A contingency view of transferring and adapting best practices within online communities

Haiyi Zhu, Robert E. Kraut, Aniket Kittur

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

2 Scopus citations

Abstract

Online communities, much like companies in the business world, often need to transfer "best practices" internally from one unit to another to improve their performance. Organizational scholars disagree about how much a recipient unit should modify a best practice when incorporating it. Some evidence indicates that modifying a practice that has been successful in one environment will introduce problems, undercut its effectiveness and harm the performance of the recipient unit. Other evidence, though, suggests that recipients need to adapt the practice to fit their local environment. The current research introduces a contingency perspective on practice transfer, holding that the value of modifications depends on when they are introduced and who introduces them. Empirical research on the transfer of a quality-improvement practice between projects within Wikipedia shows that modifications are more helpful if they are introduced after the receiving project has had experience with the imported practice. Furthermore, modifications are more effective if they are introduced by members who have experience in a variety of other projects.

Original languageEnglish (US)
Title of host publicationProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
PublisherAssociation for Computing Machinery
Pages729-743
Number of pages15
ISBN (Electronic)9781450335928
DOIs
StatePublished - Feb 27 2016
Event19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016 - San Francisco, United States
Duration: Feb 27 2016Mar 2 2016

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW
Volume27

Other

Other19th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2016
Country/TerritoryUnited States
CitySan Francisco
Period2/27/163/2/16

Bibliographical note

Funding Information:
We thank Yochai Benkler, Yuqing Ren, Jason Hong, and the members of the GroupLens at University of Minnesota for helpful feedback. We also thank Doug Phillips and Jacob Thebault-Spieker for editing help. This research was supported by NSF grants IIS-1111166, IIS-1217559, IIS- 0968484, IIS-1111124 and IIS-1149797, Google Faculty Awards, Google Social Interactions program, and Facebook PhD Fellowship.

Keywords

  • Best practice adaptation
  • Contingency view
  • Practice modification
  • Propensity score matching (PSM)

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