Understanding the role of ICT in South African Sustainable Manufacturing Practice

Abstract

Existing literature perceived Economic, Social and Environmental (ESE) factors as three key drivers of Sustainable Manufacturing Practice (SMP). ICT is not considered as a driving factor, but only as a tool that supports the achievement of SMP. The aim of this study is to investigate the role of ICT in achieving SMP in South Africa. A systematic literature review was conducted. The Google Scholar search engine was used to retrieve 1,352 articles that were analysed in this study. Themes and constructs were analysed based on the scope of the study. The findings revealed that South African manufacturing stakeholders are leveraging the advancement of ICT such as Artificial Intelligence and smart production systems to drive SMP through reduced waste and optimisation of resources. Also, the findings revealed that ICT plays a significant role that warrant its consideration as a fourth factor that drives SMP. This study emphasised the role of ICT as a driver in achieving SMP and presents the ESET model (ESE with the addition of Technology) to support the argument that ICT is a major driving factor for SMP. Understanding the role of ICT can influence how the issues of SMP are addressed and stakeholders can rethink strategies for SMP. Further empirical studies with a broader scope are encouraged because the review process and the scope of this study limits its generalisability

ICT, energy consumption, financial development, and environmental degradation in South Africa

“…We present discussions of the empirical outputs of two models (i) basic model that explores the impact of fixed telephone subscription while adjusting for the effect of renewable energy consumption and fossil fuel consumption, and (ii) standard model where the basic model is controlled for the effect of trade openness, financial development and GDP per capita. 2 The diagnostics and estimates of Model 1 are presented in Panel A and Panel B of Table 5, respectively. The F-statistics of the Bounds test is greater than the critical value of the upper bound suggesting that there is a long-run relationship between the variables based on ARDL (1,1,1) specification.…”