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Agricultural innovation systems and farm technology adoption: findings from a study of the Ghanaian plantain sector
Abstract and Figures
Purpose: We assess farm technology adoption in an integrated analysis of social networks and innovation in plantain production in Ghana. The paper explores the strength of social networks in the agricultural innovation systems (AISs) and the effect of AISs on adoption of improved farm technology.
Methodology/Approach: The paper uses social network analysis (SNA) tools to identify, map and analyze the AISs and the two-stage Heckman selection model. Combining qualitative and quantitative methods allows testing the differential effects of social networks on technology adoption.
Findings: We find weak innovation systems in the study area. Farmers are central in the social networks but have little to no influence in the innovation system perspective. Social network capital plays a critical role in improving adoption of improved farm technology.
Practical implication: Focal farmers are important actors disseminating farm technology. They should be supported by policies to interact more effectively with research and extension agents. Strengthening the role of social networking in the innovation system will enhance adoption of improved farm technology.
Theoretical implications: The inclusion of SNA indicators in the adoption model is a novel approach for quantifying the effect of the innovation system and contributes to understanding the roles of different actors. Further validation of the SNA indicators is needed for a comprehensive analysis of the innovation system.
Originality/value: The innovation system approach is useful for researchers and policy-makers by encouraging them to consider new innovation actors and relationships in technology development and dissemination. Combining quantitative and qualitative methods can help to identify starting points for policies to promote innovations among farmers.
full text available here: http://www.tandfonline.com/eprint/vfQutrwNb6K2qZhFuzPe/full
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... Previous studies have examined the impacts of IPs on farmers' welfare. These include studies that examined the impact of IPs on technology adoption (Asante et al. 2021;Bush et al. 2021;Nyikahadzoi et al. 2012;Pamuk, Rijn, and Van 2019;Weyori et al. 2018) and the welfare of farmers (Ahimbisibwe et al. 2020;Mango et al. 2017;Mapila, Kirsten, and Meyer 2012;Pamuk et al. 2015). However, the impact of IPs is inconclusive according to empirical research, which implies that the effectiveness of IPs varies from one platform to another. ...
... Only a few studies on IPs have been conducted in Ghana (Martey et al. 2014;Weyori et al. 2018); consequently, there is a lack of empirical research on the impact of IPs on farmers' welfare. Additionally, while previous studies have focused primarily on a single or double welfare indicator, our study adds to the body of literature by investigating the effect of IPs on three key welfare indicators: maize yield, household income and per capita household expenditure using the doubly robust IPWRA method, complemented by the PSM technique. ...
... This approach by itself is inadequate for promoting agricultural innovation (World Bank 2007). Given the advancements in agricultural research and development in the African region, it is unfortunate that the livelihoods of resource-poor farmers have not seen significant improvement (Tenywa et al. 2011;Weyori et al. 2018). According to Pamuk et al. (2015), the conventional research approach has not yielded significant results due to its oversimplified perspective on the innovation process. ...
... Pathak, Brown, and Best (2019) found that the characteristics of the farm play an essential role in the adoption of precision agriculture. Weyori et al. (2018) found that smallholder farmers with larger farm sizes were older, above 58 years, and had more farming experience, though with an education level of less than five years. Furthermore, Weyori et al. (2018) also found that smallholder farmers S. Afr. ...
... Weyori et al. (2018) found that smallholder farmers with larger farm sizes were older, above 58 years, and had more farming experience, though with an education level of less than five years. Furthermore, Weyori et al. (2018) also found that smallholder farmers S. Afr. J. Agric. ...
Social media has the potential to provide enhanced and faster measures of disseminating agricultural information to smallholder farmers. This study investigated socioeconomic characteristics encompassing demographic factors affecting smallholder farmers' adoption of social media. The study focused on varying livestock and crop smallholder farmers, including cattle, goats, maize, sugarcane, and leguminous crop producers. A cross-sectional survey was employed to collect the data using a structured questionnaire. Descriptive statistics and a Binary Logistic Regression was used to analyse the data. The sample size was 217 smallholder farmers. The results revealed that age, level of education, annual farming income, and cooperative membership were statistically significant (p < 0.05) in social media adoption. The study findings show that skills and training in ICT increase the probability of adopting social media, and the socioeconomic characteristics of smallholder farmers influence its adoption. The study concludes that stakeholders such as local government must improve smallholder farmers' basic literacy and skills in digital technology. It further recommends that policymakers formulate policies that provide the necessary infrastructure and supporting inputs such as open access internet, cell towers, and cooperative social media platforms that allow for interactive interactions with relevant stakeholders that provide advisory services.
