Title: Big data analytics adoption: an empirical study in the Malaysian warehousing sector
Authors: Siti Norida Wahab; Muhammad Iskandar Hamzah; Nazura Mohamed Sayuti; Wei Chern Lee; Say Yik Tan
Addresses: Department of Logistics Management, Faculty of Business and Information Science, UCSI University, KL Campus, 56000, Kuala Lumpur, Malaysia ' Department of Entrepreneurship and Marketing Studies, Faculty of Business and Management, Universiti Teknologi MARA Cawangan Selangor, Kampus Puncak Alam, 42300 Bandar Puncak Alam, Selangor, Malaysia ' Faculty of Business and Management, Universiti Teknologi MARA Cawangan Selangor, Kampus Puncak Alam, 42300 Bandar Puncak Alam, Selangor, Malaysia ' Department of Logistics Management, Faculty of Business and Information Science, UCSI University, KL Campus, 56000, Kuala Lumpur, Malaysia ' Department of Logistics Management, Faculty of Business and Information Science, UCSI University, KL Campus, 56000, Kuala Lumpur, Malaysia
Abstract: This paper aims to identify the factors affecting big data analytics (BDA) adoption in the Malaysian warehousing sector. The technology-organisation-environment (TOE) model serves as the underpinning framework. The survey data from 110 logistics firms were collected and analysed using PLS-SEM. The empirical results revealed that relative advantage, technological infrastructure, absorptive capability and government support influence the levels of BDA adoption, whilst industry competition appeared to be of no significant influence. This study is expected to facilitate warehousing firms in implementing the most appropriate strategies in adopting BDA. Warehousing firms that place great emphasis on operational superiority, ICT infrastructures, and technology assimilation, are more likely to adopt BDA. Considering that there is a paucity of evidence regarding the determinants of BDA adoption among Malaysian warehousing firms, this study enriches TOE-based literature on BDA. Furthermore, the findings potentially assist logistics practitioners in developing a holistic blueprint in managing their large data sets.
Keywords: big data analytics; BDA; warehousing; sustainable warehouse; fourth industrial revolution; IR 4.0; technological advancement.
DOI: 10.1504/IJLSM.2021.117703
International Journal of Logistics Systems and Management, 2021 Vol.40 No.1, pp.121 - 144
Received: 11 May 2019
Accepted: 29 Aug 2019
Published online: 21 Sep 2021 *