**Figure 2.**

#### **Figure 3.**

*Multifunctionality and Impacts of Organic and Conventional Agriculture*

with very unfavorable to very favorable.

**6.1 Support for community-based agriculture**

agriculture.

this weakness in mind.

(7) = extremely important.

**6. Results**

agriculture.

the socioeconomic and ecological concerns associated with corporate commodity agriculture or, more broadly, conventional food production systems [2, 14, 36, 37]. Community-based agriculture with its emphasis on holistic and locally based agriculture systems has catalyzed regionally based economic activity, the focus of which is to reinvigorate rural communities and economies and improve farmer income [13]. The growing interest and belief in the potential of civic agriculture systems to bolster rural communities and their economies rests on the findings of [2, 24, 38], which indicate that several small locally owned and operated businesses (farms) are positively correlated with economically vibrant communities and superior income equity. These findings speak to the thesis that a sustainable agricultural production system must meet economic and social criteria in addition to addressing ecological concerns (see **Figure 1**).

3.CAA leaders were asked to indicate how they felt about farmers cooperatives. Their responses were measured on a five point Likert-type scale, anchored

4.Leaders were also asked to use a "yes" or "no" response to indicate whether their organization supports community-based food production, the local farmers' market, and whether they encouraged clients to participate in urban

The questionnaire was reviewed by faculty of the Applied Survey Laboratory at North Carolina A&T State University and two leaders of CAAs. The response rate for the survey was approximately 39%. We acknowledge that the results are probably biased because of the relatively low response rate. However, because CAAs are probably subjected to similar socializing influences with regard to the variables of the study, we believe that the low response rate is not a very serious problem. [39] suggested that discrepancies and bias due to non-response are a greater threat for variables denoting characteristics of an entity than for those variables that represent opinions, attitudes or processes. Nonetheless, the results should be interpreted with

**Figure 2** shows that 48% of CAAs provide program support for community based food production, 53% support local farmers market and 36% support urban

The data in **Figure 3** show that approximately 85% of CAAs rated the importance of farmers using organic methods to produce food greater than a 5 on a 7 point scale. We see this as indicating that CAAs believe that it is important for farmers to use organic methods, which is in contrast to the relatively small number (48%) of

The response pattern in **Figure 3** also shows that over 80% of CAAs believe that

it is important for farmers to use organic methods of production. The response pattern shown in **Table 1** below indicates that CAAs overwhelmingly agree that community-based farming is more likely to do a better job of preserving the land:

CAAs that offer program support for community-based food production. Response is based on a 7-point scale Where (1) = not important and

**92**

*How important is it for more farmers to use organic methods for producing food? (N = 122).*


*Response is based on a 5-point scale, where (1) = strongly disagree and (5) = very strongly disagree.\*(1) = very unfavorable and (5) = very favorable.*

#### **Table 1.**

*Summary of descriptives for selected variables.*


*use); land = opinion on the statement that community-based farming preserves the quality of land better than large corporate farms; environment = opinion on the statement that community-based farming* 

*preserves the environment better than large corporate farms; cooperatives = extent of favorable perception of farmers' cooperatives; promote = opinion on the duty of citizens to buy locally grown farm produce.*

**Table 2.**

**95**

independent variables.

**7. Discussion**

*Accounting for the Impact of Sustainable Agriculture: The Role of Community Based…*

**6.2 Predicting support for sustainable agricultural production systems**

**Table 2** shows the results of logit models using the stepwise procedure (backward deletion) in SPSS. The use of stepwise procedures when the object of the analysis is prediction and there is no formal theory to guide the selection of variables to enter the model. The overall goal of the procedure is to maximize R2 while minimizing the number of predictors. In our case, we employed common sense logic. We used the arguments in the instrumentation section to explain the relevance of questions to the study objective and the size of the correlation with the dependent variable. Based on this, we selected the initial set of six variables shown in **Table 2**. In all models, all variables have the anticipated sign in the right direction, i.e., all the variables should have a positive effect on the likelihood of CAAs supporting farmer's market. The best model is Model 1, with three variables predicting CAAs support for local farmers' market. Those CAAs with programs supporting community based food production, those that encourage clients to participate in urban agriculture and those that believe that community-based farming is better than corporate farming for preserving the quality of the land are more likely to support the local farmers market. These three variables have coefficients of 3.380, 1.208 and 0.801 respectively. The model Chi-square 45.289 was significant at the 0.001 level. These variables produced R2 of 0.319, odds ratio of 10.806, 3.347 and 2.228 respectively. The size of the odds ratios indicates that there would be substantial improvement in support for farmers markets with a unit change in the

For example, CAAs with programs supporting community-based agriculture are almost 11 times more likely to support farmers markets. We believe that support for farmers markets is the most meaningful measure of CAAs overall support for community-based agriculture, since this form of support translates into income for

The data show that there is moderate support for community based agriculture (see **Figure 3**). 53% of CAAs report that they support farmers markets and 48 and 36% report program support for community-based and urban agriculture respectively. These results are encouraging, given that community-based agriculture is not

farmers and the community in general through the multiplier effect.

