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Developing a model for competitive advantage through integration of data mining within a strategic knowledge management framework: A deep case study of a global mining and manufacturing company

Moayer, Sanaz (2016) Developing a model for competitive advantage through integration of data mining within a strategic knowledge management framework: A deep case study of a global mining and manufacturing company. PhD thesis, Murdoch University.

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Abstract

The study explores the benefits, limitations and opportunities arising from the application of an integrated (hard and soft systems) Knowledge Management (KM) model within a global mining and manufacturing company. It employs a mixed method (interview and survey approach) to explore related Knowledge Management (KM), Organisational Learning (OL), and Data Mining (DM) processes (as a proxy for broader data management tools and practices). It employs the Resource Based View (RBV) and Knowledge Based View (KBV) of strategy to explore how the case company has built unique human knowledge capability based on a Continuous Improvement (CI) culture supported by Global Virtual Teams (GVTs) and Communities of Best Practice (CoBP). It is argued and statistically proven that this unique capability has supported the Competitive Advantage and possibly survival of the case company during a period of challenging market conditions.

The study also explores to role of Data Mining and related Business Intelligence (BI) and ICT platforms to leverage knowledge embedded across the firm’s global networks. By exploring the gaps and synergies between hard (technological) and soft (human) systems, this deep case study of a multinational, mining, processing, and manufacturing firm addresses one of some of the key questions still to be resolved in organisational and information system studies.

These questions are examined through detailed interviews with ten senior managers and their reports, (115 survey respondents, identifying as technical specialists, departmental and operational managers/ senior supervisors, working in nine1 operations across five continents). The practices spanning the global operations of the case organisation are compared with a conceptual model of Strategic Knowledge Management (SKM) and Resource based Competitive Advantage (RCA) derived from the relevant academic literature. The study aims to contribute to the body of knowledge exploring tacit and explicit knowledge, Organisational Learning (OL), and Data Mining (management) practices as a strategic resource and basis for competitive advantage. It also aims to inform current knowledge and data management practices employed by Global Virtual Teams (GVT) and Communities of Best Practice (CoBP) spanning the case organisation’s mining, refining and manufacturing operations.

The study uses NVivo to analyse the qualitative data on the relationships between KM practices in the case organisation (involving knowledge creation; knowledge storage; knowledge transfer; and knowledge application), Data Mining processes, (extracting, transforming, and loading transaction data; storing and managing data; providing access; analysing and presenting) and the sustainable competitive advantage for the case organisation. The relationships identified in Stage 1 qualitative findings are supported by the Stage 2 survey results based on the PLS structural equation modelling (SEM) analysis.

The empirical evidence generated from the mixed method approach indicates that KM practices positively affected Data Mining processes in the case organisation and that soft KM systems and practices focused on the creation, configuration, and practical application of tacit knowledge were crucial to the organisation’s Competitive Advantage (CA).

The Competitive Advantage (CA) impact of these soft system elements far outweighed hard systems despite the technical production orientation of the business. The company’s current Data Mining activities did not have a significant mediating effect on the relationship between Knowledge Management and the organisation’s Competitive Advantage. These results suggest that the Data Mining systems (as an important part of the organisation’s hard KM systems) have not been effectively integrated with the soft knowledge creation, transfer and application systems in the organisation. This is highlighted in the study implications as a major opportunity for the case organisation which faced with lean market conditions over the past decade has been very successful in generating and applying a scalable, portfolio of useful knowledge via Global Virtual Teams. Based on these findings, the study concludes with recommendations on how hard knowledge and data management systems can augment the value of the soft KM practices, and generate Competitive Advantage for global mining and manufacturing companies in the knowledge age.

Publication Type: Thesis (PhD)
Murdoch Affiliation: School Of Business and Governance
Supervisor: Gardner, Scott and Huang, Amy
URI: http://researchrepository.murdoch.edu.au/id/eprint/34754
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