Probabilistic typology of management decision making in private forest properties

We conducted a quantitative study of private forest owner management behavior based on face-to-face interviews with 380 randomly selected private forest owners in Slovenia. Forest owners were asked to rate the relevance of nineteen factors representing information related to the social, ecological, and economic aspects of decision making based on a five-point Likert scale. This information was consolidated into major categories with Principal Component Analysis. Expectation maximization (EM) clustering was used to build a probabilistic private forest owner decision making typology. Six major categories of information determined 64% of the variability in decision making: non-wood goods and services, forest economics, property administration, optimization of wood production, forest protection, and minimum cutting restrictions. EM clustering revealed two decision making types differing in their attitude towards the total economic value of forests: Materialists, whose decisions are mainly related to the extractive value of forests and Non-materialists, who manage for non-extractive value. Full-time farmers, owners living within 2km of their holdings, and owners who permanently cooperated with the public forest service were much more likely to be Materialists. The uncertainty in private forest owner typology building and the applicability of probabilistic models of private forest owners to end-users is discussed.