71% agree and 20% strongly agree. The pattern also shows that there is very strong agreement among CAAs' leadership that small farms are better for the environment than large cooperate farms. 67% of CAAs' leadership agrees with the statement, and 18% strongly agree. Only 15% of CAAs' leadership can be collectively categorized as strongly disagree, disagree or are indifferent to the statement that small farms are better for the environment. A similar pattern is also evident among CAA leaders with respect to their opinion concerning the duty of citizens to purchase (promote) locally grown produce. Here, 69% agree and 23% strongly agree that it is the duty of good citizens to purchase (promote) locally grown farm products. CAA leaders' pattern of response to the statement that vibrant community-based farming is more likely to keep family farmers on the land than large corporate farming is similar to the overall pattern response shown in **Table 1**. Generally, the data in **Figures 2** and **3** and **Table 1** show that CAAs believe in organic/sustainable and community-based food production system. CAAs support for a sustainable food production system speaks to their potential to serve as a linchpin in their communities for promoting sustainable agricultural production systems and ensuring collective impact.

*DOI: http://dx.doi.org/10.5772/intechopen.84385*

*Logistic regressions results: Factors that influence the likelihood of supporting local farmers market.*

**94**

*Accounting for the Impact of Sustainable Agriculture: The Role of Community Based… DOI: http://dx.doi.org/10.5772/intechopen.84385*

71% agree and 20% strongly agree. The pattern also shows that there is very strong agreement among CAAs' leadership that small farms are better for the environment than large cooperate farms. 67% of CAAs' leadership agrees with the statement, and 18% strongly agree. Only 15% of CAAs' leadership can be collectively categorized as strongly disagree, disagree or are indifferent to the statement that small farms are better for the environment. A similar pattern is also evident among CAA leaders with respect to their opinion concerning the duty of citizens to purchase (promote) locally grown produce. Here, 69% agree and 23% strongly agree that it is the duty of good citizens to purchase (promote) locally grown farm products. CAA leaders' pattern of response to the statement that vibrant community-based farming is more likely to keep family farmers on the land than large corporate farming is similar to the overall pattern response shown in **Table 1**. Generally, the data in **Figures 2** and **3** and **Table 1** show that CAAs believe in organic/sustainable and community-based food production system. CAAs support for a sustainable food production system speaks to their potential to serve as a linchpin in their communities for promoting sustainable agricultural production systems and ensuring collective impact.

### **6.2 Predicting support for sustainable agricultural production systems**

**Table 2** shows the results of logit models using the stepwise procedure (backward deletion) in SPSS. The use of stepwise procedures when the object of the analysis is prediction and there is no formal theory to guide the selection of variables to enter the model. The overall goal of the procedure is to maximize R2 while minimizing the number of predictors. In our case, we employed common sense logic. We used the arguments in the instrumentation section to explain the relevance of questions to the study objective and the size of the correlation with the dependent variable. Based on this, we selected the initial set of six variables shown in **Table 2**. In all models, all variables have the anticipated sign in the right direction, i.e., all the variables should have a positive effect on the likelihood of CAAs supporting farmer's market. The best model is Model 1, with three variables predicting CAAs support for local farmers' market. Those CAAs with programs supporting community based food production, those that encourage clients to participate in urban agriculture and those that believe that community-based farming is better than corporate farming for preserving the quality of the land are more likely to support the local farmers market. These three variables have coefficients of 3.380, 1.208 and 0.801 respectively. The model Chi-square 45.289 was significant at the 0.001 level. These variables produced R2 of 0.319, odds ratio of 10.806, 3.347 and 2.228 respectively. The size of the odds ratios indicates that there would be substantial improvement in support for farmers markets with a unit change in the independent variables.

For example, CAAs with programs supporting community-based agriculture are almost 11 times more likely to support farmers markets. We believe that support for farmers markets is the most meaningful measure of CAAs overall support for community-based agriculture, since this form of support translates into income for farmers and the community in general through the multiplier effect.

