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dc.contributor.advisorBreivik, Einar
dc.contributor.authorMüller, Marco
dc.date.accessioned2020-01-31T13:09:56Z
dc.date.available2020-01-31T13:09:56Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/11250/2639078
dc.description.abstractPharmaceutical companies today are under great pressure to successfully launch new specialty drugs, high-tech products for small patient populations with cost intensive R&D and complex mechanisms of effect. At the same time, increasing privacy regulation limits the availability of data for market research in the medical markets, forcing pharmaceutical companies to find ways of creating transparency. Researchers can draw from a large, yet disperse body of literature investigating the factors that favour early adoption of a drug. The thesis introduces Roger’s Diffusion of Innovation framework to organize literature on factors that speed up new product adoption among physicians. The framework is expanded to suit the pharmaceutical markets, especially to differentiate between fixed variables and such that are subject to change during an adoption process. Afterwards different approaches to quantitative diffusion modelling are introduced with an exemplary paper each. The different levels of modelling, from macro-level (national sales) down to micro-level (individual behaviour) are explained. Subsequently, the limitations through German privacy regulation as well as through market specific features on data availability for pharmaceutical market research are presented. A comparison between quantitative diffusion models on different levels with the current privacy regulation shows which analysis approaches might still be feasible. Based on the prior analysis, a quantitative model for drug adoption in the German pharmaceutical market is developed, using Multiple Regression Analysis as the statistical tool. It is found that under some conditions, a very simple two-variable model using the salesforce visits’ and their assessment of a doctor’s adoption behaviour can explain more than 40% of the variance in sales between hospitals. Limited availability of independent data causes the model to be largely influenced through the sales force’s agenda in reporting. Although this data is naturally biased, it seems unlikely that data availability from independent sources will improve in the future. Pharmaceutical companies will need to further utilize their sales force to collaborate with physicians and adapt their incentive systems to live up to the new requirements.nb_NO
dc.language.isoengnb_NO
dc.subjectstrategy and managementnb_NO
dc.titleMarket entry in the German pharmaceutical market : a framework for business intelligence measuresnb_NO
dc.typeMaster thesisnb_NO
dc.description.localcodenhhmasnb_NO


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