4.1. Socioeconomic characteristics of women farmers in Kabare and Mulungwishi
Table 1 provides information on the socioeconomic characteristics of women farmers in the two sites, Kabare and Mulungwishi. The results show that the majority of women farmers (83%) in both areas were married, with no significant difference between the sites. This is a common social status and general trend in rural areas due to early marriages [43–44]. Women’s social status can affect how they engage in agricultural activities and make decisions related to their farmland and households [45]. In the investigated farming areas, decisions about credit were made jointly between man and women (87% of cases). A farmer in Mulungwishi argued : ‘’It's essential to let your husband know before committing to a debt, even if he is not present, because he can intervene if you are unable to pay back. Without his consent, he may assume you're receiving financial support from another man, potentially jeopardizing your relationship. Maintaining harmony within the family requires transparency and keeping your partner informed about all financial decisions’’. Even in so-called matriarchal societies in the Basanga community in Mulungwishi where it is falsely assumed that women exercise authority and control over their households, women firmly recognize the social power of their husbands, who make most important socio-economic decisions and control resources [46]. The age distribution of these women farmers was similar in both sites, with the majority of women in the 40–59 age range. This age is an important demographic in rural farming communities because farmers might have acquired experiences that significantly impact their communities' economic and social development. Also, such farmers ‘age matters when demanding credit [47–48].
A significant difference was found in the proportion of women who were born and grew up in the study area, with a higher percentage (73%) in Kabare compared to Mulungwishi (51%). This suggests that women in Kabare are more likely to have stronger ties to their community, which could impact their access to resources.
However, the level of education varied significantly between the sites, with a higher percentage of women in Kabare who could not read or write (44%), and a higher percentage of women in Mulungwishi with a secondary education. A very small proportion of women (6%) had a university education in both sites. he higher percentage of women in Mulungwishi with a secondary education indicates that they had more opportunities to pursue education, which can increase their chances of finding formal employment outside of farming. Also, results reveal women's unequal access to education in these regions, particularly in South Kivu [44]. Education is a determining factor in accessing financial services and other agricultural resources, contributing to women's empowerment [49]. Education can help individuals make the most of credit opportunities by improving financial literacy and building relationships with lenders.
Further, we noticed that the household size varied across the sites, with a higher proportion of households with five or fewer members in Kabare, and a higher proportion of households with nine or more members in Mulungwishi. About 56% of women interviewed perceived the landholding status as insecure, with no significant difference between the sites. This is a concerning finding, because insecure land tenure does not give women opportunity to access credit as a land title is the most frequently required collateral by financial institutions[22–50]. Also, land-insecure farmers can hesitate to take credit for investing in long-term practices like agroforestry or crop diversification because they could lose their land at any time. This lack of control over their land can discourage farmers from making investments that may take years to pay off [51–52]. The size of farmland varied significantly between the sites, with a higher proportion of women in Kabare having farm sizes of 5 ares or less and a higher proportion of women in Mulungwishi having farm sizes of 6 ares or more. This is not surprising because the cultivated land size per capita in DRC is small, ranging from 0.17 to 0.25 hectares [6–18]. Within vegetable production sites, the crop field size is typically even smaller due to households' high demand for land focused on producing short-cycle crops in high demand in markets during the dry season [10, 32–52]. As a result, smaller farms are less attractive to potential lenders, especially microfinance institutions [18–50].
Another interesting finding is the distance of farmers from urban settlements, which did not vary significantly between the sites. About 58% of farmers interviewed thought they lived far away from cities. This can lead to several challenges in accessing credit. For example, microfinance institutions may be less likely to offer credit to farmers whom they perceive to be located in remote or hard-to-reach areas due to concerns about the difficulty of servicing loans (security, infrastructures, high credit cost) and the perceived higher risk associated with lending to geographically isolated farmers. These concerns are shared by many lenders in Africa [18, 21–48]. In the USA, [53] found that closer credit office branches were to the farming communities, the more farmers applied for loans, reducing borrower search and travel costs. Comparison is not always fair because, despite the proximity of market gardeners to urban centers where banks and microfinance are well established, access to credit has not been guaranteed. This is evidenced by the challenges faced by urban farmers to access credit or government subsidies in Kinshasa DRC [17], Ndola in Zambia, Bulawayo, Zimbabwe, and Beijing in China [54].
