The acceptance of big data analytics factors in the smart supply chain performance among Malaysian small and medium-sized enterprises (SMEs)

Amir, Nur Syafiqah Najwa (2023) The acceptance of big data analytics factors in the smart supply chain performance among Malaysian small and medium-sized enterprises (SMEs). Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

	Text (24 Pages) The acceptance of big data analytics factors in the smart supply chain performance among Malaysian small and medium-sized enterprises (SMEs).pdf - Submitted Version Download (274kB)
	Text (Full Text) The acceptance of big data analytics factors in the smart supply chain performance among Malaysian small and medium-sized enterprises (SMEs).pdf - Submitted Version Restricted to Registered users only Download (1MB)

Abstract

Big Data Analytics (BDA) plays a vital role in achieving the target of the company in Smart Supply Chain performance (SSCP). The acceptance of big data analytics in Malaysian SMEs has becomes major barrier. This is because the SMEs in Malaysia are still left behind in how to integrate the big data analytics and have a lack of strong awareness of applying effective big data analytics to smart supply chain performance. Although, some of Malaysian Small and Medium-Sized Enterprises (SMEs) now realize the value of the adoption of big data analytics, but some of the SMEs are not actively using it. Therefore, this research is to study the acceptance of big data analytics on the smart supply chain performance and aim to determine the relationship between the dependent and the independent variables (adoption of BDA acceptance and the impact on smart supply chain performance). This research was conducted by using a quantitative method. This research will be focus on the employees who are working in the SME company who is in the work position of executive-level and above as they take more responsible in decision making. The data was collected from 120 respondents through a questionnaire design using Google Forms and an online platform. Therefore, the result from the Multiple Regression Analysis and Pearson’s Correlation Coefficient showed that both variables in this study had a significant and strong relationship together. In conclusion, through this research, it is hoped that it can provide the guideline to the SMEs for them to know the criteria that are needed for employees to apply and use the big data analytics on the smart supply chain in their work which can produce an effective and efficient way of doing business.

Actions (login required)

View Item