The impact of industry 4.0 on South Africa’s manufacturing sector
This study investigates the impacts of Industry 4.0 (I4.0) on the South African manufacturing sector in light of the Fourth Industrial Revolution (4IR) and the Industry 4.0 concept. The South African manufacturing sector, consisting of approximately 11,400 VAT-registered organizations, is explored i...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Journal of Open Innovation: Technology, Market and Complexity |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2199853124000209 |
| _version_ | 1797217079288397824 |
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| author | Nicholas Ngepah Charles Shaaba Saba David Oluwaseun Kajewole |
| author_facet | Nicholas Ngepah Charles Shaaba Saba David Oluwaseun Kajewole |
| author_sort | Nicholas Ngepah |
| collection | DOAJ |
| description | This study investigates the impacts of Industry 4.0 (I4.0) on the South African manufacturing sector in light of the Fourth Industrial Revolution (4IR) and the Industry 4.0 concept. The South African manufacturing sector, consisting of approximately 11,400 VAT-registered organizations, is explored in a novel approach. No prior study has analyzed the cointegrating and long-run effects of I4.0 on this sector. The autoregressive distributed lag (ARDL) model is employed, accommodating both stationary and nonstationary variables without recalculating the order of integration. To address endogeneity, small sample bias, serial correlation, and heterogeneity, the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) models are estimated. Long-run relationships among variables, including manufacturing value added (MVA), I4.0, carbon dioxide emissions, Foreign Direct Investments (FDI), and inflation, are considered. Vector Autoregressive (VECM) modeling is used to establish causality relationships, while the Cumulative Dynamic Multiplier (CDM) visually illustrates impact relationships. Data from the World Bank's WDI (2023), covering the period 2000Q1–2020Q4, are employed. Key findings include a significant negative relationship between I4.0 and South Africa's MVA. Policy implications suggest substantial investments in advanced education, Information and Communications Technology (ICT), and medium to high technology exploration. The study reveals positive associations between carbon dioxide and MVA, significant short and long-run impacts of FDI on MVA, and a long-run relationship between inflation and MVA. These insights provide valuable considerations for strategic investments and policy decisions in the context of technological advancements. |
| first_indexed | 2024-03-08T04:07:13Z |
| format | Article |
| id | doaj.art-120f000565214a8482d1f6c116c816df |
| institution | Directory Open Access Journal |
| issn | 2199-8531 |
| language | English |
| last_indexed | 2024-04-24T11:56:09Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Open Innovation: Technology, Market and Complexity |
| spelling | doaj.art-120f000565214a8482d1f6c116c816df2024-04-09T04:12:59ZengElsevierJournal of Open Innovation: Technology, Market and Complexity2199-85312024-03-01101100226The impact of industry 4.0 on South Africa’s manufacturing sectorNicholas Ngepah0Charles Shaaba Saba1David Oluwaseun Kajewole2School of Economics, College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, South AfricaCorresponding author.; School of Economics, College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, South AfricaSchool of Economics, College of Business and Economics, University of Johannesburg, Auckland Park Kingsway Campus, South AfricaThis study investigates the impacts of Industry 4.0 (I4.0) on the South African manufacturing sector in light of the Fourth Industrial Revolution (4IR) and the Industry 4.0 concept. The South African manufacturing sector, consisting of approximately 11,400 VAT-registered organizations, is explored in a novel approach. No prior study has analyzed the cointegrating and long-run effects of I4.0 on this sector. The autoregressive distributed lag (ARDL) model is employed, accommodating both stationary and nonstationary variables without recalculating the order of integration. To address endogeneity, small sample bias, serial correlation, and heterogeneity, the Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) models are estimated. Long-run relationships among variables, including manufacturing value added (MVA), I4.0, carbon dioxide emissions, Foreign Direct Investments (FDI), and inflation, are considered. Vector Autoregressive (VECM) modeling is used to establish causality relationships, while the Cumulative Dynamic Multiplier (CDM) visually illustrates impact relationships. Data from the World Bank's WDI (2023), covering the period 2000Q1–2020Q4, are employed. Key findings include a significant negative relationship between I4.0 and South Africa's MVA. Policy implications suggest substantial investments in advanced education, Information and Communications Technology (ICT), and medium to high technology exploration. The study reveals positive associations between carbon dioxide and MVA, significant short and long-run impacts of FDI on MVA, and a long-run relationship between inflation and MVA. These insights provide valuable considerations for strategic investments and policy decisions in the context of technological advancements.http://www.sciencedirect.com/science/article/pii/S2199853124000209Industry 4.0Information and communications technology (ICT)Manufacturing value added (MVA)High-techNonlinear autoregressive distributed lag (NARDL)South Africa |
| spellingShingle | Nicholas Ngepah Charles Shaaba Saba David Oluwaseun Kajewole The impact of industry 4.0 on South Africa’s manufacturing sector Journal of Open Innovation: Technology, Market and Complexity Industry 4.0 Information and communications technology (ICT) Manufacturing value added (MVA) High-tech Nonlinear autoregressive distributed lag (NARDL) South Africa |
| title | The impact of industry 4.0 on South Africa’s manufacturing sector |
| title_full | The impact of industry 4.0 on South Africa’s manufacturing sector |
| title_fullStr | The impact of industry 4.0 on South Africa’s manufacturing sector |
| title_full_unstemmed | The impact of industry 4.0 on South Africa’s manufacturing sector |
| title_short | The impact of industry 4.0 on South Africa’s manufacturing sector |
| title_sort | impact of industry 4 0 on south africa s manufacturing sector |
| topic | Industry 4.0 Information and communications technology (ICT) Manufacturing value added (MVA) High-tech Nonlinear autoregressive distributed lag (NARDL) South Africa |
| url | http://www.sciencedirect.com/science/article/pii/S2199853124000209 |
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