LAUSR

SMEs increasingly participate in collaborative innovation networks (CINs), enabling them to access valuable external knowledge from other actors while maintaining high levels of internal competencies. The SME absorbs this knowledge to achieve reciprocal learning through its contribution to the common CIN goals, and one-way learning to improve its own organization's performance. This knowledge absorption varies according to the SME's context, described with factors such as the turbulence of its external environment, the motivations to contribute to the CIN, or the cognitive distance separating it from the network actors. To better guide this knowledge absorption, this research uses a two-stage mixed method to propose a contextualized operational measure of absorptive capacity (ACAP) for an SME embedded in a CIN. A qualitative phase consisting of semi-structured interviews was implemented first and enabled characterizing the SME's ACAP through a set of practices and dimensions that it could implement. Then a quantitative phase using the partial least squares (PLS) method established a model predicting the absorption dimensions and practices that the SME should master primarily according to its context in the CIN. Hence, this study provides SMEs with an instrument to assess their strengths and weaknesses with regard to ACAP in CINs.