Academic journal article Asian Social Science

Methodical Bases for Developing Predictive Scenarios of Agribusiness

Academic journal article Asian Social Science

Methodical Bases for Developing Predictive Scenarios of Agribusiness

Article excerpt


Complexity of the agricultural business tasks, high dynamism and non-linear nature of the contemporary socio-economic processes which differs functioning of any industry are placing new requirements for predictive studies. The purpose of this study is to develop a set of methodological provisions for the construction of predictive scenarios of the agricultural business by identifying current trends, the impact factors of the environment and the interpretation of results forecasting and analytical calculations. This article considers the influence of climatic factors on the economic impact of the frumentaceous and the grape branches of agriculture. The system of economic and mathematical prognostics models of the main industrial indicators was developed. The methodology for scenario forecasting of indicators of frumentaceous production and vine growing was proposed based on the use of the influence of solar activity on agrobiological processes.

Keywords: agricultural business, forecasting, scenario forecast methodology, the trend - cyclical patterns, price, cost, cost effectiveness, the cycles of solar activity, grain production, viticulture, economic and mathematical models

1. Introduction

Today a variety of mathematical models is use to predict the performance of the agricultural business. Effectiveness of prognostic study depends primarily on the choice of indicators, the availability of the necessary information base used the information and analytical tools and skills of the researcher. An important place in the development of forecasting activity in relation to the agricultural business belongs to the practical demand forecasts obtained. It should be kept in mind essentially nonlinearity of processes under investigation, which creates serious difficulties in obtaining reliable results at medium and especially in long-term forecasting (Panasyuk et al., 2014).

Negotiation of these difficulties is strongly influenced on the modeling level of the investigated processes of agrarian business allowing use the best modern informative and theoretical and methodological endeavours. Because of the complexity of the investigated phenomena, usually chronological heterogeneity of information sets, the duration of the study period, and therefore the changes in trends in its different parts is nigh on impossible to adequately describe the actual processes of agrarian business only through the use of a single, quite difficult mathematical model. And here it should be kept in mind as the modeling of individual indicators of the agricultural business as their totality. It means that, to obtain simulation results having sufficiently high accuracy, it is expedient to use some system of mathematical models, having sufficient flexibility and adaptability to changes in both the modeling object and its environment.

2. Methods

The successful functioning of the agricultural business depends on many factors, but the most important and meaningful component of information-analytical support of the management of its sustainable development is the prediction of grain production and viticulture. Productivity, the gross yield, crop area, sales price, the cost of its production, sales revenue, profit, profitability are included to the most important indicators of the state and development of these industries (Renaud-Gentié et al., 2014).

The proposed method of forecasting performances of grain farming and viticulture are based on the use of multivariate complex of mathematical economic regression, trending and trend-cycle models, extrapolation and adaptive prediction of the main indicators such as productivity, cost, selling price, the value of cultural area (Chernobay, 2012).

Choice and use of a set of mathematical modeling tools in the forecast process depend on informative database and taking into account the need to harmonize the influence factors on grain production and viticulture. The simulation of performances for the development of grain production and vine growing intended for further prognostic studies should therefore take into account the requirements of flexibility and adaptability of the built models from the position of prediction. …

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