A comparison of logarithmic goal programming and conjoint analysis to generate priority point vectors: an experimental approach

The utility of a service or product can be considered as an aggregation of utilities of multiple attributes, that the consumers consider while choosing a product. The two methods used to generate a linear utility function are the logarithmic goal programming model (LGPM) and the conjoint analysis method (CAM). In these two methodologies, the procedures used to collect data and generate the utility function differ significantly. This is possibly the first study to compare the two methods for determining the utility function of a product (here vehicle insurance policy). For this study we will be collecting the data from the same set of respondents (customers) for the same set of five different brands of the product (vehicle insurance policy) available in the market. The similarities and differences among LGPM and CAM approaches are examined to provide useful insights in terms of consistency in consumer behaviour while prioritizing their choices for a product. The study addresses if the priority order of consumer choices for a product remains the same or changes if the methodology changes. Moreover, we apply a multinomial logit choice model to derive a choice probability of the brands available in the market using both approaches.