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A conceptual model of farmers’ informational activity: a tool for improved support of livestock farming management

Published online by Cambridge University Press:  01 June 2010

M. A. Magne ,
M. Cerf  and
S. Ingrand
M. A. Magne*
Affiliation:
INRA, UMR1273 Métafort, Equipe Select, F-63122 Saint-Genès Champanelle, France
M. Cerf
Affiliation:
UMR SAD-APT, Equipe PRAXIS, Bâtiment EGER, BP1, F-78850 Thivernal-Grignon, France
S. Ingrand
Affiliation:
INRA, UMR1273 Métafort, Equipe Select, F-63122 Saint-Genès Champanelle, France
*
†E-mail: [email protected]
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Abstract

Farmers have been slow to adopt decision support system (DSS) models and their outputs, mainly owing to (i) the complexity of the data involved, which most potential users are unable to collect and process; and (ii) inability to integrate these models into real representations of their informational environments. This situation raises questions about the way farm management researchers have modelled information and information management, and especially about the quality of the information assessed by the farmers. We consider that to review advisory procedures we need to understand how farmers select and use farm management-related information, rather than focusing on decisions made in particular situations. The aim of this study was to build a conceptual model of the farmer-targeted farm management-related information system. This model was developed using data collected in commercial beef cattle farms. The design structure and operational procedures are based on (i) data categories representing the diversity of the informational activity; and (ii) selected criteria for supporting decisions. The model is composed of two subsystems, each composed of two units. First, an organizational subsystem organizes, finalizes and monitors informational activity. Second, a processing subsystem builds and exploits the informational resources. This conceptual model makes it possible to describe and understand the diverse range of farmers’ informational activity by taking into account both the flow of information and the way farmers make sense of that information. This model could serve as a component of biodecisional DSS models for assigning information in the decision-making process. The next task will be to take into account the broad range of farmers’ perceptions of the management situations in DSS models.

Keywords

informational activitydecision-makingfarm managementmodellinglivestock farming system
Type
Full Paper
Information
animal , Volume 4 , Issue 6 , June 2010 , pp. 842 - 852
Copyright
Copyright © The Animal Consortium 2010

