26th International Association for Management of Technology Conference - IAMOT 2017

Innovation Front End is an important topic in Innovation Management, especially when considering Start-up companies where most of the company success is derived from a well developed idea and business plan. Digitalization and digital transformation are fields where Start-ups are very present and have a key role in the innovation processes of many industries. Although a topic with increasing interest, the literature regarding Start-ups is yet scarce and research considering the Fuzzy Front End actives in these companies are even more rare. Fuzzy Front End in large companies is normally composed by three major steps: Idea Generation, Product (Service) definition, Project Evaluation (Kim & Wilemon, 2002). In Start-up Companies, innovation project and company is tied together as almost a single entity. In other hand, big corporations uses mechanisms such Innovation Awards, partnerships and Merger & Acquisition processes to practice the so called Open Innovation (Chesbrough, 2004). This article aims to reduce the scientific gap in this area studying 222 Start-up companies that participate in a Innovation Award promoted by German-Brazilian Commerce Chamber and sponsored by five major German organizations: Bayer, Basf, Siemens, Volkswagen and Club Transatlantico. In this paper, the proposal is to use primary and secondary data sources. The primary data source is the interviews with organizers of the Innovation Award of the Brazil-Germany Chamber of Commerce (AHK) to understand the criteria used in the selection of start-ups to be awarded, the motivations behind the project and The interest of the sponsoring companies in relation to the categories to be awarded that were Sciences of Life, Culture, Cities of the Future, Digitization and Mobility. The secondary data source is the AHK Innovation Award database on the Start-ups platform known as Fundacity.com. Fundacity.com is a platform that has until the present moment more than 72 thousand active users, 42 thousand Start-ups, 1,600 groups of investors in 175 countries. From this universe, we will study the 222 Start-ups that have applied to participate in the AHK Innovation Award. For that two different multivariate data analysis were implemented: Association Analysis and Text Mining. The association analysis is to identify correlation between being well succeeded in the selection process composed by five phases (desclassified, 1st Round, 2nd Round, Finalists, Winners) and five structural factors: comprehension of Problem & Solution, Proposed Innovation & Applied Technology, Market, Business Model and profile of Team & Entrepreneur. The text mining analysis is to identify concepts among the data provided by the Start-up to their evaluators that could improve the chances of being well evaluated in the classification processes. The data gathering and preparation processes are over and the research is ending the phase of data analysis and final discussions. Final results are expected for early January 2017.