New Product Positing And Pricing Based On Hierarchy Discrete Choice Experiments

With the rapid development of China’s market economy, commodity markets gradually from the “enterprise product-oriented” rapidly converted as the center of the customer to the“customer-oriented”. Customer is the main source of corporate profits, only the product satisfy customer demand, enterprise can make profits. Therefore, in the process of launching new products, enterprises should fully understand the preferences of consumers’ demand and get the preferences information, on this basis, to optimize the new product positioning and pricing, thus win the market.In induction and summarizes the new product pricing, positioning and new products optimization methods, this article introduced a new product positing and pricing optimization model based on hierarchy discrete choice experiments to make the product line market profit maximization. And in smart phone as empirical research object, proof the feasibility and validity of the model. To be specific, the research emphasis of this article is as follows:Firstly, to build a new product optimal positioning and pricing model based on hierarchical discrete choice experiment, put forward the hierarchical structure of product selection, m brand as the product identification, to improve the original utility function, the brand and price to quantify the influence consumer preferences. At the same time, in combination the common product line optimization model with the research situation in this article, and make it simplified and improvement to meet the demand of research of this article.Secondly, the object of our study is complex multi-attributes product, general discrete choice experiment can’t deal with this problem, based on this, this paper presents a hierarchical information integration method to deal with this problem. The experiments simulate the real market situation, in order to brand as the dependent variable and the choice experiment, let consumer make choice for these different products. After get the data, use the MNL model to analyze and get the date of consumer preference for each attribute or attribute level of utility.Thirdly, take the smart phones for example, we use genetic algorithm to solve the problem and verify the effectiveness of the optimization model. Regard the new product positioning and pricing optimization problem as a combinatorial optimization problem, the product attributes and attribute level analogy for chromosome genes and alleles. Throughthe selection, crossover and mutation operator finally obtaining the outline of new product,then combining the market conditions to analyze and discuss the new product.