Sustainable Development Goal 2 aims to end hunger, achieve food and nutrition security and promote sustainable agriculture by 2030. This requires that small-scale producers be included in, and benefit from, the rapid growth and transformation under way in food systems. Small-scale producers interact with various actors when they link with markets, including product traders, logistics firms, processors and retailers. The literature has explored primarily how large firms interact with farmers through formal contracts and resource provision arrangements. Although important, contracts constitute a very small share of smallholder market interactions. There has been little exploration of whether non-contract interactions between small farmers and both small- and large-scale value chain actors have affected small farmers’ livelihoods. This scoping review covers 202 studies on that topic. We find that non-contract interactions, de facto mostly with small and medium enterprises, benefit small-scale producers via similar mechanisms that the literature has previously credited to large firms. Small and medium enterprises, not just large enterprises, address idiosyncratic market failures and asset shortfalls of small-scale producers by providing them, through informal arrangements, with complementary services such as input provision, credit, information and logistics. Providing these services directly supports Sustainable Development Goal 2 by improving farmer welfare through technology adoption and greater productivity.
The past two decades have seen tremendous growth in developing regions. Urbanization has soared, diets have diversified and food supply chains have expanded. This growth has created huge markets for farmers, along with employment in various supply-chain segments1,2, including food processors, wholesalers and logistics firms. They are referred to as the ‘hidden middle’ because, though they constitute 40% of the average food supply chain, they are often missing from policy debates3. Their rise is important to small-scale producers because they are the farmers’ proximate interface with the market, through which farmers sell their products, receive logistics and intermediation services and buy farm inputs. The potential role of these value chain actors in assisting farmers to adopt sustainable practices and attain higher incomes is especially notable in light of Sustainable Development Goal 2 (SDG 2), which aims to end hunger, achieve food and nutrition security and promote sustainable agriculture by 2030. This requires that small-scale producers benefit from the growth and transformation under way in food systems.
The midstream and downstream of the food output and input supply chains have emerged as a growing field of research4,5,6. However, this literature has largely focused on the contracting of farmers by value chain actors, and in particular the formal provision of resources within contract arrangements with large processors and supermarkets7,8,9,10. Yet just a very small share of small-scale producers sell under contract directly to large firms3. Largely missing from the literature is evidence on (1) whether and how much value chain actors provide resources and services to farmers when the relation does not involve a formal contract and (2) whether interactions with these enterprises benefit small-scale producers in the absence of a formal contract. These questions pertain mostly to small and medium enterprises (SMEs) as they typically do not formally contract with farmers.
Here we present the findings of a protocol-driven scoping review that explores whether transactions without formal contracts with value chain actors improve the welfare of small-scale producers in developing regions. We filtered for studies that consider supply-chain transactions by value chain actors involving small-scale producers (that is, non-credit input purchase, logistics service purchase and output sales by farmers to/from value chain actors) that are not governed by formal contracts. This yielded a set of studies largely focused on SMEs. Then we analysed whether the outcomes of these economic relations were positive for small-scale producers, as well as what explained any positive or negative outcomes (Fig. 1). See the Methods for full details and Box 1 for a summary.
A key contribution of this review is to show that, contrary to expectations, it is common for SMEs in non-contract relations to undertake complementary resource provision similar to that observed among large companies in contract schemes11,12. In addition, when SME value chain actors provide these services that are beyond their core activities, it is correlated with technology adoption and higher productivity among farmers. These findings are instrumental towards achieving the goals of SDG 2. Particularly in developing countries in Africa and South Asia (where small-scale producers dominate), the growth and transformation of food systems drives a proliferation of midstream SMEs which, our results show, can be a force inclusive of, and beneficial to, small-scale producers.
Figure 2a presents the distribution of the included studies by publication type. A majority of the included studies (73%) are peer-reviewed journal articles. Ten percent are working papers published in grey-literature outlets, 7% are conference papers, and book chapters and theses/dissertations each account for 5% of the included studies. Most studies were scored as being of ‘high quality’ using the criteria explained in the Methods; just 15.5% (quantitative) and 20% (qualitative) of the studies were scored as being of low quality, usually because the study lacked sufficient details on its methodological approach.
