Urbanization is a major factor causing unsupported perceptions within the traditional vision offorest management. Urbanization has led to a reconstruction on forest owners’ economicdependency on the forestry. This contributes in emigration from rural areas to bigger cities.To understand how distant forest owners, manage their forest they need to be segmentedaccording to specific criteria. The purpose of the study is to create a segmentation model thatis theoretically anchored and empirically verified, to increase the customer value and maptheir different needs. Through the purpose a research question was developed: How can asegmentation model for absentee proprietors within the forest industry be developed toincrease the customer value? A segmentation model provides comprehensive knowledge andinsights about forest owners’ different needs. The empirical data, collected through surveys,was presented individually and some connections could be found. Through these connectionsproperty area and distance were chosen as factors that are appropriate for segmentation. Basedon the segmentation factors a correlation analysis was made to create four demographicsegmentations. The visitors: small area, small distance. Conservationists: small area, largedistance. Investors: large area, small distance. Specifiers: large area, large distance. Theconclusion shows that a segmentation model over absentee proprietors is necessary for thestrategic management in forest companies, when it comes to decisions regarding sales criteria,communication and recommended approaches.

Master of Science / Department of Agricultural Economics / Michael R. Langemeier / The overall objective of this study was to examine the relative efficiency of farmers in various age groups. Nine Hundred sixty-four sole proprietors, who were members of the Kansas Farm Management Association (KFMA) with continuous data from 2002-2006, were split up into four groups based on age. Comparing the fourth age group (over 65 years of age) to the first age group (under or equal to 45 years of age) was of primary importance in this study. Comparisons were made utilizing variables pertaining to farm size and tenure, specialization, efficiency, liquidity, and solvency. In this study, there are four age groups; under or equal to 45 years, 46 to 55 years, 56 to 65 years, and greater than 65 years old. T-tests were used to compare variables among age groups. Nineteen variables were statistically different between age groups one and four. The fourth age group performed poorly in terms of cost efficiency. Based on the results, the fourth age group had a difficult time covering unpaid labor and capital expenses. Discriminant analysis was used to determine which variables discriminate the most between age groups. The top three variables in this discriminant analysis were the asset turnover ratio, the economic total expense ratio, and percent acres owned. The top three variables in the discriminant analysis involving groups one and four were the debt to asset ratio, asset turnover ratio, and net farm income.