Open-access Performance determinants for agroindustrial projects in collective actions of small farmers

Determinantes de desempenho para projetos agroindustriais em ações coletivas de pequenos agricultores

Abstracts

Abstract  The important economic and social role of agroindustrial collective actions does not eliminate the challenges related to the sustained feasibility of these enterprises. This article presents and discusses the main determinants that affect the performance and feasibility of collective agroindustrial projects, assessing the importance of each determinant for establishing the future performance of enterprises. A systematic literature review supported the structuring of the proposed analytical framework, which suggested the use of 24 determinants grouped into five factors. Afterwards, a panel of 20 experts used a multiple-criteria decision-making method, the Simple Multi-Attribute Rating Technique (SMART), to evaluate the relative importance of the determinants proposed by the model. The framework indicates the importance of each determinant on the performance of the collective agroindustrial projects, allowing the user to apply it with a decision-making tool. The proposed model combines and incorporates a wide number of sparse determinants in other works and highlights the factor “management, operation and finance” as a factor of success in making projects feasible.

Keywords:  collective action; farmers’ organization; agroindustrial; family farmer; performance; feasibility


Resumo  O importante papel econômico e social das ações coletivas agroindustriais não elimina os desafios relacionados com a viabilidade sustentada destas organizações. Este artigo apresenta e discute os principais determinantes que afetam o desempenho e a viabilidade dos projetos agroindustriais coletivos, avaliando a importância de cada determinante para o estabelecimento do desempenho futuro da iniciativa produtiva. O desenvolvimento de uma revisão sistemática de literatura apoiou a estruturação do framework analítico proposto, que sugeriu a utilização de 24 determinantes agrupados em cinco fatores. Em seguida, um painel com 20 especialistas determinou a importância relativa de cada determinante, recorrendo a técnica multicritério SMART para ponderação. O framework indica a importância de cada determinante no desempenho dos projetos agroindustriais coletivos, permitindo aos stakeholders destas organizações a aplicação como um instrumento de tomada de decisão mais assertivo. O modelo combina e incorpora um amplo número de determinantes, superando outros estudos que consideram um número limitado, e, ainda, destaca o fator “Gestão, Operação e Finanças” como condição relevante para o sucesso dos projetos.

Palavras-chave:  ações coletivas; organizações de agricultores; agroindustrial; agricultura familiar; desempenho; viabilidade


1. Introduction

The identification and analysis of project success determinants aimed at increasing agricultural and agroindustrial productivity have been the focus of attention of researchers in economics, management and sociology, among other fields. These projects have important potential to contribute to the improvement of agricultural productivity and yield and, consequently, the sustainable reduction of hunger and poverty (International Fund for Agricultural Development, 2016).

In this context, agroindustrial collective actions stand out for the relevance of their economic and social roles. Around the world, most rural development policies are based on promoting the development of collective actions, intermediated by associations and cooperatives of small farmers. Found in large numbers and having extensive representativity, these enterprises play a role in creating more favorable conditions for small rural farmers (Hellin et al., 2009).

A collective action can be understood as the joining of forces of two or more actors (individuals, companies or institutions) to obtain a specific desired result (Narrod et al., 2009). Therefore, collective action stem from the identification of a common interest by a group of individuals or entities, and recognition that this interest could be served through joint, coordinated actions (Olson, 1965). In agroindustrial systems, these collective initiatives can assume various forms, such as cooperatives, associations, networks, clusters, local production arrangements, and production agglomerates (Ménard & Klein, 2004). However, cooperatives and associations have been the most numerous and successful initiatives (Wenningkamp & Schmidt, 2016).

Public and private initiatives to promote the production capacity and commercialization of family farms have given these entities an important strategic role in orsithe pursuit of territorial economic development and social inclusion (Orsi et al., 2017). The positive effects of these enterprises are widely recognized and provide important conditions for the feasibility of small-scale agricultural activities (Latynskiy & Berger, 2016; Ahado et al., 2024). In Brazil, around 3.9 million establishments are classified as family farming or 77% of the total, responsible for 67% of the people employed in agriculture and 23% of all agricultural production (Instituto Brasileiro de Geografia e Estatística, 2019.)

However, collective production and governance structures have restrictions and conditions particular to these enterprises (Ensslin et al., 2014; Briggeman et al., 2016) that impose considerable challenges for management practices and economic feasibility. These challenges include: (i) conflicts of interest inherent to agroindustrial cooperatives (Cook, 1995); (ii) the presence of governance conditions intrinsic to initiatives involving groups of people (Wilson et al., 2013); and (iii) lack of resources and/or heterogeneity of the socioeconomic conditions of the farmers involved (Di Gregorio et al., 2012). Therefore, the characteristics of collective rural projects significantly limit the performance and feasibility of production initiatives. Despite the importance and potential of these initiatives, the results for many enterprises, especially in developing countries, have revealed many unsuccessful cases and failures (Shiferaw et al., 2011; Neves et al., 2019), with ambitious, unachieved objectives (Markelova & Mwangi, 2010).

In spite of the efforts of researchers and public policymakers around the world, knowledge about the determinants to measure the effectiveness of collective production initiatives and their capacity to generate benefits for their members is still limited (Latynskiy & Berger, 2016). This knowledge gap is even more pronounced when looking at agroindustrial enterprises. Defined here as production units that operate within the agro-industrial system (SAI), that is, in the set of activities that contribute to the production of agroindustrial products, from the production of raw materials to the arrival of the product to the consumer (Batalha, 2021).

The literature is not conclusive in pointing out a model that comprehensively consider the peculiarities of rural collective action in the performance evaluation process (Donovan et al., 2017). It is possible to identify clear limitations in the literature (Sellare et al., 2023). Most studies that have investigated the feasibility of collective rural organizations have used a limited number of characteristics and attributes, and many fundamental factors for efficient analysis are often overlooked (Gyau et al., 2014). Most have focused on assessing the characteristics of farmers (individuals) and not those of enterprises (groups) (Serigati & Azevedo, 2013), thereby limiting the quality of the results obtained.

In view of the above, this article explores which determinants affect the performance and feasibility of collective agroindustrial projects. It also assesses the importance of each determinant for establishing the future performance of enterprises. To achieve these objectives, this article proposes a conceptual framework that incorporates the main performance determinants for collective agroindustrial projects. The investigated performance determinants must be understood as the factors, conditions or characteristics of diverse nature and origin that affect the performance of the project and the reach of the expected objectives.

This framework was validated by experts with recognized experience in the rural development projects. The proposed analytical model enables identifying and understanding the possible effect of each determinant on the future performance of a project, making it possible to select and develop more efficient production projects that have a greater likelihood of success. Furthermore, targeted management actions can enhance the results and competitiveness of the small rural organization, which often lacks the essential competitive conditions in increasingly dynamic markets. This context, considering that the prosperity of cooperatives in Brazil is a decisive factor for food security and sustainability of agricultural activities in the country (Ferreira da Silva et al., 2022).

In addition to this introduction, the article presents a brief theoretical foundation, followed by a detailed methodology of the investigation, moving on to the presentation and discussion of the results, and the conclusions. At the end, the reader has access to the references used and the appendix.

