The purpose of this paper is to provide a model that tests to what extent researchers’ interactions in the early stage of their collaborative network activities affect the number of collaborative outputs (COs) produced (e.g. joint publications, joint grant proposals and joint patents).
Using self-reports from 100 tenured/tenure-track faculty at a US-based university, partial least squares (PLS) path models are run to test the extent to which researchers’ individual innovativeness (Iinnov) affects the number of COs they produced taking into account the tie strength (TS) of a researcher to other conversational partners. Iinnov is determined by the specific indicators obtained from researchers’ interactions in the early stage of their collaborative network activities.
The results indicate that researchers’ Iinnov positively affects the volume of their COs. Furthermore, TS negatively affects the relationship between researchers’ Iinnov and the volume of their COs, which is consistent with the famous “Strength of Weak Ties” theory.
By investigating the degree of impact of researchers’ Iinnov on their CO, college administration could be informed regarding the extent that the social cohesion formed by interpersonal ties affects or drives the collaboration activity that results in COs. When this paper is extended to the entire university, university administration would know the capability of the different colleges, or even the university as a whole, in transforming the ideas embedded in researchers’ networks into a productive work in a collaborative manner.
It is one of the foremost attempts to investigate the relationship between researchers’ Iinnov during ideation phase and their CO. Moreover, this paper contributes to the literature regarding the transformation of tacit knowledge into explicit knowledge at a university context.
Cimenler, O., Reeves, K., Skvoretz, J. and Oztekin, A. (2016), "A causal analytic model to evaluate the impact of researchers’ individual innovativeness on their collaborative outputs", Journal of Modelling in Management, Vol. 11 No. 2, pp. 585-611. https://doi.org/10.1108/JM2-09-2014-0072Download as .RIS
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