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The present work attempts based on the analysis of linear structure equationmodels, to compile regulation factors of the success of agricultural enterprises atthe management level. For generation and evaluation reasons, the findings fromthe factor research are the focus of the study. After introducing the topic ofsuccess factor research, current empirical methods are compared based on theirexplanatory potential. As a result of the comparison, it was decided to apply aconfirmatory approach.Linear structure equation models with latent variables are applied to the database.The explanation of the method occurs in chapter 3. They are applied on thefactor analysis as well as the path analysis because linear structural equationmodels concern both.In the following, the database, which is based on the results of annual financialstatements of agricultural enterprises from southern Saxony-Anhalt, is introduced.Following, there occurs the characterisation and discussion of the data.The next chapter contains the results of the partial analytical investigation ofpossible variables which may influence the success of agricultural enterprises.Embedded in a theoretical framework, the basic theoretical hypotheses wereformulated. The theoretical basis of research hypotheses is based on the managementmodel for enterprises, which makes a distinction between managementlevel and other dimensions of business administration. Based on these results,and on the results of the descriptive evaluation, concrete research hypotheses areformulated. The hypotheses imply a positive effect of the single dimensions ofbusiness administration, such as market orientation, technology orientation, costorientation and resource orientation, on enterprise success.The hypotheses are tested in factor-analytic models, and structured equationmodels of the first and second order are discussed regarding content. As a result,production and costs orientation and market orientation most affect enterprisesuccess. Therefore, the influence of management and business administrationwere found to be factors of success in different performance data. However, theresults are to be interpreted in the scope of the formulated models.
