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Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective

Author

Listed:
  • Harkaran Kava

    (Loughborough University)

  • Konstantina Spanaki

    (Audencia Business School)

  • Thanos Papadopoulos

    (Kent Business School, University of Kent)

  • Stella Despoudi

    (Aston Business School - Aston University [Birmingham])

  • Oscar Rodriguez-Espindola

    (Aston Business School - Aston University [Birmingham])

  • Masoud Fakhimi

    (Surrey Business School [Guildford] - UNIS - University of Surrey)

Abstract

We introduce the BDA dynamics and explore the associated applications in renewable energy sector with a focus on data-driven innovation. Our study draws on the exponential growth of renewable energy initiatives over the last decades and on the paucity of literature to illustrate the use of BDA in the energy industry. We conduct a qualitative field study in the UK with stakeholder interviews and analyse our results using thematic analysis. Our findings indicate that no matter if the importance of the energy sector for 'people's well-being, industrial competitiveness, and societal advancement, old fashioned approaches to analytics for organisational processes are currently applied widely within the energy sector. These are triggered by resistance to change and insufficient organisational knowledge about BDA, hindering innovation opportunities. Furthermore, for energy organisations to integrate BDA approaches, they need to deal with challenges such as training employees on BDA and the associated costs. Overall, our study provides insights from practitioners about adopting BDA innovations in the renewable energy sector to inform decision-makers and provide recommendations for future research.

Suggested Citation

  • Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
    • Handle: RePEc:hal:journl:hal-03781046
    Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-03781046
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    References listed on IDEAS

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    1. Chao Fu & Dongyue Wang & Wenjun Chang, 2023. "Data-driven analysis of influence between radiologists for diagnosis of breast lesions," Annals of Operations Research, Springer, vol. 328(1), pages 419-449, September.

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    Keywords

    Big Data Analytics; energy sector; renewable energy; diffusion of innovations; field study;
    All these keywords.

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