Social Media Participation, Low-Carbon Agricultural Practices, and Economic Performance of Banana Farmers in Southern China

Low-carbon agricultural practices (LAPs) can reduce carbon emissions in agricultural production for farmers in developing countries. However, the role of emerging social media has not received enough attention in the diffusion of LAPs among farmers. This study first attempts to examine the impact of farmers’ social media participation on their adoption intensity of LAPs using the Zero-truncated Poisson model and specify the effect of each participation activity on social media by the endogenous-treatment Poisson regression model, then discuss the economic performance of LAPs using the quantile regression model, based on the primary data collected from banana farmers in Southern China. The results show that social media participation exerts a positive and significant effect on farmers’ adoption intensity of LAPs. Specifically, the adoption intensity of LAPs in the treated group who participated in the short-video social media is about 1.1 times higher than that in the control group. The treatment effects of the five activities (watch, like, forward, comment, and release) on farmers’ adoption intensity of LAPs are positive and significant. We also find that adoption of LAPs can increase household income of farmers, and the effect presents particularly significant for those at the higher income level. Whilst, Social media participation can significantly increase household income of farmers who are at the lower income level. Our findings underscore the important role of social media in the diffusion of LAPs among farmers and income growth of households in developing countries. Thus, supportive strategies can be designed by policymakers for encouraging farmers to participate the emerging social media platforms and adopt more LAPs in agricultural production.

Improved Seeds Adoption Among Smallholder Rice Farmers in Togo: The Case of NERICA in the Savannah Region

The low adoption of new technologies, particularly improved seeds, remains a critical issue hampering the development of agriculture in many developing countries. The objective of this research is to identify the determinants of (i) the farmer’s knowledge,( ii) the adoption decision and (iii) the adoption intensity of NERICA rice varieties in the Togolese Savannah region. Probit and Tobit models were used to analyse data collected from 150 rice growers randomly selected. The results of the estimations showed that the knowledge, the adoption decision and the adoption intensity of NERICA are determined by socio-economic and institutional factors. The common factors affecting the knowledge, the adoption decision and the adoption intensity are credit access, extension service and gender. However, the adoption intensity is specifically affected by the rice income, the land ownership and the membership to a farmer’s base organization. These findings suggest the necessity to improve the agricultural credit access, the extension services access and to take gender into account in policies making in order to give men and women the same chances of access to innovations.

Improved Seeds Adoption Among Smallholder Rice Farmers in Togo: The Case of NERICA in the Savannah Region

The low adoption of new technologies, particularly improved seeds, remains a critical issue hampering the development of agriculture in many developing countries. The objective of this research is to identify the determinants of (i) the farmer’s knowledge,( ii) the adoption decision and (iii) the adoption intensity of NERICA rice varieties in the Togolese Savannah region. Probit and Tobit models were used to analyse data collected from 150 rice growers randomly selected. The results of the estimations showed that the knowledge, the adoption decision and the adoption intensity of NERICA are determined by socio-economic and institutional factors. The common factors affecting the knowledge, the adoption decision and the adoption intensity are credit access, extension service and gender. However, the adoption intensity is specifically affected by the rice income, the land ownership and the membership to a farmer’s base organization. These findings suggest the necessity to improve the agricultural credit access, the extension services access and to take gender into account in policies making in order to give men and women the same chances of access to innovations.

Adoption Intensity of Selected Organic-Based Soil Fertility Management Technologies in the Central Highlands of Kenya

Soil fertility decline continues to be a major challenge limiting agricultural productivity globally. Despite the novelty of organic-based technologies in enhancing agricultural production in Kenya's central highlands, adoption is low. Therefore, we carried out a cross-sectional household survey of 300 randomly selected smallholder farmers to determine the specific organic-based practices by farmers; and the socioeconomic factors that influence the adoption intensity of selected organic-based technologies. We used descriptive statistics to summarize the data and the Tobit regression model to evaluate the socioeconomic determinants of adoption intensity of selected organic-based technologies. We identified nine organic-based technologies that had different adoption rates among the farmers. The majority of the farmers had adopted manure (97%) and manure combined with fertilizer (92%) in Murang'a and Tharaka-Nithi, respectively. Manure was applied to the largest land in Murang'a with 31% of the cultivated land. In comparison, manure combined with fertilizer had the highest adoption intensity in Tharaka-Nithi applied to about 25% of the cultivated land. Gender, age of the household head, level of education, household size, access to external labor, training, Tropical Livestock Unit, agriculture group membership, access to credit, land cultivated, and farming experience influenced the adoption intensity of organic-based technologies among smallholder farmers. Based on the smallholder farmers' adoption behavior, this study can be used to disaggregate the farming households better in order to tailor specific organic-based soil fertility technologies solutions that meet their unique needs. One group would be those households that face specific constraints, as reflected in their low adoption rates, women-headed households and older farmers, and thus require more targeted / intensive efforts to overcome these barriers. The other group would be those households that require less focus because, when confronted with the technologies, they are more likely to adopt them easily, for example, the male-headed households. Hence, the smallholder farmers' adoption behavior, can enable policymakers to form a base for designing appropriate policies that encourage the adoption of organic-based soil fertility technology by smallholder farmers.