There has been a dramatic increase in research interest in the relationship between small-scale producers and our focal actors in the past ten years. Over 40% of our selected studies were published within the past four years and over 80% in the past ten years (Fig. 3). Across all studies, 33% are of settings in Asia, 49% in Africa and 21% in Latin America. Thus, less attention has been given to measuring the impacts of small-scale producers’ engagement with these focal actors in Asia or Latin America compared with Africa. This might reflect more funding opportunities and/or the prevalence of small-scale agriculture in Africa.
While 77% of the included studies focused on crop production, just 18% focused on livestock production (with the remaining studies having a dual focus). This reveals a gap in the literature, particularly given rising animal-protein consumption and the associated supply response in developing countries. More studies on livestock will be important to improve the likelihood of small-scale producers’ successful participation in value chains with sustainable agricultural practices1,13,14. We also find more emphasis on high-value crops in 55% of the studies, compared with 39% that look at staple crops (Fig. 2b).
There is an extremely limited gender and environmental focus in the literature. Only 24 (12%) of the 202 studies include a focus on gender, and 17 (9%) focus on the extent to which marketing channels promote the adoption of environmentally sound agricultural practices. This demonstrates a mismatch between rhetoric and reality in policy debates (which highlight gender mainstreaming and sustainability) and development research. Further research on gender-related issues and how SMEs in the midstream of value chains could increase farmer adoption of environmentally safe practices is needed to guide efforts to promote sustainable agricultural practices in line with SDG 2.
Few studies consider a primary outcome (such as income, poverty or food security) alongside a secondary or intermediate outcome (such as technology adoption or increased yields). This indicates that the final welfare effect of farmers’ interactions with market channels is a gap in the literature.
Non-contract SME market channels provide key services
A key finding of this review is that value chain actors across the midstream segments of trade, processing and logistics provide a wide set of complementary services to farmers, outside the vehicle of formal resource provision contracts. More surprisingly, this is not restricted to large enterprises but is widespread among SMEs. We categorized the focal actor cases in the included studies by whether they were identified as being small and find that the value chain actors (that is, traders, processors and logistics companies) in an overwhelming majority of the included studies are not large multinational companies but SMEs. Small enterprises comprised 75% of the cases for traders and almost 90% for processors. This is probably because we excluded formal contract arrangements, typically conducted by larger enterprises.
Finding that SME value chain actors provide complementary services shifts the debate on their role in markets. These findings show that SMEs directly improve the market context for small-scale producers and promote inclusion, while such improvements were previously attributed mostly to large companies using contract arrangements. Thus, SMEs (which are more accessible to small-scale producers than are formal contract arrangements) play an important role in facilitating inclusive growth as food systems transform in developing regions.
Table 1 disaggregates the kinds of services (beyond purchasing) provided by output market channels. The main complementary service provided by SME processors (also the second most common for traders) is credit provision. Credit was provided in 22% and 31% of farmer interactions with traders and SME processors, respectively (OM2B in Fig. 1). This links to the traditional tied-output credit market literature of the 1970s focused on SME traders, which cast them as exploitative actors who offered advances of credit to farmers and then gouged them with exorbitant implicit interest rates extracted at harvest from the sale price15.
Our findings differ from the traditional tied credit–output literature in that we find that credit provision is provided not only by traders but also by other value chain actors and is actually more likely to be provided by SME processors even in the absence of contracts. We also find that the majority of outcomes of the transactions are beneficial to small farmers, not exploitative as suggested by the old literature.
Processors and cooperatives also provide extension services and inputs to farmers. In 35% of interactions with cooperatives (19% for processors) that purchased products from small-scale producers, the buyer also offered some sort of training (OM2A in Fig. 1), while in 25–30% of interactions with these focal actors, inputs were provided.
Compared with traders and cooperatives, supermarkets are less likely to provide credit and inputs but not less likely to arrange for transportation of the product. We refer to these logistics services (such as transport) as OM2C in Fig. 1. Purchase agreements can involve farmers being included on a buyer’s lists or, less formally, repeated transactions between a farmer and an output market channel (Table 3). For supermarkets and traders, the provision of purchase agreements (informal but consistent interactions) was prevalent, provided in 50% and 25% of links with farmers, respectively. This indicates that there is some effort to formalize the relationship and guarantee repeated interactions in these market channels.
