additionally, the use of innovative methodologies to analyze the interdependence of sustainability factors, such as MICMAC analysis, has been underutilized. This gap underscores the need for context-specific studies that integrate comprehensive methodologies to address the multifaceted challenges and opportunities in sustaining small agricultural businesses. This study contributes to filling these gaps by providing an in-depth exploration of both internal and external factors within the Saudi agricultural sector, employing advanced structural analysis to uncover critical drivers and their interconnections.

Research Method and Data

Structural Analysis Approach

The structural analysis method is a tool that is used to structure ideas and systematic reflections of a specific phenomenon by using the Cross-Impact Matrix Multiplication Applied to Classification Software (MICMAC) which is a structural analysis software (Godet, 2001). MICMAC is utilized to structure respondents’ ideas and as a forecasting method of their opinion of the phenomenon under exploration. This software is considered a dynamics approach of the qualitative system (Mirakyan & De Guio, 2015). It helps describe a system by a structural analysis matrix for its concepts/factors’ relations that probably help reveal the essential concepts/factors of the system’s evolution. This software is built to determine the independent and dependent concepts/factors with a consideration of the direct and indirect relation (Godet & Durance, 1997).

The structural analysis approach was implemented through the following three stages Godet (2001): (i) identification and definition of concepts: which is used to identify all concepts that structure the cognitive universe of the phenomenon’s community, and it is the least formal and most crucial to do the next stages; (ii) description of relations between concepts or factors (N) that are identified in stage 1 in a matrix. This step consists of reconstituting and describing the network of relations between factors in the cells of the cross-impact matrix, and the number of cells is calculated by this equation: N × (N − 1). These cells show the direct connection between each concept or factor with others (i and j) in the system of the phenomenon under study in terms of influence degree (columns) by using the next scale (0) no influence, (1) weak influence, (2) medium influence, and (3) strong influence (Table 1) that rated individually by a sample of small farmers which helps in organizing and classifying their responses in a collective cross matrix. Figure 1 shows concepts or factors to be redefined, making analysis of this system more accurate. Figure 1 shows the structural diagram of Table 1; (iii) identification of the main factors: This step consists of identifying the main factors (Table 4) based on their sum of rows which indicates the influence of each one on other factors of the studied phenomenon (Equation 1), and their sum of rows which indicates to which the degree of each factor dependency of this phenomenon on others factors (Equation 2) that calculated by the MIC-MAC program which commonly used in prospective studies.

$D I_{j} = \sum_{j = 1}^{n} V_{ij} i and j = 1, 2, 3 \dots, n$ (1)

$D D_{i} = \sum_{i = 1}^{n} V_{ij} i and j = 1, 2, 3 \dots, n$ (2)

Table 1.

Cross-Impact Matrix.

		The dependency among factors
		V1	V2	V3	V4
The direct influence among factors	V1	0	1	2	3
	V2	1	0	3	0
	V3	1	2	0	1
	V4	3	2	0	0

	V1	V2	V3	V4	Total
Total influence (In rows)	6	4	4	5	19
Total dependency (In columns)	5	5	5	4	19

Figure 1.

Structural diagram of the cross-impact matrix.

The results of this process come in the form of a graph, a matrix, or a mathematical calculation subset. At the end of the structural analysis of the phenomenon under study, the cognitive map is ready to be conducted.

Constructing Steps of the Collective Cognitive Map

The cognitive map, whether collective or individual, has two main elements: concepts and links. A collective cognitive map is constructed by aggregating individual cognitive maps (Foley, 2010), an average of individual maps representing individual experiences. Concepts are the phenomenon’s factors, and the links represent the influence and dependency volume between them, which concept can be influenced by other concepts, depending on their degree of importance in the phenomenon under study; the relative importance of each of these concepts is determined based on the number of factors which it is linked with whether directly or indirectly, either as an influencing factor or as an influenced factor. Recall that the primary goal of this study is to highlight and analyze the representations of a sample of small farmers on factors that might be linked to small farms’ sustainability. To achieve this goal, we follow an approach that contains three stages to build a collective (average) map using the MIC-MAC software (Table 2). This approach is based on the alternation between two design stages: individual and collective. This approach would allow us to draw an average cognitive map using Mic-Mac to analyze and identify the factors that affect small farms’ sustainability in the Saudi context (specifically, the Qassim region).

