Among the users of factor analysis there seems to be a tendency to extend the use of this method to tasks where it suits poorly. It is therefore important to emphasise at least the following aspects: 1) More critical attention should be paid to problems of interpretation especially at situations where method is aimed at analysing the causal relationships among the variables; 2) The study problem should be stated so clearly as to make it plausible to evaluate the suitability of factor model to the problem.
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A hypothetic problem is outlined as an example of the type of problem to which factor analysis should not be applied. Apart from this, attention is paid to industrialisation, a concept characterised by several variables, none of which can be held constant while analysing its influence on attitudes by multi-variable cross-tabulation techniques.
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Some alternative ways of using factor analysis in the field of forest owners’ behaviour are explored in the article, in the light of two new Finnish publications. The philosophical and mathematical propertied of factor analysis are often considered too restrictive, and thus its applicability to different fields too limited. A good knowledge of the method and the subject matter theories seems to be an important prerequisite for a successful application of factor analysis. Otherwise the researcher is too dependent on the general recommendations concerning the use of factor analysis and cannot fit its use in his special situation and the whole methodological setting of the study.
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The data used to control the developed methods are presented in chapter two. The third chapter presents the statistical analysis conducted. The factor analysis shows that tree stand characteristics must be divided into three factors to able the information needed for site indexing to distinguish different site classes. The phases of model development are presented and the results of calculations with control data are shown.
The results indicate that for calculations of nature-normal forests the suitable amount of tree stand characters for creating the site indexing function, is three. These are: number of trees (N), basal area of the stand (G) and mean height (H).
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Being a logging contractor involves several uncertainties, amongst others, information quality in the work order received from customers. The information quality of work orders is of the utmost importance for logging contactors, in order to be able to plan and conduct work properly. The purpose of this paper is three-fold: 1) identifying work order information components in harvesting, 2) identifying work order information quality dimensions in harvesting and 3) assessing work order information quality in harvesting. The paper is based on interviews and a survey. Various interviews took place in Sweden with professionals within the harvesting industry as well as logging contractors, and thereafter a survey was developed. Random selection was conducted and 100 Swedish logging contractors were contacted by telephone in order to answer the survey, with a response rate of 82% from the sample. The paper concludes that the information quality dimension of accuracy concerns the individual work order information components, whereas timeliness is related to receiving the complete work orders. A factor analysis has been conducted with five factors emerging. The assessment of work order information quality in harvesting implies that the potential for improvement exists with regard to increasing the accuracy of the order information for the components of “Cleaning under story trees – not conducted” and “Cleaning under story trees – of low standard” as well as “Landing – size”, and “Landing – placement”. However, their effect on capacity is utilization needs to be explored.