Adoption of artificial intelligence for manufacturing SMEs’ growth and survival in South Africa

A systematic literature review

Authors

  • Emmanuel Akoh Durban University of Technology

DOI:

https://doi.org/10.20525/ijrbs.v13i6.3561

Keywords:

Artificial intelligence, manufacturing SMEs, benefits, challenges, South Africa

Abstract

This study advances research and practice related to adopting artificial intelligence (AI) in the context of South Africa (SA). The study evaluated AI adoption by South African manufacturing Small and Medium Enterprises (SMEs); established the challenges faced by manufacturing SMEs in adopting AI; and developed a framework for adopting AI for manufacturing SMEs’ growth and survival. The study adopted a systematic literature review approach. Articles from Scopus and Google scholar databases, ranging from the years 2018 to 2024, were used. Of the 206 articles found, 54 were shortlisted. The systematic review analysis was performed using the PRISMA framework. The results identified AI adoption by South African manufacturing SMEs is low, limiting their innovation and productivity. The results also show, despite the numerous benefits AI adoption can offer manufacturing SMEs in the country, a major constraint is the lack of a framework to enhance adoption and implementation. Hence, this study was conducted to develop a framework to improve AI adoption by South African manufacturing SMEs. The findings contribute to the body of knowledge and provide new insights to manufacturing SME owners/managers, policymakers and practitioners into AI adoption to enhance manufacturing SMEs’ ability to compete on the global stage.

Downloads

Download data is not yet available.

References

Aarstad, A., & Saidl, M. (2019). Barriers to adopting AI technology in SMEs. A multiple case study on perceived barriers discouraging Nordic Small and Medium-size Enterprises to adopt Artificial Intelligence-Based solutions. [master’s thesis]: Copenhagen Business School. https://research-api.cbs.dk/ws/portalfiles/portal/60704162/790410_Aarstad_Saidl_Barriers_to_Adopting_AI_Technology_in_SMEs.pdf.

Achieng, M. S., & Malatji, M. (2022). Digital transformation of small and medium enterprises in Sub-Saharan Africa: A scoping review. Journal of Transdisciplinary Research in Southern Africa. 18(1), 01-13. https://doi.org/10.4102/td.v18i1.1257 DOI: https://doi.org/10.4102/td.v18i1.1257

Adão, V., Vincent, M., & Davies, M. (2019). The Fourth Industrial Revolution is here – are South African executives ready? Deloitte. https://www2.deloitte.com/za/en/pages/consumer-industrial-products/articles/industry-4-0--are-you-ready.html [Accessed June 18, 2024].

Ade-Ibijola, A., & Okonkwo, C. (2023). “Artificial Intelligence in Africa: Emerging challenges,” in Responsible AI in Africa. Social and Cultural Studies of Robots and AI, eds. D. O. Eke, K. Wakunuma, and S. Akintoye (Palgrave Macmillan, Cham). https://doi.org/10.1007/978-3-031-08215-3_5 DOI: https://doi.org/10.1007/978-3-031-08215-3_5

Akoh, E. I., & Lekhanya, L. M. (2022). Social entrepreneurship and networking challenges: Impact on sustainable development in South Africa. Problems and Perspectives in Management. 20(4), 195-209. https://doi.org/10.21511/ppm.20(4).2022.15 DOI: https://doi.org/10.21511/ppm.20(4).2022.15

Alexandra, R. (2022). Key opportunities and challenges for 4IR in South Africa. Working Paper Series WP 2021-8d. SARChi Industrial Development, University of Johannesburg. https://www.uj.ac.za/wp-content/uploads/2021/10/sarchi-wp-2021-08d-alexander-october-2022.pdf. [Accessed June 20, 2024].

Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial intelligence adoption: AI readiness at firm level. Pacific Asia Conference on Information System (PACIS) proceedings. 37. https://aisel.aisnet.org/pacis2018/37

Amankwah-Amoah, J., & Lu, Y. (2022). Harnessing AI for business development: a review of drivers and challenges in Africa. Production Planning & Control, The Management of Operations, pp. 1-10. https://doi.org/10.1080/09537287.2022.2069049 DOI: https://doi.org/10.1080/09537287.2022.2069049

Aron, J. (2023). Alan Turing. The father of modern computer science. New Scientist. https://newscientist.com/people/alan-turing [Accessed June 15, 2024].

