Non-industrial private forest landowners’ choices of timber management strategies and potential allowable cut.

In the study, the potential allowable cut in the district of Pohjois-Savo - based on the non-industrial private forest landowners' (NIPF) choices of timber management strategies - was clarified. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP). The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7 and NFI8), to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the same MELA system as has been used in the calculation of the national cutting budget. The data consisted of the NIPF holdings (from the TASO planning system) that had been inventoried compartmentwise and had forestry plans made during the years 1984-1992. The NIPF landowners' choices of timber management strategies were clarified by a two-phase mail inquiry. The most preferred strategy obtained was "sustainability" (chosen by 62 % of landowners). The second in order of preference was "finance" (17 %) and the third was "saving" (11 %). "No cuttings", and "maximum cuttings" were the least preferred (9 % and 1 %, resp.). The factors promoting the choices of strategies with intensive cuttings were a) "farmer as forest owner" and "owning fields", b) "increase in the size of the forest holding", c) agriculture and forestry orientation in production, d) "decreasing short term stumpage earning expectations", e) "increasing intensity of future cuttings", and f) "choice of forest taxation system based on site productivity". The potential allowable cut defined in the study was 20 % higher than the average of the realized drain during the years 1988-1993, which in turn, was at the same level as the cutting budget based on the combining of forestry plans in eastern Finland. Respectively, the potential allowable cut defined in the study was 12 % lower than the NFI8-based greatest sustained allowable cut for the 1990s. Using the method presented in this study, timber management strategies can be clarified for non-industrial private forest landowners in different parts of Finland. Based on the choices of timber managemet strategies, regular cutting budgets can be calculated more realistically than before.

Non-industrial private forest landowners’ choices of timber management strategies.

The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.

Consumer Evaluation of Hybrid Innovations (summary section only)

Hybrid innovations, or new products that combine two existing product categories into one, are increasingly popular in today’s marketplace. Despite this proliferation, few studies address them. The purpose of this thesis is to examine consumer evaluation of hybrid innovations by focusing on consumer categorization of such innovations and on factors contributing positively and negatively to their evaluation. This issue is examined by means of three studies. The first study addresses the proportion of consumers categorizing hybrid products as single- versus dual-purpose, what contributes to such a categorization, what differences can be found between the two groups, and if categorization can and should be included in models of innovation adoption. The second study expands on the scope by including motivation as a predictor of consumer evaluation and examines two cognitive and affective factors and their differential impact on innovation evaluation. Finally, the third study examines the product comparisons single- versus dual-purpose categorization induce. These three essays together build up a broader understanding of hybrid innovation evaluation. The thesis uses theories from both psychology and marketing to examine the issues at hand. Conceptual combination and analogical learning theories from psychology are used to comprehend categorization and knowledge transfer. From marketing, consumer behavior and innovation adoption studies are addressed to better understand the link between categorization and product evaluation and the factors contributing to product evaluation. The main results of the current thesis are that (1) most consumers categorize hybrid products as single- and not as dual-purpose products, (2) consumers that categorize them as dual-purpose find them more attractive (3) motivation has a significant effect on consumer evaluation of innovations; cognitive factors promote an emphasis on product net benefits, whereas affective factors induce consumers to consider product meaning in the form of categorization and perceived product complexity, (4) categorization constrains subsequent product evaluation, and (5) categorization can and should be included to models of innovation adoption. Maria Sääksjärvi is associated with CERS, the Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration

Evaluation of the profitability of fast-growing tropical trees.

The profitability of fast-growing trees was investigated in the northeastern and eastern provinces of Thailand. The financial, economic, and tentative environmental-economic profitability was determined separately for three fast-growing plantation tree species and for three categories of plantation managers: the private industry, the state (the Royal Forest Department) and the farmers. Fast-growing tree crops were also compared with teak (Tectona grandis), a traditional medium or long rotation species, and Para rubber (Hevea brasiliensis) which presently is the most common cultivated tree in Thailand. The optimal rotation for Eucalyptus camaldulensis pulpwood production was eight years. This was the most profitable species in pulpwood production. In sawlog production Acacia mangium and Melia azedarach showed a better financial profitability. Para rubber was more profitable and teak less profitable than the three fast-growing species. The economic profitability was higher than the financial one, and the tentative environmental-economic profitability was slightly higher than the economic profitability. The profitability of tree growing is sensitive to plantation yields and labour cost changes and especially to wood prices. Management options which aim at pulpwood production are more sensitive to input or output changes than those options which include sawlog production. There is an urgent need to improve the growth and yield data and to study the environmental impacts of tree plantations for all species and plantation types.