• Conference
  • Learning and Innovating

Conférence : Communications par affiche dans un congrès international ou national

For SMEs, it is difficult to access to the resources needed for innovation. Also, developing collaboration between SMEs and various entities has become indispensable for SMEs. The concept of open innovation emphasizes the importance of resources from inside and outside the firm boundaries in the aim to capture and create value (Chesbrough, 2006). However, OI is not a universal character and must be adapted to the SME’s profile. In this work, we propose to identify factors that affect the OI adoption capacity in SMEs.
OI consists of three different processes: outside-in, inside-out and coupled-process (Gassmann & Enkel, 2004) for capturing assets in external entities and for bringing its knowledge and technologies to its external environment. Each process corresponds to an OI strategy and uses different skills, also the three models have not the same relevance for enterprises (Gassmann & Enkel, 2004). Implementing OI within a structure imply significant impacts on the organization itself and on its management (Dodgson, Gann, & Salter, 2006). Internal structure of enterprise impacts its ability to collaborate and exchange information with external entities (Argote & Miron-Spektor, 2011). Therefore, some organizational models are more favorable to open innovation processes than others are.
When a structure has decided to develop a new approach for innovation, the implementation of the change requires an experimental field where best adapted solutions need to be identified regards to the enterprise characteristics (Lewin, 1947). The goal of our work is to propose an adoption model of OI for SMEs. The first step is to collect data from 112 selected scientific papers for identifying main indicators that impact, positively or negatively, the OI adoption by SMEs. During this step, each paper was reviewed and analyzed to extract the factors related to the OI adoption. This step allowed us to identify 143 factors. These factors were analyzed in order to detect redundancy (eg.: identify whether there are synonyms or similarities). The second step was the classification of the selected factors according to: the same theme, occurrence, etc. During this phase we regroup all factors in 51 adoption indicators related to 4 groups (Knowledge, Strategy, Environment and Organization). Finally, in the last step we used characteristics of SMEs and research results to give signs to indicators (positive / negative impact).
The adoption model obtained will be used as a tool for SMEs OI adoption evaluation. We envisage validating the model through a questionnaire where each question will be the translation of each indicator.