Improving Individual Digital Literacy in the Digital Era: From the Perspective of Learning
- DOI
- 10.2991/978-94-6463-264-4_43How to use a DOI?
- Keywords
- digital transformation; individual learning; job performance; adaptive performance; innovative performance
- Abstract
Digital transformation, including adoption of various digital technologies such as artificial intelligence, algorithm, information-computer technology, is prevalent in nowadays organizations. Extant research proposes that digital transformation has claimed new job demands and brought up challenges and difficulties for employees to adapt to the new digital workplace. This paper aims to seeks idea to promote employees’ adaptivity from the perspective of learning. It intends to set theoretical and empirical linkages between digital transformation and favorable workplace outcomes through the mediating role of individual learning. Drawing from two-wave survey data collected from 433 Chinese employees, this study conducts hierarchical linear regression analyses and proves that digital transformation promotes individual learning. Moreover, digital transformation further enhances job performance, adaptive performance and innovative performance via learning.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qiwei Zhou AU - Ye Sun AU - Yunfeng Zhang PY - 2023 DA - 2023/09/28 TI - Improving Individual Digital Literacy in the Digital Era: From the Perspective of Learning BT - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023) PB - Atlantis Press SP - 388 EP - 395 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-264-4_43 DO - 10.2991/978-94-6463-264-4_43 ID - Zhou2023 ER -