Collaborative distance: Multi-level analysis framework for recommending collaboration structure and safeguards

Douglas C. Derrick, Gina S. Ligon, Erin P. Miles, Leif W. Lundmark, J. S. Elson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We developed a framework that assists in capturing the differences between two organizations. Collaborative distance captures the degree of similarity between the cooperating organizations across four separate levels of analysis: sector, organization, functional, and individual. Organizations that are very similar to each other are said to have “low collaborative distance” and organizations that differ on important characteristics are said to have “high collaborative distance”. We propose that this measure coupled with problem complexity ought to dictate the structure and safeguards for inter-organizational collaboration. We show a sample calculation of this measure.

Original languageEnglish (US)
Title of host publicationProceedings of the 50th Annual Hawaii International Conference on System Sciences, HICSS 2017
EditorsTung X. Bui, Ralph Sprague
PublisherIEEE Computer Society
Pages678-686
Number of pages9
ISBN (Electronic)9780998133102
StatePublished - 2017
Event50th Annual Hawaii International Conference on System Sciences, HICSS 2017 - Big Island, United States
Duration: Jan 3 2017Jan 7 2017

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2017-January
ISSN (Print)1530-1605

Conference

Conference50th Annual Hawaii International Conference on System Sciences, HICSS 2017
Country/TerritoryUnited States
CityBig Island
Period1/3/171/7/17

ASJC Scopus subject areas

  • General Engineering

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