We consider that three levels of formality can govern relations between output market channels and farmers. The first includes written contracts and/or contract farming arrangements—which we exclude from this scoping review. The second includes oral or unwritten contracts such as a farmer being included on a supplier’s lists, which suggests some degree of formality. The third includes repetition of transactions between a farmer and buyer. For traders, we assume that purchase agreements fall into category 3 (the least formal interaction). For processors, since over 90% of them were identified as small, we also consider purchase agreements to be in category 3. For supermarkets and government programmes captured in this scoping review, we consider purchase agreements to be in category 2 or 3. These less formal arrangements are quite common in modern value chains in developing countries.
The ‘other modern’ market channels (agro-export companies, marketing platforms and high-value chains) also tend to provide services for farmers in addition to an output market. Inputs were provided to farmers in 38% of links with these modern market channels. Extension and credit were provided in 25% and 19% of the interactions, respectively. Almost 31% of these interactions involved a purchase agreement, while transportation arrangements (OM2C) were made in 19% of these interactions. These modern market channels are therefore similar to the main output market channels in providing these additional services.
Although our sample size is limited for input suppliers, we find that they also provide additional services, such as credit and training (Extended Data Table 1). In over 40% of interactions with cooperatives (where their primary role was as an input provider), training/extension was offered. This was also the case for 31% and 33% of farmer interactions with other input suppliers and logistics service providers, respectively (IS2A and L2A in Fig. 1). Finally, logistics service suppliers (in 44% of their interactions with farmers) and cooperatives (in 25% of their interactions as input provider) purchased output from farmers. This is consistent with studies that have documented that some truckers also serve as wholesalers or purchase output from farmers on behalf of traders6,16, and this underscores how the provision of complementary services in the midstream and downstream of input and output value chains is well recognized in the private sector.
Across product types, the share of focal actor cases where complementary services were provided is higher for links with livestock farmers compared with crop farmers (Extended Data Table 2). Among crop farmers, the particular type of assistance varies between interactions dealing with high-value crops compared with staple crops. For example, the percentage of cases where an output buyer provided a purchase agreement is much higher for high-value crops (34%) compared with staple crops (22%). However, provision of warehouse services is higher (at 6%) for staple crops than for high-value crops (at 2%).
Government agencies provide fewer services
Contrary to what we find for non-government output market channels, we do not see much evidence of complementary service provision by government agencies. Instead, the agencies tend to focus on their primary role of buying farmers’ output (OM1). However, they are similar to supermarkets and traders in the high likelihood of using purchase agreements (50%), which we also refer to as a primary market function (an OM1 activity) since it may be somewhat more consistent (guaranteed) than the spot market (Fig. 1).
Non-contract market channels improve farmers’ welfare
Another main finding of this scoping review is that a majority of the recorded interactions between small-scale producers and value chain actors are positive. Specifically, 83% of cases exhibit a positive result for at least one outcome assessed in the study. This value is 81% for output intermediaries, 96% for input suppliers (largely cooperatives and agro-dealers) and 100% for providers of logistical services (although there are just nine cases in the latter group).
Table 2 displays the outcome patterns by geographical location and product type. It is less common for engagement between market channels and small-scale farmers to result in a positive outcome for farmers in Latin America compared with other continents. While interactions are generally positive, the share of total interactions with a positive outcome is higher for studies looking at livestock (87%) compared with crops (83%). Among crops, it is higher for staple-crop farmers (88%) than for farmers of high-value crops (83%).
Among all outcomes assessed in these studies, the study focal actors produced a positive outcome for farmers in 77% of the cases (Extended Data Table 3). Across the three outcome categories illustrated in Fig. 1, this value is 77% for primary outcomes such as income and food security, 67% for intermediary outcomes such as yield and 84% for secondary outcomes such as technology adoption. Because so many of these observations are of buyers, the values for buyers alone are very similar (at 77%, 63% and 82% for primary, intermediary and secondary outcomes, respectively). For input suppliers alone, these values are 88%, 93% and 94% (N = 64 in total).
