A Study of Emerging Trends in Multidisciplinary Innovation

  • Authors

    • Dr. Rebecca Green Associate Professor, Arizona State University, USA. Author
    • Dr. Steven Young Professor, University of Washington, USA. Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-2021PI3V9H

    Published 01-03-2021

  • Multidisciplinary Innovation, Interdisciplinary Research, Emerging Technologies, Innovation Ecosystems, Artificial Intelligence, Digital Transformation, Sustainable Development

    Issue

    Vol. 4 No. 1 (2021)

    Section

    Articles

    How to Cite

    [1]
    R. Green and S. Young, “A Study of Emerging Trends in Multidisciplinary Innovation”, ijmiet, vol. 4, no. 1, pp. 01–13, Jan. 2021, doi: 10.67228/30715628/IJMIET-2021PI3V9H.

  • Abstract

    The use of multidisciplinary innovation has become a forceful paradigm of solving a multi-dimensional global problem, which cannot be successfully solved within the field of one field. The convergence of long-standing previously separate areas of study has been very fast due to the rapid changes in digital technologies, artificial intelligence, biotechnology, materials science, and sustainability sciences. This paper entails an in-depth analysis of the new trends in the field of multidisciplinary innovation both in conceptual bases, technological forces, collaborative patterns, methodological approaches, as well as real-life performances of the entire occurrence in industrial, academia, and society spheres. The research research systematically examines the interdisciplinary integration as a way of promoting creativity, improving the efficiency of problem solving and facilitating disruptive innovation. In addition, the paper explores the application of enabling technologies, including artificial intelligence, big data analytics, cyber-physical systems, and digital twins, that are the stimulants of cross-domain collaboration. It is suggested to use a structured approach that will combine qualitative literature analysis, trend mapping, and innovation ecosystem modeling to assess the results of multidisciplinary innovation. The findings demonstrate that organizations with multidiscipline strategies are more efficient in terms of innovation, transfer faster transfer of technologies and perform better in terms of sustainability. Other important issues like knowledge integration complexity, governance and communication issues are also explored critically. The results highlight the need of adaptive education systems, policy frameworks and organizational set up to facilitate multidisciplinary innovation. This work will be a contribution to the academic literature and practice in industries through its contribution to the unified perspective of emergent trends and sustained actionable implications on researchers, policy makers, and leaders of innovation.

  • References

    [1] J. Klein, Interdisciplinarity: History, Theory, and Practice, Detroit, MI, USA: Wayne State Univ. Press, 1990.

    [2] H. A. Simon, “The architecture of complexity,” Proc. Amer. Philos. Soc., vol. 106, no. 6, pp. 467–482, 1962.

    [3] R. Ackoff, “Systems, messes, and interactive planning,” Manage. Sci., vol. 17, no. 11, pp. 661–671, 1971.

    [4] J. Schumpeter, Capitalism, Socialism and Democracy, 3rd ed., New York, NY, USA: Harper & Row, 1950.

    [5] H. Etzkowitz and L. Leydesdorff, “The Triple Helix—University–industry–government relations: A laboratory for knowledge-based economic development,” EASST Rev., vol. 14, no. 1, pp. 14–19, 1995.

    [6] H. Etzkowitz and L. Leydesdorff, “The dynamics of innovation: From National Systems and ‘Mode 2’ to a Triple Helix of university–industry–government relations,” Res. Policy, vol. 29, no. 2, pp. 109–123, 2000.

    [7] M. Porter, “Clusters and the new economics of competition,” Harvard Bus. Rev., vol. 76, no. 6, pp. 77–90, 1998.

    [8] H. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology, Boston, MA, USA: Harvard Business School Press, 2003.

    [9] E. Brynjolfsson and A. McAfee, The Second Machine Age, New York, NY, USA: W. W. Norton & Company, 2014.

    [10] R. Rajkumar et al., “Cyber-physical systems: The next computing revolution,” in Proc. Design Automation Conf. (DAC), 2010, pp. 731–736.

    [11] L. Atzori, A. Iera, and G. Morabito, “The Internet of Things: A survey,” Comput. Netw., vol. 54, no. 15, pp. 2787–2805, 2010.

    [12] Y. Huang et al., “Artificial intelligence in interdisciplinary research,” Nature Mach. Intell., vol. 2, no. 2, pp. 76–79, 2020.

    [13] B. Latour, Reassembling the Social: An Introduction to Actor-Network-Theory, Oxford, U.K.: Oxford Univ. Press, 2005.

    [14] F. Westfall and T. Boyd, “Evaluating interdisciplinary research outcomes: Metrics and challenges,” Res. Eval., vol. 27, no. 2, pp. 123–134, 2018.

    [15] OECD, Innovation and Multidisciplinary Research: Policy and Practice, Paris, France: OECD Publishing, 2019.

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