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Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

The agricultural sector has experienced a transformative impact through the adoption of digital technologies, particularly mobile applications designed for farmers. This study investigates the factors influencing smallholder farmers' willingness to adopt digital application tools in Ogun State, Nigeria, focusing on the IITA herbicide calculator and Akilimo mobile applications.

Data were gathered from 572 smallholder farmers participating in the Zero Hunger project. This research contributes to the limited empirical evidence in Nigeria concerning farmers' willingness to adopt digital application tools. The study analyzes the effects of education, training, access to internet services, smartphone ownership, willingness to use paid applications, awareness of application tools and the cost of digital tools on farmers' willingness to adopt. Gender differentials in willingness to adopt were also explored.

The results indicate positive and statistically significant effects of education, training, internet access, smartphone ownership, willingness to use paid applications, awareness of application tools and the cost of digital tools on farmers' willingness to adopt. However, female farmers exhibited a lower willingness to adopt digital application tools.

Policymakers are urged to create supportive policies promoting basic formal education and provide effective extension services to enhance farmers' training. Additionally, efforts should be made to reduce the cost of digital applications and improve internet accessibility in rural areas. Encouraging female farmers to adopt advanced agricultural technologies is essential. Stakeholders are advised to raise awareness of digital application tools to expedite the adoption of agricultural technologies in the country.

This study will be helpful for the government to determine the state’s readiness for digital agriculture, it will help technology developers and agricultural technology startups to understand the factors determining farmers willingness to adopt digital application tools.

This study offers insights into the readiness of Ogun State, Nigeria, for digital agriculture. It provides valuable information for technology developers and agricultural startups to understand the determinants of farmers' willingness to adopt digital application tools, contributing to the advancement of the agricultural technology landscape.

This study investigates the effect of education on crop insurance knowledge within the context of noncompliance experiences. In addition, the study delves into the role of government endorsement in education, which is instructive for the implementation of future insurance promotions.

The study designs a randomized controlled trial (RCT) conducted in Jiangsu Province, China. A total of 518 sample farmers were randomly assigned to two experiments: The Education Experiment and the government’s Endorsement Experiment, respectively. After conducting a set of rigorous exogeneity tests, econometric analysis was conducted using baseline survey data and post experiment data.

Our results revealed that insurance education served as an effective tool in improving farmers’ insurance knowledge, especially their understanding of insurance mechanisms. However, this effect can be mitigated by the noncompliant insurance experience of farmers. Moreover, government-endorsed education proved to be more efficient in improving farmers’ insurance knowledge, thus highlighting the significance of building trust between insureds and insurers.

This study contributes to the literature by demonstrating that using a simple education tool, such as, brochures, can effectively improve farmers insurance knowledge. In addition, insurance mechanisms are now more urgently in need of universalization than policy information. Furthermore, by conducting the RCT, this study obtains unbiased causal inference on the effect of education on insurance knowledge and underscores the role of government endorsement in this process. In addition, the study illustrates the tradeoff between insurers’ efforts in enhancing education and regulating noncompliant insurance misconducts, which compromises education efforts. Overall, this study provides insights into the marketing strategies of insurers and government propaganda aimed at stimulating farmers’ incentives to purchase insurance.

A partnership model is necessary for palm oil plantations’ sustainability. The developed model does not identify the optimal technique for smallholder palm oil because it faces complex challenges. This study aims to determine a partnership model for sustainable palm oil plantation business in Indonesia.

Qualitative research methods were used, and data analysis was performed using NVivo 12 Plus software, which helps improve the accuracy of qualitative studies and provides implications for evidence-based studies. All respondents, whether through surveys, interviews or focus group discussions, understood their contributions to this research and provided consent.

The results indicate that the core–plasma partnership pattern implemented by companies needs to be considered a relevant model for partnerships in the Indonesian palm oil industry. Social networks play a role in implementing this partnership pattern, which is influenced by the diversity of the actors involved. However, complexity arises from the dynamics of power and position among these actors, which demands increased interaction and mutual trust. Therefore, various dimensions must be considered, including plantation management, product marketing, cultivation techniques and sustainable development.

The research results have limitations, particularly regarding access to information for company policymakers, because there remains complexity related to the position and dominance of power between actors, which influences the achievement of common goals. A more complex analysis is needed to produce complete research. Further studies are required to provide a more comprehensive explanation of the humanist approach in the context of palm plantations.