The provision of complementary services appears to be instrumental in fostering a positive outcome from farmers’ interactions with these input and output market channels. Table 3 presents information on the links that lead to either positive or negative/inconclusive outcomes for farmers. Among output intermediaries (columns 1 and 2), it is more common for positive outcomes to follow from exchanges that include arrangements for transportation, the provision of credit or inputs, and the provision of extension. For example, 12% of cases with positive impacts involve the buyers extending some sort of logistical assistance to arrange for transportation of the agricultural products, while this value is just 8% for cases with negative or inconclusive impacts. This pattern is consistent with the mechanism (OM2 in Fig. 1) laid out in the conceptual framework. For input suppliers, a higher percentage of cases with a positive impact involve the suppliers also purchasing output from the farmers. The provision of marketing services alongside input supply (IS2D in Fig. 1) is consistent with the rise of farmer aggregator services that supply farmers with inputs but also procure their outputs or link them with buyers13.
Overall, these results shed light on a set of activities undertaken by focal actors that tend to yield additional benefits for farmers. These services appear to fill gaps in what small-scale producers require to undertake transactions, including arranging transport and providing credit and inputs, private extension, storage and warehousing, and even irrigation services. In the great majority of cases, the interaction with these midstream enterprises benefits the farmers, and this benefit tends to be greater for men than for women in the limited studies with gender considerations.
Contrary to our expectations, it is not more common for cases with positive outcomes to include informal purchase agreements compared with cases that have negative or inconclusive outcomes. The difference between positive and negative outcomes seems to derive from the complementary services that output intermediaries provide for farmers beyond buying their products. These include the provision of training, credit and logistics services. This is extremely important as it indicates that the provision of complementary services by output intermediaries tends to be key for the interaction to be positive for small-scale producers, even conditional on the existence of pseudo-contracts.
Facilitators of positive outcomes
One hundred eighteen of the 202 included studies mention at least one condition that enables interactions with our focal actors to have a positive effect on small-scale producers. These conditions can be grouped into three broad categories. (1) Complementary services and activities provided by focal actors can bolster the positive effect of the interaction with small-scale producers. These activities—IS2, OM2 and L2 in Fig. 1—refer to additional services provided by input suppliers, output market channels and logistics service providers, alongside their main role of input or output intermediation (IS1, OM1 or L1, respectively). (2) Positive outcomes can derive from access to infrastructure. (3) A conducive policy environment can facilitate mutually beneficial interactions between farmers and the focal actors.
The provision of complementary services is a key condition supporting positive outcomes of small-scale producers’ interactions with focal actors. This was noted in 65% of the instances where positive enabling conditions were mentioned. The services most frequently cited were capacity building and training (extension) for farmers (mentioned in 23% of the included studies) and the provision of credit (mentioned in 16%). Other important complementary services include the availability of multistakeholder market platforms (mentioned in 14%) and market information (mentioned in 12%) (Extended Data Fig. 2).
The included studies demonstrate that training and capacity building can support small-scale producers as they upgrade their production to satisfy the requirements of modern market channels17,18,19,20,21. Market information increases the speed of farm product sales while allowing farmers to bargain more effectively and obtain better prices22,23,24. Providing timely access to affordable credit also supports the adoption of modern technologies25,26, and platforms that facilitate interactions among stakeholders improve the performance of value chains27,28.
The availability of rural infrastructure, including irrigation, transportation, processing, storage and communications, was noted as a facilitating condition in 23% of the studies. In addition to easing the provision of complementary services, access to transportation (road infrastructure) enables farmers to gain better price terms from both informal and formal market channels29,30, and cold storage infrastructure, which reduces food wastage, has been found to increase producers’ sales and generate higher prices in the off season17,31,32.
A stable policy environment, characterized by enforcement of regulations and the enactment of enabling policies, was mentioned as a facilitating condition in 18% of the studies. Strong regulations can help protect farmers from exploitation by output intermediaries33. Furthermore, supportive marketing and trade policy reforms (liberalization of input and maize markets) have been found to lead to increased input use and crop productivity34.
Factors associated with negative outcomes
Forty-six of the 202 studies (23%) explicitly discussed challenges that impede the ability of value chain actors to upgrade producers’ practices or improve their welfare. In order of importance (that is, the number of studies that mentioned a factor), the main inhibitors were capacity constraints, lack of trust between farmers and the focal actors, high transaction costs, non-inclusiveness, financial constraints and market power (Extended Data Fig. 3).
