The Use of Cox Regression Model to Analyze the Factors that Influence Consumer Purchase Decision on a Product

Internal (the consumer itself) and external factors influence the consumer to buy a product. It is these factors that can affect the length of time the consumer to buy a product. Time-to-event data analysis is the method to analyze the data when the response of interest is the time until some event occurs. The data to be analyzed is in the form of time, also called failure time or survival time. Cox regression model is a semiparametric regression models that are examining the relationship of independent variables with failure time (survival time). In addition to the estimated regression coefficients obtained, by using the Cox regression model approach, can also be estimated hazard ratio (HR) of two individuals with different covariates. This paper presented an examination of the use of Cox regression models to resolve problems related to consumer purchasing decisions. To clarify the exposure will be used simulated data and bootstrap resampling by using R software, where the response is examined is the time it takes the consumer to decide to buy a product is calculated from the first time consumers know the product, while the independent variables examined were level of education, occupation and monthly income of the consumer. Output program produces estimates of regression coefficients and standard errors of each coefficient. Interpretation of the hazard ratios for two covariates of each independent variable are presented in the discussion.