1. © European Communities, 2007 Introduction The utilisation and economic success of foresight activities in farm management have been seldom scrutinised. The research questions in this study were: 1) what kinds of foresight activities do farms have overall and 2) does economic success differ in different farm groups according to their future orientation and goals. Four important dimensions were defined and they were then used as basis for questionnaire construction. These measuring dimensions in defining the level of foresight activities in farms were: 1) the time scale of foresight (operational, strategic, visionary), 2) foresight perspective (passive, reactive, preactive, proactive), 3) the operational focus of the foresight activities (in what processes in farm management) and 4) the scale of the used foresight information (anticipating changes from local to global market). Material and methods The data consisted of a questionnaire that was prepared in March 2007 as part of yearly repeated Farm Accountancy Data Network (FADN) survey in Finland. The basic data that was used in measuring the economic success was taken from the FADN data (years 2004-2006). The system bases on a sample of over 1,000 farms and the database is maintained by MTT. Results The analysis of the asked future orientation and goals was done through a factor analysis and K-means cluster analysis. In factor analysis the extraction method was the Maximum Likelihood and rotation method was Varimax with Kaiser Normalization. According to the analysis the farms were then grouped into three farm groups; 1) the traditional and environmentally oriented farmer, 2) the economically oriented ”Euro” farmer, 3) The growth oriented ”economics of scale” farmer. These constructed groups were then scrutinised against a selected structural and economic indicators. Conclucions According to the results it seems that the constructed three farm groups differ from each other in term of future orientation, farm structure and in term of economical success. The analysis methods in this case were suitable. The factor analysis of the future goals of farms was the starting point and after that the clustering by factor scores resulted in three farm groups. Contact Pasi Rikkonen MTT Agrifood Research Finland, Economic Research Tel. +358 9 5608 6265 Fax +358 9 563 1164 E-mail: pasi.rikkonen@mtt.fipasi.rikkonen@mtt.fi NOTES 1.Poster Title Replace the mock-up text of the poster title (”Joint Research Centre”) with the text of your own title. Keep the original font colour (100c 80m 0y 0k). Keep the flush-right justification. Set it in Helvetica Rounded Bold Condensed, if you own the typeface. Otherwise, in Arial, Helvetica or Verdana – plain or bold. 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Place any additional logos on the bottom of the poster, evenly spaced between the JRC and (if there is one) the Directorate or Institute logo, and vertically centred with them. 2008 INTERNATIONAL CONFERENCE Defining foresight activities and economic success in farm management – empirical results from Finnish FADN farms The traditional and environ- mentally oriented farmer The growth oriented ”economics of scale” farmer The economi- cally oriented farmer N (farms in a group)39140104 Foresight perspective Operational, -Passive Strategic & visionary, -Preactive Operational & strategic, -Proactive Year of birth*195519621960 Working hours / year*2 4833 8683 386 Arable land*32,360,852,6 ESU (European Size Unit)*24,552,745,0 Gross return*66 506151 947125 828 Family farm income*15 15931 86726 770 Entrepreneurial profit*-22 396-24 478-21 800 Profitability coefficient*0,270,540,52 Equity ratio*897680 Debt-equity ratio* *mean values 326258 % of farms in different production lines The traditional and environ- mentally oriented farmer The growth oriented ”economics of scale” farmer The economi- cally oriented farmer Dairy farms38,5 %42,3 %34,1 % Farms in cereal production30,8 %23,9 %27,5 % Other crop farms12,8 %4,2 %11,0 % Mixed production7,7 %9,9 %11,0 % Horticulture farms5,1 %4,2 %5,5 % Other livestock farms2,6 %1,4 %1,1 % Other beef farms2,6 %6,3 %5,5 % Pig farms0,0 %7,7 %4,4 %