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Networks and Networking

AbstractSuppose we are given a network G=(V,E) with arc distances and a linear cost function for lengthening arcs. In this note, we consider a network‐interdiction problem in which the shortest path from source node s to sink node t is to be increased to at least τ units via a least‐cost investment strategy. This problem is shown to reduce to a simple minimum‐cost‐flow problem. Applications and generalizations are discussed, including the multiple‐destination case.

This article sets out to reinforce andfurther develop an emerging paradigm: social network analysis, which represents social structure in terms of relationships (ties) between social objects. Not all the social objects are directly linked, and objects may be connected by multiple relationships of affect, influence, information, or goods and services. Network analysis deals with the types and patterns of relationships, and the causes and consequences of these patterns. The article applies the paradigm to the study of organizational structure by both developing theoretical constructs and presenting methodology for carrying out social network analysis in organizations. An analysis of three organizations from the Aston Study is presented using social network analysis to test propositions about differences between mechanistic and organic structures.

ARTICLE SEEKS TO DISCOVER WHAT NETWORK NEWS HAS BEEN SAYING ABOUT THE LEGISLATIVE BRANCH GENERALLY. DATA WERE ISOLATED FROM PRINTED ABSTRACTS PROVIDED BY VANDERBILT UNIVERSITY TELEVISION NEWS ARCHIVE FOR FIVE WEEKS IN EARLY 1976. FINDINGS INCLUDE: GREATER COVERAGE IS PROVIDED THE SENATE; THE MOST FREQUENT TYPE OF COVERAGE INVOLVES "COMMITTEE ACTION", AND ALL COVERAGE WAS "NEGATIVE".

This research examines and compares patterns of coordination among clusters of organizations which are all members of a larger network of human service agencies. The blockmodeling procedure developed by Breiger et al. was used to analyze the data collected, and three tightly connected clusters of agencies werefound to exist in the network. By evaluating the reasons why organizations reported being involved with others, it was found that the three interorganizational clusters existed for three predominantly different reasons: resource transactions, direct services, and planning and coordination. The three clusters were then compared on a number of dimensions of interorganizational coordination, and it was found there were significantly different patterns of relationships among these clusters of agencies while no significant differences among the clusters were found on perceived effectiveness and the degree of impact of the relationships. A theoretical explanation for the observed results is developed. The major conclusion is that it is important to determine the different reasons for interorganizational relationships if one is to understand the various patterns of coordination among clusters of organizations within interorganizational networks.