Table 2.

Collective Cognitive Map Construction Process (Average).

First stepIdentification of concepts	A- The researcher collects data through a semi-structured interview about the individual perceptions of the interviewees about the sustainability phenomenon of small agricultural businesses.B- By the end of the interviews, the researcher identifies concepts, ideas, or examples that are related to this phenomenon.C- The researcher creates a list of concepts or factors which will be used in the second step.
Second stepMarking the value of the link between concepts	A- The interviewees asked about the influence degree between each pair of concepts based on a 4-level scale (0: no impact; 1: low impact; 2: medium impact; and 3: high impact) in the cross-impact matrix, where the rows and columns of this matrix have the same names and the number of these concepts.
Third stepConstruction of the collective cognitive map	A- The researcher builds a collective matrix to find all the common concepts of the respondents and an aggregated causal intensity. The arithmetic mean might be one of the most suitable techniques for aggregating individual maps (Ford & Hegarty, 1984).B- The researcher constructs the collective matrix using the MIC-MAC program.

Data

Many researchers who used the cognitive map method stated that there are many methods to collect data of any phenomena’s concepts and links that are essential constructions of causal maps, whether collective or individual maps; and most of them who used this method used interviews as collecting data method (Goodhew et al., 2005). In this study, we used a semi-structured interview method for constructing the cognitive maps with indirect questions style about farms’ sustainability in general because asking individuals about their success or failure, they usually attribute their success to internal factors and failures to external factors (Okolo et al., 2018); As mentioned by Pinfold (2001), business owners are aware of the factors of failure, but they think that these factors apply to others and not themselves.

In this study, the interview questions were open-ended without including words related to success and failure in sustaining farms. The questions were indirect to let interviewees answer without being guided or affected by the interviewer: Q1: Based on your experience, enumerate factors that support small farms’ sustainability; Q2: Based on your experience, enumerate factors that hinder small farms’ sustainability. In the data analysis process of 41 interviews, approximately 44 concepts were identified. We chose a list of 29 concepts/factors that are the most common among respondents and that may affect small agricultural businesses’ sustainability. Individual cross-impact matrices assessed these concepts and then aggregated into a collective (average) cross-impact matrix (Table 3) that was analyzed by MICMAC software, which has analytical capacity and is commonly used in prospective studies (Chatterjee & Dhaigude, 2020; Godet, 2001). Additionally, it enables us to classify these concepts/factors according to their sensitivity (dependency factors) and influence (independent factors; see Figure 2) by their influence and dependency rates according to the collected data that configure the cognitive universe of small farmers about farm sustainability.

Table 3.

The Collective Cross-Impact Matrix: Identification of Relationships Between Concepts.

