An Empirical Analysis of Strategies and Efficiencies in Social Networks
University of Michigan at Ann Arbor - School of Information
Marshall W. Van Alstyne
Boston University - Department of Management Information Systems; Massachusetts Institute of Technology (MIT) - Sloan School
February 1, 2006
Boston U. School of Management Research Paper No. 2010-29
MIT Sloan Research Paper No. 4682-08
This research examines hypotheses about the efficient and strategic uses of social networks by a specific group of white collar workers. We examine existing theory that relates network structure to performance and put forward two new hypotheses. The first addition merges explore/exploit theory with social networks, proposing that optimal network characteristics evolve over the course of a career from those favoring exploration to those favoring exploitation of knowledge and relationships. The second concerns efficient movement of information through a network, proposing that frequent short communication outperforms infrequent lengthy communication. Using a unique data set containing email patterns and accounting records for several dozen executive recruiters, we find statistically significant differences related to network (1) structure (2) flow and (3) age. Consistent with existing theory, more central position is associated with higher output. Consistent with the two proposed theories, exploration strategies among early career recruiters and exploitation strategies among senior recruiters are both positively associated with performance, while more frequent shorter messages are associated with higher output. Results of this research have the potential to create a more complete understanding of different types of efficiency associated with social networks.
Number of Pages in PDF File: 40
Keywords: social networks, email, productivityworking papers series
Date posted: September 20, 2010 ; Last revised: March 27, 2012
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo4 in 0.297 seconds