Learning from the historical failure of farm management models to aid management practice. Part 1. The rise and demise of theoretical models of farm economics

A potential source of lessons for agricultural modellers aspiring to influence farm decision making is the historical experience of agricultural economists in the field, variously termed 'Farm Management Research' or 'Farm Management'. Although the histories of Farm Management in the USA and in Australia differ significantly, in both cases the field was originally characterised by pragmatic on-farm research by agricultural scientists and later taken over by agricultural economists committed to theory-based economic analysis to enable rational planning and decision making. But in both countries, it became painfully evident to reflective participants that model-based Farm Management was not proving relevant to practical managers of farms. An insightful few went further to conclude not just that theoretical models of practice had not been relevant but that they could not be relevant, and since the late 1970s, the field has been in crisis. In this series of 2 papers, we seek insights that might explain this extraordinary 'market' failure of models that generate theoretical best practice as a basis for intervention. As an 'experiment', the history of Farm Management is enriched by the discontinuity between 2 'eras' characterised by 2 contrasting intervention approaches, an 'early' interactive and pragmatic era and a 'late' academic and theoretical era. In this first paper, after a brief history of the early pragmatic era and the 'take-over' by economic theorists, we analyse the 'crisis of relevance' that led to demise, relying heavily on the remarkable intellectual journey of John Dillon, the first Professor of Farm Management in Australia who turned from being elder economic theoretician to pioneer philosopher of pragmatic Farming Systems Research. The significant turn to Farming Systems Research by disillusioned Farm Management economists in the 1980s was preceded by a turn to another systems approach 2 decades earlier, that of agricultural systems modelling. Learning from the autecology of these significant systems efforts to influence the management of farms is the aim of the second paper in this series