	ICF1	ICF2	ICF3	ICF4	ICF5	ICF6	ICF7	ICF8	ICF9	ICF10	ICF11	ICF12	ICF13	ICF14	ICF15	ICF16	ICF17	ICF18	ICF19	ICF20	ICF21	ICF22	ICF23	ICF24	ICF25	ICF26	ICF27	ICF28	ICF29	DEPF
ICF1	0	0	3	1	2	2	1	2	2	2	3	1	1	1	3	3	2	0	2	1	1	2	1	1	1	1	3	3	0	3
ICF2	2	0	3	2	2	2	0	0	2	3	2	0	2	1	1	3	1	1	0	2	3	1	1	2	0	1	1	1	1	2
ICF3	2	0	0	1	2	1	2	2	3	3	3	2	1	2	3	3	2	2	2	2	0	1	2	2	3	2	3	2	2	3
ICF4	2	0	3	0	2	1	2	1	2	2	2	0	1	0	2	3	0	0	0	0	1	0	1	1	1	0	2	2	0	1
ICF5	3	0	3	0	0	2	2	1	3	3	1	2	1	0	2	2	1	0	1	1	1	2	2	0	2	0	2	2	3	3
ICF6	3	1	3	2	0	0	2	1	2	1	3	0	1	1	2	3	1	2	0	0	0	0	1	2	0	1	3	3	1	3
ICF7	3	0	3	2	1	0	0	2	2	3	2	2	2	2	3	0	1	0	1	1	0	1	2	1	0	2	2	2	3	2
ICF8	3	0	3	2	0	2	2	0	1	2	3	0	2	2	1	3	0	0	2	0	1	1	1	2	0	0	2	3	0	3
ICF9	2	0	2	1	1	1	2	1	0	3	1	1	1	1	2	3	0	0	1	2	0	2	1	1	0	1	3	3	2	3
ICF10	2	1	2	2	1	1	1	2	3	0	2	2	3	2	2	3	0	1	0	1	1	1	2	1	1	1	2	2	0	2
ICF11	3	0	2	1	0	2	1	2	1	3	0	1	2	2	2	3	1	2	2	1	1	1	1	2	1	2	3	3	1	3
ICF12	1	0	2	1	1	1	1	1	3	3	2	0	0	2	1	3	1	0	1	1	2	2	1	0	0	2	2	2	3	3
ICF13	3	0	3	1	2	1	1	1	3	3	0	1	0	2	2	3	0	1	2	0	0	2	2	1	0	0	3	1	1	3
ICF14	3	1	2	1	0	1	2	2	2	3	2	2	1	0	1	3	0	0	1	1	1	2	2	2	0	1	2	3	1	2
ICF15	3	0	2	1	1	2	1	1	3	3	3	1	1	1	0	3	1	1	1	2	1	1	2	3	0	1	2	2	2	3
ICF16	3	0	2	1	2	1	2	2	3	3	2	1	2	2	2	0	1	1	2	0	1	1	2	1	0	1	3	3	2	2
ICF17	3	1	3	0	1	1	1	1	2	3	3	2	0	0	1	1	0	2	2	2	0	1	0	0	2	3	3	3	0	3
ICF18	1	0	3	2	1	2	2	0	2	3	3	1	1	0	1	3	2	0	1	0	1	2	0	1	2	1	2	2	1	3
ICF19	3	0	3	2	0	2	1	1	3	3	2	2	1	1	2	3	1	2	0	1	1	1	1	2	0	1	3	3	3	2
ICF20	3	0	3	1	1	1	2	1	3	3	3	2	2	2	3	3	2	0	2	0	3	2	2	2	0	3	3	3	1	3
ICF21	1	3	2	1	1	2	1	0	1	3	1	0	1	1	1	3	0	0	1	0	0	1	0	1	0	0	0	2	1	1
ICF22	3	0	2	2	1	1	1	1	3	3	3	1	2	2	3	3	2	1	2	2	3	0	2	0	0	2	3	3	2	3
ICF23	2	2	2	1	2	3	2	0	2	3	1	0	2	1	1	3	0	2	1	0	1	2	0	2	0	1	2	3	2	3
ICF24	3	0	3	2	1	2	1	1	3	1	2	1	2	2	3	1	2	2	2	0	1	0	2	0	2	2	3	1	2	2
ICF25	3	1	3	1	2	1	1	1	3	3	3	2	0	2	3	3	2	2	2	2	2	1	2	2	0	1	3	3	1	3
ICF26	3	0	2	0	0	0	0	0	0	0	3	0	1	0	3	3	1	1	1	3	0	0	0	1	0	0	3	3	0	2
ICF27	3	1	3	2	2	1	1	2	3	3	3	1	0	2	3	3	2	2	2	1	1	1	2	2	0	2	0	3	0	3
ICF28	3	0	3	1	1	1	1	2	2	2	3	1	1	1	1	3	1	0	2	1	1	1	1	3	0	3	3	0	2	2
ICF29	1	0	3	2	0	2	2	3	3	3	3	0	3	1	3	3	0	2	0	0	3	0	2	1	0	0	3	2	0	1
DEPF	2	0	2	0	1	1	0	0	1	1	0	0	1	0	0	3	0	0	1	0	1	0	0	0	2	0	1	2	1	0

Figure 2.

Classification of variables, according to independence and dependence criteria.