Table 1
Socioeconomic characteristics of women farmers in investigated sites
Modalities | Category | Kabare | Mulungwishi | Overall | Statistic test values |
n | % | n | % | % | χ2 | p-value |
Marital status | Married | 99 | 82 | 93 | 83 | 83 | 0.019 | 0.891 |
| Unmarried | 21 | 18 | 19 | 17 | 17 |
Age | 17–39 | 55 | 46 | 43 | 38 | 42 | 1.478 | 0.478 |
| 40–59 | 50 | 42 | 51 | 46 | 44 |
| ≥ 60 | 15 | 13 | 18 | 16 | 14 |
Born and grew up in the area | Yes | 88 | 73 | 57 | 51 | 63 | 12.447 | 0.000*** |
No | 32 | 27 | 55 | 49 | 37 |
Education level | Cannot read or write | 53 | 44 | 10 | 9 | 27 | 39.216 | 0.000*** |
| Primary | 36 | 30 | 47 | 42 | 36 | |
| Secondary | 24 | 20 | 49 | 44 | 31 | |
| University | 7 | 6 | 6 | 5 | 6 | |
Household size | ≤ 5 | 30 | 25 | 40 | 36 | 30 | | |
| 5–8 | 39 | 33 | 44 | 39 | 36 | 8.160 | 0.017* |
≥ 9 | 51 | 43 | 28 | 25 | 34 |
Decision- making about credit | Jointly | 105 | 88 | 96 | 86 | 87 | 0,160 | 0.690 |
Only woman | 15 | 12 | 16 | 14 | 13 |
Perception of landholding status | Secure | 47 | 39 | 55 | 49 | 44 | 2.324 | 0.127 |
Insecure | 73 | 61 | 57 | 51 | 56 | | |
Farmland size | ≤ 5 ares | 49 | 41 | 75 | 67 | 53 | 15.898 | 0.000*** |
≥ 6 ares | 71 | 59 | 37 | 33 | 47 | |
Income generated | Not enough | 38 | 32 | 40 | 36 | 34 | 0.492 | 0.483 |
Enough | 82 | 68 | 71 | 64 | 66 | | |
Intention to demand credit | Yes | 57 | 48 | 67 | 60 | 54 | 3.298 | 0.069 |
No | 62 | 52 | 45 | 40 | 46 | |
Access to market | Easy | 42 | 35 | 52 | 46 | 41 | 2.964 | 0.085 |
Not easy | 77 | 65 | 60 | 54 | 59 | | |
Membership to VSLAs | Yes | 52 | 43 | 28 | 25 | 35 | 8.619 | 0.003** |
No | 68 | 57 | 84 | 75 | 65 |
Contact with NGO or farmers groups | Yes | 53 | 44 | 22 | 20 | 32 | 15.926 | 0.000*** |
No | 67 | 56 | 90 | 80 | 157 |
Distance from town(Km) | Very long (≥ 30) | 20 | 16 | 17 | 15 | 16 | 0.378 | 0.828 |
Long (15–29) | 67 | 56 | 67 | 60 | 58 |
Short (1–14) | 33 | 27 | 28 | 25 | 26 |
Most women farmers in both sites claimed to generate enough income from vegetable production per cropping cycle, with no significant difference between the sites. Findings also revealed that membership of Village Savings and Loans Associations (VSLAs) was significantly higher in Kabare compared to Mulungwishi, and a significantly higher proportion of women in both sites had contact with NGOs or other farmers' groups (see Table 1). This noticeable difference in contact with NGOs between the two regions is because the conflicts and wars that South Kivu has experienced attracted the attention of many humanitarian organizations willing to provide services such as healthcare and social support. In Southeast Asia, [4] noticed that women borrowed money from NGOs, and these organizations, depending on their mission, can promote sustainable agriculture and women's empowerment [10–55].
4.2. Factors associated with credit-seeking intentions among women farmers
Chauke et al. [41] argue that access to credit starts with farmers' expressed intention to seek it. In this study, results show that the intention to seek credit was slightly higher (60%) in Mulungwishi than in Kabare (48%), but the difference was not statistically significant (see Table 1). The potential factors associated with women farmers 'intentions to seek credit in these regions are presented in Table 2.