... These platforms bring farmers together with public and private actors to exchange knowledge and ideas for joint learning, action, and problem-solving (Cullen et al., 2014;Ros-Tonen et al., 2015). MSPs recognise that farmers' local knowledge, experiences, and own initiatives fundamentally shape agricultural innovations and can trigger peer-to-peer learning between farmers (Adolwa et al., 2017;Dabire et al., 2017;Weyori et al., 2018). This paper focuses on the inclusion of smallholder farmers' local knowledge in knowledge exchange and joint learning in MSPs. ...
... The research team was surprised by the evidence of peer-to-peer learning (design principle 4), given that the meetings were organised only once a year. The literature mentions continuous engagement and participation by farmers as preconditions for knowledge and innovation uptake (Betge et al., 2020;Dabire et al., 2017;Weyori et al., 2018). While increased yields or income resulting from MSPs are also reported in the literature (e.g. ...
Research on knowledge exchange in multi-stakeholder platforms (MSPs) within smallholder farmer settings has primarily focused on adaptive designs and increased innovation rates. This paper addresses a knowledge gap by providing insights into the limited understanding of how knowledge sharing in MSPs can be inclusive of smallholder farmers’ knowledge. It shares experiences with a farmer-centred approach to learning and knowledge-sharing with smallholder farmers in Ghana and places this iteratively developed approach within a theoretical perspective. We relate the farmer-centred approach to five design principles inspired by human-centred design rules and inclusive development dimensions. Findings from observations, interviews, and focus group discussions illustrate how the farmer-centred approach creates multifunctional spaces for peer-to-peer learning, interaction with institutional actors, and network building (design principle 1). Prior farmer-centred research ensured that themes addressed were relevant to participant farmers and brought their innovations ‘from below’ to the table (design principles 2 and 3). A majority representation of farmers, facilitation by local researchers, and organising platform meetings at the district level created a safe space for farmers to share their knowledge and feel included and empowered (design principle 4). Several local institutional actors took ownership of the platform principles, which created opportunities for their manifestation in future collaborations with farmers (design principle 5). However, challenges remain in engaging crucial actors from higher scale levels and reducing donor dependency. The design principles presented in this paper contribute to the genuine inclusion of farmers’ knowledge and innovations. We recommend government agencies at the national and district levels incorporate these design principles into their work plans and budgets and prioritise farmers’ knowledge and innovation capacity for inclusive learning and knowledge co-creation.
... The innovation process is influenced by complexity of multiple factors which influences outcomes of interventions. Studies have shown that farmers demographic characteristics and personal goals (Assan et al., 2018;Pannell and Zilberman, 2020;Tsige et al., 2020); trialability and observability of the innovation (Pannell et al., 2011;Weersink and Fulton, 2020); farmers social network and interaction (Maertens and Barrett, 2013;Weyori et al., 2018;Streletskaya et al., 2020); farmers access to information and extension services (Nyasimi et al., 2017;Say et al., 2018); relative advantage of the technology (Meijer et al., 2015;Brown et al., 2017;Rodenburg et al., 2021); sociocultural and political conditions in the external environment (Kendall et al., 2022;Shilomboleni, 2022) are crucial in shaping the innovation process. Moreover, the local context and enabling conditions is critical to shape innovation process (Zanello et al., 2016;Hermans et al., 2021). ...
... decisions about whether and at what points to engage with or disengage from a process of trialling innovations (Hermans et al., 2021). Farmers involvement and interaction within the social system provide access to information, enhances social capital, build trust, and can influence decision making in relation to innovations (Weyori et al., 2018;Leeuwis and Aarts, 2020). Farmers awareness of innovation is largely determined by their social networks, which can be both informal (friends, community members) and formal (extension agents and non-state actors). ...
