| Título: | Discrete choice modelling in conjoint analysis |
| Autores: | Lukban, Albert. |
| Fecha: | 1997 |
| Publicador: | McGill University - MCGILL |
| Fuente: |
 |
| Tipo: | Electronic Thesis or Dissertation |
| Tema: | Statistics. |
| Descripción: |
Strategic planning is not only necessary in today's global economy where markets are becoming more susceptible to international competition, it is vital. The foresight of market reactions can lead to a competitive advantage. Market share losses can be minimized (and market share gains maximized) with the knowledge obtained from primary marketing research involving a stated preference study to examine consumer behaviour. Before launching a new product or providing a service, discrete choice analysis can empower strategic planners, managers and marketers with a tool which aids in optimizing products and services for a potential market with the end of maximizing sales and services. Discrete choice analysis is a tool to understand human choice behaviour. It is employed for statistical inference on a model of choice behaviour from data obtained by sampling from a population of decision makers. This thesis gives an overview of the basic concepts of conjoint analysis which addresses discrete choice analysis for strategic product and service planning. The statistical model specification, the multinomial logit, is derived assuming that decision makers follow a choice rule called utility maximization, where these random utilities are Gumbel distributed. The model is applied to a stated preference study in which environmentally friendly vehicles are presented as possible vehicle choices. |
| Idioma: | en |
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