The Digital Transformation of the Retail Industry, Taking Decathlon as an Example
- DOI
- 10.2991/978-94-6463-300-9_84How to use a DOI?
- Keywords
- Digital Transformation; Retail; Challenge
- Abstract
In the digital era, digital transformation is in rapid development. At the same time, Digital transformation also brings many opportunities for the retail industry. The world’s largest retailer of sporting goods is Decathlon, and it has a leading position in the international sports brand retail market. In order to maintain an important position in the international sports brand market, they pursue innovation and future development in the digital era. Taking Decathlon as an example, this article analyzes every phase of Decathlon’s digital transformation route and some problems in it, the main issues include talent recruitment, data transparency, predictability, and adaptability in enterprises. And some relevant suggestions were put forward to address the corresponding issues, including developing strategies to attract talent, data encryption technology, and strengthening infrastructure. In addition, it points out the limitations of Digital transformation caused by the different sizes and locations of retailers. These will help Decathlon and other retailers to clarify the direction and method of transformation.
- Copyright
- © 2023 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 - Yankun Yang PY - 2023 DA - 2023/11/27 TI - The Digital Transformation of the Retail Industry, Taking Decathlon as an Example BT - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023) PB - Atlantis Press SP - 817 EP - 824 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-300-9_84 DO - 10.2991/978-94-6463-300-9_84 ID - Yang2023 ER -