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The systematic improvement of advice given by public sector call centres

The persistent demand for increased accountability and value for money in the public sector from both the public and governments raises the issue of quality of service in advice-giving by governmental agencies. The goal of this study is to develop a model to validate frameworks able to contribute to improved advice-giving through the application of knowledge management principles. Zack's (2001) Four Knowledge Problem Model, Brogowicz, Delene, and Lyth's (1990) Synthesised Service Quality Model, and Markus's (2001) Theory of Knowledge Reuse are used to examine knowledge strategies in advice-giving through the application of a case study methodology. Two Queensland public-sector call centres are investigated. This study confirms that although the studied call centres operate under differing business drivers, agents have developed strategies generally consistent with those suggested by Zack (2001) to deal with uncertain, complex, and ambiguous problem types. No equivocal problems were encountered in the study. The solution of the former problem pair of uncertainty and complexity relies on knowledge that is codified and stored in databases, while the latter equivocality and ambiguity, seeks out experts who apply both technical and functional knowledge to the problem resolution. Roles performed by call-centre agents predominantly align with those described by Markus (2001), with the opportunity to enhance performance through contribution by shared-work producers to knowledge repositories. The problem-solving strategies employed by agents and the technical capabilities of the call centres combine to deliver a level of service quality which, although meeting client expectations, has been able to be improved through the application of knowledge strategies targeting efficient problem resolution through knowledge reuse.

Identiferoai:union.ndltd.org:ADTP/265271
Date January 2006
CreatorsSchefe, Neville Lindsay
PublisherQueensland University of Technology
Source SetsAustraliasian Digital Theses Program
Detected LanguageEnglish
RightsCopyright Neville Lindsay Schefe

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