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References

Blackmore, BS 2000. Using information technology to improve crop management – weather and agro-environmental management. In Proceedings of the AgMet Millennium Conference (ed. DA Mc Gilloway), pp. 30–38. Met. EiReann, Dublin, Ireland.Google Scholar
Brook, R 1988. IDSS: building better tools for making farm decisions. Agricultural Engineering 68–69, 18–19.Google Scholar
Carberry, PS, Hochman, Z, McCown, RL, Dalgliesh, NP, Foale, MA, Poulton, PL, Hargreaves, JNG, Hargreaves, DMG, Cawthray, S, Hillcoat, N, Robertson, MJ 2002. The FARMSCAPE approach to decision support: farmers’, advisers’, researchers’ monitoring, simulation, communication and performance evaluation. Agricultural Systems 74, 141–177.CrossRefGoogle Scholar
Cerf, M, Magne, MA 2007. La mobilisation des intervenants du développement par des publics cibles: le cas du conseil en agriculture. @ctivités 4, 112–122.Google Scholar
Darré, JP, Mathieu, A, Lasseur, J 2004. Le sens des pratiques. Conceptions d’agriculteurs et modèles d’agronomes. INRA, Paris, France.Google Scholar
Food and Agriculture Organization of the United Nations (FAO) 2005. Le secteur de l’élevage à l’heure de la mondialisation: incidence des marchés en mutation. In: Rapport présenté à la 19e session du Comité de l’Agriculture de la FAO, Rome, Italy, 13p.Google Scholar
Gibon, A, Hermansen, JE 2006. Sustainability concept in Livestock Farming Systems’ research orientations. EAAP, Session 1. Ethics of sustainability, Antalya, Turquie.Google Scholar
Girard, N, Navarrete, M 2005. Quelles synergies entre connaissances scientifiques et empiriques? L’exemple des cultures du safran et de la truffe. Natures Sciences Sociétés 13, 33–44.CrossRefGoogle Scholar
Guyot, B 2006. Dynamiques informationnelles dans les organisations, 236 p. Hermès Sciences Publications, Lavoisier Paris, France.Google Scholar
Just, DR, Wolf, S, Zilberman, D 2003. Principles of risk management service relations in agriculture. Agricultural Systems 75, 199–213.CrossRefGoogle Scholar
Kadlec, EJ 1985. Farm Management: Decisions, Operation, Control. Prentice-Hall Inc., Upper Saddle River, NJ, USA.Google Scholar
Kay, DR, Edwards, MW 1999. Farm Manager, 4th edition. The McGraw-Hill, Inc, Boston, MA, USA.Google Scholar
Laurent, C 2000. L’exploitation agricole au coeur des choix du développement local français et européen. Revue d’Economie Régionale et Urbaine 3, 427–442.Google Scholar
Le Moigne, JL 1990. La modélisation des systèmes complexes, pp. 3–17, 129–138. Bordas, Paris, France.Google Scholar
Lorino, P 1991. Le contrôle de gestion stratégique. La gestion par les activités. Dunod, Paris, France.Google Scholar
Magne, MA, Couzy, C, Ingrand, S 2005. Comprendre comment les éleveurs de bovin allaitant mobilisent des informations pour concevoir et piloter leur activité d’élevage: distinguer le Support, l’Origine et le Contenu (SOC). 12e Rencontres autour des Recherches sur les Ruminants, pp. 65–68. Paris, France.Google Scholar
McCown, RL 2002. Changing systems for supporting farmers’ decisions: problems, paradigms, and prospects. Agricultural Systems 74, 179–220.CrossRefGoogle Scholar
Rougoor, CW, Trip, G, Hiurne, RBM, Renkema, JA 1998. How to define and study farmers’ management capacity: theory and use in agricultural economics. Agricultural Economics 18, 216–272.CrossRefGoogle Scholar
Simon, HA 1955. A behavioural model of rational choice. Quarterly Journal of Economics 69, 99–118.CrossRefGoogle Scholar
Slavik, M 2004. Changes in Information Systems in Czech Agriculture. The Journal of Agricultural Education & Extension 10, 193–202.CrossRefGoogle Scholar
Solano, C, Leon, H, Perez, E, Herrero, M 2003. The role of personal information sources on the decision-making process of Costa Rican dairy farmers. Agricultural Systems 76, 3–18.CrossRefGoogle Scholar
Stafford, JV 2000. Implementing precision agriculture in the 21st century. Journal of Agricultural Engineering Research 76, 267–275.CrossRefGoogle Scholar
Stoorvogel, JJ, Antle, J 2007. Integrated assessment of agricultural systems: a challenge of system and model complexity. Farming Systems Design. In International Symposium on Methodologies on Integrated Analysis of Farm Production Systems. Book 1: Farm-regional scale design and improvement (ed. M Donatelli, J Hatfield and A Rizzoli), pp. 8–9. La Goliardica Pavese, Catania, Italy.Google Scholar
Thysen, I 2000. Agriculture in the Information Society. Journal of Agricultural Engineering Research 76, 297–303.CrossRefGoogle Scholar
Timko, M, Loynes, RMA 1989. Market information needs for Prairie farmers. Canadian Journal of Agricultural Economics 37, 609–627.CrossRefGoogle Scholar
US National Research Council (NRC) 1997. Precision Agriculture in the 21st Century: Geospatial and Information Technologies in Crop Management. National Academy Press, Washington, DC, USA.Google Scholar
US North Central Regional Research in Farm Information Systems 1994. Information Management of Your Farm: Facilitators Guide. Station Bulletin 604, publication 337. University of Minnesota, Minneapolis, MN, USA.Google Scholar
Van Der Ploeg, JD 1993. Rural sociology and the new agrarian question. A Perspective from the Netherlands. Sociologia Ruralis 33, 240–260.CrossRefGoogle Scholar