Overcoming Entrepreneurial Challenges with Big Data Analytics Adoption to Accelerate Economic Recovery: Evidence from Malaysian Small Medium Enterprises
- DOI
- 10.2991/aebmr.k.220501.033How to use a DOI?
- Keywords
- Small Medium Enterprises; Malaysia; Absorptive Capacity; Big Data Analytics; Performance; Technological Resource Competency
- Abstract
COVID-19, the worldwide epidemic coronavirus illness, has a substantial influence on the world economy. Big Data Analytics (BDA) assists organization in gaining relevant insights, is being hailed as a new tactical weapon in the sector during this pandemic covid-19 period. This study looked at the impact of organizational factors on BDA adoption to boost business by enhancing organizational performance. SmartPLS 3.3.2 was used to analyse data from 185 manufacturing SMEs in Malaysia in this study. This research identifies key organizational factors that influence BDA adoption and it impact on the organizational performance. The novelty of this research is significant as it integrate organizational context with adoption big data analytics on the impact of organizational performance to example a holistic view of research model. The findings facilitate Malaysian SMEs in strategizing BDA adoption, the changing business climate, and may serve as a model for businesses in developing countries as a key driver in accelerating economic recovery.
- Copyright
- © 2022 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license.
Cite this article
TY - CONF AU - Chun Hong Loh AU - Ai Ping Teoh AU - Keni Keni PY - 2022 DA - 2022/05/11 TI - Overcoming Entrepreneurial Challenges with Big Data Analytics Adoption to Accelerate Economic Recovery: Evidence from Malaysian Small Medium Enterprises BT - Proceedings of the tenth International Conference on Entrepreneurship and Business Management 2021 (ICEBM 2021) PB - Atlantis Press SP - 213 EP - 218 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.220501.033 DO - 10.2991/aebmr.k.220501.033 ID - Loh2022 ER -