Open Access
Issue
SHS Web of Conf.
Volume 92, 2021
The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
Article Number 06011
Number of page(s) 7
Section Corporate Social Responsibility and Consumer Claims
DOI https://doi.org/10.1051/shsconf/20219206011
Published online 13 January 2021
  1. Mircică, N. (2019). Cyber-physical systems for cognitive industrial Internet of Things: sensory big data, smart mobile devices, and automated manufacturing processes. Analysis and Metaphysics, 18, 37-43. [Google Scholar]
  2. Rezaei, S., Valaei, N. (2017). Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning, 35(5), 688-702. [Google Scholar]
  3. Adams, C., Grecu, I., Grecu, G., Balica, R. (2020). Technology-related behaviors and attitudes: Compulsive smartphone usage, stress, and social anxiety. Review of Contemporary Philosophy, 19, 71-77. [Google Scholar]
  4. Gray-Hawkins, M., Michalkova, L., Suler, P., Zhuravleva, N. A. (2019). Real-time process monitoring in Industry 4.0 manufacturing systems: Sensing, smart, and sustainable technologies. Economics, Management, and Financial Markets, 14(4), 30-36. [Google Scholar]
  5. Faulds, D. J., Mangold, W. G., Raju, P. S., Valsalan, S. (2018). The mobile shopping revolution: Redefining the consumer decision process. Business Horizons, 61(2), 323-338. [Google Scholar]
  6. Mihăilă, R. (2018). The ascendance of postmodernism in the educational sphere. Educational Philosophy and Theory, 50(14), 1578-1579. [Google Scholar]
  7. Pickard, M., Grecu, I., Grecu, G. (2019). Sustainable smart manufacturing in Industry 4.0: Real-time resource planning, process monitoring, and production control. Economics, Management, and Financial Markets, 14(3), 30-36. [Google Scholar]
  8. Tooby, C. (2019). Governance mechanisms of analytical algorithms: The inherent regulatory capacity of data-driven automated decision-making. Contemporary Readings in Law and Social Justice, 11(1), 39-44. [Google Scholar]
  9. Westbrook, L., Pera, A., Neguriță, O., Grecu, I., Grecu, G. (2019). Real-time data-driven technologies: Transparency and fairness of automated decision-making process governed by intricate algorithms. Contemporary Readings in Law and Social Justice, 11(1), 45-50. [Google Scholar]
  10. Ashraf, A. R., Thongpapanl, N., Menguc, B., Northey, G. (2017). The role of M-Commerce readiness in emerging and developed markets. Journal of International Marketing, 25(2), 25-51. [Google Scholar]
  11. Sion, G. (2019). Self-portraits in social media: Means of communicating emotion through visual content-sharing applications. Linguistic and Philosophical Investigations, 18, 133-139. [Google Scholar]
  12. Kassick, D. (2019). Workforce analytics and human resource metrics: Algorithmically managed workers, tracking and surveillance technologies, and wearable biological measuring devices. Psychosociological Issues in Human Resource Management, 7(2), 55-60. [Google Scholar]
  13. Durkin, K. (2019). Artificial intelligence-driven smart healthcare services, wearable medical devices, and body sensor networks. American Journal of Medical Research, 6(2), 37-42. [Google Scholar]
  14. Fuentes, C., Svingstedt, A. (2017). Mobile phones and the practice of shopping: A study of how young adults use smartphones to shop. Journal of Retailing and Consumer Services, 38, 38-137. [Google Scholar]
  15. Meyers, T. D., Vagner, L., Janoskova, K., Grecu, I., Grecu, G. (2019). Big data-driven algorithmic decision-making in selecting and managing employees: Advanced predictive analytics, workforce metrics, and digital innovations for enhancing organizational human capital. Psychosociological Issues in Human Resource Management, 7(2), 49-54. [Google Scholar]
  16. Sion, G. (2019). Commodifying intimate relationships through geosocial networking mobile apps: Data-driven dating, sexual sociality, and online body objectification. Journal of Research in Gender Studies, 9(2), 78-84. [Google Scholar]
  17. Lăzăroiu, G. (2018). Postmodernism as an epistemological phenomenon. Educational Philosophy and Theory, 50(14), 1389-1390. [Google Scholar]
  18. Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior, 86, 109-128. [Google Scholar]
  19. Krech, S. (2019). Medical big data analytics and smart Internet of Things-enabled mobile-based health monitoring systems. American Journal of Medical Research, 6(2), 31-36. [Google Scholar]
  20. Park, S., Lee, D. (2017). An empirical study on consumer online shopping channel choice behavior in omni-channel environment. Telematics and Informatics, 34(8), 1398-1407. [Google Scholar]
  21. Cadge, K., Lăzăroiu, G., Durana, P., Kovalova, E. (2019). Initiating sexual behaviors with online dating partners: Stereotypical gender norms, intimate personal data, and romantic compatibility. Journal of Research in Gender Studies, 9(2), 71-77. [Google Scholar]
  22. Gutberlet, T. (2019). Data-driven smart sustainable cities: Highly networked urban environments and automated algorithmic decision-making processes. Geopolitics, History, and International Relations, 11(2), 55-61. [Google Scholar]
  23. Kim, M., Kim, J., Choi, J., Trivedi, M. (2017). Mobile shopping through applications: Understanding application possession and mobile purchase. Journal of Interactive Marketing, 39, 55-68. [Google Scholar]
  24. Lyakina, M., Sheehy, M., Podhorska, I. (2019). Networked and integrated urban technologies in Internet of Things-enabled smart sustainable cities. Geopolitics, History, and International Relations, 11(2), 62-68. [Google Scholar]
  25. Liébana-Cabanillas, F., de Luna, I.R., Montoro-Ríos, F. (2017). Intention to use new mobile payment systems: a comparative analysis of SMS and NFC payments. Economic Research-Ekonomska Istraživanja, 30(1), 892-910. [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.