2. Theorical Foundation

Rural collective actions may take several institutional forms, the most common being rural cooperatives and associations. Regardless of the institutional form, the common and central point between the collective organizational models of the agro-industrial system is, according to Markelova et al. (2009), the voluntary action of a group of people in pursuit of a shared goal.

These collective organizations act with multiple purposes, promoting many services to its members with the function of raising the economic and social welfare (Corsi et al., 2017), for example, adding value to the activity, reducing transaction costs, and accessing new markets for marketing. In small-scale agriculture, the benefits are even more evident, considering the great challenges of this segment in relation to the organization of production, adding value and marketing (Silva & Nunes, 2023).

The collective enterprise not only generates benefits to the producers, but it is also worth mentioning that they face particular challenges, especially the cooperatives, which are (Vitaliano, 1983):

  1. Free rider problem: individuals who access benefits without incurring costs to the organization;

  2. Horizon problem: the member tends to seek short-term benefits from the organization, as there is no incentive to accumulate capital;

  3. Portfolio problem: acting together, individuals tend to take greater risks than acting alone;

  4. Control problem: wrong choices may occur due to collective control – associates, professional managers, councils;

  5. Problem of influence costs: some individuals can influence decisions for particular interests;

The performance of the venture also depends on other variables related to the group condition, such as the level of trust, reputation, and reciprocity among members (Ostrom, 1990). The theoretical foundations are best presented in section 4.1 and 4.2, considering the results of the systematic review. Now the study moves on to its research method.

3. Methodology

In order to build the conceptual framework, a systematic literature review was performed, with the objective of identifying and qualifying the determinants found in the literature. To assess the relative importance of each determinant, 20 experts were then interviewed, using the multiple-criteria method called the Simple Multi-Attribute Rating Technique (SMART). The procedures will be detailed below.

3.1. Systematic literature review (SLR)

Systematic literature reviews (SLR) enable researchers to recognize and assess existing intellectual knowledge on a topic, making it possible to create research questions and incorporate more solid knowledge (Tranfield et al., 2003). The study protocol was divided into three stages: planning, execution, and analysis of the results (Almeida Biolchini et al., 2007). The guiding question was: “Which determinants impact the performance of agroindustrial collective actions?”. A set of keywords that represent the constructs “Agroindustrial” (“Agricultural; “Agribusiness; “Farm” and “Rural”), “Collective Action” (“Collective Action and Common pool resource”) and “Performance” (“Performance”; “Management”; “Viability”; “Feasibility”; “Effective”; “Income”; “Profit” and “Result”) were identified and tested on search platforms.

The information search was conducted in three databases: Web of Science, Scopus and Scielo. Only articles published in English and Portuguese were selected. The protocol did not define the initial period for the search, but the data extraction occurred in April 2018. The SLR was performed with support from the software StArt (State of the Art through Systematic Review), provided by the Federal University of São Carlos (UFSCar). Figure 1 presents the stages carried out and the results of each filter adopted.

Figure 1
Structure Systematic Literature Review

The initial search yielded 1,487 articles, of which 353 were excluded for being duplicates. Reading the title, abstract and keywords (Filter 1) resulted in 154 articles selected. Inclusion and exclusion criteria were applied to support the decision, for example, exclusion of studies classified in non-adherent research areas (eg, biology and biotechnology), and studies that did not directly address the performance of collective action. The other filters (2 and 3) also applied exclusion and selection criteria. After reading the introduction and conclusion (Filter 2), 74 articles were chosen for full reading (Filter 3). Following this reading, 51 articles were selected and nine were included for cross-referencing, for a total of 60 studies used.

The stage identified 454 determining factors for the success of the collective enterprise. Considering the allocation in five factors the percentage distribution found was the following: 36.10% - “group characteristics”; 23.90% - “trust, commitment and participation”; 22.34% - “management, operation and finances”; 9.35% - “individual characteristics”, and 8.31% - “local infrastructure”. The duplicate and similar determinants were grouped, and considering the premises of the study, 24 different determinants were selected and organized into five factors.

The study considers that the success of the collective enterprise can be defined in several ways. The success or failure of the performance achieved depends on the individual objectives and goals of each group (Lopes et al., 2015). Performance is a subjective phenomenon that can be interpreted differently according to the socio-economic context and the audience in question (Ishak et al., 2020). The experts were guided to consider success as the enterprise's ability to achieve the productive and economic goals indicated in the initial project.

3.2. Hierarchization of the factors and determinants

In a prior stage, a panel of experts was invited to validate and indicate the importance of each determinant identified in the bibliographic search. To quantify and transform the importance into a numerical scale, a multiple-criteria decision-making method, the Simple Multi-Attribute Rating Technique (SMART), which was developed by Edwards (1971), was applied. The tool is based on the premise that an alternative is formed by certain criteria and their values, and each criterion has a weight that represents its importance in comparison to other criteria (Siregar et al., 2017). Therefore, it is possible to adequately convert the importance (weights) of factors into real numbers (Velasquez & Hester, 2013).

The application of SMART was structured into two stages (Gomes & Gomes, 2019). In the first stage, experts rank the criteria according to their perception of importance for each one, from most important to least important. To do this, interviewers asked the interviewee to “rank in descending order the importance of each factor”.

In the next stage, experts assess the relative importance of each criterion by answering the following question: “compared to the least preferred factor, how many times do you consider the other factors more important for the project's performance?”. This process starts with the least important criterion, which receives a weight equal to 10 units (following the technique's premises), up to the most important criterion, which receives higher and proportional weights according to its importance.

Finally, it is necessary to standardize the scores in relation to the total points assigned in the judgment. Thus, following the proposal of Goodwin & Wright (2014), the maximum value found is standardized as “1” and the others are proportional to this value, up to the minimum limit of “0”

Divided into three sections, the tool seeks to characterize the experts interviewed, then qualify each according to their knowledge and experience in the topic and, finally, obtain the experts’ judgments in relation to each factor and determinant.

The selection of the experts started with identification of the institutions considered relevant in the process of implementing and developing rural programs and projects in Brazil and in the state of São Paulo. They are: Coordination of Sustainable Rural Development of the State of São Paulo – CDRS (9 experts); Land Institute of the State of São Paulo – ITESP (3 experts); Agribusiness Development Coordination – CODEAGRO (1 experts); National Cooperative Learning Service – SECOOP/SP (1 experts); Brazilian Micro and Small Business Support Service – SEBRAE (3 experts); Research Institutions and Universities (3 experts). The professionals who made up the panel of experts were selected within the sphere of these institutions.

The institutions were contacted, and the authors presented the objectives and the research instrument. Experts from these organizations who had the necessary qualifications for participation were then selected, possessing proven experience in technical assistance, management, and research focused on family farming, associations, and cooperatives. Among the functions performed, these professionals are responsible for project development, general area coordination, technical assistance to producers and organizations, field team supervision, and coordination, among other duties.