Results

Based on the results of the interview analysis, the most common concepts that affect small farms’ sustainability are 29 concepts. To analyze these common factors and to determine the relational nature among them in terms of influence and dependence, the study used a structural analysis matrix to classify and rank them according to their influence volume and dependency on one another (see Table 4). Table 5 shows the ranking of the most important factors - based on the total number of rows (influences)- that support small agricultural businesses’ sustainability. These factors include the capacity to use loans for expanding farm, attention to quality control, property ownership, percentage of cultivated land out of farm space, risk management, having a marketing strategy, continuous monitoring, periodic analysis of the market, employing experienced and competent workers, ability to fulfill its obligations, among others, which in line with some previous studies for example, Hornowski et al. (2020), Candemir et al. (2021), Tan et al. (2022), Tritsch et al. (2022). For instance, Hornowski et al. (2020) emphasize the importance of financial resources, including loan utilization, in expanding farm operations and enhancing productivity, particularly for small farms. Similarly, Candemir et al. (2021) underscore the role of organized marketing strategies and cooperative models in improving farm sustainability by providing better market access and shared resources. Gorjian et al. (2021) highlighted the importance of technological advancements, such as solar-powered agricultural machinery, in optimizing operations and reducing reliance on traditional energy sources, which aligns with the emphasis on resource-efficient practices. Shahzad et al. (2021) further emphasized the critical role of skilled labor and succession planning in sustaining family farms, demonstrating that experienced and competent workers are essential for operational continuity. Tan et al. (2022) connected agricultural productivity to environmental management, showing that strategic resource use and risk management practices are crucial for mitigating environmental degradation and maintaining agricultural viability. Tritsch et al. (2022) also highlighted the necessity of tailored business strategies, including continuous market monitoring and periodic analysis, as key drivers for the success of small-scale agricultural producers in Texas. Collectively, these studies corroborate the importance of the identified factors, reinforcing their relevance in enhancing agribusiness performance and sustainability across diverse contexts.

Table 4.

The Influences and Dependencies of Concepts/Factors According to the Collective Cognitive Matrix.

No.	Factor label	Factor abbreviation	Total number of rows	Total number of columns
1	Ability to fulfill its obligations	ICF1	48	72
2	Activating the role of associations in providing services	ICF2	42	11
3	Attention to quality control	ICF3	58	75
4	Benefit from others’ experiences	ICF4	32	36
5	Keeping up with renewable and alternative energy innovations	ICF5	45	31
6	Benefit from government agricultural guidance	ICF6	42	40
7	Keeping up with modern agricultural technological innovations	ICF7	45	38
8	Classifying the harvested products into ABCD grades in order to take advantage of their price differences	ICF8	41	34
9	Conducting studies and research independently	ICF9	41	66
10	Continuous learning about agriculture	ICF10	44	74
11	Continuous monitoring	ICF11	49	64
12	Determine a percentage of profits for continuous development and improvement	ICF12	42	29
13	Determine crops compatible with the type of farm soil and water	ICF13	42	38
14	Diversification of agricultural crops	ICF14	44	36
15	Employing experienced and competent workers	ICF15	48	57
16	Familiarity with the agricultural calendar	ICF16	48	79
17	Financial transactions documentation	ICF17	44	27
18	Keeping up with government laws and regulations of the agricultural sector	ICF18	43	27
19	Having marketing strategy	ICF19	50	37
20	Capacity to use loans for expanding farm	ICF20	59	27
21	Agricultural associations services for farmers.	ICF21	29	32
22	Percentage of cultivated land out of farm space	ICF22	56	32
23	Periodic analysis of soil and water	ICF23	46	38
24	Periodic analysis of the market	ICF24	49	39
25	Property ownership	ICF25	58	17
26	Relying on feasibility studies for future development	ICF26	30	35
27	Risk management	ICF27	54	70
28	Having strategic and operational plans	ICF28	46	70
29	Visit agricultural exhibitions	ICF29	46	38
30	Small farms sustainability	DEPF	20	72
Total			1,341	1,341

Table 5.

Ranking of the Essential Concepts/Factors of Small Farms Sustainability in Order of Influence and Dependence.

