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dc.contributor.authorBaddoo, N.
dc.contributor.authorHall, T.
dc.date.accessioned2010-02-18T14:00:38Z
dc.date.available2010-02-18T14:00:38Z
dc.date.issued2002
dc.identifier.citationBaddoo , N & Hall , T 2002 , ' Software Process Improvement Motivators : An Analysis using Multidimensional Scaling ' , Empirical Software Engineering , vol. 7 , no. 2 , pp. 93-114 . https://doi.org/10.1023/A:1015203013834
dc.identifier.issn1382-3256
dc.identifier.otherPURE: 98131
dc.identifier.otherPURE UUID: 704aeeec-22cd-4e8d-af9b-9c6264a1507f
dc.identifier.otherdspace: 2299/4297
dc.identifier.otherScopus: 0036605809
dc.identifier.urihttp://hdl.handle.net/2299/4297
dc.description“The original publication is available at: www.springerlink.com ”. Copyright Springer. DOI: 10.1023/A:1015203013834 [Full text of this article is not available in the UHRA]
dc.description.abstractIn this paper we present an analysis of software practitioners' motivations for software process improvement (SPI). Our findings are based on an empirical study of SPI in 13 software companies where we conducted focus groups with nearly 200 software practitioners. Our aim is to better understand how companies can maximise practitioner support for SPI. This insight should help SPI managers establish more effective SPI implementation strategies. In this paper we introduce the use of multidimensional scaling (MDS) in SPI research. MDS is a social science data analysis technique designed to generate a rich visual understanding of human issues. By using MDS we found evidence to suggest distinct clusters of punitive and rewarding SPI motivators. Furthermore our analysis also suggests that different clusters of motivations exist for different staff groups.en
dc.language.isoeng
dc.relation.ispartofEmpirical Software Engineering
dc.titleSoftware Process Improvement Motivators : An Analysis using Multidimensional Scalingen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionScience & Technology Research Institute
dc.description.statusPeer reviewed
rioxxterms.versionofrecordhttps://doi.org/10.1023/A:1015203013834
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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