Record Details

Big Data, Tacit Knowledge and Organizational Competitiveness

Journal of Intelligence Studies in Business

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Field Value
 
Title Big Data, Tacit Knowledge and Organizational Competitiveness
 
Creator Kabir, Nowshade
Carayannis, Elias
 
Subject —
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Description In the process of conducting everyday business, organizations generate and gather a large number of information about their customers, suppliers, competitors, processes, operations, routines and procedures. They also capture communication data from mobile devices, instruments, tools, machines and transmissions. Much of this data possesses an enormous amount of valuable knowledge, exploitation of which could yield economic benefit. Many organizations are taking advantage of business analytics and intelligence solutions to help them find new insights in their business processes and performance. For companies, however, it is still a nascent area, and many of them understand that there are more knowledge and insights that can be extracted from available big data using creativity, recombination and innovative methods, apply it to new knowledge creation and produce substantial value. This has created a need for finding a suitable approach in the firm’s big data related strategy. In this paper, the authors concur that big data is indeed a source of firm’s competitive advantage and consider that it is essential to have the right combination of people, tool and data along with management support and data‐oriented culture to gain competitiveness from big data. However, the authors also argue that organizations should consider the knowledge hidden in the big data as tacit knowledge and they should take advantage of the cumulative experience garnered by the companies and studies done so far by the scholars in this sphere from knowledge management perspective. Based on this idea, a big data oriented framework of organizational knowledge‐based strategy is proposed here.
 
Publisher Journal of Intelligence Studies in Business
 
Contributor —
 
Date 2013-12-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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Format application/pdf
 
Identifier https://ojs.hh.se/index.php/JISIB/article/view/76
 
Source Journal of Intelligence Studies in Business; Vol 3, No 3 (2013): JISIB
2001-015X
2001-0168
 
Language eng
 
Relation https://ojs.hh.se/index.php/JISIB/article/view/76/pdf_4