CHOOSING ACCURATELY: COMPETITIVE INTELLIGENCE ON PROSPECTING PARTNERS FOR TECHNOLOGICAL COOPERATION

• Main Author: Quadros, Ruy
• Publication Date: 2014
• Other Authors: Santos, Glicia Vieira dos, Consoni, Flávia, Quintão, Rubia
• Format: Article
• Language: eng
• Source: Revista de Administração e Inovação
• Download full: https://www.revistas.usp.br/rai/article/view/100226
• topic: Mapping out technological capabilities; Snowball sampling; External sources of innovation management; Strategic search of external partners; Technological cooperation

The paper discusses the results of a project aimed at developing and testing a methodology for the identification, qualification and classification of capabilities of Brazilian research groups (RGs) in technologies applicable to the automotive industry. The project was commissioned by the major R&D centre of a multinational corporation in the business of car manufacturing. The point of departure is the literature pointing out the need for firms to manage systematically rather than empirically their external sources of innovation. Regarding routines for prospecting and qualifying external R&D (Research and Development) partners, an important function in managing external sources, the paper introduces the concept of strategic search (competitive intelligence). The contribution of this paper is proposition of a new use for the methodology snowball sampling. Snowball sampling was originally used to map risk groups (“hidden populations” usually belonging to both social extremes: the deprived and the elites), ie carriers of the AIDS (SIDA) virus, drug addicts, chemical dependents, etc. The major steps of the methodology developed and tested by the authors are described. Such methodology is presented as a tool for strategic search. The result of the implementation of the methodology is a database with quantitative and qualitative information on Brazilian technological competencies applicable to the automotive industry in the technological areas of Materials, Powertrains and Fuels, Manufacturing Technologies, On-board Electronics and Ergonomics. The databank comprises 265 research groups in various science and engineering disciplines. And some of its aggregate results are presented and illustrated.