N	Ranking	Factor label
1	20	Capacity to use loans for expanding farm
2	3	Attention to quality control
3	25	Property ownership
4	22	Percentage of cultivated land out of farm space
5	27	Risk management
6	19	Having marketing strategy
7	11	Continuous monitoring
8	24	Periodic analysis of the market
9	15	Employing experienced and competent workers
10	1	Ability to fulfill its obligations
11	16	Familiarity with the agricultural calendar
12	23	Periodic analysis of soil and water
13	28	Having strategic and operational plans
14	29	Visit agricultural exhibitions
15	5	Keeping up with renewable and alternative energy innovations
16	7	Keeping up with modern agricultural technological innovations
17	10	Continuous learning about agriculture
18	14	Diversification of agricultural crops
19	17	Financial transactions documentation
20	18	Keeping up with government laws and regulations of the agricultural sector
21	2	Activating the role of associations in providing services
22	6	Benefit from government agricultural guidance
23	12	Determine a percentage of profits for continuous development and improvement
24	13	Determine crops compatible with the type of farm soil and water
25	8	Classifying the harvested products into ABCD grades in order to take advantage of their price differences
26	9	Conducting studies and research independently

The collective cognitive map can be presented by the influence-dependence graph (Figure 3) or the influence-dependence plan (Figure 4). This graph shows the complexity of the network of interrelation between the small farms’ sustainability phenomenon concepts/factors, which makes it very difficult to give an appropriate interpretation. Nevertheless, identifying the most important concepts/factors that interpret this phenomenon is possible. The graph clearly shows there are two levels of concepts/factors: (i) the sensitive concepts/factors that are influenced by others that are located in the center of the graph; they are only classified as very important when sustainability direct links enter into them; (ii) the influence concepts/factors that have a direct influence on the other phenomenon’s concepts/factors. They are only considered important when many direct links influence other concepts/factors. This category has the concepts/factors that have a direct strong influence on others; these concepts/factors are linked to the internal environment by seven of them, which are determining a percentage of profits for continuous development and improvement (ICF12), determining crops compatible with the type of farm soil and water (ICF13), financial transactions documentation (ICF17), capacity to use loans for expanding farm (ICF20), percentage of cultivated land out of farm space (ICF22), periodic analysis of soil and water (ICF23), and Property ownership (ICF25). In addition, the external environment has a strong influence by four concepts/factors, which are activating the role of associations in providing services (ICF2), keeping up with renewable and alternative energy innovations (ICF5), keeping up with government laws and regulations of the agricultural sector (ICF18), and agricultural associations services for farmers (ICF21).

Figure 3.

Collective cognitive map (influence-dependence graph).

Figure 4.

Collective cognitive map (influence-dependence plan).

The influences/dependencies map is a graph that shows each concept/factor in its location in a scatter plot according to its influence (the total of columns) and dependence (the total of rows) on others (Figures 4 and 5). This scatter plot of the classified concepts/factors resulting from the structural analysis makes it possible to distinguish them among four zones (independent, relay or mediator, excluded, and dependent), allowing perfect readability of the phenomenon under study. These zones differ based on the role of each zone’s concepts/factors that can play in this phenomenon.

Figure 5.

The influence and dependency map of the small farmers collective cognitive map.

In this influence-dependence plan, we distinguish four categories of factors allowing legibility of the farm sustainability phenomenon: (i) zone A includes the independent factors with a high influence index and a low dependency index, called the explanatory factors of small agricultural businesses sustainability. This zone’s factors include activating the role of associations in providing services, keeping up with renewable and alternative energy innovations, benefiting from government agricultural guidance, keeping up with modern agricultural technological innovations, determining a percentage of profits for continuous development and improvement, determining crops compatible with the type of farm soil and water, diversification of crops, financial transactions documentation, keeping up with government laws and regulations of the agricultural sector, having a marketing strategy, capacity to use loans for expanding the farm, percentage of cultivated land out of farm space, periodic analysis of soil and water, periodic analysis of the market, property ownership, and visit agricultural exhibitions. (ii) zone B includes the relay factors that redistribute the influence by reinforcing, weakening, or reducing the effect caused by the independent factors that reduce or increase the sustainability of small farms based on their high index of influence and the dependency, which called the mediating factors (Agi & Nishant, 2017). This zone’s factors include ability to fulfill its obligations, attention to quality control, conducting studies and research independently, continuous learning about agriculture, continuous monitoring, employing experienced, and competent workers, familiarity with the agricultural calendar, risk management, and having strategic and operational plans. (iii) zone C includes the excluded factors with a low influence and dependency index, which do not seriously influence the sustainability of small farms. This zone includes benefits from others’ experiences, agricultural associations’ services for farmers, and reliance on feasibility studies for future development. (iv) Zone D includes dependent factors with a low influence index and a high dependency index, and they are conditioned by many factors in Zone A and Zone B; one factor in this zone is small agricultural businesses sustainability.