Climate-smart agriculture (CSA) has gained traction as one of the effective strategies in tackling the climate crisis. Many CSA practices have been promoted by development agencies to smallholder farmers based on the assumption that farmers would adopt these innovations for their potential benefits. However, the adoption of CSA practices in Ghana and much of Africa remains low and decision making and on-farm innovation processes are poorly understood. This study seeks to provide empirical and participatory insight into how smallholder farmers innovate. Based on a novel application of a participatory video methodology, in farming communities in the Upper West Region of Ghana, that have been exposed to multiple CSA intervention programmes, the paper analyses farmers’ own self-curated accounts of experiences with CSA innovation. The findings show that farmer’s motivation to adopt CSA innovations is driven by their concerns for food security, economic gains, and the environmental impact of climate change on their farming activities and livelihood. The study reveals a mismatch between the CSA technologies and practices advanced by the development agencies and what farmers perceive as relevant and important in addressing their farming challenges. In particular, the findings show that in a pool of more than 12 CSA technologies and practices that had been promoted through three donor-driven intervention programmes in the communities, farmers selected less labour intensive, less costly, and CSA technologies and practices that fitted to their current farming practices and the local context. Agricultural extension agents served as an important information source on the CSA innovation and their practical implementation and farmers’ social groups played a crucial role in facilitating learning about the CSA technologies and practices. There is the need to integrate farmers voices using innovative methodologies such as participatory videos to better understand farmers’ experiences in the innovation process which will help inform the design of effective interventions and promote adoption of innovations aimed at enhancing the productivity of smallholder farmers and reducing environmental impacts in African food systems. By focusing on the innovations that farmers perceive as beneficial and adaptable to their local contexts, development organizations can use their resources more efficiently and promote adoption of contextually appropriate CSA innovations.
... Our results from Hypothesis 1, which suggests Influential Farmers are unlikely to retrieve information from those who retrieve information from them showed that key farmers with a variety of information or great expertise were popular advisors for their peers and were less keen to seek information from their peers which confirms the study of Weyori et al. (2017) that farmers in the central position (''focal farmers'') could be worked with more closely by extension services for more effective results since they are popular and influential. Key farmers have a better knowledge of agricultural practices and have the capacity to transfer this knowledge to their peers. ...
It is well established that a person’s productivity is strongly related to interactions among their network cycles. Despite this, much of the literature concerning farmers’ productivity describes only their formal relationships with extension officials, ignoring their personal relationships. This study was motivated by the need to understand how farmers can use their social networks to promote information diffusion and learning among themselves. The study assessed whether farmers’ information networks can positively influence their productivity and performance through the study of their network structure. We used survey data from 200 Ghanaian farmers. The data was then analyzed using descriptive statistics and an exponential random graph model (ERGM). The results of this study showed that farmers’ information networks had a positive effect on their performance and productivity. The study also revealed that farmers seek information from key and influential farmers while key farmers also seek information from other key farmers. A further finding of the study showed that many factors contributed to the successful diffusion of information, such as popularity, activity spread, reciprocity, multiple connections, and homophily of experience. However, on the other hand, transitivity was not significant in this network. Hence, this study clarifies the effect of the structural characteristics of farmers’ information network which influence information diffusion for higher performance and productivity. This study argues that agricultural managers should take measures to ensure that farmers understand how their information network can benefit their peers, as well as their own performance and productivity.
... As such, they are always enthusiastic about looking for new and up-to-date information. This is consistent with other studies which claim that information is spread faster and best with "focal farmers" (Arif et al., 2017;Weyori et al., 2018). These farmers are popular and influential. ...
