EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 46 (2022) ITM Web Conf., 46 (2022) 02002 References
Open Access
Issue
ITM Web Conf.
Volume 46, 2022
International Conference on Engineering and Applied Sciences (ICEAS’22)
Article Number 02002
Number of page(s) 6
Section Computer Sciences
DOI https://doi.org/10.1051/itmconf/20224602002
Published online 06 June 2022
  1. Zeng, Delin & Tim, Yenni & Yu, Jiaxin & Liu, Wenyuan. (2020). Actualizing big data analytics for smart cities: A cascading affordance study. International Journal of Information Management. 54. 102156. 10.1016/j.ijinfomgt.2020.102156. [Google Scholar]
  2. Bansal, Veena & Shukla, Shubham. (2021). Exploring Big Data Analytics Adoption using Affordance Theory. 131-138. 10.5220/0010509801310138. [Google Scholar]
  3. Pozzi, Giulia & Pigni, Federico & Vitari, Claudio. (2014). Affordance Theory in the IS Discipline: A Review and Synthesis of the Literature. 20th Americas Conference on Information Systems, AMCIS 2014. [Google Scholar]
  4. Dorothy E. Leidner, Ester Gonzalez, Hope Koch, [Google Scholar]
  5. An affordance perspective of enterprise social media and organizational socialization, [Google Scholar]
  6. The Journal of Strategic Information Systems, [Google Scholar]
  7. Visvizi, A., Lytras, M. D., Damiani, E., & Mathkour, H. (2018). Policy making for smart cities: Innovation and social inclusive economic growth for sustainability. Journal of Science and Technology Policy Management, 9(2),126–133. [CrossRef] [Google Scholar]
  8. Müller, O., Junglas, I., Brocke, J., & Debortoli, S. (2016). Utilizing big data analytics for information systems research: Challenges, promises and guidelines. European Journal of Information Systems, 25(4),289–302 [CrossRef] [Google Scholar]
  9. Deanne Larson, Victor Chang, A review and future direction of agile, business intelligence, analytics and data science, International Journal of Information Management, Volume 36, Issue 5, 2016, Pages700-710, [Google Scholar]
  10. Ervan Ismail Sumardjo Sumardjo Djuara P Lubis Rilus A Kinseng Siti Dewi Sri Ratna Sari Year: 2022 Digital Communication and Community Development of Leading Tourism Areas in Indonesia (Tanjung Lesung Case Study) RUSET EAI DOI: 10.4108/eai.14-9-2021.2317175 [Google Scholar]
  11. Eka Aprilia Rindu Rika Gamayuni Saring Suhendro Year: 2022 E-government as Good Governance in Building Post-Covid 19 Technological Innovations ICEBE EAI DOI: 10.4108/eai.7-10-2021.2316234 [Google Scholar]
  12. Baccarne, Bastiaan & Mechant, Peter & Schuurman, Dimitri. (2014). Empowered Cities? An Analysis of the Structure and Generated Value of the Smart City Ghent. 10.1007/978-3-319-06160-3_8. [Google Scholar]
  13. Sharifi, A., Khavarian-Garmsir, A. R., & Kummitha, R. K. R. (2021). Contributions of Smart City Solutions and Technologies to Resilience against the COVID-19 Pandemic: A Literature Review. Sustainability, 13(14), 8018. doi:10.3390/su13148018 [CrossRef] [Google Scholar]
  14. Remy, Constance Marie Dominique; Pärnpuu, Triin; Hedman, Jonas./Smart Cities & Sustainable Information Systems. Frederiksberg: Copenhagen Business School, CBS, 2018. (DIGI Communications; No. 2018/2). [Google Scholar]
  15. B. Baccarne, D. Schuurman, P. Mechant, and L. De Marez, “The role of urban living labs in a smart city,” in XXV ISPIM Innovation Conference, Proceedings, Dublin, Ireland, 2014. [Google Scholar]
  16. Baccarne, B., Mechant, P., Schuurman, D. (2014). Empowered Cities? An Analysis of the Structure and Generated Value of the Smart City Ghent. In: Dameri, R., Rosenthal-Sabroux, C. (eds) Smart City. Progress in IS. Springer, Cham. https://doi.org/10.1007/978-3-319-06160-3_8 [Google Scholar]
  17. Khan, M.I., Khan, S., Khan, U. and Haleem, A. (2021), “Modeling the Big Data challenges in context of smart cities – an integrated fuzzy ISM- DEMATEL approach”, International Journal of Building Pathology and Adaptation, Vol. ahead- of-print No. ahead-of- print. https://doi.org/10.1108/IJBPA-02-2021-0027 [Google Scholar]
  18. Nam, D., Lee, J., and Lee, H. (2019). Business analytics adoption process: An innovation diffusion perspective. International Journal of Information Management, 49:411–423. [CrossRef] [Google Scholar]
  19. Pozzi, Giulia & Pigni, Federico & Vitari, Claudio. (2014). Affordance Theory in the IS Discipline: a Review and Synthesis of the Literature. 20th Americas Conference on Information Systems, AMCIS 2014. [Google Scholar]
  20. Strauss, L. M., & Hoppen, N. (2019). A framework to analyze affordances when using big data and analytics in organizations: A proposal. Revista de Administração Mackenzie, 20(4). doi:10.1590/1678-6971/eRAMR190182 [Google Scholar]
  21. Wamba, S., Gunasekaran, A., Akter, S., Ren, S., Dubey, R., and Childe, S. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70:356–365. [CrossRef] [Google Scholar]
  22. Wamba, S. F., Akter, S., Edwards, A., Chopin, G., and Gnanzou, D. (2015). How big data can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165:234–246. [CrossRef] [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.