Research has explored how embeddedness in small-world networks influences individual and firm outcomes. We show that there remains significant heterogeneity among networks classified as small-world networks. We develop measures of the efficiency of a network, which allow us to refine predictions associated with small-world networks. A network is classified as a small-world network if it exhibits a distance between nodes that is comparable to the distance found in random networks of similar sizeswith ties randomly allocated among nodesin addition to containing dense clusters. To assess how efficient a network is, there are two questions worth asking: (a) What is a compelling random network for baseline levels of distance and clustering? and (b) How proximal should an observed value be to the baseline to be deemed comparable? Our framework tests properties of networks, using simulation, to further classify small-world networks according to their efficiency. Our results suggest that small-world networks exhibit significant variation in efficiency. We explore implications for the field of management and organization.
computational modeling, longitudinal data analysis, quantitative research, sampling, research design
Management Sciences and Quantitative Methods | Strategic Management Policy
Strategy and Organisation
Organizational Research Methods
SAGE Publications (UK and US)
OPSAHL, Tore; VERNET, Antoine; ALNUAIMI, Tufool; and GEORGE, Gerard.
Revisiting the small-world phenomenon: Efficiency variation and classification of small-world networks. (2017). Organizational Research Methods. 20, (1), 149-173. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/5085
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