This study provides an important theoretical implementation: a more humane approach through a partnership model that adds value and is based on aspects of morality in implementing partnerships in the palm oil plantation sector. It also provides new and substantial insights regarding practical implementation for policymakers and practitioners who want to improve partnership practices in sustainable palm oil businesses by implementing value-added and morality-based partnership models in Indonesia as well as other developing countries.

The goal of this study is to predict the farmers’ concerns about agricultural index-insurance (AII) for weather risk mitigation of horticultural crops in hilly regions. The key impetus of analysis is to prioritize the AII requirements based on the farmers’ perspectives using the requirements prioritization approach.

The integrated approach has been applied in this paper. Initially, the MoSCoW prioritization technique has been employed to prioritize the AII attributes utilizing a four-dimensional agriculture insurance scale. Later, the rank sum weighting method was deployed to assign the ultimate rank to AII attributes based on the farmers’ responses.

Findings specified that out of 15 AII attributes, majority of 11 attributes were placed in “must have” and “should have” categories that related to claim, design, premium and grievance management dimensions. However, three AII attributes are placed in the “could have” category. Additionally, findings of rank-sum weighting method-based ranking can help insurers in redesigning farmers-oriented AII services for risk mitigation of horticulture crops by incorporating these ranks as per their priority level.

The prioritized AII attributes are helpful for insurers and managers in order to solve the problems associated with design, premium, claim and grievance management of AII.

Findings deliver significant insights to insurers to incorporate the prioritized AII attributes ranked by farmers.

This is the initial known analysis that integrated the MoSCoW and rank sum weighting method to prioritize the AII requirements prioritization among Indian farmers.

Reducing carbon emissions in agriculture is vital for fostering sustainable agricultural growth and promoting ecological well-being in rural areas. The adoption of Low-Carbon Agriculture (LCA) by farmers holds great potential to accomplish substantial reductions in carbon emissions. The purpose of this study is to explore the farmers' preference and willingness to engage in LCA.

This study employs the Choice Experiment (CE) method to examine farmers' preferences and willingness to adopt LCA, using field survey data of 544 rural farmers in the Weihe River Basin between June and July 2023. We further investigate differences in willingness to pay (WTP) and personal characteristics among different farmer categories.

The empirical results reveal that farmers prioritize government-led initiatives providing pertinent technical training as a key aspect of the LCA program. Farmers' decisions to participate in LCA are influenced by factors including age, gender, education and the proportion of farm income in household income, with their evaluations further shaped by subjective attitudes and habits. Notably, we discovered that nearly half of the farmers exhibit indifference towards LCA attributes.

To the best of the authors' knowledge, this study is the first to investigate farmers' attitudes toward LCA from their own perspectives and to analyze the factors influencing them from both subjective and objective standpoints. This study presents a fresh perspective for advocating LCA, bolstering rural ecology and nurturing sustainable development in developing nations.

Amid the growing global emphasis on sustainable agriculture, organizations and governments face a pressing need to equip farmers with the knowledge and tools necessary for the adoption of sustainable farming practices, aligning with the Sustainable Development Goals (SDGs). However, understanding the complex relationship between training programs and the adoption of sustainable practices among small-scale farmers remains a critical challenge. Taking a human resource approach, this paper attempts to understand the interrelationships between training effectiveness, farmers’ psychological and demographic characteristics in explaining the adoption of sustainable farming practices.

We employed a multi-stage random sampling method and administered a structured questionnaire to collect data from 331 small farmers who were part of a government-led, large-scale intervention aimed at training them in sustainable farming practices.

Our research findings not only emphasize the critical role of HR approach through training but also underscore its importance in the broader mission of aligning with the SDGs. Specifically, we demonstrate that sustained exposure to training, intrinsic motivation to acquire knowledge, and the innovative capacity of farmers collectively enhance the effectiveness of training programs, thereby contributing significantly to the widespread adoption of sustainable farming practices in line with SDGs.

Drawing from self-determination theory, training effectiveness literature, and the call for improved alignment with the SDGs, this study presents a model that explains how psychological characteristics, combined with the quality and quantity of training influence the adoption of sustainable farming practices among small-scale farmers.

The aim of this study is to examine the availability, utilization and effectiveness of various information sources in enhancing the knowledge and practices of Lakadong turmeric farmers.

