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dc.contributor.advisorvon Hellens, Liisa
dc.contributor.authorHalloran, Patricken_US
dc.date.accessioned2018-01-23T02:46:21Z
dc.date.available2018-01-23T02:46:21Z
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/10072/366789
dc.description.abstractWhile software process improvement (SPI) is generally reported to deliver significant benefits and impressive returns, many companies provide evidence of low process maturity, failure to maintain SPI in the longer term and often report severe difficulties in their experience of getting SPI off the ground. Moreover, a number of empirical studies of critical success factors and barriers to success in SPI underline the influence that organisational factors have on SPI success. (Paulish and Carleton, 1994; Paulk and Chrissis, 2000). The introduction of a software process improvement programme is not only akin to introducing organisational change but for SPI implementations to be effective and successful an understanding of the social, organisational and cultural perspectives is required. Although there is a degree of uncertainty as to what organisational learning actually is, and how it occurs, this research explores the efforts of SPI, in relation to the knowledge creation and learning to determine the type of learning that is conducive to continuous improvement. This dissertation explores the premise that knowledge is the most decisive factor in software development and advancement strategies like SPI depend on learning and the creation of new knowledge. On this basis, the SPI-learning phenomenon is better managed through an infrastructure that supports learning at individual and organisational levels. This highlights the need for further understanding of the infrastructure required for individual and organisational learning and management of knowledge that is considered intrinsic to an SPI strategy. This research was undertaken as a longitudinal case study in a small software organisation, to explore the progress of a RAPID software process improvement program. The RAPID model is a modified version of SPICE ISO-15504 that has been designed for use in small organisations. The RAPID data was examined using the OLEC model, which has been developed as part of this dissertation, to explore the types of learning that lead to continuous improvement in the organisation. The OLEC model follows a 3 stage process of identifying where knowledge is situated in the organisation, establishes the constructs and processes of learning and finally, the types of learning that are related to behavioural change in the SPI activities as they are undertaken. The final phase of the OLEC model describes a learning infrastructure that has been formulated as an outcome of this research. This learning infrastructure employs both the individual and organisational dimensions, and situated knowledge processes within the socio-structural and cultural systems of the organisation’s formative context. Mechanisms of authority, power and control; formal goals and objectives; education and training; managerial style and leadership; and rewards and motivation are all considered essential components of the infrastructure. All of these facilitate and build the desired SPI model through an experiential learning process fostered by a communication process of dialogue and collaboration that are enacted and enabled through the individual’s motivations and commitment to learning.en_US
dc.languageEnglishen_US
dc.publisherGriffith Universityen_US
dc.publisher.placeBrisbaneen_US
dc.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.en_US
dc.subject.keywordssoftware process improvementen_US
dc.subject.keywordssoftware qualityen_US
dc.subject.keywordschange managementen_US
dc.subject.keywordsorganisational learningen_US
dc.subject.keywordsknowledge managementen_US
dc.titleAn Infrastructure for Software Process Improvement that facilitates Organisational Learning and Knowledge Management for SME’sen_US
dc.typeGriffith thesisen_US
gro.facultyScience, Environment, Engineering and Technologyen_US
gro.description.notepublicThis theses has had material troughout the text removed for copyright reasons. Chapter 8 parts 8.2, 8.3 and 8.4 plus Appendices have also been removed.en_US
gro.hasfulltextFull Text
dc.contributor.otheradvisorGasston, Jenny
dc.rights.accessRightsPublicen_US
gro.identifier.gurtIDgu1315791744999en_US
gro.identifier.ADTnumberadt-QGU20071112.115137en_US
gro.source.ADTshelfnoADT0en_US
gro.source.GURTshelfnoGURT1377en_US
gro.thesis.degreelevelThesis (PhD Doctorate)en_US
gro.thesis.degreeprogramDoctor of Philosophy (PhD)en_US
gro.departmentSchool of Information and Communication Technologyen_US
gro.griffith.authorHalloran, Patrick J.


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