Identifying of risks in pricing using a regression model of demand on price dependence

The aim of the article. The main purpose of the article is to describe scientific and methodological approaches of determining the price elasticity of demand as a regression model based on the price and risk assessment of price variations on the received model.The results of the analysis. The study is based on the assumption that the index of price elasticity of demand on high-tech innovation is not constant as it is commonly understood in the classical sense. Onthe stage of commodity market release and subsequent sales growth, the index of price elasticity of demand may vary within certain limits. Index value and thereafter market response are closely related to the current price.Achieving the stated purpose of the article is possible when having factual information about prices and corresponding volumes of sales of new high-tech products for a short period of time, on the basis of which types of demand and prices interrelation are modeled.Risk assessment of pricing and profit optimization by the regression of demand depending on price consists of three stages:a) obtaining of a regression model of the demand on the price;b) obtaining of function of demand price elasticity and risk assessment of pricing depending on behavior of the function;c) determination of the price of company to receive a maximum operating profit based on the specific model of price to demand function.To receive the regression model of dependence of demand on price it is recommended to use specific reference models. The article includes linear, hyperbolic and parabolic models. The regression dependence of price elasticity of demand on price for each of the reference models of demand is obtained on the basis of the function elasticity concept in mathematical analysis. The concept of function of price elasticity of demand expresses this dependence. For the received functions of price elasticity of demand, the article provides intervals with the highest and lowest risk of increasing or lowering prices. For each of the reference regression models of dependence of demand on price when using the research methods of the extremum optimal prices were obtained, through which businesses can count on the maximum price.Conclusions and direction of further researches. The results of the study provide the approach based on the existence of a regression of price elasticity of demand for the price of high-tech products which can be used as a tool for the assessment and prevention of risks in the pricing at all stages of the product life cycle.Methods of assessing risks of pricing and profit optimization for the regression demand on price allows companies with different pricing strategies, such as the strategy of skimming or a strategy to capture the market to assess the risks of pricing and optimal price at which it will receive the maximum profit.In order to confirm the findings of Methods of assessing risks of pricing and profit optimization for the regression of demand on price approbation of the theoretical results to actual data is required. Themain task of approbation should be consider as getting the functions of price elasticity of demand, evaluating pricing risks and determining the optimal selling prices for different groups of new high-tech products.