Knowledge Transfer Performance of Industry-University-Research Institute Collaboration in China: The Moderating Effect of Partner Difference

How to realize the sustainable development of the industry-university-research institute (IUR) collaboration innovation ecosystem has become a key factor restricting the independent innovation capability of Chinese enterprises. Knowledge transfer performance is a key consideration in the process of R&D collaboration between companies and research institutes; how to improve the performance of knowledge transfer depends on the matching between the partners of IUR collaboration. This article seeks to explore the influence mechanism of partner differences in the industry-university-research institute collaboration on the performance of knowledge transfer from the perspective of enterprises. Specifically, the study explores the moderating effect of technical knowledge difference and goal difference on the relationship between absorptive capacity, learning willingness, and knowledge transfer performance. The study applied the partial least squares structural equation modeling approach to model these relationships, based on survey data gathered from 211 Chinese firms. The results show that the goal difference of industry-university-research institute collaboration partners has a negative moderating effect on the relationship between learning willingness, absorptive capacity, and knowledge transfer performance. The greater the degree of goal difference, the lower the role of the enterprise’s learning willingness and absorptive capacity to promote knowledge transfer performance. Technical knowledge difference has a significant inverted U-shaped effect on the relationship between absorptive capacity and knowledge transfer performance: a high degree of technical knowledge difference weakens the effects of absorptive capacity on knowledge transfer performance, while a low degree of technical knowledge difference will also negatively moderate the effects of absorptive capacity on knowledge transfer performance. The research conclusions provide scientists, government bodies, and decision makers with the necessary information for a better understanding of the effective mechanism of sustainable knowledge transfer in the IUR innovation ecosystem.

MEASURING THE KNOWLEDGE TRANSFER PERFORMANCE AT UNIVERSITIES

Measuring the universities' knowledge transfer performance is important for both policymakers and universities due to the recognized social and economic impact of the knowledge transfer process. The aim of this paper is to investigate and discuss the contemporary knowledge transfer metrics used for measuring the knowledge transfer activities at universities. The research results show that the universities need to consider several important aspects when selecting and reporting on their knowledge transfer activities, such as the purpose and continuity of data collection and reporting on knowledge transfer activities, internal and external context in which universities operate, and implementation of common definitions for knowledge transfer indicators. Additional aspects identified from the conducted research which are important for the overall assessment of the universities’ knowledge transfer performances are the collection of both quantitative and qualitative data on knowledge transfer activities, and harmonization of the knowledge transfer metrics that will enable the universities to measure and compare their knowledge transfer activities, nationally and internationally.

Examining the Effects of a Pedagogical Agent With Dual-Channel Emotional Cues on Learner Emotions, Cognitive Load, and Knowledge Transfer Performance

Despite the continuous emphasis on emotion in multimedia learning, it was still unclear how pedagogical agent emotional cues might affect learning. In the present study, a between-subjects experiment was performed to examine the effects of a pedagogical agent with dual-channel emotional cues on learners' emotions, cognitive load, and knowledge transfer performance. Participants from a central Chinese university (age mean = 21.26, N = 66) were randomly divided into three groups. These groups received instructions from an affective pedagogical agent, a neutral pedagogical agent, or a neutral voice narration without pedagogical agent embodiment. Results showed that learners assigned the affective pedagogical agent reported a significantly higher emotional level than learners assigned the neutral pedagogical agent. Learners’ perceived task difficulty was not significantly different among groups while instructional efficiency was significantly higher for learners with the affective pedagogical agent. Moreover, learners assigned to the affective pedagogical agent performed significantly better on the knowledge transfer test than those assigned the neutral pedagogical agent or the neutral voice.