17 Pages., Given the marked heterogeneous conditions in smallholder agriculture in Sub-Saharan Africa, there is a growing policy interest in site-specific extension advice and the use of digital extension tools to provide site-specific information. Empirical ex-ante studies on the design of digital extension tools and their use are rare. Using data from a choice experiment in Nigeria, we elicit and analyze the preferences of extension agents for major design features of ICT-enabled decision support tools (DSTs) aimed at site-specific nutrient management extension advice. We estimate different models, including mixed logit, latent class and attribute non-attendance models. We find that extension agents are generally willing to use such DSTs and prefer a DST with a more user-friendly interface that requires less time to generate results. We also find that preferences are heterogeneous: some extension agents care more about the effectiveness-related features of DSTs, such as information accuracy and level of detail, while others prioritise practical features, such as tool platform, language and interface ease-of-use. Recognising and accommodating such preference differences may facilitate the adoption of DSTs by extension agents and thus enhance the scope for such tools to impact the agricultural production decisions of farmers.
20 pages, To achieve social sustainability, there is a need to incorporate social metrics of farmers’ well- being into agricultural monitoring systems. We contribute to the operationalisation of the measurement of farmers’ well- being by determining how farm- level factors influence farmers’ satisfaction with their work and quality of life. Using a data sample of 1099 farms that are part of the Farm Accountancy Data Network (FADN) in nine European countries, we tested a set of hypotheses related to work satisfaction and life quality perception based on a structural equation model. Satisfaction with on- farm work has a significant and substantial influence on satisfaction with quality of life. Farm- level aspects, such as working time, age of assets, financial situation of the farm and community engagement, significantly influenced farmers’ satisfaction with farming, but their joint effect explained less than one- fifth of the satisfaction. The results suggest that agricultural information systems intended to monitor and compare sustainability progress on farms would benefit from the integration of a metric measuring social concerns from the farmers’ point of view
22 pages, Many stated preference studies have shown that individuals’ attitudes play an important role in explaining their behaviour and helping to disentangle preference heterogeneity. When responses to attitudinal questions are introduced into discrete choice models, a suitable approach that corrects for potential endogeneity must be adopted. We use a discrete choice experiment to analyse the preferences of residents regarding the use of agri-environmental practices in the peri-urban area of Milan (Italy). A detailed analysis of these preferences is relevant for policymakers as farmers on the peri-urban fringe are often asked to provide environmental services to urban-dwellers. We apply a latent class model that we extend to include indicators of individuals’ attitudes towards the relationship between agriculture and the environment. Besides the application of the control function approach to deal with endogeneity, our main contribution is the use of a refutability test to check the exogeneity of the instruments in the agri-environmental setting. Our results show that attitudinal indicators help to disentangle the preference heterogeneity and that the respondents’ willingness-to-pay distribution differs according to the indicators’ values.
29 pages, Agent-based models are important tools for simulating farmers’ behaviour in response to changing environmental, economic or institutional conditions and policies. This article introduces an agent-based modelling approach that combines behavioural factors with standard bio-economic modelling of agricultural production. More specifically, our framework integrates the cumulative prospect theory and social interactions with constrained optimisation decisions in agricultural production. We apply our modelling approach to an exemplary bio-economic model on the assessment of weed control decisions. Results show the effects of heterogeneous farm decision-making and social networks on mechanical weed control and herbicide use. This framework provides a generic and conceptually sound approach to improve the scope for representing farmers’ decision-making and allows the simulation of their decisions and recent advances in behavioural economics to be aligned with existing bio-economic models of agricultural systems.