First, regarding age, younger farmers (17–39 years old) had a higher intention to seek credit (48%) compared to older farmers (40–59) and those above 60 years old. This finding is consistent with the studies of [47–48], establishing a positive and significant relationship between farmers 'age and credit demand among agricultural households in Zimbabwe and Ghana, respectively. Chandio and Jiang [56] explain that young farmers actively seek credit as they are more inclined to adopt new farm technology for better farm production. This aligns with respondents' willingness to invest heavily in various vegetables (see Fig. 5 supplementary materials). Also, being flexible and connected to cities, young women farmers may seek credit to start activities beyond farming, e.g., selling clothes, beer, and groceries in their communities or large cities.
In this study, the education level was not associated with credit-seeking intentions, with most farmers having at least a primary education level, which agrees with a recent study in South Kivu by [19]. Other studies have emphasized that education increases the probability of demanding or accessing credit services as it enables farmers to navigate the procedure to gain formal credit [21, 47–48]. Our results reveal that women who discussed with fellow farmers in groups or NGOs had a significantly higher intention to demand credit (40%) compared to those who did not (60%). This trend is also observed in other developing countries where women's low access to formal extension services has resulted in an increased reliance on informal social networks [55].
Further, results in Table 2 show that women farmers who perceived their landholding as secure had a higher intention to demand credit (38%) than those who perceived it as insecure. Surprisingly, farmers with small cropland sizes had a significantly higher intention to demand credit (48%) than those with larger cropland sizes. Our findings are consistent with [50–51] explaining how to secure land holding and crop size can affect loan demand and approval, leading to secure and sustainable investments. However, [57] argues that land security (ownership titles) alone is not enough to solve the limited credit access problem among smallholder farmers in developing countries.
Our findings also indicate that access to markets was not easy, with a slightly higher proportion (65%) of women farmers in Kabare reporting difficulty accessing markets. However, the difference was not statistically significant ( see Table 1). Nevertheless, results in Table 2 show that those women farmers who had easy access to markets to sell their harvests had a higher intention to demand credit (47%) than those who did not have easy access (53%). Access to markets is often a critical factor that lenders consider when evaluating creditworthiness, as it indicates the potential for income generation and the ability to repay loans. This trend of farmers' access to the market in Kabare is consistent with a report by [13–15], highlighting poor market linkage due mainly to unpassable roads in rural DRC.
Moreover, income generated per cropping cycle had a significant effect on credit demand, with farmers who generated good incomes (˃ 250$US) having a higher intention to demand credit (79%) than those who did not generate high incomes (≤ 250$US). Income generated is an essential indicator of the borrower's repayment ability. If the credit seeker has a higher income, they are more likely to repay the loan on time, which makes them more attractive to lenders. Although many studies found a significant association between income and credit demand among agricultural households [19, 21–24]; scholars often overlook the decision-making process in seeking credit. Here, we found that a larger proportion of women farmers (87%) made decisions jointly with their husbands or relatives when seeking credit or making finance-related decisions, a finding which is in line with [58–59].