Smallholder farmers in developing countries are considered the backbone of the agricultural sector. Their activities can promote food security and enhance economic growth if proper attention is given. We can understand these farmers and their operations better if we effectively engage them by studying their network structure. Farmer networking is often regarded as a better means of connecting smallholder farmers to markets, enhancing their welfare and stimulating modernization within the farming sector. Exponential random graph model (ERGM) which is a method in social network analysis was used to examine the network construction process and the microstructure of the smallholder farmers’ network in Ghana. Our findings revealed that their network was well connected and centered on some farmers who were popular within the community. While some of these farmers hold positions within the community, others are advanced in age. The microstructure shows some sort of hierarchy structure as the formation of this network depends on the ability of a farmer to receive ties but not vice versa. Hence, this study illuminates how the structural characteristics of this network affect social collaborations among farmers, thus influencing information diffusion for productivity and performance. It is recommended that smallholder farmers' networks should be utilized for helping and monitoring the progress of the agricultural sector by the government and stakeholders. This will enable them develop novel ways through which they can help make agriculture more productive and enhance food security.
... These important actors in the innovation system connect with each other to exchange and generate new innovations to increase the productivity of farmers. The interaction between all these actors is crucial for a sustainable innovation process [3]. ...
Purpose
Collaboration in agricultural value chains (AVCs) has the potential to increase smallholders’ participation in international value chains and increase their benefits from participation. This scoping review explores existing collaboration models among stakeholders of AVCs in developing countries, examines enablers and constraints of collaboration and identifies policy gaps.
Design/methodology/approach
We systematically searched three databases, CAB Abstracts, Econlit (EBSCO) and Agricola, for studies published between 2005 and 2023 and included 59 relevant studies on AVC collaboration.
Findings
The primary motivations for collaboration are to enhance market access and improve product quality. Key outcomes of collaboration include improvements in farmers’ welfare, market participation and increased production; only a few studies consider improved risk management as an important outcome. Robust support from government and non-governmental entities is a primary enabler of collaboration. Conversely, conflicts of interest among stakeholders and resource limitations constrain collaboration possibilities. Collaboration involving high-value crops prioritizes income increases, whereas collaboration involving staple crops focuses on improving household food security.
Research limitations/implications
This study may have publication bias as unsuccessful instances of collaboration are less likely to be published.
Originality/value
This study is unique in highlighting collaboration models’ characteristics and identifying AVC policy and programmatic areas where private firms, farmers’ groups, local governments and donor agencies can contribute.
The research conducted in this study focused on exploring the challenges associated with frugal business modelling in the context of agribusinesses. The study employed a cross-sectional survey design and targeted managers and operational staff working in agribusinesses affiliated with the National Association of Seed Traders of Ghana (NASTAG). The collected data underwent a series of statistical analyses, including exploratory factor analysis, principal component analysis, and varimax rotation. These analyses were performed on the questionnaires, which contained variables assessing the challenges related to frugal business modelling. The findings of the study revealed that several challenges hinder the frugal business modelling in Ghana. These challenges were categorised into six factors: coordination, information and dissemination, regulation and supervision, funding, service delivery, and the institutional framework. These factors emerged after applying exploratory factor analysis, principal component analysis, and varimax rotation techniques. Together, these six factors accounted for 65.6% of the explained variance in the data. The identified challenges have both theoretical and practical implications for enhancing the sustainability of agribusinesses. They provide valuable insights into the specific areas that need attention and improvement to promote the long-term viability of agribusiness operations. However, despite the significance of these findings, the study also recommended the exploration of longitudinal studies. Conducting longitudinal research would enable a deeper understanding of the enduring impact of frugal business modelling on agribusiness sustainability. By examining agribusinesses over an extended period, researchers can gain insights into the dynamics and long-term effects of frugal practices on sustainability outcomes.
Drawing upon data regarding cooperative patents applied for and authorized in the agricultural industry between 2019 and 2022, this paper conducts an analysis of the collaborative innovation network in agricultural technology involving agricultural enterprises, universities, and research institutes. From a social network perspective, this study empirically examines the impact relationships within agricultural science and technology collaborative innovation networks, employing the Exponential Random Graph Model (ERGM) across two dimensions: endogenous network configuration and exogenous node attributes. The findings reveal that both internal and external factors contribute to the dynamics of the agricultural technology collaborative innovation network, resulting in a significant sparsity effect. This effect gives rise to triangular and star-shaped structures that facilitate resource sharing. Furthermore, the agricultural science and technology collaboration network exhibits a high degree of openness and regional assortativity, enhancing the likelihood of connections between organizations. However, the influence of innovation capability and organization type on network promotion is less pronounced.
