Victoria Konovalenko Sletti, Guest Editor, Inland Norway University of Applied Sciences, Norway

Big data has become an important part of many organizations’ strategic agendas – both public and private. The scope of the research literature addresses big data from the technological or managerial perspective, and this special issue invites authors to focus on the second one. While previous studies have given essential focus to technological aspects, such as infrastructure and analytical tools, other areas of research have been underexplored, including human skills and knowledge, management and orchestration of these resources, and their connection to strategy and operations thinking (Gupta & George, 2016; Mikalef, Pappas, Krogstie, & Giannakos, 2018).

It has been suggested that with the spread of big data and big data tools, longstanding ideas about decision making, management practices, competitive strategy formulation, and value creation will be changed (Pappas, Mikalef, Giannakos, Krogstie, & Lekakos, 2018). There are several reasons for this. One reason is the managerial challenge of dealing with a phenomenon that represents a complex interplay of human and technological components (Pedersen & Wilkinson, 2019). Another reason is that big data shifts the focus from the organizations to the ecosystems. Due to this, the boundaries between internal and external knowledge assets seem to be blurred. Creating value is often the result of managing knowledge assets, which are reflected through the components of intellectual capital: human, structural, and relational capital. The emergence of big data offers a new interpretative lens for intellectual capital management (Erickson & Rothberg, 2014; Secundo, Del Vecchio, Dumay, & Passiante, 2017; De Santis & Presti, 2018; Ndou, Secundo, Dumay, & Gjevori, 2018; Alomari, Shehada, & El-Daour, 2020). Therefore, the nascent research topics call for new studies of big data in digital business ecosystems and in relation to intellectual capital management.

Academic literature recognizes that big data projects may be successful not only due to the big data itself and the analytical tools used to process it – that is, the resources and methods comprising big data analytics. An important role is attached to big data analytics capability, which is broadly defined as the “ability of a firm to provide insights using data management, infrastructure, and talent to transform business into a competitive force” (Akter, Wamba, Gunasekaran, Dubey, & Childe, 2016). The concept of big data analytics capability stretches beyond solely focusing on big data resources to include other related and relevant organizational resources that are important for realizing full strategic potential. Even though research literature has addressed the types of resources and resource picking for capability building, very little is known about management processes that lead to the development of big data analytics capability (Mikalef et al., 2018).

For this special issue, we welcome novel and original contributions addressing a variety of management perspectives on big data. Topics to be addressed may include but are not limited to the following:

  • Management processes and practices fostering the acquisition of big data.
  • Managing and orchestrating resources to develop big data analytics capability.
  • Managing big data in the digital business ecosystems.
  • The role of big data actors: their degree of involvement and influence on digital transformation and social change. Who are the main stakeholders in the creation of a big data ecosystem for an organization?
  • Re-conceptualising intellectual capital (management) perspective through big data.
  • Evaluating the impact of big data on the intellectual capital components.
  • Estimating the potential business value of big data and performance measures to benchmark big data effectiveness. How can organizations measure the value extracted from big data?
  • Achieving digital transformation and creating sustainable societies through the use of big data
  • Big data-driven sustainable development: How do various practices and strategies co-exist and co-evolve in the digital society?
  • Top and middle managers’ trust in big data. Do decision makers embrace or reject big data-enabled decision making? How are leaders and organizational structures willing to adopt and implement big data-related approaches in decision making?

Paper submission

Papers should be submitted to JEMI before the end of 31 May 2021 at This email address is being protected from spambots. You need JavaScript enabled to view it. and the Guest Editor: This email address is being protected from spambots. You need JavaScript enabled to view it.. The papers will undergo a double-blind review. Submissions must be in English, should be 8000 - 9000 words, and follow the submission requirements (paper template, etc.) posted on the JEMI website at

Submission deadline: 31 May 2021
Papers reviewed: 31 August 2021
Revised papers reviewed and accepted: 30 November 2021
Final versions of accepted papers delivered: 30 December 2021
Papers published: 2022


  • Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113-131.
  • Alomari, I., Shehada, F., & El-Daour, J. (2020). Integrating Big Data and intellectual capital: Resource complementarity in business value creation. Paper presented at The 1st international Conference on Information Technology and Business ICITB.
  • De Santis, F., & Presti, C. (2018). The relationship between intellectual capital and big data: A review. Meditari Accountancy Research.
  • Erickson, S., & Rothberg, H. (2014). Big data and knowledge management: Establishing a conceptual foundation. Electronic Journal of Knowledge Management, 12(2), 108-116.
  • Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049-1064.
  • Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: A systematic literature review and research agenda. Information Systems and e-Business Management, 16(3), 547-578.
  • Ndou, V., Secundo, G., Dumay, J., & Gjevori, E. (2018). Understanding intellectual capital disclosure in online media Big Data. Meditari Accountancy Research, 26(3), 499-530.
  • Pappas, I. O., Mikalef, P., Giannakos, M. N., Krogstie, J., & Lekakos, G. (2018). Big data and business analytics ecosystems: Paving the way towards digital transformation and sustainable societies. Information Systems and e-Business Management, 16, 479-491.
  • Pedersen, J. S., & Wilkinson, A. (2019). The promise, application and pitfalls of big data. In J. S. Pedersen & A. Wilkinson (Eds.), Big Data: Promise, Application and Pitfalls (pp. 1-21): Edward Elgar Publishing.
  • Secundo, G., Del Vecchio, P., Dumay, J., & Passiante, G. (2017). Intellectual capital in the age of Big Data: Establishing a research agenda. Journal of Intellectual Capital, 18(2), 242-261.

International teams of researchers are welcome!

Journal of Entrepreneurship, Management and Innovation (JEMI)

is indexed in Web of Science