The interviews took place individually between September and November 2019. Eighteen in-person interviews were conducted by the authors, who went to the experts, and two interviews were done remotely. The results were processed in an electronic spreadsheet to standardize the data, normalize the judgments. The answers are processed quantitatively according to the position of the expert (Gomes and Gomes, 2019) and group the responses. A simple average of the judgments was applied to the grouping process, since, having met the selection criteria, the opinion of each expert had the same relevance. Having presented the method adopted to develop the study, it is possible to move on to discussing the results.

4. Results and discussion

4.1. Conceptual framework

The conceptual framework underlying the proposed analytical model was initially structured on the basis of models provided by Shiferaw et al. (2011), Fischer & Qaim (2014), Gyau et al. (2014), Donovan et al. (2017) and Amiquero et al. (2023). Alterations and new proposals were made to ensure the best inclusion of the performance determinants and their investigation in a structured way. Figure 2 presents the framework.

Figure 2
Conceptual Framework - Performance of Collective Agroindustrial Projects.

The review process enabled the identification of a broad set of determinants, substantially complementing previous studies that have adopted a limited number of conditions. The review identified that most of the previous studies were not dedicated to looking at determinants of a distinct nature, but were limited to one dimension, e.g. governance or individual characteristics. This amplitude allowed the proposed framework to be applied to a wide variety of collective rural enterprises, without restrictions as to audience, activity or geographic location. In addition, proposals structured into factors permit decision-makers to investigate or treat each factor independently, if necessary.

The proposed analytical model incorporated the “management, operation and finance” factor among the determinants to be investigated. This factor is often neglected in current models of analysis of collective agroindustrial projects, and when its determinants are evaluated, they are usually included individually and in factors that do not represent the management function. Most of the research is dedicated to the conditions of collective actions themselves, such as trust or leadership, neglecting, for example, the operational and technical capacity of the rural organization. This incorporation recognizes and assumes that the long-term feasibility of rural enterprises depends on adequate levels of business management of the organizations.

The framework considers that project performance is a direct function of the presence of the proposed factors - “Local infrastructure” (e.g., distance to consumer market), “Trust, commitment and participation” (e.g., collective and transparent decisions), “Individual characteristics” (e.g., educational level of producers) “Group characteristics” (e.g., presence of conflicts) “Management, operation and finance” (e.g., the financial condition) which are formed by the identified determinants.

Tables 1, 2, 3, 4, 5 and 6 present the determinants that make up the factors that participated in the proposed analytical model. Appendix A Appendix A Reviewed articles that analyse the determinants of the performance of collective agro-industrial projects. presents the coding of the articles used, in addition to the study locations, organizations investigated, projects, and performance dimensions (Agrawal, 2001; Bassi & Carestiato, 2016; Baynes et al., 2015; Call & Jagger, 2017; Coppock & Desta, 2013; Coulibaly-Lingani et al., 2014; Degrande et al., 2014; Francesconi & Wouterse, 2015; Hajjar et al., 2011; Gouët & van Paassen, 2012; Herbel et al., 2015; Islam et al., 2011; Jones, 2004; Werthmann, 2015; Turner et al., 2013; Tierling & Schmidt, 2017; Sisay et al., 2017; Stefani et al., 2017; Shiferaw et al., 2008; Schöll et al., 2016; Kaganzi et al., 2009; Place et al., 2004; Ragasa & Golan, 2014; Pretty & Ward, 2001; Ruben & Heras, 2012; Oerlemans & Assouline, 2004; Newbery et al., 2013; Mills et al., 2011; Knickel et al., 2008; Kola et al., 2014; Lamprinopoulou et al., 2006; Landolt & Haller, 2015; Liang et al., 2015; Lyon, 2003; McRoberts et al., 2013; Newbery et al., 2013; Wangel & Blomkvist, 2013).

Table 1
Determinants - Local infrastructure.
Table 2
Determinants - Individual characteristics.
Table 3
Determinants - Group characteristics
Table 4
Determinants - Management, operation and Finance
Table 5
Determinants -Trust, commitment and participation
Table 6
Importance of factors and determinants for the success of collective agroindustrial enterprises

4.2. Performance determinants

The performance determinants proposed by the model will be presented in the following.

Local infrastructure

The “local infrastructure” factor can be broken down into four determinants (see Table 1). The authors who observed the determinants are presented in “Appendix A Appendix A Reviewed articles that analyse the determinants of the performance of collective agro-industrial projects. ” by the codes indicated in the tables (Tables 1, 2, 3, 4 and 5), example, Author [1]. This factor assumes that the environmental and local conditions where the organizations operate have a direct influence on project performance.

Individual characteristics

The three determinants that compose the “individual characteristics” factor are presented in Table 2. They are directly related to the characteristics of the farmers who participate in the collective production activities associated with the rural enterprise under analysis.

Characteristics of the group

The six determinants that make up the “characteristics of the group” factor are presented in Table 3. They reflect the main characteristics of the groups responsible for the collective enterprises that can have an impact on the success of the enterprises implemented by the groups.

Management, operation and finance

The “management, operation and finance” factor is made up of six determinants, as shown in Table 4. They are related to the business characteristics of rural organizations and are, therefore, highly relevant determining the performance and efficiency of collective initiatives. It is expected that in the absence of adequate levels of management and technical and commercial capacity, collective enterprises will encounter major difficulties in achieving their objectives.

Trust, commitment and participation

The five determinants that form the “trust, commitment and participation” factor are presented in Table 5. These determinants have their origin, for the most part, in the collective structure of organizations and in relationship between associates. There is widespread recognition of the direct effect of these factors on collective action that determine the overall performance of organizations executing projects.

4.3. Importance of the determinants for performance

The conceptual framework developed was presented to and examined by a panel of experts. The objective of this methodological stage was to enable the experts to validate and, mainly, classify the various factors according to the importance they assigned to each factor for the success of collective agroindustrial enterprises of small farmers. The results presented do not allow us to identify statistical differences among the determinants, a condition that does not interfere with the quality of the material in view of the method and the objective of the study. It is important to point out that the experts, when asked, did not add any new determinants or factors to those already contained in the model under analysis.

The Table 6 presents the importance assigned (W) and overall classification (OC), first for each factor (F), numbered from 1 to 5 and, then, for each determinant identified with its factor (F), classified from first to twenty-first, according to its importance. The ordering of the factors follows the logic of formation and development of the collective rural organization, that is, in a given territory with its local infrastructure (1), individual producers (2) form a group (3) with their own characteristics, and need to carry out the management of the rural enterprise (4), considering an environment in which there must be trust, commitment and participation (5).

In the view of the experts, “trust, commitment and participation” is the most important factor for the success of projects, receiving a weight of 0.27, followed by the determinants of the “management, operation and finance” factor (0.23). The “characteristics of the group” factor occupied third place with 0.20, followed by “individual characteristics,” with 0.17. “Local infrastructure” was ranked in last place, with 0.12. Following is a more detailed breakdown of the 12 determinants which, in the experts’ opinion, contribute more significantly to the success of collective agroindustrial enterprises of small farmers.

The experts interviewed attributed the most importance to “experience and practical knowledge of agricultural activities” in the overall classification, with a weight of 0.081. As farmers obtain greater experience and knowledge, it is expected they will have better production results and the necessary conditions to meet quality and productivity standards (Paumgarten et al., 2012). Individual production inefficiencies and incapabilities will not have any direct effects on collective results.

