Open Access
Issue |
SHS Web of Conf.
Volume 92, 2021
The 20th International Scientific Conference Globalization and its Socio-Economic Consequences 2020
|
|
---|---|---|
Article Number | 05015 | |
Number of page(s) | 6 | |
Section | Collaborative Economics, Digital Platforms and Multimedia | |
DOI | https://doi.org/10.1051/shsconf/20219205015 | |
Published online | 13 January 2021 |
- Costea, E.-A. (2020). Machine learning-based natural language processing algorithms and electronic health records data. Linguistic and Philosophical Investigations, 19, 93-99. [CrossRef] [Google Scholar]
- 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. [CrossRef] [Google Scholar]
- Hubert, M., Blut, M., Brock, C., Backhaus, C., Eberhardt, T. (2017). Acceptance of smartphone-based mobile shopping: Mobile benefits, customer characteristics, perceived risk and the impact of application context. Psychology & Marketing, 34(2), 175-194. [CrossRef] [Google Scholar]
- Sion, G. (2019). Smart city big data analytics: Urban technological innovations and the cognitive Internet of Things. Geopolitics, History, and International Relations, 11(2), 69-75. [CrossRef] [Google Scholar]
- Lafferty, C. (2019). Sustainable Internet-of-Things-based manufacturing systems: Industry 4.0 wireless networks, advanced digitalization, and big data-driven smart production. Economics, Management, and Financial Markets, 14(4), 16-22. [Google Scholar]
- Coatney, K. (2019). Cyber-physical smart manufacturing systems: Sustainable industrial networks, cognitive automation, and big data-driven innovation. Economics, Management, and Financial Markets, 14(4), 23-29. [Google Scholar]
- 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, 137-146. [CrossRef] [Google Scholar]
- Atwell, G. J., Lăzăroiu, G. (2019). Are autonomous vehicles only a technological step? The sustainable deployment of self-driving cars on public roads. Contemporary Readings in Law and Social Justice, 11(2), 22-28. [CrossRef] [Google Scholar]
- Kearney, H., Kliestik, T., Kovacova, M., Vochozka, M. (2019). The embedding of smart digital technologies within urban infrastructures: Governance networks, real-time data sustainability, and the cognitive Internet of Things. Geopolitics, History, and International Relations, 11(1), 98-103. [CrossRef] [Google Scholar]
- Hyers, D. (2019). Sensor networks and intelligent automation systems for big data-driven smart manufacturing in cyber-physical connected environments. Journal of Self-Governance and Management Economics, 7(4), 14-20. [Google Scholar]
- 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. [CrossRef] [Google Scholar]
- Harrower, K. (2019). Algorithmic decision-making in organizations: Network data mining, measuring and monitoring work performance, and managerial control. Psychosociological Issues in Human Resource Management, 7(2), 7-12. [CrossRef] [Google Scholar]
- Sion, G. (2019). Is selfie-posting behavior a kind of nonpathological narcissism? Analysis and Metaphysics, 18, 71-77. [CrossRef] [Google Scholar]
- Tarute, A., Nikou, S., Gatautis, R. (2017). Mobile application driven consumer engagement. Telematics and Informatics, 34(4), 145-156. [CrossRef] [Google Scholar]
- Cosgrave, K. W. (2019). The smart cyber-physical systems of sustainable Industry 4.0: Innovation-driven manufacturing technologies, creative cognitive computing, and advanced robotics. Journal of Self-Governance and Management Economics, 7(3), 7-13. [Google Scholar]
- Groß, M. (2018). Mobile shopping loyalty: The salient moderating role of normative and functional compatibility beliefs. Technology in Society, 55, 146-159. [CrossRef] [Google Scholar]
- Kapoor, A. P., Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43, 342-351. [CrossRef] [Google Scholar]
- Kenrick, N., Svabova, L., Nica, E. (2019). Real-time health-related data, wearable medical sensor devices, and smart cyber-physical systems. American Journal of Medical Research, 6(2). [Google Scholar]
- Eriksson, N., Rosenbröijer, C.-J., Fagerstrøm, A. (2017). The relationship between young consumers’ decision-making styles and propensity to shop clothing online with a smartphone. Procedia Computer Science, 121, 519-524. [CrossRef] [Google Scholar]
- Wingard, D. (2019). Data-driven automated decision-making in assessing employee performance and productivity: Designing and implementing workforce metrics and analytics. Psychosociological Issues in Human Resource Management, 7(2), 13-18. [CrossRef] [Google Scholar]
- Gupta, A., Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36, 1-7. [CrossRef] [Google Scholar]
- McLean, G. (2018). Examining the determinants and outcomes of mobile app engagement – A longitudinal perspective. Computers in Human Behavior, 84, 392-403, [CrossRef] [Google Scholar]
- Furnham, P. (2019). Automation and autonomy of big data-driven algorithmic decision-making. Contemporary Readings in Law and Social Justice, 11(1), 51-56. [CrossRef] [Google Scholar]
- Byrne, S. (2019). Remote medical monitoring and cloud-based Internet of Things healthcare systems. American Journal of Medical Research, 6(2), 19-24. [Google Scholar]
- 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. [CrossRef] [Google Scholar]
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