Kava, Harkaran, Spanaki, Konstantina, Papadopoulos, Thanos, Despoudi, Stella, Rodriguez-Espindola, Oscar, Fakhimi, Masoud (2021) Data analytics diffusion in the UK renewable energy sector: an innovation perspective. Annals of Operations Research, . ISSN 0254-5330. E-ISSN 1572-9338. (doi:10.1007/s10479-021-04263-1) (KAR id:90002)
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Official URL: https://doi.org/10.1007/s10479-021-04263-1 |
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.
Item Type: | Article |
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DOI/Identification number: | 10.1007/s10479-021-04263-1 |
Uncontrolled keywords: | Big Data Analytics, energy sector, renewable energy, diffusion of innovations, field study |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Thanos Papadopoulos |
Date Deposited: | 02 Sep 2021 15:21 UTC |
Last Modified: | 05 Nov 2024 12:55 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/90002 (The current URI for this page, for reference purposes) |
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