The determinant “participation of associates in activities” of organizations was assigned the second greatest importance with a weight of 0.066. This expressive result was supported by the literature, which has also recognized the benefit of farmers participating in group collective activities (meetings, training, etc.) for the success of collective projects (Uetake, 2015; Lopes et al., 2015).

“Management capacity” ranked third overall, with a weight of 0.064, in the performance of initiatives, i.e., this determinant has an impact of 6.4% on the success of projects. The impact considers the assumptions of the study, among them that adequate performance (success) is a direct function of the presence of the determinants. This expressive result is in line with the recognized relevance of adequate levels of management in relation to the performance and economic sustainability of enterprises, especially agroindustrial enterprise. There is no lack of evidence that supports the impact of the process, as highlighted by Sebhatu et al. (2021). This situation largely justifies the insertion of determinants linked to management in the analytical model, as proposed in this article.

With a weight of 0.062, “trust within the organization” was the fourth most important factor. The literature has already pointed out the importance of this theme. It is expected that an adequate level of trust will be directly favorable for the results of collective actions and their production initiatives (Tadesse & Kassie, 2017). This determinant also favors other internal conditions of organizations.

The next two determinants, like the last, make up the “trust, commitment and participation” factor. They are “collective and transparent decisions,” with a weight of 0.057, and “cohesion and involvement among associates,” with a weight of 0.055. The first is conducive to the quality of decisions made and achieving combined objectives. The second is essential for the efficient operation of collective rural organizations. Without this condition, it is unlikely that projects will unfold. The results of Ahmad et al. (2024) observing collective organizations in Indonesia indicate the importance of cohesion.

The experts interviewed ranked “leadership of the organization and project” in seventh place among the determinants, with a weight of 0.051; i.e., it has an importance of 5.1% in relation to project performance (considering that all determinants have a summed importance of 100%). There is extensive literature that refers to the positive impacts of adequate leadership on rural enterprises, as well as being a condition that directly favors other determinants. Murunga et al. (2021) for example, highlight in their results the importance of leadership in collective organizations in Kenya. The leader is an actor responsible for motivating, aggregating and directing the action of the users involved, and must also have the skills and competences necessary for the efficient management of the collective enterprise (Markelova et al., 2009).

The “educational level of the farmers” is the eighth determinant, with a weight of 0.051. This result is justified by the expectation that more years of formal education will result in farmers having adequate levels of skill and educational competencies, which will promote better results in production activities (Barham & Chitemi, 2009).

The “management, operation and finance” factor has determinants in ninth and tenth place: “technical and production capacity,” with a weight of 0.047, and “commercial capacity,” with a weight of 0.046. The literature points out that technical and production inefficiencies can undermine the feasibility of projects, especially in small-scale rural organizations. The results of Barry & Rousselière (2022) observing French cooperatives highlight the need to provide quality and efficiency in production processes. Adequate commercial capacity enables organizations to stay competitive in relation to the market and in terms of sales. In high-value markets, the cooperative is one of the only forms of access for small farmers (Fernando et al., 2021).

It is worth noting that the nine determinants with the highest importance accounted for 37.5% of the number of variables, with a cumulative importance of 53.56%. Special attention needs to be paid to these determinants due to their relevance for the success of businesses.

The “conflicts, differences and internal disputes” determinant occupied the 11th position, with a weight of 0.041. As the level of conflicts and disputes increases, it is expected that the success of projects will decrease (Jelsma et al., 2017). This condition is widely discussed in the literature because of its effect on the performance of collective initiatives, and due to specific characteristics of organizational models, such as distribution of benefits and heterogeneity among members.

Twelfth place was assigned to “regular access to water, energy, telephony and Internet,” with a weight of 0.039. Access to water is especially important for agricultural activities, without which they are not feasible, in addition to power failures, which can have a substantial impact. In addition to enabling access to information in general, access to modern communication technologies is increasingly essential for the insertion of rural production into more modern and lucrative channels of commercialization.

5. Conclusions

There are many challenges for the sustained viability of collective rural organizations. The collective form of ownership and governance, along with specific characteristics of family farmers and agroindustrial production and commercialization systems, result in strong singularities in the assessment and implementation processes of collective agroindustrial projects. The importance of this article is rooted in this context.

Therefore, this article contributes to efforts to provide decision-makers with an analytical framework that will enable them to evaluate the odds of success of collective agroindustrial projects by family farmers. The findings make it possible to identify which factors should receive greater or less attention in the selection and implementation process of collective agroindustrial production projects.

The construction of the framework collaborates with the scientific literature dedicated to discussing the determinants of efficiency in agroindustrial collective actions. Knowledge of the performance determinants of collective agricultural production actions is still limited. And the literature so far does not provide a model that is widely applied and that is recognized to be efficient in including the particularities of these enterprise.

The proposed framework surpasses much of the studies in the field, which adopt a limited number of determinants and often overlook fundamental factors. It also contributed to the inclusion of aspects that are not exclusively financial, especially linked to the relationship among members of collective actions.

The study advances considerably in this direction, as it incorporates conditions of a different nature and origin in a broad and structured framework, such as those related to local infrastructure, characteristics of the individual and the group, the quality of management and the environment of trust, commitment and participation within the enterprise. It allows, for example, the consideration of the education level of the producers and the marketing capacity of the organization—along with other determinants—in a structured manner.

The results indicated that the factors “trust, commitment, and participation” and “management, operation, and finance” were ranked first and second in terms of importance. This allows us to conclude that, considering the experts' experience, these factors significantly influence the performance of the collective rural organization, thus stakeholders and decision-makers in the field should pay special attention to them.

The study further innovates by contributing to the literature through measuring the importance of determinants for the performance of the enterprise from the perspective of a wide range of specialists. The empirical measurement of the weight of each determinant is important and yields practical results. Firstly, it incorporates the real and qualified experience of specialists considering the context of family farming, differing from most studies that only consider the literature. Secondly, the classification of importance directly contributes to the direction of new investigations and provides practical managerial actions.

As a practical implication, the proposed framework enables various stakeholders, including public and private development agencies, technical assistance and rural extension agencies, organizations, banks, development institutions, to apply a structured tool for decision-making and selection of investment options. Furthermore, it enables the differentiation between conditions inherent to the enterprises, such as management and leadership capacity, and those that are situational, such as road quality and access to water and energy. This differentiation allows for the targeted direction of public efforts—through public policies—and private efforts.

The scientific literature and technical manuals of rural extension organizations do not seek to directly present the importance of each determinant in the performance of the collective rural business. In contrast, the framework sheds light on the need for differentiation and special attention to the determinants that have the greatest effect on performance.

Management measures can also be employed to tailor determinants to achieve better results. For example, between investing in the development of management capacity or expanding the network of an organization's contacts, the first option was chosen, since it has a greater weight on performance.

Regarding the limitations of the study, the large number of determinants (variables) had a direct impact on the choice of the multi-criteria technique to be used and prevented the use of more robust multi-criteria techniques. The number of experts (20) meets the requirements of the multi-criteria technique but made statistical tests impossible.

