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Features of diagnostics as a crisis management tool for agricultural enterprises
The article considers theoretical and practical approaches to diagnosing the crisis state of agricultural enterprises within the framework of anti-crisis management. It is argued that anti- crisis management is a strategic process that changes the activities of the enterprise based on the diagnosis of potential problems, as well as taking into account the features of the institutional environment at the stages of the crisis.
It is substantiated that for small farms and medium-sized agricultural enterprises it is advisable to combine the consideration of the general and local crisis, since they very often coincide. The need to take into account certain external factors when diagnosing the crisis state of agricultural enterprises is proven, since most of them are unable to form anti-crisis potential, the potential for stability and are more dependent on the environment.
The use of a combined approach to conducting a crisis diagnosis of an agricultural enterprise and analyzing external factors is proposed. It is substantiated that the development of financial analysis models for predicting threats to the enterprise can be considered within the framework of the early crisis warning system. It is emphasized that financial ratios are important tools for predicting problems in the economic activity of the enterprise, and it is advisable to use them when developing predictive models. It is substantiated that managing an enterprise during a crisis is possible only if a diagnosis of potential problems is carried out, since its results provide a high justification for management decisions regarding the development of a plan for overcoming the crisis and recovery. It is proved that the combined model for conducting diagnostics is advisable to use at the stage of the crisis, when there is a need for prompt decision- making.
Key words: diagnostics, anti-crisis management, agricultural enterprise, stages of the crisis, financial indicators, external factors.
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