Eyewitness misidentification is the main cause of wrongful convictions, and is mainly due to falsememories and lacking police procedures. False memories can be said to have occurred whenpeople believe they have seen or experienced an event that did not occur or, at least, not in theway they remembered. This is a common problem in witnessing crime. A group of researchers atLund University developed a software implemented algorithm capable to detecting falsememories. This algorithm is intended to be used as the core of a new product, a forensictechnology, which the police can use to minimize eyewitness misidentification.The thesis first describes a generic theoretical framework to analyze a market opportunity for newproduct concepts. When applying this framework to this particular forensic technology, PESTanalysis shows low influence of external factors, although uncertainty is fairly high. Porter's fiveforce analysis suggests that the industry is less attractive due to high buyer's power, a largenumber of competitors and high rivalry. Finally, SWOT analysis shows an equilibrated number ofpositive and negative elements in both internal and external features. Therefore, in order tosuccessfully enter the identified market, some issues must be addressed, such as the need of aviable prototyping process and an understanding of the ethical and public aspects of thetechnology. Two different strategies are proposed for market entry. The first one is a lead-userapproach that seeks early consumer involvement of the, and the second is a cooperation/licensingstrategy with integration of the technology into a pre-existing industry solution

Projecte final de carrera realitzat en col.laboració amb Lunds Universitet