1. Introduction
According to data from 2023, the prevalence of moderate or severe food insecurity was 31.9 percent in rural areas compared with 29.9 percent in periurban areas and 25.5 percent in urban areas. Globally and in all regions except Northern America and Europe, the prevalence of food insecurity, at both levels of severity, is consistently higher in rural areas than in urban areas (
FAO et al. 2024). In this context, one of the ways to end poverty and food insecurity includes the development of agricultural and rural livelihood through actions/movements that aim to improve the quality of life of those living in these regions, for example, through solidarity economy enterprises. The historical roots of the solidarity economy are in the mid-nineteenth century Europe, where co-operative movements developed in response to social issues resulting from the Industrial Revolution. The foundations of the solidarity economy are solidarity, the equal sharing of profits, and self-management (
Singer 2002).
In the European and Latin American contexts, the concepts of the solidarity economy have developed in different ways.
Da Ros (
2007) notes that the term “solidarity economy” was forged in Latin America in the early 1980s, using a markedly political discourse and playing a relevant role in the struggle against the social problems intrinsic to the current economic systems (
Guerra 2004). In Europe, the emergence of the solidarity economy dates to the late 1980s and developed both at the theoretical–academic and practical levels through insertion and proximity services (
Da Ros 2007).
In Brazil, the first solidarity economy initiatives occurred after the economic and social crisis of the 1970s (
Ribeiro and De Müylder 2014). However, it was not until 2000, with the election of a leftist president, that effective public policies aimed at supporting solidarity economy organizations became a priority for generating income and encouraging social integration (
Gaiger 2013). Many of the guidelines outlined in the Declaration of the Brazilian Solidarity Economy originated from debates that occurred in the Brazilian Solidarity Economy Forum (
FBES 2003). In 2003, the National Secretariat of Solidarity Economy (SENAES) was created by the left-wing government, while the National Program for Incubators of Popular Co-operatives (Proninc) was reinstated (
Singer 2009). In 2013, through Decree No. 8163, the National Program for Supporting Social Associations and Co-operatives (PronaCPSocial) was founded with the purpose of “planning, coordinating, executing and monitoring actions aimed at the development of social co-operatives and social solidarity economic enterprises” (
Brasil 2013b).
Co-operatives, the group addressed in this study, occupy a crucial position within numerous sectors and stand out as an important group of solidarity organizations, contributing to food security and poverty reduction in different areas around the world (
Sánchez-Hernández and Castilla-Polo 2021). However, there are other types of organizations within the solidarity economy, such as mutual societies, associations, and informal groups, that follow the principles of solidarity, democracy, and self-management, with a focus on human life and the dignity of the worker (
Monzon and Chaves 2008;
Telles et al. 2020;
Castilla-Polo and Sánchez-Hernández 2020;
Sánchez-Hernández and Castilla-Polo 2021).
According to data from the national survey of SEEs carried out by the National Secretariat for Solidarity Economy (SENAES;
Brasil 2013c), there were 19,708 solidarity economy organizations in Brazil in 2013, of which almost 55% (10,793) functioned exclusively in rural areas. Although these numbers are slightly lower when compared to those from 2007 (
Brasil 2007) when the number of enterprises was 21,859, there has been significant growth in relation to the numbers in the 1970s, when only 139 SEEs existed in Brazil (
Ribeiro and De Müylder 2014).
During the 2nd National Conference on Sustainable Rural Development and Solidarity in 2013, policies were established to stimulate the development of mechanisms that could help improve management on family farms and ensure partnerships with other farmers, including co-operatives and participation in the solidarity economy, as these mechanisms are extremely relevant for strengthening family agriculture and consequently for sustainable rural development (
Brasil 2013a). In this context,
Christoffoli et al. (
2013) highlighted the importance of SEEs for the maintenance of family farming and as a means to support sustainable rural development; the alternatives of self-management and collective thinking offer possibilities for more economically, socially, and environmentally sustainable rural and social organization and production. Subsequently,
Martínez-Campillo and Fernández-Santos (
2017) argued that the growing demand for these organizations can trigger social change, yet there was a need to use indicators that measure the impacts of this change.
