RT Journal Article
SR 00
ID 10.1016/j.agsy.2016.07.010
A1 Robert, Marion
A1 Dury, Jérôme
A1 Thomas, Alban
A1 Therond, Olivier
A1 Sekhar, Muddu
A1 Badiger, Shrinivas
A1 Ruiz, Laurent
A1 Bergez, Jacques Eric
T1 CMFDM: A methodology to guide the design of a conceptual model of farmers' decision-making processes
JF Agricultural Systems
YR 2016
FD 2016-10
VO 148
SP 86
OP 94
K1 Decision modeling
K1 Farming systems
K1 Water management
K1 Case-based analysis
K1 Cognitive task analysis
K1 UML
AB 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.
PB Applied Science Publishers
SN 0308-521X
LK https://publications.ut-capitole.fr/id/eprint/22458/
UL http://tse-fr.eu/pub/31122