• norsk
    • English
  • English 
    • norsk
    • English
  • Login
View Item 
  •   Home
  • Norges Handelshøyskole
  • Thesis
  • Master Thesis
  • View Item
  •   Home
  • Norges Handelshøyskole
  • Thesis
  • Master Thesis
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Market entry in the German pharmaceutical market : a framework for business intelligence measures

Müller, Marco
Master thesis
Thumbnail
View/Open
masterthesis.pdf (3.355Mb)
URI
http://hdl.handle.net/11250/2639078
Date
2018
Metadata
Show full item record
Collections
  • Master Thesis [4657]
Abstract
Pharmaceutical 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.

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit
 

 

Browse

ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDocument TypesJournalsThis CollectionBy Issue DateAuthorsTitlesSubjectsDocument TypesJournals

My Account

Login

Statistics

View Usage Statistics

Contact Us | Send Feedback

Privacy policy
DSpace software copyright © 2002-2019  DuraSpace

Service from  Unit