Other studies also showed the positive effects of SEEs on sustainable development and in combating social exclusion, demonstrating outcomes such as social innovation, natural resource preservation, economic autonomy, local development, and social transformation (
França Filho 2008;
Singer 2014;
Martino et al. 2016;
Rover et al. 2017). Additionally,
Arruda et al. (
2015) used a case study to highlight the relevance of solidarity economy ventures for sustainable rural development. The authors suggested that development must be evaluated through advances in human quality of life, including economic, social, environmental, political and cultural aspects.
According to the
Olmedo and O’Shaughnessy (
2022) study, rural-community-based social enterprises play a relevant role in contributing to rural development. The same authors stated that rural social enterprises contribute to multidimensional development (social, economic, and environmental), combining the community characteristics and local focus with the emphasis on the development of external relationships, with social entrepreneurship as well as innovative, locally focused solutions, suggesting that the way in which rural social enterprises work aligns with the principles of an endogenous rural development approach.
Thus, the activities of rural solidarity economy enterprises (RSEEs) have a concrete impact on important social indicators, especially in terms of food security, access to resources, and quality of life, not only for the associated farmers but also for consumers and the surrounding community. Thus, it is important to evaluate the performance of an enterprise by measuring the social transformation generated through their organizational activities (
Stevens et al. 2015).
Because of their social role, the decision-making processes in SEEs encompass multiple points of view and a wide range of criteria. As such, decision-making tools and/or instruments must incorporate the multiple aspects presented in the decision-making process, which leads to the use of the multicriteria decision aid methodology.
Lee and Nowell (
2015) noted the complexity of evaluating performance in the nonprofit sector, as the outcomes are often difficult to measure since many are not quantitative. For this reason,
Grieco et al. (
2015) argued that the concept of performance evaluation in social organizations, including charitable enterprises, is a major challenge for scholars, mainly because of the difficulty of converting qualitative data related to the social mission into quantitative metrics.
In this context,
Ebrahim and Rangan (
2014) offered three different categories to evaluate the results of social enterprises: outputs (immediate results); outcomes (medium- and long-term results); and impacts (impacts on the roots of social problems or social transformation). However, it is impractical for some organizations to assess long-term results and social impacts, particularly in poorly structured enterprises or those in the early stages of development. According to
Ebrahim and Rangan (
2014), what is most important is developing metrics and structured measurement systems based on the organization’s mission and objectives.
Therefore, the present study developed and applied a new instrument for the performance evaluation of rural solidarity economy enterprises (RSEEs) through the use of MCDA methodology, which can subsequently be used to support management in RSEEs. Thus, this study is novel in that it developed a new performance evaluation instrument that is applicable to solidarity economy enterprises, while also contributing to the literature on the subject, as there are few studies that have addressed the performance evaluation of SEEs. The proposed approach aims to support decision making in these enterprises based on the MCDA methodology, in particular using ELECTRE-TRI. The methodology was applied to solidarity economy co-operatives (co-ops) in the southwest state of Paraná, Brazil, to assess to the applicability of the model and conduct a sensitivity analysis. This paper is structured as follows:
Section 2 discusses the ELECTRE-TRI method and presents the data collection methodology;
Section 3 describes the proposed model together with the results;
Section 4 discusses the application of the model; and
Section 5 draws conclusions and suggestions for future research.
3. Results
The results of applying the model classified the participating co-ops into three levels of performance based on the principles of the solidarity economy. The three levels were defined by the decision makers and the analyst to evaluate participants’ performance in the six dimensions, based on the principles of solidarity economy), as well as the limits of the reference boundaries between the levels. This was essential so that each alternative could be safely allocated to one of the levels defined in the model. To define the limits for the criteria, the degree of importance of the weight that each criterion exerted on the problem for the decision maker was considered. In
Figure 1, the dark green indicates the allocation of the alternative to a certain category, and the light green indicates its possible reallocation into another category.
From
Figure 1, we can see that for the dimension “Democratic management and legalization”, the majority of co-ops presented average performance (
, and only co-op 4 was evaluated as good (
In “Valuing human labor”, no co-op achieved good performance (
, two co-ops (3 and 6) performed poorly (
, and the other co-ops presented average results (
). In “Technological and economic feasibility”, three co-ops (1, 4, and 8) presented a good result (
), while four (3, 5, 6, and 7) had a poor result (
). For “Commitment to minorities”, the performance was the poorest among all co-ops, since five (2, 3, 5, 6, and 7) performed poorly (
), and the others only achieved an average result (
). The results for “Environmental sustainability” also showed that no participating co-op achieved good performance: 50% were average (
), and 50% were poor (
) in this dimension. The best results were obtained in the “Co-operation and solidarity” dimension, since four co-ops (1, 2, 4 and 8) achieved good performance (
) and only one (3) showed poor performance (
).