In the future, it will be important to subject the developed framework to empirical validation testing to compare the results presented here with the real conditions and outcomes of projects already underway. A valuable research agenda could focus on developing variables to empirically measure each determinant and on efforts to incorporate the model into standard investment evaluation methods.

Appendix A


Reviewed articles that analyse the determinants of the performance of collective agro-industrial projects.

Acknowledgments

This work as supported by the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Financing Code 001.

  • How to cite:
    Perressim, W. S., & Batalha, M. O. (2024). Performance determinants for agroindustrial projects in collective actions of small farmers. Revista de Economia e Sociologia Rural, 62(4), e274751. https://doi.org/10.1590/1806-9479.2023.274751
  • JEL Classification:
    J54; P13; Q13

References

  • Agrawal, A. (2001). Common property institutions and sustainable governance of resources. World Development, 29(10), 1649-1672. http://doi.org/10.1016/S0305-750X(01)00063-8
    » http://doi.org/10.1016/S0305-750X(01)00063-8
  • Ahado, S., Hejkrlik, J., Ratinger, T., & Kepuladze, T. A. (2024). Supported cooperative groups and the economic performance of small farmers: evidence from Georgia. Journal of Development Effectiveness, 16(1), 101-117. http://doi.org/10.1080/19439342.2022.2158902
    » http://doi.org/10.1080/19439342.2022.2158902
  • Ahmad, S. R., Shadbolt, N., & Reid, J. (2024). Collective action for rice smallholder’s value chain: insight from Yogyakarta, Indonesia. Journal of Co-operative Organization and Management, 12(1), 100236. http://doi.org/10.1016/j.jcom.2024.100236
    » http://doi.org/10.1016/j.jcom.2024.100236
  • Almeida Biolchini, J. C., Mian, P. G., Natali, A. C. C., Conte, T. U., & Travassos, G. H. (2007). Scientific research ontology to support systematic review in software engineering. Advanced Engineering Informatics, 21(2), 133-151. http://doi.org/10.1016/j.aei.2006.11.006
    » http://doi.org/10.1016/j.aei.2006.11.006
  • Amiquero, K. S., Wubben, E., van Dam, Y., & Trienekens, J. (2023). Success and failure factors in agricultural cooperatives. International Journal on Food System Dynamics, 14(1), 1-21. http://doi.org/10.18461/ijfsd.v14i1.E1
    » http://doi.org/10.18461/ijfsd.v14i1.E1
  • Barham, J., & Chitemi, C. (2009). Collective action initiatives to improve marketing performance: lessons from farmer groups in Tanzania. Food Policy, 34(1), 53-59. http://doi.org/10.1016/j.foodpol.2008.10.002
    » http://doi.org/10.1016/j.foodpol.2008.10.002
  • Barry, I., & Rousselière, D. (2022). Do quality incentive payments improve cooperative performance? The case of small French agricultural cooperatives. Journal of Agricultural Economics, 73(3), 938-948. http://doi.org/10.1111/1477-9552.12475
    » http://doi.org/10.1111/1477-9552.12475
  • Bassi, I., & Carestiato, N. (2016). Common property organisations as actors in rural development: a case study of a mountain area in Italy. The International Journal of the Commons, 10(1),
  • Batalha, M. (2021). Gestão agroindustrial (4ª ed.). São Paulo: Atlas.
  • Baynes, J., Herbohn, J., Smith, C., Fisher, R., & Bray, D. (2015). Key factors which influence the success of community forestry in developing countries. Global Environmental Change, 35, 226-238. http://doi.org/10.1016/j.gloenvcha.2015.09.011
    » http://doi.org/10.1016/j.gloenvcha.2015.09.011
  • Briggeman, B. C., Jacobs, K. L., Kenkel, P., & Mckee, G. (2016). Current trends in cooperative finance. Agricultural Finance Review, 76(3), 402-410. http://doi.org/10.1108/AFR-04-2016-0034
    » http://doi.org/10.1108/AFR-04-2016-0034
  • Call, M., & Jagger, P. (2017). Social capital, collective action, and communal grazing lands in Uganda. The International Journal of the Commons, 11(2), 854-876. http://doi.org/10.18352/ijc.761
    » http://doi.org/10.18352/ijc.761
  • Cook, M. L. (1995). The future of US agricultural cooperatives: a neo-institutional approach. American Journal of Agricultural Economics, 77(5), 1153-1159. http://doi.org/10.2307/1243338
    » http://doi.org/10.2307/1243338
  • Coppock, D. L., & Desta, S. (2013). Collective action, innovation, and wealth generation among settled pastoral women in northern Kenya. Rangeland Ecology and Management, 66(1), 95-105. http://doi.org/10.2111/REM-D-11-00211.1
    » http://doi.org/10.2111/REM-D-11-00211.1
  • Corsi, S., Marchisio, L. V., & Orsi, L. (2017). Connecting smallholder farmers to local markets: drivers of collective action, land tenure and food security in East Chad. Land Use Policy, 68, 39-47. http://doi.org/10.1016/j.landusepol.2017.07.025
    » http://doi.org/10.1016/j.landusepol.2017.07.025
  • Coulibaly-Lingani, P., Tigabu, M., Savadogo, P., & Odén, P. C. (2014). Participatory forest management in Burkina Faso: members’ perception of performance. Journal of Forestry Research, 25(3), 637-646. http://doi.org/10.1007/s11676-014-0502-x
    » http://doi.org/10.1007/s11676-014-0502-x
  • Degrande, A., Gyau, A., Foundjem-Tita, D., & Tollens, E. (2014). Improving smallholders’ participation in tree product value chains: experiences from the Congo Basin. Forests, Trees and Livelihoods, 23(1-2), 102-115. http://doi.org/10.1080/14728028.2014.886867
    » http://doi.org/10.1080/14728028.2014.886867
  • Di Gregorio, M. K., Hagedorn, K., Kirk, B., Korf, N., McCarthy, R., Meinzen-Dick, S., Swallow, B., Mwangi, & Markelova, H. (2012). Property rights and collective action for poverty reduction: a framework for analysis. In E. Mwangi, H. Markelov, & R. S. Meinzen-Dick (Eds.), Collective action and property rights for poverty reduction: Insights from Africa and Asia (pp. 25-48). Philadelphia: University of Pennsylvania Press. http://doi.org/10.9783/9780812207873.25
    » http://doi.org/10.9783/9780812207873.25
  • Donovan, J., Blare, T., & Poole, N. (2017). Stuck in a rut: emerging cocoa cooperatives in Peru and the factors that influence their performance. International Journal of Agricultural Sustainability, 15(2), 169-184. http://doi.org/10.1080/14735903.2017.1286831
    » http://doi.org/10.1080/14735903.2017.1286831
  • Edwards, W. (1971). Social utilities. The Engineering Economist Summer Symposium Series, 6, 119-129.
