%0 Journal Article
%@ 0308-521X
%A Robert, Marion
%A Dury, Jérôme
%A Thomas, Alban
%A Therond, Olivier
%A Sekhar, Muddu
%A Badiger, Shrinivas
%A Ruiz, Laurent
%A Bergez, Jacques Eric
%D 2016
%F publications:22458
%I Applied Science Publishers
%J Agricultural Systems
%K Decision modeling
%K Farming systems
%K Water management
%K Case-based analysis
%K Cognitive task analysis
%K UML
%P 86-94
%R 10.1016/j.agsy.2016.07.010
%T CMFDM: A methodology to guide the design of a conceptual model of farmers' decision-making processes
%U https://publications.ut-capitole.fr/id/eprint/22458/
%V 148
%X The agricultural research community offers languages and approaches to model farmers' decision-making processes but does not often clearly detail the steps necessary to build an agent model underlying farmers' decision-making processes. We propose an original and readily applicable methodology for modelers to guide data acquisition and analysis, incorporate expert knowledge, and conceptualize decision-making processes in farming systems using a software engineering language to support the development of the model. We propose a step-by-step approach that combines decision-making analysis with a modeling approach inspired by cognitive sciences and software-development methods. The methodology starts with case-based analysis to study and determine the complexity of decision-making processes and provide tools to obtain a generic and conceptual model of the decisional agent in the studied farming system. A generic farm representation and decision diagrams are obtained from cross-case analysis and are modeled with Unified Modeling Language. We applied the methodology to a research question on water management in an emerging country (India). Our methodology bridges the gap between field observations and the design of the decision model. It is a useful tool to guide modelers in building decision model in farming system.