DOES CREDIT ACCESS IMPROVE ADOPTION INTENSITY OF IMPROVED MAIZE SEED VARIETIES?

This study investigated the effect of credit access on the adoption intensity of improved maize varieties in Osun State. A number of 150 maize farmers were selected through a multistage sampling procedure from using a structured questionnaire. Descriptive statistics, adoption index, and Tobit regression model were used to analyse the data collected. The results showed that Majority of maize farmers were over 40 years (52.6%), male (87%), and married (87%). The result also showed that majority of the farmers did not adopt improved maize varieties (55%) in the state. Swan 1 improved variety was majorly adopted (87.1%), while DMR-ESR-W variety was less adopted (62.9%) in the State. Just a few of maize farmers had access to credit in the State (20%). The mean adoption intensity in the State was observed to 62%. Based on adoption intensity of improved maize varieties, adopters were classified as partial adopters (65%) and full adopters (35%). Tobit regression estimates showed that credit access, household size, secondary occupation, years of education and extension contact have significant effect on the adoption intensity of improved maize varieties. In accordance with the findings, we therefore recommend that microfinance institutions should look attentively at scaling up their credit services to enhancing adoption intensity of improved maize varieties.

Determinants of improved chickpea variety adoption in high barind region of Bangladesh

Chickpea production in Bangladesh has been decreasing over time. Comprehensive farmlevel adoption of modern chickpea varieties can change the scenario. This paper endeavours to ascertain the determinants of adoption and adoption intensity of improved chickpea variety in the high barind region of Bangladesh. The outcomes from Cragg’s double hurdle model showed that organization membership, information sources, crop diversification index, and village location are the crucial factors that positively influenced both the adoption and adoption level. Farmers with organization membership are 15.5% more probable to adopt improved chickpea while by adding one more information source, the adoption probability can be increased by 6.3%. Meanwhile, women’s decisions, training, credit accessibility, and farm size have effects only in favour of initial adoption. The adoption probability is approximately 15% more in the household where women can participate in the decision-making process. Adopters with higher formal education, off-farm income, and mobile usage capability devote a greater proportion of their land to the improved variety cultivation. Strengthen of the network among farmers and their information sources should be emphasized to stimulate the diffusion process of the improved chickpea variety. Besides, training should be available for both female and male of the farm families since women also affect the adoption decision. Int. J. Agril. Res. Innov. Tech. 10(1): 56-63, June 2020

Technology Adoption and Extension Strategies in Mediterranean Agriculture: The Case of Family Farms in Chile

Extension services play a crucial role by improving skills and access to information that result in greater farm level innovations, especially on family farms which are the predominant form of agriculture in the world. This study analyzed the connection between strategies implemented by extension services and technology adoption on family farms. Using the case of the Servicio de Asesoría Técnica (SAT) Program, we developed a bottom-up adoption index (AI) for vegetable and berry farmers in three regions of Central Chile. We implemented 10 focus groups totaling 101 participants, all recipients of technical assistance from private extension companies (PECs) funded by the SAT Program. After the focus group sessions, we surveyed participating farmers to gather information on socio-economic attributes and adopted technologies. Using cluster analysis, we identified three groups of farmers according to their adoption intensity. The results indicate that extension strategies used by PECs have distinct effects on the adoption of new technologies. Higher adoption indexes were positively associated with the duration of the extension visits, the number of group activities, and the use of incentives and credits provided by the Chilean government. The value of production and farm size were positively associated with adoption intensity.

Joint Model of Application-Based Ride Hailing Adoption, Intensity of Use, and Intermediate Public Transport Consideration among Workers in Chennai City

The introduction of mobile application-based ride hailing services represents a convergence between technologies, supply of vehicles, and demand in near real time. There is growing interest in quantifying the demand for such services from regulatory, operational, and system evaluation perspectives. Several studies model the decision to adopt ride hailing and the extent of the use of ride hailing, either separately or by bundling them into a single choice dimension, disregarding potential endogeneity between these decisions. Unlike developed countries, the literature is sparser for ride hailing in developing countries, where the demand may differ considerably because of differences in vehicle ownership, and availability and patronage of many transit and intermediate public transport (IPT) modes (the shared modes carrying 40% shares in some cases). This study aims to bridge these gaps in the literature by investigating three interrelated choice dimensions among workers in Chennai city: consideration of IPT modes, the adoption of ride hailing services and the subsequent usage intensity of ride hailing services. The main factors influencing these decisions are identified by estimating a trivariate probit model. The results indicate that sociodemographic and locational characteristics and the availability of IPT modes influence ride hailing adoption, whereas work-related constraints and perception of other modes affect its frequency. Work and non-work characteristics affect both the dimensions of ride hailing. Further, endogeneity is observed between ride hailing and IPT adoption after controlling for these variables, whereas evidence of endogeneity is absent among other dimensions. Mainly, the model separates the effect of the exogenous influences on the usage frequency level from their effect on the adoption of ride hailing services.