Methodology for pricing using price elasticity of demand. Case type: automotive parts sector

The pricing in the company under study, dedicated to the marketing of automotive parts sector, is done empirically for at least 50,000 products. This paper establishes a methodology for the allocation and change in the price level of these products, using as a tool, price elasticity of demand. For that purpose, we initially do a grouping of parts according to their elasticity through the use of cluster analysis, obtaining 7 groups that are characterized quantitatively and qualitatively. Objectives and policies of pricing for these groups are determined, allowing thus establishing the methodology for the pricing of the company. Additionally, in the document the CPI calculation technique is used for determining the impact of price variation of each group on the total variation. Thus, the study shows that it is possible to establish precise methods for fixing prices through the use of price elasticity of demand. To achieve this goal for many products, it is useful to use the tools provided by the multivariate statistics as they allow better analysis of the data. Besides this, it is apparent that the use of methodologies for calculating inflation rates is useful in determining the impact of the adopted pricing policies

• Tipo de recurso: http://purl.org/coar/resource_type/c_7066
• Fecha de publicación: 2012
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/11625
• Acceso en línea: https://revistas.uptc.edu.co/index.php/cenes/article/view/13; https://repositorio.uptc.edu.co/handle/001/11625
• Palabra clave: price fixing; price elasticity of demand; multivariate statistics; cluster analysis; inflation; Laspeyres Index; Fijación de precios; elasticidad al precio de la demanda; estadística multivariada; análisis de conglomerados; inflación; índice tipo Laspeyres; (Price fixing; price elasticity of demand; multivariate statistics; cluster)
• License: http://creativecommons.org/licenses/by-nc-sa/4.0