Project: Platforms of Big Data Foresight (PLATBIDAFO)

Project Nr. 01.2.2-LMT-K-718-02-0019

Project duration 2018 11 – 2021 10

Project is implemented under funding of European Regional Development Fund.

The idea of the project is based on platforms that enable insights into the future of big data. One of the key aspects of technological change is the economic benefits and productivity generated by the platform. Platforms have different scales. Some of them operate on a small scale and others on a large scale. New technologies offer new opportunities to expand the scale of platforms. Choudary (2015) presents five essential elements of platforms: (1) data, (2) infrastructure, (3) community, (4) market players, and (5) network market. The chosen platform structure, new technologies provide many new choices and opportunities. The research ideas are based on three themes: (1) Open Innovation and Social Behavior Research (Crowdsourcing), (2) E-Commerce, and (3) Matching Platforms. The first topic is widely applied today to SMEs and large corporations. There is a need to analyze these topics and integrate them with digital platforms and the processing of big data resources.

Project aim to create new type digital Big Data platforms that allow us create, organize and use digital content for economic and social wellbeing of society using new methods joining Big Data and Future Foresight methodologies.

Project SMART specialisation area: Inclusive and creative society, Technologies and processes for the development and implementation of break-through innovations.

Project will develop:

New Open Innovation management tools with Big Data Foresight;
R&D product (KIBS – knowledge intensive business services);
New E-commerce and business management tools for Big Data Foresight;
R&D product (Big Data pilot model);
Summary report of testing;
6 scientific articles and 3 conference papers;
1 scientific conference.

Research leader prof. Jari Kaivo-oja.

Principal researchers: prof. Arūnas Augustinaitis, prof. Steffen Roth, dr. Theresa Lauraeus, dr. Mathew Ferns Mathew, dr. Austė Kiškienė, Darius Verbyla ir Mikkel Knudsen.

Scientific results created during the project:

Kaivo-oja, J., & Stein Knudsen, M. (2019). Collaborative Robots Between Industry 4.0 And the Platform Economy: Where Next for Cobots? Proceedings of 10th International Symposium on Intelligent Manufacturing and Service Systems, p. 846-855.

Kaivo-oja, J., Stein Knudsen, M., & Lauraeus, T. (2019). Proliferation of Digital Twins: Towards new horizons of Digital Twin-technology. Proceedings of 10th International Symposium on Intelligent Manufacturing and Service Systems, p. 464-473.

Mawaak, M. (2019). Bubble to panopticon: dark undercurrents of the big data torrent. Kybernetes, 49(3), p. 1046-1060.

Roth, S., Dahms, H., Welz, F., & Cattacin, S. (2019). Print theories of computer societies. Introduction to the digital transformation of social theory. Technological forecasting and social change, 149, p. 1-6.

Roth, S., Kaivo-oja, J., Schwede, P., Valentinov, V., & Žažar, K. (2019). Big data insights into social macro trends (1800–2000): A replication study. Technological forecasting and social change, 149, p. 1-8.

Roth, S., & Kaivo-oja, J. (2019). Harnessing big data for a multifunctional theory of the firm. European Management Journal, 38(1), p. 54-61.

Kaivo-oja, J., Knudsen, M., & Lauraeus, T. (2019). Digital Twins approach and future knowledge management challenges: Where we shall need system integration, synergy analyses and synergy measurements? KMO2019 Conference. July 15-18, 2019 KMO 2019, 14th International Conference on Knowledge Management in Organisations. Theme: The synergistic role of knowledge management in organisations, University of Salamanca, Zamora, Spain., p. 271-281.

Knudsen, M., Kaivo-oja, J., & Lauraeus, T. (2019). Enabling technologies of Industry 4.0 and their global forerunners: An empirical study of the Web of Science database. KMO2019 Conference. July 15-18, 2019 KMO 2019, 14th International Conference on Knowledge Management in Organisations. Theme: The synergistic role of knowledge management in organisations, University of Salamanca, Zamora, Spain., p. 3-13.

Roth, S. (2019). Digital transformation of social theory. A research update. Technological forecasting and social change, 146, p. 88-93.

Roth, S. (2019). The open theory and its enemy: Implicit moralisation as epistemological obstacle for general systems theory. Systems Research and Behavior science, 36(3), p. 281-288.

Kaivo-oja, J., Knudsen, M.S. and Lauraéus, T. (2020) Digital Twin: Current shifts and their future implications in the conditions of technological disruption.

Kaivo-oja, J., Vehmas, J. and Luukkanen, J. (2020) Anticipating future trends of the energy transition. Multi-level dynamics in policy agenda setting. Chapter 10. Aalto, P. (Ed. ) Electrification: Accelerated Transition to Climate Neutrality.

Kaivo-oja, J., Lauraéus, T. and Knudsen, Mikkel Stein (2020) Picking the ICT Technology Winners – Longitudinal Analysis of 21st Century Technologies on The Basis of the Gartner Hype Cycle 2008–2017: Trends, Tendencies and Weak Signals. International Journal of Web Engineering and Technology. Accepted. In press.

Kaivo-oja, J. and Lauréaus, Theresa (2020) Towards Data Driven Smart Specialisation Strategy of the Lithuanian Economy. Large Trend Data Lakes Analytics of the Lithuanian Economy. Strategically Focused Export and Import Perspectives with Lauréaus-Kaivo-oja Market Resilience Index. Manuscript. Unpublished.

Santonen, T. and Kaivo-oja, J. (2020) Crowdsourcing Delphi – Combine the best of both worlds for futures-oriented technology analysis and foresight research. Technology Analysis and Management. In review process.

Maavak, M (2021). Horizon 2020-2030: Will Emerging Risks Unravel our Global Systems? Accepted by Salus Journal for 2021 April issue

More information on the project results available at https://bigdataexcellence.com/