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Both technological and scientific fields continue to revolutionize in a similar fashion; however, a major difference is that high-tech corporations have found models to continue progressions while still keeping product costs low. The main objective was to identify which, if

Both technological and scientific fields continue to revolutionize in a similar fashion; however, a major difference is that high-tech corporations have found models to continue progressions while still keeping product costs low. The main objective was to identify which, if any, components of certain technological models could be used with the vaccine and pharmaceutical markets to significantly lower their costs. Smartphones and computers were the two main items investigated while the two main items from the scientific standpoint were vaccines and pharmaceuticals. One concept had the ability to conceivably decrease the costs of vaccines and drugs and that was "market competition". If the United States were able to allow competition within the vaccine and drug companies, it would allow for the product prices to be best affected. It would only take a few small companies to generate generic versions of the drugs and decrease the prices. It would force the larger competition to most likely decrease their prices. Furthermore, the PC companies use a cumulative density function (CDF) to effectively divide their price setting in each product cycle. It was predicted that if this CDF model were applied to the vaccine and drug markets, the prices would no longer have to be extreme. The corporations would be able to set the highest price for the wealthiest consumers and then slowly begin to decrease the costs for the middle and lower class. Unfortunately, the problem within the vaccine and pharmaceutical markets was not the lack of innovation or business models. The problem lied with their liberty to choose product costs due to poor U.S. government regulations.
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Details

Title
  • Using Technological Models to Decrease Medical/Scientific Costs
Contributors
Date Created
2016-12
Resource Type
  • Text
  • Machine-readable links