The low technical capacity of cooperatives and traders (the two major focal actors documented in the literature) limits their ability to support farmers6,35,36,37,38. Inadequate managerial and organizational skills can lead to collective action failure, and poor coordination in fulfilling agreements with buyers can limit market opportunities for the entire group39,40,41.
The detected lack of trust might reflect the prevalence of informal contract arrangements in the included studies. Low trust coupled with an unstable market environment, as well as information asymmetry due to weak institutional arrangements, creates room for opportunistic behaviour by all parties42,43,44. Moreover, a lack of trust between cooperative members and their leadership could result in failure to deliver on agreements28,45,46,47,48.
High transaction costs are generally driven by additional risks or monitoring costs both parties incur during the interaction24,40,49,50,51. Buyers fear side selling while farmers fear product rejection52,53,54. In addition, transaction costs and capacity constraints can be exacerbated when infrastructure is poor and the relationship involves the poorest and most marginalized producers36,37,38,55,56,57,58,59,60,61.
Financial constraints limit buyers’ ability to provide farmers with services ex ante and thereby help them to upgrade40,62. This closely aligns with the finding that focal actors’ provision of complementary services was instrumental for their successful interaction with farmers. However, buyers’ market power can substantially reduce the benefits farmers derive from interactions with them, as they can transfer demand shocks to remote farmers with few market options63,64.
This review confirms that that there has been a rapid development of the midstream and downstream actors in output value chains—processors, traders and cooperatives—that buy crops and livestock products from small-scale producers. Moreover, there has also been a proliferation of value chain actors in input supply chains (agro-dealers) that supply inputs as well as services (such as training and logistics arrangements) to small-scale farmers. These value chain actors and the complementary services they provide help small-scale producers upgrade their practices, raise their productivity and subsequently improve their welfare.
The importance of these actors has been recognized with a rapid increase in the number of studies on these intermediaries in the past decade. However, the available literature is heavily tilted towards crop value chains rather than livestock, and towards high-value crops rather than staple crops. Farmer interactions with market channels and across both kinds of value chains (crop and livestock) and across crop types tend to have a positive effect on small-scale producers.
Contrary to the articulated focus by policymakers and governments on gender equality and environmental sustainability, we find extremely limited emphasis on these issues in the literature. We thus note a dearth of empirical evidence on the role that SMEs in the midstream and downstream of input and output value chains can play in the adoption and dissemination of agricultural practices that will preserve the environment or increase small-scale producers’ resilience to climate change. To promote the SDGs, particularly SDG 2, additional research on how value chain actors can increase farmers’ knowledge and adoption of environmentally safe practices would be valuable. Similarly, more evidence is needed on the conditions that allow both women and men small-scale producers to benefit from SMEs. Private-sector platforms that serve as one-stop shops for farmers to secure inputs, training, credit and a guaranteed market are emerging in developing countries. Further studies on whether and how these platforms could support the adoption of sustainable agricultural practices in crop and animal production are necessary.
Given the study findings of abundant midstream enterprise activity that is generally supportive of small-scale producers, we question whether governments need to directly provide these services. It appears to us that direct public provision would crowd out these midstream enterprises and waste public resources. These midstream enterprises serve as allies to governments in the provision of key rural services. Thus, efforts to support their operation and their continued and expanded provision of complementary services to small-scale producers should be considered (Box 2).
These intermediaries can directly support zero hunger and improved welfare through the inclusion of small-scale producers that otherwise would have been excluded. They have the potential to expand small-scale producers’ access to knowledge and provide incentives to adopt sustainable agricultural practices. Thus, they can be instrumental towards achieving the objectives set forth by the United Nations’ Sustainable Development Goal of zero hunger by 2030.
A scoping review identifies trends, concepts, theories, methods and knowledge gaps across a broad range of literature65, while highlighting key areas for future research and engagement66. A scoping review comprises five steps: (1) articulating the research question, (2) searching published and grey literature for relevant studies, (3) selecting studies on the basis of pre-defined criteria, (4) extracting and charting the data and (5) collating, summarizing and reporting the results. In this review, we made use of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews65 and guidance provided by Peters et al.67 in designing and reporting the methods. This review leverages a data science framework to accelerate the work within each of the individual steps as described in the following. A protocol for this study was developed before data collection and was registered on the Open Science Framework68.
