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This study examines the drivers of marketing channel participation amongst smallholder rice farmers in the northern region of Ghana.

Using a sample of 397 smallholder rice farmers drawn from a multistage sampling procedure, the study employed multivariate probit (MVP) model in the empirical estimations. In this context, the model assumes that a rice farmer should at least participate in one market channel.

The study reveals that the wholesaler market channel is the most commonly used channel among farmers, followed by the aggregator channel. However, the processor market channel is the least patronized one in the study area. The results also show statistically significant correlation coefficients in four out of the six possible combinations, implying that market channel participation among smallholder farmers is not mutually exclusive. Rice market channel participation is positively and significantly influenced by age, gender, household headship, access to credit, extension service, irrigation, improved seed and access to price information.

This study is limited in extending the analysis to include the impact of market channels on some outcome measures. This is due to data limitation.

The findings of this study add to the growing literature on smallholder market channel participation in Ghana.

After a long observation of the high rate of rice importation and low productivity in Côte d’Ivoire, the certified rice seed was introduced and encouraged to be used by the local farmers. This study evaluates the profitability of rice production and the impact of certified seed usage on the yield and income of farmers in Côte d’Ivoire.

Data were collected from 265 rice farmers. Descriptive statistics were used to identify the challenges faced in using certified seeds. Profitability analysis was used to examine the profitability of rice production. To eliminate bias due to the counterfactuals, the endogenous switching regression was employed to investigate the impact of the certified seeds on income and yield.

The difficulties faced by the rice farmers in the procurement of certified seeds were the unavailability of seeds, the high cost of seeds and poor credit access. Furthermore, rice farmers using certified seeds get a higher net income (USD 263.74/ha) than those using farmers' seeds (USD 212.31/ha). The average treatment on the treated was 1.61 for the yield and 574.75 for the income. The average treatment on the untreated was 1.20 for the yield and 422.59 for the income. These indicate a higher yield and income among adopters of certified rice seed.

Certified rice seed usage is profitable and enhances the output and income of rice farmers. The study advocates the creation of a stronger relationship between the farmers and the extension agents to encourage the use of certified seeds and increase the profit of the farmers.

There is scant information on the profitability of certified rice seed usage and how it affect yield and income. Therefore, this study serves as empirical evidence for policymakers to develop strategies that are required to enhance certified seed usage, boost rice productivity and achieve food security.

This study identified the determinants of improved rice variety adoption and measured their impact on farm productivity and the income of smallholder farmers in Indonesia.

We used a multistage sampling procedure and data from household surveys in four districts in the Banten region of Indonesia. An endogenous switching regression (ESR) model was used to estimate the impact of adoption, and the propensity score matching (PSM) non-parametric method tested the strength of the ESR findings.

The farm productivity of adoption increased by 11.45% and the income of smallholder farmers increased by 12.10% when compared to that of traditional methods.

The positive and significant effects of improved rice variety adoption indicated that research programs that develop improved rice varieties can optimize the productivity and income of smallholder farmers.

Adopting improved rice varieties increases the productivity and income of smallholder farmers, and the level of education, rice farming experience, access to extension workers, off-farm work, and mobile phone ownership have positive and significant effects on the adoption of improved rice varieties.

Farmers in developing countries are used to recycling and purchasing seeds of old and low-yielding varieties, leading to low seed and varietal replacement rates. Seed companies in Nepal have started to conduct traders' meetings (TMs) to promote new rice varieties. This paper aims to assess the effectiveness of this approach in promoting new rice varieties.

The authors assess the effectiveness of TMs by surveying 238 agrodealers from 7 districts of Nepal. The authors used the binary logit model to study the determinants of participation in TM and an instrumental variable approach to estimate the impact of TMs on sales of the promoted rice varieties.

Results indicate that the TM significantly influences traders' knowledge and increases the probability of selling new rice varieties promoted. However, TMs did not significantly increase the overall sales of promoted rice varieties.

The study is based on cross-section data; thus, unobserved fixed effects could not be accounted for. The study finds only one relevant and valid instrumental variable and therefore could not conduct any exogeneity test.

Seed companies in Nepal started to conduct TMs to promote new rice varieties since 2019. However, to the best of the authors’ knowledge, the usefulness of TMs and the impact of these events in changing traders' attitudes toward domestic rice seed varieties or in business performance (annual sales of the promoted varieties) have not been assessed. Therefore, the study findings will help to promote the market-driven seed system and increase the seed replacement rate.

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.

Post-harvest losses are becoming a huge issue worldwide and are predominantly severe in developing countries. Seeking ways to control post-harvest losses is important because losses decrease farm income by more than 15% for approximately 480 million small-scale farmers.

The study engaged Wave 4 (2018/2019) of the Living Standards Measurement Studies–Integrated Survey on Agriculture, to examine the impact of soil technology such as fertilisers, herbicides, pesticides and certified crops on post-harvest losses in Nigeria. The study engaged descriptive statistics, logit regression and propensity score matching (PSM) to analyse the data.

The study found that approximately 38% of the household harvest was lost along the value chain. In addition, the results showed that among the indicators of soil technology, crop certification has a significant impact on the reduction of post-harvest losses. The implication is that from the nearest neighbour and kernel-based matching, the use of certified crops by households contributed to 1.62 and 1.36% reduction in post-harvest losses, respectively. In contrast, pesticide, herbicide and fertiliser use had no significant impact on post-harvest losses.

