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RESEARCH ARTICLE
Contents Vol 57(2)

Learning from the historical failure of farm management models to aid management practice. Part 2. Three systems approaches

R. L. McCown A C and K. A. Parton B
+ Author Affiliations
- Author Affiliations

A CSIRO Sustainable Ecosystems, Agricultural Production Systems Research Unit, Toowoomba, Qld 4350, Australia.

B Faculty of Science and Agriculture, Charles Sturt University, Orange, NSW 2800, Australia.

C Corresponding author. Email: Bob.McCown@csiro.au

Australian Journal of Agricultural Research 57(2) 157-172 https://doi.org/10.1071/AR05052
Submitted: 18 February 2005  Accepted: 7 September 2005   Published: 24 February 2006

Abstract

Part 1 analysed the difficulties experienced in the field of academic Farm Management in making complex theoretical models relevant to farming. This paper highlights the important connections developed between the field of Farm Management economics and 3 key ‘systems’ ideas and tools in agricultural science in response to difficulties and opportunities. The first systems approach reviewed is the 20-year experiment by agricultural economists in using crop and animal production simulation models in management analyses. The second systems approach reviewed is Farming Systems Research (FSR), an approach characterised by on-farm experimentation with a management orientation. Many pioneers of FSR were Farm Management economists disenchanted by the inapplicability of economic theory to farm management. The FSR that emerged is interpreted as a scion of the early era of Farm Management prior to the coup by economics theorists in the 1940s. A third systems approach reviewed is a ‘soft’ intervention to facilitate farmer learning. Although evolving from FSR, this approach has surprising similarities to the ‘goal adjusting’ consulting performed by the legendary Australian Farm Management consultant cum academic, Jack Makeham. The paper concludes with discussion of a recent innovation that combines these 3 approaches. It uses a soft intervention approach that features farmers shaping their goals and expectations by ‘experimenting’ in a local, but virtual, environment provided by simulation of the production system using ‘hard’ models.


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