PhD Graduate Guang Ying Mo, in collaboration with Tsahi Hayat, published an article in American Behavioral Scientist that analyzes how social and network structures affect the giving and receiving of advice among researchers. The authors find that network size correlates the most with advice giving and receiving.
Guang Ying Mo obtained her PhD in Sociology from the University of Toronto in 2015. She is currently a postdoctoral fellow at the Ontario Telemedicine Network. Her research focuses on social networks and innovation.
We have posted the citation and the abstract of the article below. The full text is available through the University of Toronto Library Portal here.
Hayat, Tsahi and Guang Ying Mo. 2015. “Advice Giving and Receiving Within a Research Network.” American Behavioral Scientist, 59(5):582-598.
One of the central components of research-related networked work is the exchange of advice through which researchers are expected to share useful information, especially critical information that others might not possess. A key enabler for advice exchange is the minimizing of structural constraints in the organizations. In this study, we wish to gain a better understanding of how structural constraints, in the form of social and network structure, interplay with advice exchange. Our study’s focal point is the Graphics, Animation, and New Media (GRAND) network, a national research organization in Canada. By conducting a social network survey (N = 101), we were able to study advice giving and receiving among GRAND members. Our findings indicate that the centrality of researchers in the communication network positively correlates with both advice giving and receiving. However, the effective network size of communication networks more strongly correlates with advice giving and receiving, especially for the researchers who hold higher hierarchical positions in GRAND. Overall, our findings indicate that both the communication network and the hierarchical structure are strongly correlated with advice giving and receiving. Furthermore, by looking at the combined correlation between social and network structures with advice exchange, we can offer a better understanding of researchers’ interactions. Our findings are then discussed within the context of their potential implications for other studies on the topic of research collaboration.
Read the full article here.