The Electronic Journal of Knowledge Management publishes original articles on topics relevant to studying, implementing, measuring and managing knowledge management and intellectual capital.

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Journal Article

Toward a Deeper Understanding of Competitive Knowledge Assets  pp79-88

Scott Erickson, Helen N. Rothberg

© Apr 2019 Volume 17 Issue 1, Editor: Ettore Bolisani, pp1 - 99

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Knowledge management (KM) is founded on an underlying assumption that better management of knowledge assets will lead to more competitive success, including better financial performance. Demonstrating that relationship has always been a core concern of the discipline. KM scholarship has demonstrated that differences exist in knowledge assets, requiring different approaches for successfully exploiting them. With the growth of use of other intangibles such as big data systems and business analytics/intelligence, the strategic choices have become even more complex. Everything from expensive information technology‑based KM systems to communities of practice, from data monitoring to predictive analytics might be appropriate in a given scenario. Metrics have developed to assess these different competitive situations, giving us a general idea of the levels of data, explicit knowledge, tacit knowledge, and intelligence in any given industry. The methodology and results have been extensively covered in other work and so will not be repeated here. But this paper starts from those established quantitative metrics. Thus, we know that industries such as pharmaceuticals require competence in managing all intangibles. Others, such as financial services, seem to develop very little knowledge even though big data and intelligence levels are very high. Alternatively, branded consumer goods often have high levels of knowledge but little intelligence. We can speculate on where particularly high intangible asset development, specifically in which particular areas (e.g. operations, marketing relationships, R&D). What we don’t have is empirical evidence to back up such speculation. If the key competitive requirement, leading to better financial performance, is highly developed knowledge in operations, can we provide some data to support that conclusion? This paper will explore some additional metrics (key personnel, brand equity, social media sentiment), seeking to add to our more specific explanations about how and where intangibles matter. The point is to develop some more precise, more objective metrics allowing a deeper look inside organizations. If so, we can gain a better understanding how intangible assets, especially knowledge, contribute to competitiveness.


Keywords: knowledge, big data, intangible assets, intelligence, social media, brand equity


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Journal Issue

Volume 17 Issue 1 / Apr 2019  pp1‑99

Editor: Ettore Bolisani

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Keywords: Job satisfaction, knowledge sharing, organizational culture, company performance, Hofstede’s cultural dimensions, structural equation modeling, knowledge management, knowledge workers, Trust, Knowledge sharing, Social Capital, Networks, Tacit knowledge, Knowledge workers, knowledge, innovation, Baltic Countries, manufacturing sector, Co-design, Empathetic participatory design, repertory grid technique, prototyping, situation awareness, tacit knowledge, explicit knowledge, ICT development, knowledge transfer, post-acquisition integration, acquisition, mergers and acquisition (M&A), case study, knowledge transfer factors knowledge, big data, intangible assets, intelligence, social media, brand equity, literature review, research trends, scientific journals, scientific conferences


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