Table 2
Factors affecting vegetable farmers' intention to demand credit in Mulungwishi
Variables | Modalities | Intend to seek credit | No intention to seek credit | Statistics |
| | n | % | n | % | χ2 | p-value |
Marital statuts | Married | 106 | 85 | 85 | 79 | 1.466 | 0.226 |
Unmarried | 18 | 15 | 22 | 21 |
Age (years) | Younger (17–39) | 60 | 48 | 38 | 36 | 6.337 | 0.042* |
Old (40–59) | 52 | 42 | 48 | 45 |
Older (≥ 60) | 12 | 10 | 21 | 20 |
Education level | No level | 29 | 23 | 34 | 32 | 4.488 | 0.213 |
Primary | 44 | 36 | 38 | 36 |
High school | 41 | 33 | 32 | 30 |
Under graduate | 10 | 8 | 3 | 3 |
Household size(persons) | Small (≥ 4) | 34 | 27 | 36 | 34 | 2.785 | 0.248 |
Medium (5–8) | 50 | 40 | 32 | 30 | | |
| Large ( ˃9) | 40 | 32 | 39 | 36 | | |
Membership to VSLA | Yes | 38 | 31 | 41 | 38 | 1.509 | 0.220 |
No | 86 | 69 | 66 | 62 | |
Discussion with fellow farmers in groups or NGO | Yes | 49 | 40 | 26 | 24 | 6.066 | 0.014* |
No | 75 | 60 | 81 | 76 | | |
Landholding perception | Secure | 47 | 38 | 55 | 51 | 4.244 | 0.039* |
Insecure | 77 | 62 | 52 | 49 | |
Cropland size | Small (≤ 5ares) | 59 | 48 | 65 | 61 | 4.005 | 0.045* |
Large (≥ 6 ares) | 65 | 52 | 42 | 49 |
Access to market | Easy | 58 | 47 | 36 | 35 | 4.104 | 0.043* |
Not easy | 66 | 53 | 71 | 66 |
Income generated /cropping season | Not enough (≤ 250 | 26 | 21 | 51 | 48 | 18.909 | 0.000*** |
Good (˃250$US) | 98 | 79 | 55 | 52 | |
Decision-making around credit demand | Jointly | 108 | 87 | 93 | 85 | 6.514 | 0.039* |
Self | 16 | 13 | 16 | 15 |
4.3. Type and size of credit women farmers were willing to obtain
Figure 3 shows the distribution of farmers in the two study areas according to the types of credit needed. Results indicate that in Kabare, the majority of farmers (70%) desire credit in cash, while 22% would prefer credit in the form of agricultural inputs, and only 8% are interested in any credit available. In Mulungwishi, however, more farmers (55%) want credit in the form of agricultural inputs compared to those who desire credit in cash (32%). Only 13% of farmers said they could receive any credit available. In Kabare, a respondent stated:'' I would prefer cash rather than credit in the form of input provision because I can adapt cash to production needs. Growing vegetables within marshlands is a complex activity that requires permanent cash in steps. The land had to be rented, the drainage works carried out, the land plowed, and the manure purchased and transported to the field''. This distribution of farmers' credit preferences in the two sites suggests a variation in the type of credit desired by farmers depending on their location and circumstances. This matches a recent study by [19] showing that almost 67% of tomato growers in South Kivu demand credit in cash, while in Mulungwishi, [39] reported that farmers needed support in terms of agricultural input provision. This information could help policymakers and financial institutions to better understand the credit needs of farmers in these locations and develop tailored credit products to meet their needs.
Figure 4 reveals the amount of credit ($ U.S.) farmers would demand if the lenders were available in the investigated sites. Significant differences existed between the amount desired and the location of farmers (X2 = 13.436, p = 0.004). For the Kabare site, more than half of the farmers (52%) intended to demand less than $US 100, and 27% of farmers intended to demand credit between $US 100 and 200. However, in Mulungwishi, about 30% of farmers intended to demand a loan of $US 300. Compared with Kenyan farmers, the desired amount was slightly lower, but in Kenya, many women apply for group loans, and the amount granted varies from $ U.S. 50-5000 [60]. The overall distribution across both sites is similar, with more farmers intending to demand ≤ 100 $ U.S credit. The implications of these results could be significant for policymakers and financial institutions. They suggest that credit demand is not uniform across the sites. Therefore, financial institutions should consider tailoring their credit products to meet the specific needs of farmers in different regions, considering the specific factors that may influence credit demand. This could lead to higher credit uptake and better outcomes for farmers.
4.4. Farmers’ allocation of agricultural loans in Kabare and Mulungwishi
Farmers are often criticized for directing the credit they obtain towards often unproductive activities for which it is not intended, which leads to over-indebtedness and default on payments. For instance, research on credit accessibility for tomato growers in South Kivu illustrates how farmers obtained a loan to produce tomatoes but utilized the funds mainly to settle debts and cover household expenses [19].
Figure 5 displays the items of expenditure to which farmers intend to allocate credits. The most important observation is a significant difference in the distribution of credit allocation preferences among farmers across the sites (p-value = 0.006). Looking at the results, 47% of farmers in Kabare desire credit for purchasing agricultural inputs, while 74% of farmers in Mulungwishi have the same preference. Starting commercial activities is the preferred option for 26% of farmers in Kabare and 7% of farmers in Mulungwishi. Finally, 12% of farmers in Kabare and 7% of Mulungwishi prefer credit for starting animal farming. The overall distribution of credit allocation preferences shows that most farmers (61%) prefer credit for purchasing agricultural inputs, followed by starting commercial activities (16%).
