Primary Outcomes (explanation)
Experience with network brokerage is a complex concept. Therefore, we will measure both its structural and behavioural dimensions.
As far as the structural aspects are concerned, we will sample subjects' ego networks in different social settings. Based on previous research and taking into account that the subjects are university students, we will ask them to provide the names of no more than five people important to them in the areas of family, friendships made before university, friendships made during university, work, roommates, and members of various associations (e.g., cultural, political, musical, sports), people they have common hobbies with and finally we leave them with the option of naming at most 5 other important people who were not addressed in the previous social settings. We will also ask about their alter-alter ties i.e., possible connections between nominees.
Regarding the behavioral aspects of brokerage, we will ask them to answer a 16-item questionnaire, 12 of which derived from previous research (Obstfeld, D. 2005. Social networks, the tertius iungens orientation, and involvement in innovation. Administrative Science Quarterly, 50: 100–130; Grosser, T. J., Obstfeld, D., Labianca, G., & Borgatti, S. 2019. Measuring mediation and separation brokerage orientations: A further step toward studying the social network brokerage process. Academy of Management Discoveries, 5(2): 114-136). Specifically, we aim to capture whether individuals report high or low scores on behaviors typically associated with network brokerage.
We will follow different strategies to analyze these data. Regarding network data, we will compute and use both triadic and community-level measures of brokerage (i.e., Burt 1992 metrics and community detection algorithms as in Bianchi et al., 2023, Structure of personal networks and cognitive abilities: A study on a sample of Italian older adult, Social Networks).
Concerning the behavioral aspects of brokerage, we will perform a cluster analysis of responses, to identify common factors and build indeces out of them.
We plan to conduct parallel regression with the structural and behavioral measures (in their different operationalizations, for the purpose of conducting robustness checks).
Nevertheless, we plan to show the correlation among structural and behavioral measures.