Discussion of the Small Farms Sustainability Dimensions

The purpose of this study and the thoughts and opinions presented by interviewees about this phenomenon generated the central dimensions and subdimensions of the study. We conducted an inclusive analysis of collected data and identified the overarching dimensions (Table 6). The first dimension is related to personal factors, and its subdimensions are the ability to conduct independent studies and research, familiarity with the agricultural calendar, continuous learning, benefit from government agricultural guidance, visit agricultural exhibitions, capacity to use loans for expanding farms, and property ownership. These findings are consistent with Krishnaswamy et al. (2014), who conducted case studies in Bangalore, India, on three engineering industry SMEs to explore if there is influence of the nature of technological innovations and their dimensions in contributing to new product launch, market expansion, and business growth. Their findings revealed that entrepreneurial motivation was an essential factor in recognizing opportunities in the market, building technological innovations, benefiting from external assistance in tailoring these innovations to customer requirements, delivering them to customers, and having the ability to interact with customers to achieve growth in employment, investment, and sales turnover rate. Similarly, Becker et al. (2020) studied agricultural soybean and corn calendars by employing moderate-resolution satellite images (MODIS) to estimate the sowing dates, vegetative development of crops, and harvest dates. They used the dates from 120 farms in this state from 2011 to 2014 and the Enhanced Vegetation Index that the MODIS generated to analyze the seasonal trends of soybean and corn. They found that knowing the agricultural calendar of crops is significant for estimating and forecasting large-scale crop cultivation and harvesting dates.

Table 6.

Small Agricultural Businesses Sustainability Dimensions.

Dimensions	Concepts/factors
Personal dimension	- Ability to Conduct independent studies and research- Familiarity with the agricultural calendar- Continuous learning- Benefit from government agricultural guidance- Visit agricultural exhibitions- Property ownership
Internal environment dimension	- Ability to fulfill its obligations- Capacity to use loans for expanding farm- Attention to quality control- Continuous monitoring- Risk management- Employing experienced and competent workers- Determine a percentage of profits for continuous development and improvement- Determine crops compatible with the type of farm soil and water- Diversification of crops- Financial transactions documentation- Having a marketing strategy- Having strategic and operational plans- Percentage of cultivated land out of farm space- Periodic analysis of soil and water- Periodic analysis of the market
External environment dimension	- Agricultural associations services for farmers.- Keeping up with government laws and regulations in the agricultural sector- Keeping up with renewable and alternative energy innovations- Keeping up with modern agricultural technological innovations

The second dimension is the internal environment factors, and its subdimensions are the ability to fulfill its obligations, attention to quality control, continuous monitoring, risk management, employing experienced, and competent workers, determining a percentage of profits for continuous development and improvement, determining crops compatible with the type of farm soil and water, diversification of crops, financial transactions documentation, having a marketing strategy, having strategic and operational plans, percentage of cultivated land out of farm space, and periodic analysis of soil and water. Within this context, Nugraha et al. conducted a study on agricultural companies listed in the Stock Exchange of Indonesia between 2014 and 2018 to determine the factors that have influenced financial performance based on business size, liquidity, leverage, and sales growth by using Panel Data Regression Analysis method. They found that business size, liquidity, leverage, and sales growth positively influence businesses’ financial performance. They recommended that businesses monitor and control changes in business size, liquidity, leverage, and sales growth to make decisions and policies that lead to better business performance. Similarly, Saranza et al. (2024) conducted a study aiming to assess the business risk management practices and performance of businesses in the Municipality of Claver - Surigao del Norte, Philippines, using data from 313 businesses selected and purposefully analyzed by statistical tests such as mean, standard deviation, variance analysis, and Pearson rho. They found that 52% of businesses aged between 6 and 10 years were committed to risk management and strategic, financial, operational, and reputational enhancement. Furthermore, there is a positive nexus between financial business risk management and business general performance; thus, encouraging teamwork, risk management practices adherence, diffusing risk management knowledge, and encouraging continuous learning result in a robust risk management framework and strategic decision-making. In terms of strategies, Olawunmi and Clarke (2023) explored the marketing strategies of the fish farming firms that can be employed to obtain a competitive advantage in the United Kingdom, such as brand, core competency of the product, promotion, and market places and segments. Data from 200 firms was collected by an online questionnaire that was distributed through five of the UK trade associations that were randomly selected. The collected data represents both males and females of different ages and levels of experience in fish farming businesses. They found that these businesses might increase sales by employing eco-labels in product brands that can lead to premium prices, building consumer confidence, and using high-quality packaging of their products to keep them fresh for a long time. Practically, it is recommended that UK fish farms pay more attention to their marketing strategies and knowledge improvement related to their business because they are the keys to competitive advantage. Furthermore, farmers have to be creative and innovative in leveraging branding and building a core competency of their products to persuade consumers to win their trust, and they have to choose the best marketing strategy that fits their business.