## **7. Discussion**

The data show that there is moderate support for community based agriculture (see **Figure 3**). 53% of CAAs report that they support farmers markets and 48 and 36% report program support for community-based and urban agriculture respectively. These results are encouraging, given that community-based agriculture is not

*Multifunctionality and Impacts of Organic and Conventional Agriculture*

**94**

**Model 1**

> **b**

2.380\*\*\* 1.208\*\* 0.801\*\*

2.228

0.641 0.213

1.237

0.208 0.160

1.173

0.155 0.099 −1.191

116.369

45.991\*\*\*

0.323

1.104

1.167

1.232

0.203

1.225

1.898

0.563

1.755

0.510

1.666

3.347

1.187\*\*

3.278

1.159\*\*

3.187

1.146\*\*

3.146

10.806

2.411\*\*\*

11.150

2.420\*\*\*

11.251

2.414\*\*\*

11.173

Program

Urban

Land Environment Cooperatives

Promote Constant −2 log likelihood

Chi-square

R square

*\*\*p < 0.05.*

**Table 2.**

*Logistic regressions results: Factors that influence the likelihood of supporting local farmers market.*

−8.620\*\*\*

117.071 45.289\*\*\*

0.319 *Note: b = unstandardized coefficient estimate; eb = exponential of b (the odds ratio);\*\*\*p < 0.001.*

−8.818 116.698 45.662\*\*\*

0.321 *Program = CAAs with programs that support community-based food production; urban = CAAs which encourage its clients to participate in urban agriculture (grow fresh fruits and vegetables for home* 

*use); land = opinion on the statement that community-based farming preserves the quality of land better than large corporate farms; environment = opinion on the statement that community-based farming* 

*preserves the environment better than large corporate farms; cooperatives = extent of favorable perception of farmers' cooperatives; promote = opinion on the duty of citizens to buy locally grown farm produce.*

−1.353 116.425 45.936\*\*\*

0.322

**eb**

**b**

**eb**

**b**

**eb**

**b**

**eb**

**Model 2**

**Model 3**

**Model 4**

seen as a program priority for CAAs, considering the demand on their resources for other programs to address persistent poverty in the BBS [40]. The overwhelmingly strong positive opinion among CAAs concerning the use of organic methods, the role of citizens in supporting farmer's markets, the value of community-based farming in preserving the land, environment and family farms and their favorable view of cooperatives indicate that CAAs have the potential for providing strong institutional support for the development and promotion of sustainable agricultural production systems at the community level. In conducting 40 listening session with CBOs across 9 states in the Black Belt region, we discovered that advocacy is a core component of their programs. Thus, they possess the requisite experience and skills to advance sustainable agricultural production systems. CBOs represent a form of social capital and their networks foster coordination and cooperation for the common good and the promotion of sustainable behavior [9, 10, 24, 41]. Social capital is able to reduce transaction cost associated with collective action directed at solving complex problems. Increased social capital is linked with movement toward sustainable agriculture. Collective action facilitated by community organizations such as CBOs can make a difference in achieving goals because the farmer and community are more proactive in solving their own problems and are no longer dependent on the whims of government or other outside entities [20, 42]. In the context of developing and promoting sustainable agricultural systems, CBOs and their networks provide the institutional support that empowers communities to be more self-regulating and to act independently, collectively and proactively.

Promoting and developing organic/sustainable agriculture is unlike solving a technical problem, although the tendency is to treat it like a purely technical problem. A technical problem by definition is straightforward because the solution is known and protocols for implementing solutions are well defined and results are predictable and in many cases a single organization has the capacity to solve it, for example producing a crop of corn or building a bridge. On the other hand, developing and promoting organic/sustainable food production system is akin to solving an adaptive problem. An adaptive problem is complex. Its solution is not known or well understood and even when solutions are known, it requires several organizations working in unison to solve it. Developing a sustainable food production system is a collective impact initiative that seeks to find a solution to an adaptive problem. Such an initiative requires many stakeholders—a network of organizations—from different sectors learning and working together to systematically address the system of variables that will define a solution to the problem. In addition, all involved stakeholders must be committed to changing their own behavior in order to adapt to the change they seek to bring about [12]. CBOs, as we have discussed, are indispensable members of this network.

**97**

**Author details**

Terrence Thomas1

2 Ege University, Izmir, Turkey

provided the original work is properly cited.

\*, Cihat Gunden<sup>2</sup>

3 Smart-Eco Consulting, Silver Spring, MD, USA

\*Address all correspondence to: twthomas@ncat.edu

1 North Carolina A&T State University, Greensboro, NC, USA

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

and Befikadu Legesse3

*Accounting for the Impact of Sustainable Agriculture: The Role of Community Based…*

*DOI: http://dx.doi.org/10.5772/intechopen.84385*

*Accounting for the Impact of Sustainable Agriculture: The Role of Community Based… DOI: http://dx.doi.org/10.5772/intechopen.84385*