Subsequently, we conducted a sensitivity analysis of the model in relation to the credibility index (), which refers to the minimum value of , to validate the outranking relationship among the alternatives. For this, was given a value between 0.5 and 1. Thus, sensitivity analysis was performed for the degree of credibility by adopting = 0.6, = 0.7, = 0.8, and = 0.9. The thresholds of 0.5 and 1 were excluded because they were considered extremes, i.e., 0.5 was a very low requirement, and 1 was very high.
Table 3 shows the distribution of co-operatives in the performance classes after the sensitivity analysis for each degree of credibility.
From
Table 3, we can see that changes in the parameters based on the degree of credibility (
) caused small variations in the classification of co-operatives, especially for a degree of credibility (
) of 0.9. This was due to the fact that the credibility index (
) in the present model had a low demand (0.6).
For the sensitivity analysis referring to the weights given to the criteria, we analyzed all criteria by assigning the same weight (
= 0.167).
Table 4 shows the distribution of the surveyed co-ops in the models’ performance classes after sensitivity analysis with the weighted criteria.
With the changes in the parameters given the criteria weights, there were no variations in the classification of the participating co-ops. Considering the results of the two sensitivity analyses, we conclude that the model used to evaluate the performance of the RSEEs through the ELECTRE TRI-C was stable, as the alternations imposed on the parameters did not significantly affect the results. It is important to note that IRIS 2.0 software used only one pessimistic agreement variant of the ELECTRE-TRI method, so the sensitivity analyses performed here considered only the pessimistic procedure.
4. Discussion of Results
The importance of tools that convert qualitative data related to social goals into quantitative metrics was highlighted by
Grieco et al. (
2015). Thus, the model developed and applied in this study met this challenge by transforming the subjectivity of qualitative data in relation to RSEEs into objective and quantitative indicators. However, it is important to highlight that some subjectivity remains after this kind of transformation.
The model presented herein, consisting of 36 indicators across 6 categories, focused on evaluating performance in terms of the principles of the solidarity economy and is consistent with the argument put forth by
RIPESS (
2016) that the contributions of SEE organizations should be assessed based on their impact on local, national, and international development. In particular, the assessment should consider the creation of permanent jobs, development of new services, better standards of living, contributions to gender equality, protection of the environment, and the ethical creation of wealth, all of which are included in the principles of the solidary economy.
The use of the ELECTRE-TRI methodology allowed for the classification of the participating co-ops into three performance classes: poor, average, and good. Thus, decision makers have information at hand that can contribute to organizational learning and continuous improvement. Following
Pereira and Mota (
2016), the model offers recommendations for decision making and enables learning about the problems in question. The classification of the participating co-ops into three performance classes was made possible by applying the model in IRIS 2.0 Demo software.
Ribeiro (
2016) noted that based on the indicators defined with decision makers, IRIS 2.0 software allows the visualization of the results of the ELECTRE-TRI method through the classification of alternatives (in this study, the participating co-ops).
Table 5 presents the summary statistics of the survey results for
= 0.6.
We can see that the dimension in which half of the co-ops (50%) showed a good performance level was “Co-operation and solidarity”. However, it should be pointed out that in the dimensions “Valuing human labor”, “Commitment to minorities”, and “Environmental sustainability”, none of the co-ops were evaluated as good. Furthermore, in most of the dimensions, co-ops showed average performance, except for in “Technological and economic viability” and “Commitment to minorities”, for which at least half (50% and 62.5%, respectively) presented poor performance. The low performance of the co-operatives in some dimensions reflects the characteristics of the geographic region (southwest Paraná) where these enterprises were located. In the aforementioned region, the majority of the population was white (
IBGE 2023), with conservative customs. Furthermore, local rural production was mostly conventional, with the massive use of synthetic additives, pesticides, and other chemical substances. The model pointed to those dimensions as requiring further attention. The classification of co-ops based on six evaluation dimensions comes from
Bagnoli and Megali (
2011) who argue that social enterprises need a multidimensional management control system, since the performance of this type of organization assumes multiple profiles.
