Gender Divisions and Gender Policies in Top Finnish Corporations

The expansion of transnational corporations is a fundamental part of contemporary globalising processes. Through their activities, transnational corporations also have impacts on national and cultural gender relations, thus highlighting that gender relations are indeed amenable, to some extent, to social change. Accordingly, large transnational corporations have many effects and implications for gender relations in society, as well as having their own gender relations within them, characteristically in the form of men’s far greater presence in management than women’s. A key aspect in the functioning of transnational corporations is thus the way they organise and restructure gender relations within their own activities. The research presented here on gender divisions and gender policies in largest Finnish multinational and national corporations is part of a longer-term examination of the relations of gender relations in transnational corporations. It sets out the results of a survey of the largest 100 Finnish corporations with regard to the following main kinds of question: · general information on the corporation’s size, sector and economic activities; · the gender composition of their employment, middle management, top management, and board; · their gender equality plans and related policies. The human resources manager or their equivalent or delegate of 62 corporations responded to the survey. The general analysis of the data obtained from the survey is presented in this research report. Special attention is given to relations between the gender divisions and the gender policies of corporations. Interpretations of the data and more general theoretical implications are discussed in the report, with special attention to theoretical ways forward.

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.