Abstract

This study aims to investigate the complex relationship between the capabilities of Big Data, knowledge management, organizational learning, and how they collectively impact the performance of small and medium-sized firms (SMEs) in Singapore's IT industry. This study aims to demonstrate the mediating role of organizational learning processes and knowledge management in the relationship between Big Data capabilities and company performance. To achieve this, a dataset of 300 organizations will be analyzed using simple random sampling and Structural Equation Modeling-Partial Least Squares (SEM-PLS). Extensive research has shown that knowledge management and organizational learning play a crucial role in maximizing the usefulness of Big Data capabilities and enhancing business performance. The results demonstrate the need of combining knowledge management and organizational learning with Big Data initiatives to create an environment that promotes performance enhancement. This integration enables a mutually beneficial influence that motivates businesses to produce exceptional results, particularly those working in the highly competitive technology industry. The study's conclusions emphasize the crucial role of knowledge management and organizational learning as intermediary roles for Big Data to fully realize its potential. The findings have significant ramifications for technology enterprises that are small or medium-sized. They propose a reevaluation of their strategic objectives that include a comprehensive approach to overseeing Big Data, knowledge, and learning. These aspects are crucial for a company's success in the modern digital environment.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.