This study focuses on 125 Lakadong turmeric farmers in Myntkung and Biar villages, Meghalaya, India. A purposive sampling technique was used to select participants, ensuring the representation of various ages, experiences and agricultural practices. A mixed-methods approach was used, including structured interviews and focus group discussions, to gather information on the farmers.

The study found that most of the Lakadong turmeric farmers (35.2%) needed information on farming techniques and practices and 93.6% of farmers approached their friends, relatives or fellow farmers to access any information. For most farmers, 77 (62%) relied on word-of-mouth to get information. After using the information effectively and efficiently, most farmers (46.4%) agreed that there was an increase in Lakadong turmeric yields, improved crop quality and reduced pest infestation.

The study highlights informational gaps in the agricultural sector, empowering farmers to explore alternative sources. It suggests that understanding farmers’ unique needs can improve agricultural extension agencies’ programs and resources. Policymakers should invest in digital literacy programs and regional information resources. The study also suggests integrating information literacy training into agricultural operations, fostering collaboration among farmers, institutions and information providers. The geographical indication tag on Lakadong turmeric can also empowers local communities by fostering economic opportunities through the promotion and protection of this prized spice.

Existing research tends to focus more broadly on agricultural information dissemination or other crops, leaving a notable gap in the literature regarding the unique informational needs and access challenges faced by Lakadong turmeric farmers.

This paper aims to assess the role of radio programmes in agricultural development and enhancing the capacity of farmers in Oyo and Ogun states, situated in the South-West region of Nigeria. Specifically, this study investigated Farm Radio International (FRI) radio broadcast strategies, their effectiveness and how they enhance the farmers’ knowledge, skills and practices.

The paper opted for a qualitative research design, using both interviews and focus group discussions to gather data from FRI radio partners and farmers.

Findings indicated that radio is effective in influencing the practices of farmers and helping them adopt new knowledge, ideas and skills. FRI partners use rural radio forum broadcasting strategy. Also, findings indicated that the most effective broadcasting strategy to reach the farmers with agricultural information is rural radio forum.

The paper includes implications for agricultural development organisations, providing a framework for monitoring and evaluating the impact of their communication interventions, helping ensure accountability and efficient use of funds.

This paper fulfils an identified need to investigate the broadcasting strategies that are most effective in reaching farmers with agricultural information and the influence of agricultural radio programmes on their farming practices.

This paper examines why farmers self-select out of formal credit markets even though they need external funds.

We use probit and Bayesian probit estimators to detect the determinants of self-selection behavior based on a primary dataset of 2,212 rice farmers in Vietnam. After that, we use the multinomial probit (MNP) and Bayesian MNP estimators to reveal the impact of relevant factors on the decision to self-select for farmers belonging to each self-selection category.

The probit and Bayesian probit estimators show that the decision to self-select depends on household head age, income per capita, farm size, whether or not to have relatives or friends working for banks, the number of previous borrowings, risks related to natural disasters, diseases, and rice price, and the number of banks with which the farmer has relationships. The MNP and Bayesian MNP estimators give further insights into the decision of farmers to self-select in that determinants of the self-selection behavior depend on the reasons to self-select. In concrete, farm size and the number of previous borrowings mitigate the self-selection of farmers who did not apply for loans due to having access to other preferred sources of credit. The self-selection of farmers not applying for loans because of unfavorable loan terms is conditional on household head age, farming experience, income, farm size, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with. Several factors, including education, income, the distance to the nearest bank, whether or not having relatives or friends working for banks, the number of previous borrowings, risks, and the number of banks the farmer has relationships with, affect the self-selection of farmers not applying for loans because of high borrowing costs. The self-selection of farmers not applying for loans because of complex application procedures depends on income and the number of previous borrowings. Finally, the household head’s age, gender, experience, income, farm size, the amount of trade credit granted, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with are the determinants of the self-selection of farmers not applying for loans because of a fear not being able to repay.

This paper fills the knowledge gap by investigating why farmers self-select out of formal credit markets. It provides evidence of how the farmers’ subjective perceptions of rural credit markets contribute to their self-selection.

This paper shows that demand-side constraints are also vital for farmers’ access to bank credit. Improving credit access via easing supply-side constraints may not increase credit uptake without addressing demand-side factors. Given that finding, it recommends policies to improve access to bank credit for farmers regarding the demand side.