In this article, we assess the determinants of adoption of agricultural technologies under climate risk and evaluate their
impact on food security using data from Niger, together with a set of novel weather variation indicators. We employ multivariate
probit and instrumental variable techniques to model adoption decisions and their impact. We find that the adoption of both
modern inputs (inorganic fertiliser and improved seed) and organic fertiliser is positively associated with crop productivity
and crop income. The use of crop residues does not seem to correlate positively with crop productivity and could even have
a negative effect. We find a strong negative association on crop productivity among households reporting that they had experienced
a delayed onset of the rainy season. We also find that factors driving modern input use are different from those of crop residues
and organic fertiliser. While the latter can be characterised as low-investment capital requirements, more labour requirements
and longer times for results, the former includes higher investment capital requirements, fewer labour requirements and shorter
times for returns. Furthermore, we find that weather variability is one of the strongest determinants of the type of practice
adopted. In regions with greater rainfall and temperature variability, crop residue incorporation into soils is more widely
adopted. The probability of using modern inputs and organic fertiliser is negatively and strongly correlated with variability
in rainfall and temperature. Households with higher levels of wealth, education and labour are most likely to adopt modern
inputs. Distance to the nearest market and extension service also plays a strong role in adoption; the greater the distance,
the less likely they are to use modern inputs. The converse holds true for organic fertiliser use: the greater distance the
farm household is from the market and the extension centre, the more likely it is to use organic fertiliser.
Purpose
The purpose of this paper is to identify and assess the key factors that influence the adoption of agrochemicals on plantain farms in Ghana.
Design/methodology/approach
The paper employs probit estimation using data from a stratified random sample of 249 farmers in four districts in Ghana.
Findings
The results show that adoption of agrochemicals is positively associated with: being literate, older than 40 years of age, having higher income from sales, living in villages distant to Accra (capital of Ghana), having access to hi‐tech machinery, being migrant, and being linked to extension services and financial institutions. Contrary to expectation, a farmer's gender and association with farmer‐based organizations (FBO) and non‐governmental organizations (NGO) did not make a difference.
Practical implications
The results suggest that there are no exclusions to innovation systems such as agrochemical adoption based on gender or living in rural areas; women are just as technologically empowered as men, while rural farmers have an option to retain their indigenous management practices or adopt new and improved practices such as using agrochemicals. Major efforts to improve access to agrochemical adoption lie with government extension officers, as the functions of FBO and NGO have yet to make a significant difference. More needs to be done to bring young, illiterate, low income and indigene farmers into inclusive plantain science techniques and applications in Ghana.
Originality/value
The paper reveals how vulnerable groups such as rural populations and women plantain farmers are being included in systems that support agrochemical adoption.
Purpose: This paper identifies the stakeholders of System of Rice Intensification (SRI), their roles and actions and the supporting and enabling environment of innovation in the state as the elements of the Agricultural Innovation Systems (AIS) in SRI in Tripura state of India and studies the relationship matrix among the stakeholders. Methodology: A descriptive research design was followed to study the agricultural innovation system in SRI. Criterion and expert sampling were employed to select the stakeholders and data was collected by a personal interview method with the help of a semi-structured schedule. Actor Linkage Matrix was employed to study the linkage among the stakeholders in the innovation systems.
Agricultural technologies typically spread as farmers learn about profitability through social networks. This process can be nuanced, however, when net returns for some farmers may not be positive. We investigate how social learning influences demand for a resource-conserving technology in eastern Uttar Pradesh, India. We identify potential adopters through an experimental auction and randomly select a subset to adopt. We exploit this variation in adoption across networks to estimate network effects on demand for the technology one year later using a second auction. Technology benefits vary, and network effects are completely conditional on benefits. Having a benefiting adopter in one’s network increased demand by over 50 percent, whereas having a non-benefiting adopter had no effect. These effects are strong enough to bring average demand in line with expected benefits. For many farmers, however, demand remains below the market price, suggesting that network effects will lead to increased—but not rapid widespread—adoption.