One of the limitations is that this study applied the PSM, the model did not account for endogeneity. Therefore, in examining this concept, further studies should consider applying other impact model such as the difference-in-difference to account for endogeneity.

While previous studies have examined how ICT adoption, storage mechanisms and value chain among others help to minimise post-harvest losses, the aspect of how soil technology can reduce post-harvest losses has been a subject of exclusion in the extant literature. This study empirically examines the impact of soil technology adoption on post-harvest losses in Nigeria.

Climate change negatively affects agriculture and food security, and jeopardizes Myanmar's agriculture, which is vital to ensure food security, rural livelihoods, and the economy. This study explores the asymmetric impacts of climate change on Myanmar's agricultural sector.

We utilize the nonlinear autoregressive distributed lag (NARDL) approach for the years 1991–2020, the Wald test to validate the asymmetric relationship between climate change and agriculture, and the FMOLS and DOLS approaches to confirm the validity of the outcomes.

Our findings reveal that temperature has a positive impact on Myanmar's agriculture, whereas rainfall and CO2 have negative effects over the long and short terms. Evidently, decreasing temperatures more favorably impact agriculture than increasing temperatures, while increasing rainfall more negatively impacts agriculture than decreasing rainfall. Increasing carbon emissions have a more detrimental effect on agriculture than decreasing them.

We gathered data over periods longer than 30 years to provide more robust findings. However, owing to data limitations, such as missing values or unavailability, the study period spans from 1991 to 2020.

This study contributes to the existing literature on the asymmetric effects of climatic and non-climatic factors on agriculture. It is the first study in Myanmar to use the NARDL approach to measuring the effects of climate change on both the agricultural gross production index and value, providing robust findings.

This study aims to identify seasonal drought using standardized precipitation index (SPI). The following specific objectives are to generate result and identify seasonal drought and determine different scale of seasonal drought and its impacts on cropping season.

Seasonal SPI was calculated using long-term rainfall data for three seasons. The SPI was calculated using the formula and it is effective for the determinants. This study showed the functional relationship between drought duration, frequency and drought time scale using the SPI. SPI=X−X¯σ.

Seasonal drought occurs more frequently in Bangladesh that affects crops and the agricultural economy every year. More severe drought was recorded during the Kharif-1 and Kharif-2 seasons and most crops were affected in these two seasons. No severe or moderate drought was recorded during the Rabi season. The results showed that monsoon crops were severely affected severely by extreme and severe droughts during the Kharif-2 season. Eventually, the people remain jobless during the monsoon, and they experience food shortages like monga. Several obstacles were recorded during the season, including delayed preparation of land, sowing, transplanting and other farming activities because of monsoon droughts. This study revealed that very frequently, mild dryness occurs in winter, but crop loss is minimal. The scale and occurrence of extreme droughts are more frequent during monsoons and reduce crop yields, affecting livelihoods in the study area. Seasonal drought affects cropping patterns as well as reduce crop yields.

The outcome of this study derived from the secondary data and field data.

This study aims to explore how social entrepreneurship initiatives and rural development address various socio-economic challenges in rural communities following Indonesia’s independence in 1945.

Adopting a pragmatic research philosophy, this study uses a historical review and thematic analysis, extending from the PRISMA method to analyse articles and reports concerning social entrepreneurship initiatives and rural development in post-independence Indonesia.

This study reveals that social entrepreneurship initiatives and rural development programs have advanced hand in hand since Indonesia's independence. Social entrepreneurship initiatives and rural development mutually reinforce each other, with social entrepreneurship prominently featured in many rural development projects, promoting socioeconomic changes in rural communities.

While this review has covered the available literature in Indonesia's context and extends the social entrepreneurship concept by showcasing its impact in rural Indonesia, further theoretical models integrating social entrepreneurship and rural development are needed, especially with local or regional context and community-driven approaches to increase the research potential in the field.

This study is beneficial for policymakers in the field to consider the findings of this review on the strong association that social entrepreneurship has had with rural development in Indonesia.

This study highlights the importance of local values and community participation in social entrepreneurship initiatives for rural development. It is also highlighted that social entrepreneurship initiatives enable rural women to participate in entrepreneurial activities.

This study concludes that prior studies consistently demonstrate a strong association between social entrepreneurship initiatives and rural development, with government policies and programs increasingly leveraging social entrepreneurial approaches to tackle rural challenges. Additionally, rural development strategies in Indonesia align with three strategic pillars established by the government’s entrepreneurship programs. These pillars, integral to rural development through the social entrepreneurship approach, are critical for the formulation and future action plans adjustable to the current trends, issues and circumstances.

Rice is an important grain in Indian scenarios, and the purpose of the research work is to identify the attributes which can be the possible barriers in the traditional rice supply chain network.

A multilevel conceptual model is developed based on the literature review, and a field study is conducted by administering a questionnaire from the experts. Fuzzy logic methodology and a ranking score method is applied to identify the rice supply chain performance and the barriers of the traditional rice supply chain network.

The rice supply chain performance index for the traditional rice supply chain network is obtained, and the performance of the existing rice supply chain is found to be “fair”. The “information flow” is the attribute that can be a critical weak attribute in the traditional rice supply chain network. A proposed model of the blockchain technology-enabled rice supply chain network is developed as a solution for the “information flow” barrier.

The present research work is focussed on the generalized rice supply chain model of the Indian scenario, and more detailed studies can be carried out based on the regional issues.

The rice supply chain plays an important role in Indian economic development, and hence the current research paper focusses on identifying the barriers and the performance of the existing rice supply chain network.