Clustering Algorithm for Travel Distance Analysis

Zeņina, Nadežda; Borisov, Arkady

doi:10.2478/itms-2013-0013

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…HCA treats each variable as a distinct unit and then iteratively merges pairs of clusters, a process depicted in a dendrogram in the . I determined the number of clusters to retain for analysis by visually inspecting the dendrogram as well as calculating the Calinski and Harabasz (1974) pseudo‐F index and the Duda–Hart index (Duda, Hart, and Stork, 2001) index, both of which describe between‐ versus within‐cluster variance or distance (see Zenina & Borisov, 2013).…”

Section: Methodsmentioning

confidence: 99%

Does Entrepreneurship Work? Understanding What Policy Entrepreneurs Do and Whether It Matters

Arnold¹

2020

Policy Studies Journal

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When a major policy change occurs, policy entrepreneurs—advocates who devote substantial time, energy, and resources to campaigning for a specific policy outcome—are often credited as critical influences. However, there has been a little quantitative, large‐n cross‐sectional study of whether policy entrepreneurship effectuates policy change, how policy entrepreneurs pursue their goals, and whether particular entrepreneur attributes are more or less facilitative to that end. This paper aims to fill that gap by investigating policy entrepreneurship in municipalities across the State of New York, where between 2008 and 2012 hundreds of local jurisdictions passed policies to ban or restrict high‐volume hydraulic fracturing (fracking), often encouraged by anti‐fracking advocates. It demonstrates that policy entrepreneurs have a consequential, positive impact on policy adoption; that their characteristics, strategies, and goals classify into distinct archetypes; and that archetypes vary in their policy impact.

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Section: Methodsmentioning

confidence: 99%