Fixed assets are an integral component of the productive capacity of any enterprise. The financial results of the enterprise largely depend on their intensity and efficiency of use. The analysis of fixed assets is usually carried out using an integrated and systematic approach, based on their availability, their movement, efficiency of use (including their active part). In the opinion of some authors, the traditional methods of analyzing fixed assets have a number of shortcomings, since they do not take into account the life cycle of an enterprise, the ecological aspects of the operation of fixed assets, the operation specifics of the individual divisions of a company and its branches. In order to improve the methodology for analyzing fixed assets, the authors proposed to use formalized and non-formalized criteria for analyzing the risks associated with the fixed asset use. A survey questionnaire was designed to determine the likelihood of the risk of economic losses associated with the use of fixed assets. The authors propose using the integral indicator for the purpose of analyzing the risk of using fixed assets in dynamics. In order to improve the procedure for auditing, the authors proposed segregation of economic transactions with fixed assets according to their cycles in accordance with the stage of their reproduction. Operational analysis is important for managing the efficiency of the fixed asset use, especially during a critical period. Using the analysis of the regularity in grain combines performance would reduce losses during harvesting, implement the work within strictly defined time frame and remunerate the employees for high-quality and intensive performance of their tasks.
The article considers t the problem of determination of the degree of influence of uncertainty factors on the performance of an agricultural enterprise. Uncertainty and risk are an integral part of business life, and in agriculture they are all the more significant, since agricultural companies are greatly dependent on the influence of natural factors and phenomena. Consequently, the assessment of the directions and the strength of the impact of risk factors is of great importance for the plans and projects for the company's activities. After carrying out a schematic factor analysis of the financial results of the agricultural enterprise, the author selected parameters such as crop yields and average selling price, for analyzing the degree of exposure to uncertain factors. Since both the selected parameters are affected by a large number of both certain factors and factors uncontrollable for the company's management, the author finds it unacceptable to apply factor analysis to them. In the first place, the author justifies this by the difficulty in determining the weights of each influencing factor. Instead, the author suggests grouping all the factors on the basis of their certainty and definition of the influence degree for each group. For this purpose, the variability of each parameter in different series was analyzed: for several years in one enterprise and for one year in a number of similar enterprises. It was found that fluctuations in crop yields by enterprises were higher than by years. This forced the author to bring out the conclusion that there is a significantly greater influence of certain factors on this indicator. On the other hand, when analyzing prices, the opposite situation emerged: here the influence of uncertain factors is much stronger. As a result, the proposal was made for the projecting method, such as economic and mathematical modeling, to use the data from both the firm being the subject of modeling, and from the similar enterprises available from the regional Department of Agriculture. In this case, the accuracy of the forecast will be much higher, besides, it can be developed in 3 or 5 probability scenarios.
The article considers t the problem of determination of the degree of influence of a number of factors on formation of innovative behavior of employees and their groups in organizations. According to the authors’ opinion, innovative activity of employees requires, on the one hand, their own abilities and motivation, and on the other hand, readiness of the organization and provision of necessary resources for employees both for creation and implementation of ideas and projects. The authors do not deny the influence of the national business culture on the features of innovative behavior and point out the need to take into account these features. However, they deny the existence of national features that obviously make innovation development of one country easier than others, and therefore consider the experience of different countries worthy of study, but at the same time its implementation is considered possible only after a critical rethinking for existing conditions. The authors point out that innovative behavior of employees is formed under the influence of factors that can be conditionally divided into those dependent and independent of management actions, the former being of particular interest due to the possibility of controlling them. Among them the following groups of factors are identified: (i) related to the peculiarities of management style; (ii) characteristics of the workplace and job responsibilities; (iii) factors related to interpersonal and intergroup relations, and (iv) organizational factors. The influence of the key factors of each group was analyzed and evaluated either from the standpoint of positive or negative impact on the formation of innovative behavior, or from the position of the strength of influence. Based on the experience of Chinese colleagues, a comparative ranking of the factors that determine the innovativeness of behavior was carried out, in terms of their significance. At the same time, the similarity of the factors determining the innovativeness of the behavior of employees in Chinese and Russian companies was revealed, but significant differences in the degree of such influence were detected. As a result, the authors’ named key success factors in the formation of innovative behavior of the staff: (i) support from the company’s management; (ii) availability of resources of all types; (iii) system of labour remuneration; (iv) composition and structure of the team, and (v) cooperation.
The article considers the problem of population’s income inequality in the Russian Federation and detection of the factors affecting it. Population’s income differences demonstrate both intrinsic and unavoidable differences among individuals and their groups in terms of their participation in the social processes, and the governmental efforts aimed at reasonable and fair distribution of the national wealth among the citizens. The research objective was to identify the dynamics of the Gini index as acknowledged indicator for population inequality in terms of income and to analyze the factors defining such dynamics. The research was carried out based on the national statistical data. The authors detect close connection between the downturns in economy, especially decrease of the dynamics of average income per capita, and the level of population inequality in terms of income. However, contrary to expectation, the correlation is direct which means that during the periods of slowing of the income growth the values of Gini index being the avowed income inequality indicator also reduced. On the other hand, the authors point out that such connection exists only for time series. While studying the static populations’ income differences in various regions no correlation between the income size and difference values was found. Based on the research results the authors draw the conclusion about undesirability of violent fluctuations in the dynamics of the population’s effective earnings, as well as about justifiability of the efforts of national and regional authorities aimed at the improvements of the income policy.
The urgency of the present study is due to the absence of any reliable method for investment risk assessment in agribusiness which impedes attracting and control of investment processes in this sector of economy. The article presents a new approach to modelling investment risk assessment applicable for agricultural companies. Determination of the financial stability level of a company is the core of the matrix model. This is a unique system of indicators that continuously reflect the operation quality and methods. It provides an assessment of the results of decisions made and actions of managers at various levels, the measure of control and management of assets, their sources, expenses and incomes of a company. The suggested procedure may also be of use for the Department of Agrarian Policy and Business in providing scientific and methodological support for ranking agricultural companies to identify the risk of investing in their activities.
The design of management decisions is one of the most difficult and most creative processes in all managerial work. It requires thorough understanding of the current situation and prospects of both the company and its environment. The article considers the problem of determination of the degree of influence of uncertainty factors on the performance of an agricultural company. After carrying out a schematic factor analysis of the financial results of the agricultural company, the authors selected parameters such as crop yields and average selling price, for analyzing the degree of exposure to uncertain factors. Since both the selected parameters are affected by a large number of certain factors and factors uncontrollable for the company’s management, the authors find it unacceptable to apply factor analysis to them. Instead, the suggestion is made concerning grouping all the factors on the basis of their certainty and definition of the influence degree for each group. As a result, the proposal was made for the projecting method, such as economic and mathematical modeling, to use the data from both the firm being the subject of modeling, and from the similar enterprises available from the regional Department of Agriculture. In this case, the accuracy of the forecast will be much higher, besides, it can be developed in 3 or 5 probability scenarios.
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