Woodard, Josua D. (author), Sherrick, Bruce J. (author), Atwood, Deborah H. (author), Blair, Robert (author), Fogel, Greg (author), Goeser, Nicholas (author), Gold, Barry (author), Lewis, Josette (author), Mattson, Carl (author), Moseley, Jim (author), O'Mara, Collin (author), Piotti, John (author), Salas, Bill (author), Scarlett, Lynn (author), Duncanson, Kristin Weeks (author), and Yoder, Fred (author)
Format:
Journal article
Publication Date:
2018
Published:
USA
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 199 Document Number: D09927
Online via UI Library Catalog search. 10 pages., Findings of a survey among a sample of 100 farmers in District Sargodha revealed 99% used agricultural radio/TV/FM, 96% used mobile phones, 66% used magazines/newspapers/periodicals, and 61% used social media. Respondents placed highest value on enhancing their productivity.
Yu Jin (author), Huffman, Wallace E. (author), and Department of Economics, Shanghai University of Finance and Economics
Department of Economics, Iowa State University
Format:
Journal article
Publication Date:
2016
Published:
Wiley Periodicals, Inc.
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 16 Document Number: D10455
17 pages., Via online journal., This article provides new estimates of the marginal product of public agricultural research and extension on state agricultural productivity for the U.S., using updated data and definitions, and forecasts of future agricultural productivity growth by state. The underlying rationale for a number of important decisions that underlie the data used in cost‐return estimates for public agricultural research and extension are presented. The parameters of the state productivity model are estimated from a panel of contiguous U.S. 48 states from 1970 to 2004. Public research and extension are shown to be substitutes rather than complements. The econometric model of state agricultural TFP predicts growth rates of TFP for two‐thirds of states that is less than the past trend rate. The results and data indicate a real social rate of return to public investments in agricultural research of 67% and to agricultural extension of 100+%. The article concludes with guidance for TFP analyses in other countries.
26 pages, Agricultural productive services are an important means to achieve effective allocation of regional resources and play an important role in ensuring food security and improving farmers’ welfare. However, the development process of agricultural productive services still faces problems such as large differences in service levels in different segments and low participation rates in the full service. In order to investigate the influential paths of the low participation rate of farmers in the full-service process, this study takes maize farmers in northeast China as the research object. Based on 937 survey data from six cities in three northeastern provinces, we used the Item Response Theory (IRT) model to measure farmers’ information acquisition ability and constructed the Heckman two-stage model and the IV-Heckman model to analyze the logical framework of “information acquisition ability—farmers’ choice of productive agricultural services”. The main findings are as follows: firstly, the more channels there are, the stronger the farmers’ channel internalities; the higher the degree of channel differentiation, the stronger the farmers’ channel internalities. Second, after addressing the sample selection bias and endogeneity, there is a small rise in the facilitation effect of information acquisition ability on farmers’ productive agricultural service behavior. Third, this facilitation effect is achieved through farmers’ perceived usefulness of productive agricultural services, and the mediating effect of perceived ease of use is not significant. Therefore, fostering farmers’ self-perceptions and optimizing information delivery strategies are effective ways to promote farmers’ choice of agricultural productive services and to facilitate the modernization of Chinese agriculture. In general, this study helps to reveal the theoretical mechanism of farmers’ information asymmetry, and provides empirical evidence for how to promote the development of agricultural productive services.
18 pages, Based on panel data from the Rural Fixed Point Survey of the Ministry of
Agriculture over the period 2004-2016 and supplementary survey data on information
and communications technology (ICT) applications in the countryside, this paper employs
the difference in differences (DID) method to analyze the effects of ICT applications on
rural households’ agricultural total factor productivity (TFP) with mobile phone signal,
internet and 3G mobile network connections as indicators, and decomposes and evaluates
the constituent factors. Our findings reveal a positive effect of ICTs on rural households’
TFP, which primarily stemmed from rising agricultural technical efficiency. However, ICTs
exerted no significant effect on agricultural technical progress during this paper’s data
period due to limited rural human capital. These findings are consistent with robustness test
results based on counterfactual and matching methods.
14 pages., Edutainment, the combination of education with entertainment through various media such as television, radio, mobile phone applications and games, is increasingly being used as an approach to stimulate innovation and increase agricultural productivity amongst smallholder farmers in sub-Saharan Africa. Shamba Shape Up, a widely publicised makeover reality TV programme, is an example of edutainment that has received considerable attention, and airs in three countries in East Africa where it is estimated to be watched by millions of viewers.
There is no published academic research on the influence of makeover television formats on innovation systems and processes in smallholder agriculture. Using an Agricultural Innovation Systems approach, this paper explores how makeover edutainment is influencing smallholder farmer innovation systems together with the effect this is having on smallholder farms. In the absence of previous research, it articulates a Theory of Change which draws on research traditions from mass communication, agricultural extension and innovation systems.
Data came from two large scale quantitative (n = 9885 and n = 1572) surveys and in-depth participatory qualitative research comprising focus group discussions, participatory budgets, agricultural timelines, case studies and key information interviews in Kenya. An estimated 430,000 farmers in the study area were benefiting from their interaction with the programme through increased income and / or a range of related social benefits including food security, improving household health, diversification of livelihood choices, paying school fees for children and increasing their community standing / social capital.
Participatory research showed SSU enhanced an already rich communication environment and strengthened existing processes of innovation. It helped set the agenda for discussions within farming communities about opportunities for improving smallholder farms, while also giving specific ideas, information and knowledge, all in the context of featured farm families carefully selected so that a wide range of viewers would identify with them and their challenges.
Broadcasts motivated and inspired farmers to improve their own farms through a range of influences including entertainment, strong empathy with the featured host farm families, the way ideas emerged through interaction with credible experts, and importantly through stimulating widespread discussion and interaction amongst and between farmers and communities of experts on agricultural problems, solutions and opportunities. The fact that local extension workers also watched the programmes further enhanced the influence on local innovation systems.
The findings indicate that well designed makeover edutainment can strongly influence agricultural innovation processes and systems resulting in impact on the agricultural production and behaviours of large numbers of smallholder farmers.