Search methods for identifying relevant studies
We developed a comprehensive search strategy to find all relevant studies that assess the impacts of interactions between small-scale producers and our focal actors in the midstream and downstream of the food-product and input supply chains. The Supplementary Information presents the search strategy used in CAB Abstracts, and all of the search strategies used are available on the Open Science Framework68.
We searched the following electronic databases: CAB Abstracts (Clarivate Analytics), Web of Science Core Collection, Scopus, EconLit (Ebsco), Dissertations & Theses Global (ProQuest), Africa Theses and Dissertations (http://datad.aau.org/discover) and AgEcon Search (https://ageconsearch.umn.edu). In addition, over 15 sources of grey literature were searched68 using custom web-scraping scripts. The results from the databases and the grey-literature searches were combined and deduplicated. Additional studies were included through consultation with experts in this field of research and on the basis of the authors’ previous knowledge.
The studies were then screened in three phases. In a first step, each citation was analysed using a machine-learning model that added over 30 metadata fields such as the studies’ populations, geographies, interventions and outcomes of interest. This accelerated our identification of articles for exclusion, in which records were excluded by a single screener when they clearly did not meet our criteria (for example, published before 2000, not in a low- or middle-income country or focused on a non-food product).
The remaining records were imported into Covidence (https://www.covidence.org) for title/abstract and full-text screening. In both steps, studies were screened by two independent reviewers, and conflicts were resolved by a third reviewer. Studies in which insufficient information was available to determine whether our criteria for inclusion were met were passed on to the full-text screening phase. Extended Data Fig. 1 presents the number of studies included and excluded at each step of the screening process.
We included studies that assessed impacts on small-scale producers of food crops, fish, dairy and livestock in low- and middle-income countries in Africa, Asia and Latin America. Studies were included if they made a clear reference to a link or interaction between small-scale producers and the study’s focal actors in terms of a physical and/or monetary exchange. Focal actors were defined on the basis of the functional role that they play as an intermediary in the midstream and downstream of output and input supply chains (Fig. 1). Importantly, we did not include credit as an input here. We also did not include certification and its impacts on welfare effects, or contract farming between large enterprises and small farms, because they have been explored in two separate and recent systematic reviews10,69. The systematic review by Ton et al. 10 reports that contract farming may increase farmer incomes substantially, but this is largely restricted to larger farmers. Included studies measured at least one of our primary, secondary or intermediate outcomes, as shown in Fig. 1.
We focused on farmers’ output production and sale and not on their household labour supply as our focus is the farm enterprise. It is possible that value chain actors could affect labour supply and subsequently labour choices in farm enterprises, thus indirectly affecting farmer practices, but this was not part of our study.
Regarding study design, both experimental and observational studies were considered, including quantitative and qualitative work. However, studies were excluded if they lacked clear objectives or had small sample sizes and lacked a justification for this limitation. Studies using data collected before 2000 were excluded from the review, given our focus on modern marketing channels. Due to time constraints and limited expertise on the team, studies in any language other than English were also excluded from the review. We recognize this as a limitation and encourage the inclusion of this literature in future iterations on this work. For a detailed explanation of selection criteria, see the scoping review protocol in Open Science Framework68.
Data extraction and analysis
Relevant information from each included study was extracted by at least one review author. The extracted data included bibliographic information, information about the study design, sample size, producer characteristics and information about the focal actors and their interactions with producers. Information on the nature of the interactions, the outcomes measured and the effects on small-scale producers were recorded. In addition, we noted whether a study addressed issues of climate change, environmental sustainability or gender. While an assessment of study quality is not typically carried out as part of a scoping review67, we conducted a general methodological assessment on the basis of three questions related to the appropriateness of the methods used. Bibliometric data were examined to identify publishing and research trends. Journal impact factors for studies published in peer-reviewed journals were retrieved from Journal Citation Reports (Clarivate Analytics).