Table 6 presents the individual performance of each co-op in the six dimensions. In the table, the red color is related to class (
), indicating poor performance in the aforementioned dimension. The yellow color indicates average performance (
) and the green color indicates good performance (
).
From
Table 6, we can see that although these co-ops participated in the same central organization and shared the same organizational values, their performance in each of the dimensions was quite different. The dimensions that were critical for each co-op can also be observed, enabling the enterprise to direct efforts at improving performance in the areas where the outcome was poorer than expected. We highlight co-operatives 3, 6, and 7, which presented poor performance (
C1) in at least four dimensions and did not achieve a good evaluation (
C3) in the other two dimensions. These co-operatives require centralized efforts directed at improving all the dimensions evaluated herein.
Although the principles of the solidarity economy are the values that guide co-operative activities, the results for each of the evaluation dimensions demonstrated that the participating co-ops could improve their performance.
Helmig et al. (
2015), in their study on the managerial importance of organizational values, identified that the values that generally underpin nonprofit organizations have positive effects on their success. It is important to highlight that performance evaluation contributes to the success of these RSEEs in the short and long terms.
Consequently, our study contributes to the context of multidisciplinary sustainable development. Furthermore, according to
Meramveliotakis and Manioudis (
2021), in the face of recent crises (economic crisis and COVID-19), many theories, perspectives, and analyses of the workings of society are starting to be challenged. Among them are the efficiency of free markets and the accompanying conventional thinking of economic development and sustainability. In this context, solidarity enterprises that seek to develop communities and territories, as is the case of the RSEEs in this study, constitute an alternative to conventional development.
In addition, the model developed and applied in this study contributes to the self-awareness and growth of co-operatives.
Dias and Mousseau (
2002) noted that the IRIS methodology is a process that fosters learning and the progressive definition of variations in inputs and outputs. Thus, we can affirm that the proposed model is appropriate for addressing the problem of performance evaluation based on the principles of the solidarity economy for RSEEs. Furthermore, the methodology is useful for the enterprise to remain accountable to both internal and external stakeholders, which is in line with
Bagnoli and Megali (
2011), who found that organizations with social ends have multiple stakeholders, as they respond to society and not to shareholders. Finally, the sensitivity analysis showed that the model is stable.
5. Conclusions
The present study developed a performance evaluation model for rural solidarity economy enterprises based on the principles of the solidarity economy. The approach aims to support decision making in these enterprises using the MCDA methodology, particularly ELECTRE-TRI. The model was applied to solidarity economy co-operatives in the southwest state of Paraná, Brazil, to test the applicability of the model and perform sensitivity analyses.
The results of this study showed that the use of the ELECTRE-TRI method was fundamental for classifying the co-ops into three performance classes considering previously defined criteria based on the principles of solidarity economy. The model enabled an evaluation of the performance of the enterprises across six dimensions. From this, it was possible to identify the dimensions that require attention in general and those that should be addressed in particular in each of the participating co-ops. Based on these results, organizational and improvement activities and actions can be developed and implemented.
This analysis contributes to our understanding economic and social indicators by offering improvement strategies for the professionalization and strategic management of RSEEs, thus strengthening these enterprises and, consequently, family agriculture. This study also makes an important academic contribution by filling a gap in the literature, presenting a new instrument for evaluating the performance of rural organizations with social goals, based on the principles of the solidarity economy and using the MCDA methodology.
Nevertheless, this analysis is limited by the fact that the model was applied to a small group of co-ops associated with one central organization and therefore cannot be generalized across all cases. Furthermore, we highlight that the data are from 2018 and do not reflect the current situation of the co-operatives studied. However, the model can be applied to other enterprises in the solidarity economy and adapted to the particularities of each case. Future studies may apply similar analyses to other objects of study and propose new models and/or performance evaluation instruments applicable to the diverse range of solidarity economy organizations. The model can also be used continuously in the same co-operatives for current data collection and accurate results. Furthermore, the model can be adapted to consider several criteria relevant to the long-term success and sustainable development of these co-operatives. Criteria that were not addressed in this study due to the limitations of the research included innovation capacity, customer satisfaction, stakeholder relationships, and human resource management, among others.