The third dimension is resilience in external environment factors and consists of five subdimensions: periodic analysis of the market, agricultural associations services for farmers, keeping up with government laws and regulations of the agricultural sector, keeping up with renewable and alternative energy innovations, and keeping up with modern agricultural technological innovations. These results confirm the findings of Hornowski et al. (2020), who explored the directions of the changes in the small farms in Central and Eastern Poland and factors affecting their functioning and development through data collected from 19 municipal agricultural officers, 75 village mayors, and 116 small active farms, which were analyzed using the k-mean cluster and the principal component analysis to separate farms into homogenous groups. They found three types of farms: hobby, two-occupation, and professional. They asserted that the development of small farms is mainly affected by external factors, such as governmental funding and state advantages rather than entrepreneurial factors (the internal environment), and professionals pay attention to investing, developing, and innovating in farming rather than hobby and two-occupation farmers, who manage their farms with a reservedness toward investment and whose aims are to maximize the benefits related to their status. Finally, in their opinion, professional farms have the highest chances of being sustainable and contributing to the economy, while other types may focus on providing governmental funding and state advantages. Tan et al. (2022) also looked at whether the agriculture sector is influenced by environmental degradation in 35 European countries. They adopted the Driscoll and Kraay estimator to find if there is a potential influence of environmental degradation - agricultural emissions, biodiversity loss, and deforestation- besides e-governance, organic production, renewable energy, women empowerment, political stability, and social progress on agriculture. They found that biodiversity loss influences harmfully agricultural production, the increase in forest area has a positive influence on grain and vegetable production, and, on the other hand, there is no significant influence of agricultural emissions on the other independent variables but influences negatively on the production of grain and positively on vegetable production. Furthermore, using renewable energy, women empowerment, and political stability influence the dependent variables significantly and positively, but social progress has an insignificant influence on them. Finally, e-governance significantly and positively influences agricultural production. Implicationally, they found a crucial policy implication for the European agricultural sector. Regarding innovations supporting farms’ sustainability, Gorjian et al. (2021) explored integrating photovoltaic technology with electric farm tractors and agricultural robots by reviewing research and case studies. They found that challenges hinder the diffusion of modern solar-powered agricultural equipment, namely the high initial costs of photovoltaic modules and electric storage unit technologies. Furthermore, the changes in the outdoor climate that influence these equipment productivities, such as weather temperature, shading, dust accumulation, and humidity, have to be considered. Moreover, technological improvements, reduced costs, and governmental support may help deploy this sustainable equipment in real life. Finally, they expected that promoting photovoltaic technology integration with modern electrical agricultural equipment may encourage managers and owners of farms, planning and production officials, and decision-makers to use this technique in agriculture by providing insight into the newest developments and crucial challenges.