In other regions, studies also highlight that farmers demand credit mainly for purchasing agricultural inputs, including equipment and irrigation systems [2, 23, 24–60]. Figure 5 in supplementary materials shows vegetable crops in which respondents were willing to invest heavily. They may also use credit for domestic uses, starting businesses, or acquiring dairy cows to diversify their incomes [50–60]. For example, respondent no 4 said’’ If I find somewhere to borrow money from, at least 500 dollars, I can open a small grocery shop in the community. I plan to work on the farm early in the morning and will come to the shop around noon. I cannot solely rely on farming because it is not the same day I plant that I harvest’’.
Figure 5. Distribution of farmers according to the credit allocation preferences in Kabare and Mulungwishi
4.5. Perceived factors limiting access to agricultural loans in Kabare and Mulungwishi
The literature has amply shown that the challenges of the financial service market in rural areas are complex and multifaceted. However, results from previous research concurred that smallholder farmers have low access to agriculture credit due to the lack of agricultural credit-related information, lack of collateral, and absence of microfinance institutions in rural areas and the long distance between borrowers and lenders [2–19, 21–30]. Also, available loans are generally not adapted to the agricultural and animal-raising cycle [54]. In Mulungwishi, the president of a VSLA stated that '' a common mistake among farmers who criticize microfinance institutions such as FINCA is using short-term loans for long-term income-generating activities, for instance, taking six months- loan and investing it in goat farming or maize cultivation that may not yield returns quickly''. This may arise from a lack of information and enough credit use and allocation education. These challenges are in agreement with our results in Table 3, displaying the logistic regression analysis on the perceived constraints limiting access to agricultural credit by women farmers in Kabare and Mulungwishi. Results indicate that the absence of microfinance institutions, the perception of agriculture as risky and unprofitable businesses, the lack of credit information, and stereotyping of women as poor are significant constraints limiting women farmers' access to credit in the sites investigated.
On the other hand, cultural constraints do not have a significant relationship with credit access, as indicated by the large standard error, non-significant Wald statistic, and high p-value (0.999). Results showed that the power of the logit model was suitable because it correctly classified 86.14% of the known factors. To tackle these challenges, some experts and organizations have suggested that promoting mobile financial services in rural areas can help lenders offer women and men farmers increased access to credit by overcoming geographic and physical barriers and high transaction costs associated with credit [59, 60–61]. However, women farmers' mobile phone access and use and formal education in rural DRC still need to be improved..
Table 3
.Perceived factors liming credit access among women farmers interviewed
Variables | B | S.E. | Wald | p-value |
Absence of microfinance institutions | 2.733** | 0.866 | 9.953 | 0.002 |
Risky and unprofitable business | 2.593** | 0.870 | 8.886 | 0.003 |
Lack of information about credit | 4.284*** | 1.220 | 12.323 | 0.000 |
Stereotyping women as poor | 2.430** | 0.876 | 7.704 | 0.006 |
Cultural constraint | 21.384 | 25805.700 | 0.000 | 0.999 |
Constant | -0.983 | 0.677 | 2.112 | 0.146 |
B represents partial regression coefficients; SE: Stand error, *** indicates very highly significant at 1%, ** = indicates highly significant test at 5%, overall percentage predicted = 86.1%.
Reducing the perceived risk implies developing value chains of agriculture that can improve the profitability of women's farming activities. Thirdly, there is a need to provide financial education and training programs to women farmers to address the lack of information about credit.