The quality of each study’s ‘methodology description’ and ‘methodology justification’ was assessed to be high, low or uncertain/questionable. ‘High’ meant there was a clear description of the sampling methods used (for methodology) and a clear justification of the selection of the research site(s), research design and/or methods used to collect and analyse the data used (for methodology justification). Studies that clearly did not meet this were considered to be of low quality. Studies for which the reviewer remained uncertain after applying the criteria were labelled as uncertain. Overall subjective quality assessment for each study was based on how convinced a reviewer was of the quality of the methodology and its justification from the two previous questions. Papers were ranked as low, medium or high using the following guide. If the responses to the two previous questions were both high, then it received a high assessment overall. If they were both low/uncertain, then this was a study of low/uncertain quality. If the responses were high and then low or low and then high, then this was a study of medium quality.
The extracted data were summarized on the basis of emerging themes and with the aim of providing recommendations to donors and policymakers.
The data that support the findings of this study (that is, the data extracted from the 202 studies, as described in the Methods) are available from the corresponding author on request.
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We acknowledge and appreciate financial support for this work from the Ceres2030 project. We also appreciate support from the US Department of Agriculture National Institute of Food and Agriculture and Michigan AgBioResearch, Consortium of International Agricultural Research Centers (CGIAR), World Bank, International Institute for Sustainable Development (IISD) and Centre for Agriculture and Bioscience International (CABI) with core financial support from its member countries (http://www.cabi.org/about-cabi/who-we-work-with/key-donors/). These funders were in no way involved in the study design; in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. The contents are the responsibility of the authors and do not necessarily reflect the views of any donor or donor country. Any views expressed or remaining errors are solely the responsibility of the authors.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 PRISMA flowchart of screening.
The number of articles retrieved in the searches and passed each subsequent stage of screening is shown.
Extended Data Fig. 2 Main facilitators of positive interactions.
Source: Authors’ calculations. The facilitators of positive interactions between focal actors and small-scale were classified into ten different groups. The observation level is the included study that mentioned a facilitating condition for a transaction between a small-scale producer and a value chain actor. There were 118 mentions; thus, N = 118.
Extended Data Fig. 3 Main challenges in focal actor interactions with farmers.
Source: Authors’ calculations. The main challenges impeding the successful interaction between study focal actors and small-scale producers were categorized into 6 groups. The observation level is the included study that mentioned a challenge affecting the transaction between a small-scale producer and a value chain actor. Thus, N = 57.
Extended Data Table 1 Types of assistance provided by input suppliers and logistics service providers.
Source: Authors’ calculations. The type of assistance provided to farmers is disaggregated by input suppliers and logistics service providers. Included studies were coded to tabulate the focal actor linkage that was captured within the study. An individual study could look at multiple focal actors (for example traders and processors). This yielded 241 linkages or ‘focal actor cases’. Of the 241 linkages, 204 were output buyers and 37 were input suppliers or logistics providers. This table presents the distribution of services provided for input suppliers and logistics providers only; thus, N = 37.
Extended Data Table 2 Types of assistance provided by product type of farmer.
Source: Authors’ calculations. Type of assistance is disaggregated by product type of farmer. The 202 included studies were coded to tabulate the focal actor linkage that was captured within the study. An individual study could look at multiple focal actors (for example traders and processors), this yielded 241 linkages or ‘focal actor cases’. Of those 241 focal actor cases, 204 are with output buyers. This table presents the distribution of these 204 focal actor linkages for output buyers. Observations can overlap across the three columns, as some farmers produce more than one type of agricultural product (see Fig. 2b). Thus N = 226.
Extended Data Table 3 Impacts on farmers by outcome category.
Source: Authors’ calculations. The impacts of interacting with value chain actors is disaggregated by outcome type (primary, intermediary or secondary). a The unit of analysis in this table is the outcome evaluated in a given study and by a given focal actor. 555 outcomes were evaluated in the 202 included studies.
Supplementary Table 1
Data extraction form.
Supplementary Table 2
List of included studies and key characteristics.
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Liverpool-Tasie, L.S.O., Wineman, A., Young, S. et al. A scoping review of market links between value chain actors and small-scale producers in developing regions. Nat Sustain 3, 799–808 (2020). https://doi.org/10.1038/s41893-020-00621-2
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