This research seeks an answer to the following question: what is the relationship between the structure of researchers' communication network and the structure of their collaborative output networks (e.g. co-authored publications, joint grant proposals, and joint patent applications), and the impact of these structures on their citation performance and the volume of collaborative research outputs? Three complementary studies are performed to answer this main question as discussed below. 1. Study I: A frequently used output to measure scientific (or research) collaboration is co-authorship in scholarly publications. Less frequently used are joint grant proposals and patents. Many scholars believe that co-authorship as the sole measure of research collaboration is insufficient because collaboration between researchers might not result in co-authorship. Collaborations involve informal communication (i.e., conversational exchange) between researchers. Using self-reports from 100 tenured/tenure-track faculty in the College of Engineering at the University of South Florida, researchers' networks are constructed from their communication relations and collaborations in three areas: joint publications, joint grant proposals, and joint patents. The data collection: 1) provides a rich data set of both researchers' in-progress and completed collaborative outputs, 2) yields a rating from the researchers on the importance of a tie to them 3) obtains multiple types of ties between researchers allowing for the comparison of their multiple networks. Exponential Random Graph Model (ERGM) results show that the more communication researchers have the more likely they produce collaborative outputs. Furthermore, the impact of four demographic attributes: gender, race, department affiliation, and spatial proximity on collaborative output relations is tested. The results indicate that grant proposals are submitted with mixed gender teams in the college of engineering. Besides, the same race researchers are more likely to publish together. The demographics do not have an additional leverage on joint patents. 2. Study II: Previous research shows that researchers' social network metrics obtained from a collaborative output network (e.g., joint publications or co-authorship network) impact their performance determined by g-index. This study uses a richer dataset to show that a scholar's performance should be considered with respect to position in multiple networks. Previous research using only the network of researchers' joint publications shows that a researcher's distinct connections to other researchers (i.e., degree centrality), a researcher's number of repeated collaborative outputs (i.e., average tie strength), and a researchers' redundant connections to a group of researchers who are themselves well-connected (i.e., efficiency coefficient) has a positive impact on the researchers' performance, while a researcher's tendency to connect with other researchers who are themselves well-connected (i.e., eigenvector centrality) had a negative impact on the researchers' performance. The findings of this study are similar except that eigenvector centrality has a positive impact on the performance of scholars. Moreover, the results demonstrate that a researcher's tendency towards dense local neighborhoods (as measured by the local clustering coefficient) and the researchers' demographic attributes such as gender should also be considered when investigating the impact of the social network metrics on the performance of researchers. 3. Study III: This study investigates to what extent researchers' interactions in the early stage of their collaborative network activities impact the number of collaborative outputs produced (e.g., joint publications, joint grant proposals, and joint patents). Path models using the Partial Least Squares (PLS) method are run to test the extent to which researchers' individual innovativeness, as determined by the specific indicators obtained from their interactions in the early stage of their collaborative network activities, impacts the number of collaborative outputs they produced taking into account the tie strength of a researcher to other conversational partners (TS). Within a college of engineering, it is found that researchers' individual innovativeness positively impacts the volume of their collaborative outputs. It is observed that TS positively impacts researchers' individual innovativeness, whereas TS negatively impacts researchers' volume of collaborative outputs. Furthermore, TS negatively impacts the relationship between researchers' individual innovativeness and the volume of their collaborative outputs, which is consistent with `Strength of Weak Ties' Theory. The results of this study contribute to the literature regarding the transformation of tacit knowledge into explicit knowledge in a university context.

The overall research objective is motivated by two simultaneous developments. On the one hand, due to globalization and fast changing markets, organizations face increasing pressure to stay competitive and to survive in these fast changing environments. To innovate, organizations rely on recruiting and developing their workforce. As the individual is the source of innovation, an ever increasing emphasis is placed upon individual innovativeness and in particular in the investigation of sources of individual innovativeness. Leaders are essential in the promotion of employees´ innovativeness and leadership is proposed as one of the most influential predictors of individual innovativeness. In the view of innovation pressure and demographic changes, it is important for organizations to shed light on their young professionals, especially on their young professionals’ innovativeness, as they are the future workforce. This is especially important for leaders who aim to support the innovativeness of their young professionals. Nevertheless, the importance of young professionals’ innovativeness in the retail industry is still underestimated. Hence, organizations and especially leaders may benefit greatly from being aware of their young professionals’ innovativeness as one possibility to face the challenges of innovation pressure.

The overall research objective is motivated by two simultaneous developments. On the one hand, due to globalization and fast changing markets, organizations face increasing pressure to stay competitive and to survive in these fast changing environments. To innovate, organizations rely on recruiting and developing their workforce. As the individual is the source of innovation, an ever increasing emphasis is placed upon individual innovativeness and in particular in the investigation of sources of individual innovativeness. Leaders are essential in the promotion of employees´ innovativeness and leadership is proposed as one of the most influential predictors of individual innovativeness. In the view of innovation pressure and demographic changes, it is important for organizations to shed light on their young professionals, especially on their young professionals’ innovativeness, as they are the future workforce. This is especially important for leaders who aim to support the innovativeness of their young professionals. Nevertheless, the importance of young professionals’ innovativeness in the retail industry is still underestimated. Hence, organizations and especially leaders may benefit greatly from being aware of their young professionals’ innovativeness as one possibility to face the challenges of innovation pressure.:I Part I: Introduction 1 Motivation and relevance 2 Overall resource-based perspective 3 Research gaps and questions 4 Overall structure of the dissertation II Part II: Foundations 1 Structure of part II 2 Individual innovativeness 3 Leadership supporting individual innovativeness 4 Summary of part II III Part III: Empirical studies 1 & 2 1 Structure of part III 2 Overall research context 3 Overall research design 4 Study 1: Individual innovativeness of yps 5 Study 2: Leadership supporting yps’ innovativeness IV Part IV: Discussion 1 Structure of part IV 2 Discussion of study 1: Individual innovativeness of yps 3 Discussion of study 2: Leadership supporting yps’ 4 Summary of overall empirical findings V Part V: Conclusion 1 Summary of parts 2 Implications for management 3 Limitations and avenues for further research 4 Conclusion References Annexes Annex A: Related to Part II: Individual innovativeness Annex B: Related to Part II: Leadership supporting individual innovativeness Annex C: Related to Part III: Empirical study 1&2