The role of smart technology, managerial initiatives and human factors on sustainable manufacturing: a case study of Indonesian oil and gas workers

Abstract

This study aims to analyse and determine the effect of Big Data, the Internet of Things (IoT), and physical-cyber system variables on human factors in refinery industry operators and the influence of human factors and managerial initiatives on sustainable manufacturing. The method used in this study is a quantitative method using partial least square-structural equation modelling (PLS-SEM). The respondents in this study were workers of Indonesia’s upstream oil and gas sector. The results of this study indicate that Big Data, IoT, and Physical Cyber Systems (PCS) have a positive and significant effect on the human factor. In addition, there is a significant relationship between human factors and sustainable manufacturing. Furthermore, it is also found that there is a relationship between managerial initiatives and sustainable manufacturing. However, the managerial initiative cannot moderate the human factor and sustainable manufacturing.

Practitioner Summary

This research explores the profound influence of Industry 4.0 technologies, encompassing big data, IoT, and physical-cyber systems (PCS), on the human aspects of Indonesia’s oil and gas sector. The outcomes of this study offer valuable perspectives on how Industry 4.0 technologies can revolutionise the Indonesian oil and gas industry while underscoring the significance of factoring in human elements and sustainable practices within this dynamic landscape.

Keywords:

• Human factor
• big data
• IoT
• physical cyber system
• sustainable manufacturing

Acknowledgment

We acknowledge the help of all the participants, the LPDP scholarship (for the co-author) from the Ministry of Finance of the Republic of Indonesia, and Universitas Muhammadiyah Malang. The funding body of this study did not influence the study design, interpretation of the data, or write-up of this paper.

Statement of informed consent

There are no human subjects in this article, and informed consent is not applicable.

Disclosure statement

The authors hereby declare that there are no potential conflicts of interest in terms of authorship, research, and/or publication of this article.

Code availability

Not applicable.

Ethics statement

The research involving non-sensitive data and not infringing upon privacy or sensitive matters is deemed to not require ethical approval.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author upon reasonable request.

Additional information

Funding

This manuscript was funded by BPPT (Badan Pengkajian dan Penerapan Teknologi) and LPDP (Lembaga Pengelola Dana Pendidikan).