Conclusion and Implications

This study explored the key factors influencing small agricultural businesses’ sustainability. The sustainability factors of small agricultural businesses were identified by conducting 41 interviews with small farmers, which were analyzed through the Cross-Impact Matrix Multiplication Applied to Classification software (MICMAC) method. 29 significant factors for small agricultural business sustainability were identified by conducting 41 interviews with small farmers, including personal, internal, and external factors. These factors were compared pairwise to create the data for the structural analysis through the MICMAC method. Small agricultural businesses’ sustainability is a complex issue affected by many factors, so we adopted the structural analysis method that accurately chooses the significant factors for small agricultural businesses’ sustainability. Since small agricultural businesses’ sustainability is influenced by diverse factors, considering all these factors in its assessment will be all that complex. Also, even a few of these factors are difficult to deal with. The two important characteristics of small agricultural businesses’ sustainability were illustrated in this study. First, the types of small agricultural business sustainability factors were determined based on four zones in the influence-dependence plan (Figure 4). Second, the most significant factors determined by the influence-dependence graph (Figure 3) are determining a percentage of profits for continuous development and improvement, determining crops compatible with the type of farm soil and water, financial transactions documentation, capacity to use loans for expanding the farm, percentage of cultivated land out of farm space, periodic analysis of soil and water, Property ownership: activating the role of associations in providing services, keeping up with renewable and alternative energy innovations, keeping up with government laws and regulations of the agricultural sector, and agricultural associations services for farmers.

This study offers several practical and policy implications for enhancing the sustainability of small agricultural businesses. On the practical side, farmers should prioritize adopting modern management practices, such as financial documentation, effective utilization of loans, and periodic analysis of soil and water conditions, to optimize resource use and improve productivity. Strategic planning, including determining crops compatible with the soil and water type and allocating a percentage of profits for continuous development, is critical for operational resilience. Farmers should also leverage the services of agricultural associations, which can provide training, facilitate access to markets, and offer support for modern farming techniques. Additionally, embracing renewable and alternative energy technologies and staying updated on agricultural innovations can help small agribusinesses achieve both economic and environmental sustainability. Equipping farm owners and managers with these skills through training programs and workshops is essential to enhance their ability to adapt to changing environmental and market conditions. From a policy perspective, targeted interventions are required to address the key challenges identified in this study. Policymakers should focus on enhancing financial inclusion for small farmers by improving access to credit and designing agricultural-specific loan schemes. Subsidies and grants for sustainable farming practices, such as renewable energy and advanced soil management techniques, can further incentivize sustainable development. Strengthening agricultural associations is crucial, as they play a pivotal role in bridging the gap between farmers and resources, including market information, technical expertise, and innovative technologies. Additionally, regulatory frameworks should be aligned to support integrating modern technologies and sustainable practices in small agricultural businesses. These policy and practical measures collectively provide a comprehensive approach to improving the sustainability and resilience of small agribusinesses, particularly in developing contexts like Saudi Arabia.

Despite its contributions and implications, this study also has some limitations that open avenues for future research. First, the study’s context is specific to a particular region in Saudi Arabia, which may limit the generalizability of the findings to other regions or countries with different socio-economic, cultural, and environmental conditions. Future research could explore these sustainability factors in broader geographic contexts, comparing findings across regions or countries to identify universal versus context-specific factors influencing small agricultural businesses. Second, the study relies on qualitative analysis through interviews with 41 small farmers, which provides rich, detailed insights but may lack broader statistical generalizability. Future studies could complement this approach with quantitative methods, such as large-scale surveys or econometric analyses, to validate and quantify the relationships among identified factors. Incorporating a mixed-methods approach would strengthen the robustness of the findings and provide a more comprehensive understanding. Finally, the MICMAC method offers a structured analysis of factors but does not account for temporal changes or dynamic interactions between factors over time. Future research could employ longitudinal studies or dynamic modeling approaches to understand how these factors evolve and interact under changing economic, environmental, and policy conditions. This would provide more actionable insights for long-term strategic planning in the agricultural sector.

Footnotes

The authors gratefully acknowledge Qassim University,represented by the Deanship of Scientific Research,on the financial support for this research under the number (2023-SDG-1-HSRC-35898) during the academic year 1445 AH/2023 AD.

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Exploring the Factors Influencing Small Agricultural Businesses Sustainability in Saudi Arabia: A Qualitative Analysis

Abstract

Keywords

Introduction

Literature Review

Research Method and Data

Structural Analysis Approach

Constructing Steps of the Collective Cognitive Map

Data

Results

Discussion of the Small Farms Sustainability Dimensions

Conclusion and Implications

Footnotes

ORCID iD

Statements and Declarations

References