What is the special issue about?
The objective of this special issue is to explore the emerging trends of intellectual capital (IC) research in light of the rising evolution of the Big Data movement (McAfee and Brynjolfsson, 2012). As the Volume, Velocity and Variety of data (Laney, 2001) increase, it becomes more compelling than in the past to take advantage of the data. Moreover, scholars and researchers in the field of the information management have identified veracity, variability and value as additional dimensions of the phenomenon (Gandomi & Haider, 2015). The need of a major comprehension of the managerial implications related how to translate Big data into organizational value in the forms of firms’ intangible assets or Intellectual capital (IC) is arising.
The emergence of Big Data has made more temporary the boundaries among the internal and external knowledge assets on which companies can leverage to gain and sustain their competitive advantage. Creating a bridge between knowledge inside the organisation, known as human capital, and knowledge outside the organisation, known as relational capital is becoming more strategic (Borin and Donato, 2015). This approach shifts the focus of IC from the organization to the eco-systems where knowledge could be created on a wider scale (Dumay, 2013). This is known as fourth stage of IC research (Dumay and Garanina, 2015) that now reached is cusp (Dumay, 2016).
The potential contribution from Big data is more transparent management of relational capital, a more responsive control of human capital, a more punctual decision making for structural capital (Erikson and Rothberg, 2015; Manyika, et. al., 2014) need to be highlighted. Therefore, explicitly recognising the importance of Big Data can be fruitful for the analysis of the praxis of IC management as well as for the understanding of how the connections between the inside and the outside IC of an organization are made.
But how those potential benefits fit within the IC universe? In an IC perspective, what do we make of current trends related to big data, business intelligence, business analytics, cloud computing, and related topics? Behind the recent mood on Big Data, are organizations finding value in basic data and information as well? How does this trend square with the way we conceptualize IC and value it?
This special issue will work through the most recent literature concerning Intellectual Capital (IC) to develop a view of Big Data that fits with existing and new theory. We encourage exploring methodologies, technologies and processes that can open up the black box in “data enabled organisations” (Baumgarten, and Dickstein, 2013) where the practices of Big Data are exploring innovative challenges for the IC management.
We welcome both theoretical work and empirical research using quantitative or qualitative methods. All submissions should demonstrate relevance to the understanding of intellectual capital and big data as emerging field that could affect it. Possible topics include, but are not limited to:
How to submit
Submission deadline: 31 May 2017
First round feedback: 31 August 2017
Planned publication date: March 2018
Baumgarten, J. and Dickstein, M. (2013) Beyond the Hype. Building a Big Data-Enabled Organization. Available at: https://www.spencerstuart.com/research-and-insight/beyond-the-hype-building-a-big-data-enabled-organization.
Borin, E. and Donato, F. (2015), "Unlocking the potential of IC in Italian cultural ecosystems", Journal of Intellectual Capital, Vol. 16 No. 2, pp. 285–304.
Dumay, J. (2013), “The third stage of IC: towards a new IC future and beyond”, Journal of Intellectual Capital, Vol. 14 No. 1, pp. 5-9.
Dumay, J. (2016) A critical reflection on the future of intellectual capital: from reporting to disclosure, Journal of Intellectual capital, Vol. 17 No. 1,pp. 168-184.
Dumay, J. and Garanina, T. (2013), “Intellectual capital research: A critical examination of the third stage”, Journal of Intellectual Capital, Vol. 14 No. 1, pp. 10-25.
Erickson, S., & Rothberg, H. (2015). “Big Data and Knowledge Management: Establishing a Conceptual Foundation. Leading Issues in Knowledge Management”, Volume Two, 2, 204.
Gandomi, A., Haider, M., (2015), “Beyond the hype: Big data concepts, methods, and analytics”, International Journal of Information Management, 35, pp. 137-144.
Laney, D., (2001), “3-D data management: Controlling data volume, velocity and variety”, Application Delivery Strategies by META Group Inc. (2001, February 6), p. 949 Retrieved from http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf
Manyika, J., Chui, M., & Brown, B. (2011). “Big data: The next frontier for innovation, competition, and productivity”, Las Vegas: The McKinsey Global Institute.
McAfee, A., Brynjolfsson, E., (2012), “Big Data: The Management Revolution”, Harvard Business Review¬, October 2012¬, pp.61-68.