  • Ensslin, S. R., Ensslin, L., Imlau, J. M., & Chaves, L. C. (2014). Processo de mapeamento das publicações científicas de um tema: portfólio bibliográfico e análise bibliométrica sobre avaliação de desempenho de cooperativas de produção agropecuária. Revista de Economia e Sociologia Rural, 52(3), 587-608. http://doi.org/10.1590/S0103-20032014000300010
    » http://doi.org/10.1590/S0103-20032014000300010
  • Fernando, S., Garnevska, E., Ramilan, T., & Shadbolt, N. (2021). Organisational attributes of cooperatives and farmer companies. Journal of Co-operative Organization and Management, 9(1), 100132. http://doi.org/10.1016/j.jcom.2021.100132
    » http://doi.org/10.1016/j.jcom.2021.100132
  • Ferreira da Silva, F., Knebel Baggio, D., & Ferreira Lopes Santos, D. (2022). Governance and performance model for agricultural cooperatives. Estudios Gerenciales, 38(165), 464-478. http://doi.org/10.18046/j.estger.2022.165.5238
    » http://doi.org/10.18046/j.estger.2022.165.5238
  • Fischer, E., & Qaim, M. (2014). Smallholder farmers and collective action: What determines the intensity of participation? Journal of Agricultural Economics, 65(3), 683-702. http://doi.org/10.1111/1477-9552.12060
    » http://doi.org/10.1111/1477-9552.12060
  • Francesconi, G. N., & Wouterse, F. (2015). The health of farmer-based organisations in Ghana: organisational diagnostics and governance implications. The Journal of Development Studies, 51(3), 262-273. http://dx.doi.org/10.1080/00220388.2014.957275
    » http://dx.doi.org/10.1080/00220388.2014.957275
  • Gomes, L., & Gomes, C. F. S. (2019). Princípios e métodos para tomada de decisão enfoque multicritério (6. ed.). Rio de Janeiro: Atlas.
  • Goodwin, P., & Wright, G. (2014). Decision analysis for management judgment. New York: John Wiley & Sons.
  • Gouët, C., & van Paassen, A. (2012). Smallholder marketing cooperatives and smallholders’ market access: lessons learned from the actors involved. Journal of Agricultural Education and Extension, 18(4), 369-385. http://doi.org/10.1080/1389224X.2012.691784
    » http://doi.org/10.1080/1389224X.2012.691784
  • Gyau, A., Franzel, S., Chiatoh, M., Nimino, G., & Owusu, K. (2014). Collective action to improve market access for smallholder producers of agroforestry products: key lessons learned with insights from Cameroon’s experience. Current Opinion in Environmental Sustainability, 6, 68-72. http://doi.org/10.1016/j.cosust.2013.10.017
    » http://doi.org/10.1016/j.cosust.2013.10.017
  • Hajjar, R., McGrath, D. G., Kozak, R. A., & Innes, J. L. (2011). Framing community forestry challenges with a broader lens: Case studies from the Brazilian Amazon. Journal of Environmental Management, 92(9), 2159-2169. http://doi.org/10.1016/j.jenvman.2011.03.042
    » http://doi.org/10.1016/j.jenvman.2011.03.042
  • Hellin, J., Lundy, M., & Meijer, M. (2009). Farmer organization, collective action and market access in Meso-America. Food Policy, 34(1), 16-22. http://doi.org/10.1016/j.foodpol.2008.10.003
    » http://doi.org/10.1016/j.foodpol.2008.10.003
  • Herbel, D., Rocchigiani, M., & Ferrier, C. (2015). The role of the social and organisational capital in agricultural co-operatives’ development Practical lessons from the CUMA movement. Journal of Co-Operative Organization and Management, 3(1), 24-31. http://doi.org/10.1016/j.jcom.2015.02.003
    » http://doi.org/10.1016/j.jcom.2015.02.003
  • Instituto Brasileiro de Geografia e Estatística – IBGE. (2019). Agricultura familiar no Brasil e seus aspectos socioprodutivos: resultados da pesquisa agropecuária Retrieved in 2019, June 6, from https://censoagro2017.ibge.gov.br/templates/censo_agro/resultadosagro/pdf/agricultura_familiar.pdf
    » https://censoagro2017.ibge.gov.br/templates/censo_agro/resultadosagro/pdf/agricultura_familiar.pdf
  • International Fund for Agricultural Development - IFDA. (2016). Investindo nas Populações Rurais no Brasil Retrieved in 2019, June 6, from https://www.ifad.org/documents/38714170/39150184/brazil_p_web.pdf/255c3107-5607-467e-b82a-0519a7645807
    » https://www.ifad.org/documents/38714170/39150184/brazil_p_web.pdf/255c3107-5607-467e-b82a-0519a7645807
  • Ishak, S., Omar, A. R. C., Sum, S. M., Othman, A. S., & Jaafar, J. (2020). Smallholder agriculture cooperatives’performance: what is in the minds of management? Journal of Co-Operative Organization and Management, 8(2), 100110. http://doi.org/10.1016/j.jcom.2020.100110
    » http://doi.org/10.1016/j.jcom.2020.100110
  • Islam, M. M., Gray, D., Reid, J., & Kemp, P. (2011). Developing sustainable farmer-led extension groups: lessons from a Bangladeshi case study. Journal of Agricultural Education and Extension, 17(5), 425-443. http://doi.org/10.1080/1389224X.2011.596658
    » http://doi.org/10.1080/1389224X.2011.596658
  • Jelsma, I., Slingerland, M., Giller, K. E., & Bijman, J. (2017). Collective action in a smallholder oil palm production system in Indonesia: The key to sustainable and inclusive smallholder palm oil? Journal of Rural Studies, 54, 198-210. http://doi.org/10.1016/j.jrurstud.2017.06.005
    » http://doi.org/10.1016/j.jrurstud.2017.06.005
  • Jones, E. C. (2004). Wealth-based trust and the development of collective action. World Development, 32(4), 691-711. http://doi.org/10.1016/j.worlddev.2003.10.009
    » http://doi.org/10.1016/j.worlddev.2003.10.009
  • Kaganzi, E., Ferris, S., Barham, J., Abenakyo, A., Sanginga, P., & Njuki, J. (2009). Sustaining linkages to high value markets through collective action in Uganda. Food Policy, 34(1), 23-30. http://doi.org/10.1016/j.foodpol.2008.10.004
    » http://doi.org/10.1016/j.foodpol.2008.10.004
  • Knickel, K., Zerger, C., Jahn, G., & Renting, H. (2008). Limiting and enabling factors of collective farmers’ marketing initiatives: results of a comparative analysis of the situation and trends in 10 European countries. Journal of Hunger & Environmental Nutrition, 3(2-3), 247-269. http://doi.org/10.1080/19320240802244041
    » http://doi.org/10.1080/19320240802244041
  • Kola, R., Skreli, E., Osmani, M., & Tanku, A. (2014). Farmers’ characteristics as determinants of collective action: the case of Greenhouse Producers in Albania. New Medit, 13(2), 20-27.
  • Lamprinopoulou, C., Tregear, A., & Ness, M. (2006). Agrifood SMEs in Greece: the role of collective action. British Food Journal, 108(8), 663-676. http://doi.org/10.1108/00070700610682346
    » http://doi.org/10.1108/00070700610682346
