Search results

1 – 2 of 2
Article
Publication date: 11 April 2024

Norzalita Abd Aziz, Abdullah Al Mamun, Mohammad Nurul Hassan Reza and Farzana Naznen

This study aimed to examine the role of big data analytics capabilities (BDAC) in fostering organizational innovation capabilities and, consequently, in achieving economic, social…

Abstract

Purpose

This study aimed to examine the role of big data analytics capabilities (BDAC) in fostering organizational innovation capabilities and, consequently, in achieving economic, social and environmental sustainability.

Design/methodology/approach

Through the lens of dynamic capability theory, this study surveyed 115 hotels using purposive sampling to gain in-depth insights regarding the factors affecting organizational sustainability in the hospitality industry. The data analysis was conducted using partial least squares-structural equation modeling (PLS-SEM).

Findings

The findings reported a substantial impact of seven core dimensions (i.e. technology, data, basic resources, technological skills, managerial skills, organizational learning and data-driven culture) in building BDAC among hotels. Moreover, BDAC was also revealed to significantly influence innovation capabilities, positively impacting all three sorts of sustainability performance. Innovation capability also mediated the relationship between BDAC and all sustainability factors.

Practical implications

The findings will assist policymakers and practitioners in developing effective initiatives to enhance the adoption and implementation of data science and technologies, substantially contributing to the “National IR 4.0 Policy” and “Malaysia Digital Economy Blueprint” and achieving sustainable development goals (SDGs).

Originality/value

The originality of this study is established by investigating the interplay between BDAC, innovation capability and sustainability performance, particularly in the context of the hotel industry, whereas the existing studies focus on exploring the advantages of BDA.

Details

Journal of Enterprise Information Management, vol. 37 no. 3
Type: Research Article
ISSN: 1741-0398

Keywords

Abstract

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 4 no. 1
Type: Research Article
ISSN: 2633-6596

1 – 2 of 2