Analysis of the Dynamical Capabilities into the Public Research Institutes to Their Strategic Decision-Making

Abstract

Academy–industry collaborations (AICs) play a crucial role in the creation of new knowledge, by transferring this knowledge to the society and bringing into line theory and practice. Although in the state-of-the-art exists a number of efforts to analyze different factors that influence these collaborations, little attention has been paid in the application of dynamic capabilities (DCs) as an emerging tool to identify strategic elements in public research institutes (PRIs). Aiming to fill this literature gap, in this study, DCs methodology was applied to the Mexican PRI in order to classify the research activities into these strategies. A second stage was carried out to determine the influence of each DC in the global productivity and knowledge integration or transfer. The relationship between the variables was statistically analyzed using one-way analysis of variance (ANOVA) and Pearson’s correlation coefficient. The main findings of this study showed that sensing and reconfiguration capabilities have a direct interaction on the global productivity and knowledge integration or transfer of the Mexican PRI, whereas the seizing capabilities present a weak impact on these items. The proper application of the DCs framework, as a substantial instrument for the PRI, opens up an alternative to identify that the main activities should receive special attention during the strategic planning process. These strategies can improve academy–industry collaborations by promoting the process of global knowledge and technology development.

Spatio-Temporal Evolution and Development Path of Industry–University–Research Cooperation and Economic Vulnerability: Evidence from China’s Yangtze River Economic Belt

“…The results of knowledge creation directly affect the quality of knowledge interaction content and, thus, the application and development of knowledge by enterprises. This, in turn, relies on the practical testing and application effects that industries can provide as a basis and platform for the transformation of the knowledge achievements of universities and scientific research institutions, thus improving the efficiency of research and development (R&D) [66]. Erling Li et al [11] conducted a study on government-industry-universityresearch networks and argued that science, education, and investment are the determinants of agricultural innovation in China.…”