Open Access
| Issue |
SHS Web Conf.
Volume 230, 2026
SYMBICON 2026 – 5th Annual International Conference on Sustainability, Innovation, and Technology
|
|
|---|---|---|
| Article Number | 02003 | |
| Number of page(s) | 13 | |
| Section | Sustainable Innovation and Entrepreneurship | |
| DOI | https://doi.org/10.1051/shsconf/202623002003 | |
| Published online | 10 April 2026 | |
- Ministry of MSME, Annual Report 2022–2023 (Government of India, 2023). Available at: https://msme.gov.in [Google Scholar]
- S.F. Wamba, A. Gunasekaran, S. Akter, S.J.F. Ren, R. Dubey, S.J. Childe, Big data analytics and firm performance: Effects of dynamic capabilities. J. Bus. Res. 70, 356–365 (2017). https://doi.org/10.1016/j.jbusres.2016.08.009 [Google Scholar]
- S. Akter, S.F. Wamba, A. Gunasekaran, R. Dubey, S.J. Childe, How to improve firm performance using big data analytics capability and business strategy alignment? Int. J. Prod. Econ. 182, 113–131 (2016). https://doi.org/10.1016/j.ijpe.2016.08.018 [Google Scholar]
- R. Rialti, G. Marzi, C. Ciappei, D. Busso, Big data and dynamic capabilities: A bibliometric analysis and systematic literature review. Manag. Decis. 57 (2018). https://doi.org/10.1108/MD-07-2018-0821 [Google Scholar]
- R. Dubey, A. Gunasekaran, S.J. Childe, T. Papadopoulos, S.F. Wamba, Big data and predictive analytics and manufacturing performance: Integrating institutional theory, resource-based view and big data culture. Br. J. Manag. 30, 341–361 (2019). https://doi.org/10.1111/1467-8551.12355 [Google Scholar]
- A. Popovič, R. Hackney, P.S. Coelho, J. Jaklič, Towards business intelligence systems success: Effects of maturity and culture on analytical decision making. Decis. Support Syst. 54, 729–739 (2012). https://doi.org/10.1016/j.dss.2012.08.017 [Google Scholar]
- P. Mikalef, I.O. Pappas, J. Krogstie, M. Giannakos, Big data analytics capabilities: A systematic literature review and research agenda. Inf. Syst. E-Bus. Manag. 16, 547–578 (2019) [Google Scholar]
- M.-T. Huynh, M. Nippa, T. Aichner, Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research. Technol. Forecast. Soc. Change 197, 122884 (2023) [Google Scholar]
- P. Maroufkhani, R. Wagner, W.K.W. Ismail, M.B. Baroto, M. Nourani, Big data analytics and firm performance: A systematic review. Inf. Syst. Front. 22, 527–558 (2020) [Google Scholar]
- A. Braganza, L. Brooks, D. Nepelski, M. Ali, R. Moro, Resource management in big data initiatives: Processes and dynamic capabilities. J. Bus. Res. 70, 328–337 (2017) [Google Scholar]
- S. Kraus, F. Schiavone, A. Pluzhnikova, A.C. Invernizzi, Digital transformation in SMEs: A systematic literature review and research agenda. J. Small Bus. Manag. (2021) [Google Scholar]
- E. Raguseo, Big data technologies: An empirical investigation on their adoption, benefits and risks for companies. Int. J. Inf. Manag. 38, 187–195 (2018). https://doi.org/10.1016/j.ijinfomgt.2017.07.008 [Google Scholar]
- T.H. Davenport, J.G. Harris, Competing on analytics: The new science of winning (Harvard Business Review Press, 2017) [Google Scholar]
- K. Witkowski, Internet of Things, Big Data, Industry 4.0 – Innovative solutions in logistics and supply chains management. Procedia Eng. 182, 763–769 (2017). https://doi.org/10.1016/j.proeng.2017.03.197 [Google Scholar]
- T. Choi, S. Wallace, Y. Wang, Big data analytics in operations management. Prod. Oper. Manag. 27, 1868–1883 (2018). https://doi.org/10.1111/poms.12838 [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

