NEIGHBORHOODS: A TACIT SOCIAL STRUCTURE CONNECTING INDIVIDUALS AND ORGANIZATIONS

Abstract

We propose and inductively explore neighborhoods, a tacit social structure connecting individuals and organizations. Neighborhoods are clusters of individuals’ organizational reference groups, in which the people each individual knows are demographically-similar to the people other individuals know. Because of their internal similarity, neighborhoods circumscribe the social information individuals receive and thus plausibly generate shared perceptions and meaning. Using latent class cluster analysis on data from a large organization, we induce five neighborhoods. While individuals’ own attributes are related to those of others in their neighborhood, their attributes frequently differ from those in their neighborhood. Neighborhoods discriminate between individuals’ career-related perceptions and social network attributes.