alexa Modeling choice behavior for new pharmaceutical products.
Diabetes & Endocrinology

Diabetes & Endocrinology

Journal of Obesity & Weight Loss Therapy

Author(s): Bingham MF, Johnson FR, Miller D

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Abstract This paper presents a dynamic generalization of a model often used to aid marketing decisions relating to conventional products. The model uses stated-preference data in a random-utility framework to predict adoption rates for new pharmaceutical products. In addition, this paper employs a Markov model of patient learning in drug selection. While the simple learning rule presented here is only a rough approximation to reality, this model nevertheless systematically incorporates important features including learning and the influence of shifting preferences on market share. Despite its simplifications, the integrated framework of random-utility and product attribute updating presented here is capable of accommodating a variety of pharmaceutical marketing and development problems. This research demonstrates both the strengths of stated-preference market research and some of its shortcomings for pharmaceutical applications. This article was published in Value Health and referenced in Journal of Obesity & Weight Loss Therapy

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