DETERMINANTS OF EFFECTIVE SCIENCE–BUSINESS COOPERATION IN BIOTECHNOLOGY

The purpose of this article is to identify conditions favorable effective cooperation agile companies with institutions scientific in the sector biotechnology.Analysis submitted meaning attributes organizational agility in the context of building permanent Relationship science -business.Design/methodology/approach: Applied approach qualitative in the form of a case study, focusing myself on analysis cooperation PROTEON PHARMACEUTICALS SA with the University of Technology Lodz.The data was collected on on the basis of structured intelligence questionnaire conducted with a representative management enterprise.Findings: Cooperation with the university higher Maybe to be effective provided existence Relationship based on trust, complementarity resources, flexibility operational and common orientation on Implementation innovation.Agility organizational companies it favors initiating and maintaining effective relations with the sector science.Research limitations/implications: Limitation research is his disposable and quality character, based on analysis one case, which limits possibility generalizations results.No triangulation data Maybe to influence on subjectivity conclusions.Practical implications: Conclusions they can constitute basis for design effective models cooperation with universities in the sector biotechnology.Article indicates specific mechanisms and attributes organizational, which They support partnerships scientific and industrial.Social implications: Strengthening Relationship science -business contribute to accelerate transfer knowledge and innovation, increasing employment high qualified Staff and Improvement competitiveness economy based on knowledge.Originality/value: An original theoretical model was developed cooperation agile companies with a university higher, which integrates perspective practical with assumptions theory organizational agility.Article he brings new value for discussion over cooperation science and business in the condition's uncertainty and dynamic changes.