4.6. Role of Village Savings and Loan associations in Kabare and Mulungwishi
VSLAs are accepted to be crucial in promoting financial inclusion, especially for smallholder women farmers who are often excluded from formal financial institutions [62–63]. VSLAs are community-led savings groups providing members with a simple, safe, and transparent way to manage their finances. They offer saving services, basic insurance through the social fund, loans, and a social network [64]. The DRC counts 7,177 VSLAs with 170,034 members, including 141,012 women members [64]. There are exciting success stories about VSLAs in the study areas. For example, in Mulungwishi, a respondent stated," I deposit only 3000 Congolese francs (US$ 1.5) per week, but thanks to my membership in Umoja VSLA, I urgently received US$ 75 to pay my children's school fees. No bank will operate instantly like that. I have to reimburse that money with 10% of interest ". In Kabare, a respondent gratefully said that “on my son's wedding ceremony, my group offered me 200000 Congolese francs as mutual assistance. It was a worthy gift that made me proud to belong to a VSLA". Figure 3 in supplementary materials illustrates how VSLAs work in Kabare and Mulungwishi. Figure 6 shows the women's frequency of resorting to VSLAs for requesting credit in both sites studied. Overall, the results indicate that 31% of women farmers never resort to VSLAs for requesting credit, while 50% do so sometimes and 20% do so often. The chi-square value of 58.069 with a p-value = 0.000 indicates a statistically significant association between the frequency of resorting to VSLAs for requesting credit and the region where the women farmers are located. In Kabare, 74% of women farmers sometimes resort to VSLAs to request credit, and 10% do so often. In Mulungwishi, 46% of women farmers never resort to VSLAs for requesting credit, while 30% do so often. The results suggest that VSLAs are a popular source of credit for women farmers, with half of the respondents resorting to them sometimes and one-fifth using them often. In Malawi, [62] found that farmers often resorted to VSLAs to improve their saving capacity and increase agricultural investments. Overall, our findings suggest that VSLAs are a valuable tool for improving women farmers' access to credit. However, efforts are needed to address the barriers preventing some women from benefiting VSLAs.
Figure 7 reveals the amount of money women farmers in both sites borrowed from VSLAs. The t-test results indicate a significant difference between the two sites regarding the amount borrowed (p-value = 0.001) and highlight considerable variability in Mulungwishi. The loans obtained from VSLAs ranged from 12.5 to $US300, and the mean amount borrowed by farmers in Kabare was $US33, almost two times lower than that borrowed in Mulungwishi ($US77). The results imply that women farmers in Mulungwishi borrow significantly more money than those in Kabare. This difference is likely due to the ability of these farmers in each region to raise funds, often based on weekly or monthly contributions of members, as observed in other regions [63–64, 65]. A respondent in Mulungwishi commented: "Our group comprises 32 members, but the financial assistance you individually receive depends on your contributions. For last year's cropping season, three friends and I borrowed from our group 500,000 Congolese francs ($US 250 at the time of the interview), making a group purchase of pesticides, fertilizers, and seeds". Similarly, [20] reported that vegetable growers in Lubumbashi also resorted to their saving groups when they needed to purchase a moto pump for crop irrigation.
4.7. Limitations of the study
Although this study is one of the few investigating the factors associated with credit-seeking intentions among women farmers in Kabare and Mulungwishi DRC, it has some inherent limitations. First, the research was carried out during a challenging time for the Democratic Republic of the Congo, as the country was grappling with the economic impacts of the COVID-19 pandemic. The pandemic has significantly strained development efforts in many nations, including the DRC, due to mobility and trade restrictions that made it difficult for farmers to access agricultural inputs, credit, and markets for selling crops [55–66]. Therefore, some respondents assumed that the study identified individuals eligible for COVID relief. As illustrated by this quote, many farmers kept saying: "Let me listen to you; perhaps, you will support our community financially during this challenging time. Please, remember me if you come back with help." Also, the reported incomes of these women should be considered with caution for two reasons. Firstly, there is a general reluctance among them to disclose both the sources and level of income earned by their households. Secondly, they do not keep records during the sequential sale of their harvests, which is complex in the context of seasonal farming [15].
Secondly, we solely focused on women farmers, rather than comparing men and women, to understand the gendered disparities in accessing critical resources such as credit. Gender disparity is a topic of ongoing debate among researchers, as it is often seen as a potential barrier to rural development [2, 5, 9–49]. Lastly, we should have inquired about the type of guarantees or collaterals women farmers were willing to provide lenders to access credit. Furthermore, in identifying the constraints that impede women's access to credit, we exclusively relied on the factors reported by respondents without considering critical variables such as the level of education and income in the logit model. This could be an essential aspect to investigate, as it may shed light on additional potential barriers or opportunities for women to access credit through formal channels.