  • Landolt, G., & Haller, T. (2015). Alpine common property institutions under change: conditions for successful and unsuccessful collective action by alpine farmers in the canton of Grisons, Switzerland. Human Organization, 74(1), 100-111. http://doi.org/10.17730/humo.74.1.x55m464806q67156
    » http://doi.org/10.17730/humo.74.1.x55m464806q67156
  • Latynskiy, E., & Berger, T. (2016). Networks of rural producer organizations in Uganda: What can be done to make them work better? World Development, 78, 572-586. http://doi.org/10.1016/j.worlddev.2015.10.014
    » http://doi.org/10.1016/j.worlddev.2015.10.014
  • Liang, Q., Huang, Z., Lu, H., & Wang, X. (2015). Social capital, member participation, and cooperative performance: evidence from China’s Zhejiang. International Food and Agribusiness Management Review, 18(1), 49-77. http://doi.org/10.22004/ag.econ.197768
    » http://doi.org/10.22004/ag.econ.197768
  • Lopes, M., Nesbitt, H., Spyckerelle, L., Pauli, N., Clifton, J., & Erskine, W. (2015). Harnessing social capital for maize seed diffusion in Timor-Leste. Agronomy for Sustainable Development, 35(2), 847-855. http://doi.org/10.1007/s13593-015-0293-2
    » http://doi.org/10.1007/s13593-015-0293-2
  • Lyon, F. (2003). Community groups and livelihoods in remote rural areas of Ghana: How small‐scale farmers sustain collective action. Community Development Journal: An International Forum, 38(4), 323-331. http://doi.org/10.1093/cdj/38.4.323
    » http://doi.org/10.1093/cdj/38.4.323
  • Markelova, H., & Mwangi, E. (2010). Collective action for smallholder market access: evidence and implications for Africa. The Review of Policy Research, 27(5), 621-640. http://doi.org/10.1111/j.1541-1338.2010.00462.x
    » http://doi.org/10.1111/j.1541-1338.2010.00462.x
  • Markelova, H., Meinzen-Dick, R., Hellin, J., & Dohrn, S. (2009). Collective action for smallholder market access. Food Policy, 34(1), 1-7. http://doi.org/10.1016/j.foodpol.2008.10.001
    » http://doi.org/10.1016/j.foodpol.2008.10.001
  • McRoberts, K. C., Nicholson, C. F., Blake, R. W., Tucker, T. W., & Padilla, G. D. (2013). Group model building to assess rural dairy cooperative feasibility in south-central Mexico. International Food and Agribusiness Management Review, 16(3), 55-98. http://doi.org/10.22004/ag.econ.156459
    » http://doi.org/10.22004/ag.econ.156459
  • Ménard, C., & Klein, P. G. (2004). Organizational issues in the agrifood sector: toward a comparative approach. American Journal of Agricultural Economics, 86(3), 750-755. http://doi.org/10.1111/j.0002-9092.2004.00619.x
    » http://doi.org/10.1111/j.0002-9092.2004.00619.x
  • Mills, J., Gibbon, D., Ingram, J., Reed, M., Short, C., & Dwyer, J. (2011). Organising collective action for effective environmental management and social learning in Wales. Journal of Agricultural Education and Extension, 17(1), 69-83. http://doi.org/10.1080/1389224X.2011.536356
    » http://doi.org/10.1080/1389224X.2011.536356
  • Murunga, M., Partelow, S., & Breckwoldt, A. (2021). Drivers of collective action and role of conflict in Kenyan fisheries co-management. World Development, 141, 105413. http://doi.org/10.1016/j.worlddev.2021.105413
    » http://doi.org/10.1016/j.worlddev.2021.105413
  • Narrod, C., Roy, D., Okello, J., Avendaño, B., Rich, K., & Thorat, A. (2009). Public–private partnerships and collective action in high value fruit and vegetable supply chains. Food Policy, 34(1), 8-15. http://doi.org/10.1016/j.foodpol.2008.10.005
    » http://doi.org/10.1016/j.foodpol.2008.10.005
  • Neves, M. D. C. R., Castro, L. S. D., & Freitas, C. O. D. (2019). O impacto das cooperativas na produção agropecuária brasileira: uma análise econométrica espacial. Revista de Economia e Sociologia Rural, 57(4), 559-576. http://doi.org/10.1590/1806-9479.2019.187145
    » http://doi.org/10.1590/1806-9479.2019.187145
  • Newbery, R., Sauer, J., Gorton, M., Phillipson, J., & Atterton, J. (2013). Determinants of the performance of business associations in rural settlements in the United Kingdom: an analysis of members’ satisfaction and willingness-to-pay for association survival. Environment & Planning A, 45(4), 967-985. http://doi.org/10.1068/a44669
    » http://doi.org/10.1068/a44669
  • Oerlemans, N., & Assouline, G. (2004). Enhancing farmers’ networking strategies for sustainable development. Journal of Cleaner Production, 12(5), 469-478. http://doi.org/10.1016/S0959-6526(03)00105-7
    » http://doi.org/10.1016/S0959-6526(03)00105-7
  • Olson, M. (1965). The logic of collective action. Cambridge: Harvard University Press. http://doi.org/10.4159/9780674041660
    » http://doi.org/10.4159/9780674041660
  • Orsi, L., De Noni, I., Corsi, S., & Marchisio, L. V. (2017). The role of collective action in leveraging farmers’ performances: lessons from sesame seed farmers’ collaboration in eastern Chad. Journal of Rural Studies, 51, 93-104. http://doi.org/10.1016/j.jrurstud.2017.02.011
    » http://doi.org/10.1016/j.jrurstud.2017.02.011
  • Ostrom, E. (1990). Governing the commons: the evolution of institutions for collective action. Cambridge: Cambridge University Press. http://doi.org/10.1017/CBO9780511807763
    » http://doi.org/10.1017/CBO9780511807763
  • Paumgarten, F., Kassa, H., Zida, M., & Moeliono, M. (2012). Benefits, challenges, and enabling conditions of collective action to promote sustainable production and marketing of products from Africa’s dry forests. The Review of Policy Research, 29(2), 229-250. http://doi.org/10.1111/j.1541-1338.2011.00549.x
    » http://doi.org/10.1111/j.1541-1338.2011.00549.x
  • Place, F., Kariuki, G., Wangila, J., Kristjanson, P., Makauki, A., & Ndubi, J. (2004). Assessing the factors underlying differences in achievements of farmer groups: methodological issues and empirical findings from the highlands of Central Kenya. Agricultural Systems, 82(3), 257-272. http://doi.org/10.1016/j.agsy.2004.07.001
    » http://doi.org/10.1016/j.agsy.2004.07.001
  • Pretty, J., & Ward, H. (2001). Social capital and the environment. World Development, 29(2), 209-227. http://doi.org/10.1016/S0305-750X(00)00098-X
    » http://doi.org/10.1016/S0305-750X(00)00098-X
  • Ragasa, C., & Golan, J. (2014). The role of rural producer organizations for agricultural service provision in fragile states. Agricultural Economics, 45(5), 537-553. http://doi.org/10.1111/agec.12105
    » http://doi.org/10.1111/agec.12105
