Robert, Marion, Dury, Jérôme, Thomas, Alban, Therond, Olivier, Sekhar, Muddu, Badiger, Shrinivas, Ruiz, Laurent and Bergez, Jacques Eric (2016) CMFDM: A methodology to guide the design of a conceptual model of farmers' decision-making processes. Agricultural Systems, 148. pp. 86-94.

Full text not available from this repository.
Identification Number : 10.1016/j.agsy.2016.07.010

Abstract

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.

Item Type: Article
Language: English
Date: October 2016
Refereed: Yes
Uncontrolled Keywords: Decision modeling, Farming systems, Water management, Case-based analysis, Cognitive task analysis, UML
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 27 Oct 2016 08:23
Last Modified: 02 Apr 2021 15:54
OAI Identifier: oai:tse-fr.eu:31122
URI: https://publications.ut-capitole.fr/id/eprint/22458
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