  • Ruben, R., & Heras, J. (2012). Social capital, governance and performance of Ethiopian coffee cooperatives. Annals of Public and Cooperative Economics, 83(4), 463-484. http://doi.org/10.1111/j.1467-8292.2012.00473.x
    » http://doi.org/10.1111/j.1467-8292.2012.00473.x
  • Schöll, K., Markemann, A., Megersa, B., Birner, R., & Zárate, A. V. (2016). Impact of projects initiating group marketing of smallholder farmers: a case study of pig producer marketing groups in Vietnam. Journal of Co-operative Organization and Management, 4(1), 31-41. http://doi.org/10.1016/j.jcom.2016.03.002
    » http://doi.org/10.1016/j.jcom.2016.03.002
  • Sebhatu, K. T., Gezahegn, T. W., Berhanu, T., Maertens, M., Van Passel, S., & D’Haese, M. (2021). Exploring variability across cooperatives: economic performance of agricultural cooperatives in northern Ethiopia. The International Food and Agribusiness Management Review, 24(3), 397-420. http://doi.org/10.22434/IFAMR2019.0215
    » http://doi.org/10.22434/IFAMR2019.0215
  • Sellare, J., Jäckering, L., Kahsay, G., & Meemken, E. M. (2023). Five stylized facts about producer organizations and rural development. Journal of the Agricultural and Applied Economics Association, 2(3), 428-445. http://doi.org/10.1002/jaa2.70
    » http://doi.org/10.1002/jaa2.70
  • Serigati, F. C., & Azevedo, P. F. (2013). Comprometimento, características da cooperativa e desempenho financeiro: uma análise em painel com as cooperativas agrícolas paulistas. Revista de Administração (São Paulo), 48(2), 222-238. http://doi.org/10.5700/rausp1084
    » http://doi.org/10.5700/rausp1084
  • Shiferaw, B., Hellin, J., & Muricho, G. (2011). Improving market access and agricultural productivity growth in Africa: What role for producer organizations and collective action institutions? Food Security, 3(4), 475-489. http://doi.org/10.1007/s12571-011-0153-0
    » http://doi.org/10.1007/s12571-011-0153-0
  • Shiferaw, B., Obare, G., & Muricho, G. (2008). Rural market imperfections and the role of institutions in collective action to improve markets for the poor. Natural Resources Forum, 32(1), 25-38. http://doi.org/10.1111/j.1477-8947.2008.00167.x
    » http://doi.org/10.1111/j.1477-8947.2008.00167.x
  • Silva, R. M. A. D., & Nunes, E. M. (2023). Agricultura familiar e cooperativismo no Brasil: uma caracterização a partir do Censo Agropecuário de 2017. Revista de Economia e Sociologia Rural, 61(2), e252661. http://doi.org/10.1590/1806-9479.2021.252661
    » http://doi.org/10.1590/1806-9479.2021.252661
  • Siregar, D., Arisandi, D., Usman, A., Irwan, D., & Rahim, R. (2017). Research of simple multi-attribute rating technique for decision support. Journal of Physics: Conference Series, 930(1), 012015. http://doi.org/10.1088/1742-6596/930/1/012015
    » http://doi.org/10.1088/1742-6596/930/1/012015
  • Sisay, D. T., Verhees, F. J., & Van Trijp, H. C. (2017). The influence of market orientation on firm performance and members’ livelihood in Ethiopian seed producer cooperatives. Agrekon, 56(4), 366-382. http://doi.org/10.1080/03031853.2017.1409126
    » http://doi.org/10.1080/03031853.2017.1409126
  • Stefani, G., Lombardi, G. V., Romano, D., & Cei, L. (2017). Grass root collective action for territorially integrated food supply chains: a case study from Tuscany. International Journal on Food System Dynamics, 8(4), 347-362. http://doi.org/10.18461/ijfsd.v8i4.847
    » http://doi.org/10.18461/ijfsd.v8i4.847
  • Tadesse, G., & Kassie, G. T. (2017). Measuring trust and commitment in collective actions. International Journal of Social Economics, 44(7), 980-996. http://doi.org/10.1108/IJSE-09-2015-0253
    » http://doi.org/10.1108/IJSE-09-2015-0253
  • Tierling, I. M. B. M., & Schmidt, C. M. (2017). Collective action and value creation: a study in south corumbataí producers association (PR). Brazilian Journal of Management and Regional Development, 13(2)
  • Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence‐informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. http://doi.org/10.1111/1467-8551.00375
    » http://doi.org/10.1111/1467-8551.00375
  • Turner, K., Ramsing, N., Wright, S., & Antonovskaya, I. (2013). Ukraine Horticulture Development Project: the use of incentives to motivate collective action. Enterprise Development & Microfinance, 24(2), 104-117. http://doi.org/10.3362/1755-1986.2013.011
    » http://doi.org/10.3362/1755-1986.2013.011
  • Uetake, T. (2015). Agri-environmental resource management by large-scale collective action: determining key success factors. Journal of Agricultural Education and Extension, 21(4), 309-324. http://doi.org/10.1080/1389224X.2014.928224
    » http://doi.org/10.1080/1389224X.2014.928224
  • Velasquez, M., & Hester, P. T. (2013). An analysis of multi-criteria decision making methods. International Journal of Operations Research, 10(2), 56-66.
  • Vitaliano, P. (1983). Cooperative enterprise: an alternative conceptual basis for analyzing a complex institution. American Journal of Agricultural Economics, 65(5), 1078-1083. http://doi.org/10.2307/1240424
    » http://doi.org/10.2307/1240424
  • Wangel, M., & Blomkvist, H. (2013). Rural forest management in sierra leone: the role of economic (in) equality in facilitating collective action. The Journal of Development Studies, 49(11), 1564-1578. http://doi.org/10.1080/00220388.2013.800860
    » http://doi.org/10.1080/00220388.2013.800860
  • Wenningkamp, K. R., & Schmidt, C. M. (2016). Ações coletivas no agronegócio: uma análise da produção científica no Brasil a partir de teses e dissertações (1998-2012). Revista de Economia e Sociologia Rural, 54(3), 413-436. http://doi.org/10.1590/1234-56781806-94790540302
    » http://doi.org/10.1590/1234-56781806-94790540302
  • Werthmann, C. (2015). What makes institutional crafting successful? Applying the SES to case studies from India and the greater Mekong Region. Environmental Science & Policy, 53, 165-174. http://doi.org/10.1016/j.envsci.2015.01.014
    » http://doi.org/10.1016/j.envsci.2015.01.014
  • Wilson, D. S., Ostrom, E., & Cox, M. E. (2013). Generalizing the core design principles for the efficacy of groups. Journal of Economic Behavior & Organization, 90, S21-S32. http://doi.org/10.1016/j.jebo.2012.12.010
    » http://doi.org/10.1016/j.jebo.2012.12.010

Publication Dates

  • Publication in this collection
    28 Oct 2024
  • Date of issue
    2024

History

  • Received
    12 May 2023
  • Accepted
    03 Aug 2024
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