Ateba, B. B., Prinsloo, J. J., & Gawlik, R. (2019). The significance of electricity supply sustainability to industrial growth in South Africa. Energy Reports, 5, 1324-1338. https://doi.org/10.1016/j.egyr.2019.09.041 DOI: https://doi.org/10.1016/j.egyr.2019.09.041

Badghish, S., & Soomro, Y. A. (2024). Artificial intelligence adoption by SMEs to achieve sustainable business performance: Application of Technology-Organisation-Environment framework. Sustainability, 16(5), 1864. https://doi.org/10.3390/su16051864 DOI: https://doi.org/10.3390/su16051864

Baker, J. (2011). The Technology-Organisation-Environment framework. In book: Information Systems Theory, Chapter 12. Publisher: University of Hamburg, Germany. https://doi.org/10.1007/978-1-4419-6108-2_12 DOI: https://doi.org/10.1007/978-1-4419-6108-2_12

Balbaa, M., & Abdurashidova, M. (2024). The impact of artificial intelligence in decision making: A comprehensive review. EPRA International Journal of Economics, Business and Management Studies, 11(2), 27-38. https://doi.org/10.36713/epra15747 DOI: https://doi.org/10.36713/epra15747

Bettoni, A., Matteri, D., Montini, E., Gladysz, B., & Carpanzano, E. (2021). An AI adoption model for SMEs: a conceptual framework. IFAC PaperOnLine. 54(1), 702-708. https://doi.org/10.1016/j.ifacol.2021.08.082 DOI: https://doi.org/10.1016/j.ifacol.2021.08.082

Bhalerao, K., Kumar, A., Kumar, A., & Pujari, P. (2022). A study of barriers and benefits of artificial intelligence adoption in small and medium enterprise. Academy of Marketing Studies Journal. 26(S1), 1-6.

Brand, D. J. (2022). Responsible artificial intelligence in government: Development of a legal framework for South Africa. Journal of eDemocrac,. 14(1), 130-150. https://doi.org/10.29379/jedem.v14i1.678 DOI: https://doi.org/10.29379/jedem.v14i1.678

Brown, R., & Lee, N. (2014). Funding issues confronting high growth SMEs in the UK. ICAS. Edinburg, UK. https://eprints.lse.ac.uk/57264/1/Brown_Lee_Funding-issues-confronting-high-growth-SMEs-in-the-UK_2014.pdf. [Accessed June 9, 2024].

Chatterjee, S., Rana, N., Dwivedi, Y. K., & Baabdullah, A. M. (2021). Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model. Technological Forecasting and Social Change, 170(5), 120880. https://doi.org/10.1016/j.techfore.2021.120880 DOI: https://doi.org/10.1016/j.techfore.2021.120880

Chaudhuri, R., Chatterjee, S., Vrontis, D., & Chaudhuri, S. (2022). Innovation in SMEs, AI dynamism, and sustainability: The current situation and way forward. Sustainability, 14(19), 12760. https://doi.org/10.3390/su141912760 DOI: https://doi.org/10.3390/su141912760

Chintala, S. (2022). Data privacy and security challenges in AI-driven healthcare systems in India. Journal of Data Acquisition and Processing. 37(5): 2769-2778. https://doi.org/10.5281/zenodo.776608

Dasgupta, A., & Wendler, S. (2019). AI adoption strategies. Centre for Technology & Global Affairs. Working Paper Series, No 9. University of Oxford.

Davis, N. (2016). What is the Fourth Industrial Revolution? https://www.weforum.org/agenda/2016/01/what-is-the-fourth-industrial-revolution/ [Accessed June 11, 2024].

DePietro, R., Wiarda, E., & Fleisher, M. (1990). The context for change: Organization, technology and environment. The processes of technological innovation. Massachusetts, USA: Lexington Books.

Engel, U., & Dahlhaus, L. (2021). Data quality and privacy concerns in digital trace data: Insights from a Delphi study on machine learning and robots in human life, in Handbook of Computational Social Science Vol 1.. (Taylor & Francis). https://doi.org/10.4324/9781003024583-23 DOI: https://doi.org/10.4324/9781003024583-23

Futcher, M. (2018). Competitive advantage during industry 4.0: The case of South African Manufacturing SMEs. A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Engineering. https://wiredspace.wits.ac.za/server/api/core/bitstreams/9398fbb4-ca08-4d51-9724-55555213b627/content. [Accessed June 13, 2024].

Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence of South Africa manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182: 121785. https://doi.org/10.1016/j.techfore.2022.121785 DOI: https://doi.org/10.1016/j.techfore.2022.121785

Ghani, E. K., Ariffin, N., & Sukmadilaga, C. (2022). Factors influencing artificial intelligence adoption in publicly listed manufacturing companies: A technology, organisation, and environment approach. International Journal of Applied Economics, Finance and Accounting, 14(2), 108-117. https://doi.org/10.33094/ijaefa.v14i2.667 DOI: https://doi.org/10.33094/ijaefa.v14i2.667

Ghobakhloo, M., & Ching, N. T. (2019). Adoption of digital technologies of smart manufacturing in SMEs. Journal of Industrial Information Integration, 16, 100107. https://doi.org/10.1016/j.jii.2019.100107 DOI: https://doi.org/10.1016/j.jii.2019.100107

Gusenbauer, M., & Haddaway, N. R. (2020). Which academic search systems are suitable for systematic reviews or meta-analysis? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources. Research Synthesis Methods, 11(2), 181-217. https://doi.org/10.1002/jrsm.1378 DOI: https://doi.org/10.1002/jrsm.1378

Gwagwa, A., Kachidza, P., Siminyu, K., & Smith, M. (2021). Responsible artificial intelligence in Sub-Saharan Africa: Landscape and general state of play. International Development Research Centre. file:///C:/Users/inaak/Downloads/739b3b9a-6a8a-4b32-8db8-291cb621d2dd.pdf. [Accessed June 12, 2024].

Hirzallah, M. N. Y., & Alshurideh, M. T. R. (2023). The effects of the internal and the external factors affecting artificial intelligence (AI) adoption in e-innovation technology projects in the UAE? Applying both innovation and technology acceptance theory. International Journal of Data and Network Science, 7, 1321-1332. https://doi.org/10.5267/j.ijdns.2023.4.006 DOI: https://doi.org/10.5267/j.ijdns.2023.4.006

Hong, S. J., & Cho, H. (2023). The role of uncertainty and affect in decision-making on the adoption of AI-based contact tracing technology during the Covid-19 pandemic. Digital Health, 9. https://doi.org/10.1177/20552076231169836 DOI: https://doi.org/10.1177/20552076231169836

Hradecky, D., Kennell, J., Cai, W., & Davidson, R. (2022). Organisational readiness to adopt artificial intelligence in the exhibition sector in Western Europe. International Journal of Information Management, 65, 102497. https://doi.org/10.1016/j.ijinfomgt.2022.102497 DOI: https://doi.org/10.1016/j.ijinfomgt.2022.102497

Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes: An interview study of organisational AI readiness factor. Business & Information System Engineering, 63, 5-20. https://doi.org/10.1007/s12599-020-00676-7 DOI: https://doi.org/10.1007/s12599-020-00676-7

Kim, S. W., Kong, J. H., Lee, S. W., & Lee, S. (2022). Recent advances of artificial intelligence in manufacturing industrial sectors: A review. International Journal of Precision Engineering and Manufacturing, 23, 111-129. https://doi.org/10.1007/s12541-021-00600-3 DOI: https://doi.org/10.1007/s12541-021-00600-3

Kinkel, S., Baumgartner, M., & Cherubini, E. (2022). Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies. Tecnovation, 110, 102375. https://doi.org/10.1016/j.tenovation.2021.102375 DOI: https://doi.org/10.1016/j.technovation.2021.102375

Kruger, N., Dickason, Z., & Meyer, N. (2020). Factors affecting South Africa Small and Medium Enterprises risk identification and management. Journal of Contemporary Management, 17(2), 347-368. https://doi.org/10.35683/jcm20031.79 DOI: https://doi.org/10.35683/jcm20031.79

Kurup, S., & Gupta, V. (2022). Factors influencing the AI adoption in organisations. Metamorphosis, 21(2), 129-139. https://doi.org/10.1177/09726225221124035 DOI: https://doi.org/10.1177/09726225221124035

Lada, S., Chekima, B., Karim, M, R. A., Fabeil, N. F., Ayub, M. S., Amirul, S. M., Ansar, R., Bouteraa, M., Fook, L. M., & Zaki, H. O. (2023). Determining factors related to artificial intelligence (AI) adoption among Malaysia’s small and medium-sized businesses. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100144. https://doi.org/10.1016/j.joitmc.2023.100144 DOI: https://doi.org/10.1016/j.joitmc.2023.100144

Li, G., Hou, Y., Wu, A. (2017). Fourth Industrial Revolution: Technological drivers, impact and coping methods. Chinese Geographical Science, 27, 626-637. https://doi.org/10.1007/s11769-017-0890-x DOI: https://doi.org/10.1007/s11769-017-0890-x

Lu, X., Wijayaratna, K., Huang, Y., & Qiu, A. (2022). AI-enabled opportunities and transformation challenges for SMEs in the post-pandemic era: A review and research agenda. Front Public Health, 10, 885067. https://doi.org/10.3389/fpubh.2022.885067 DOI: https://doi.org/10.3389/fpubh.2022.885067

Mabotja, L. L. (2018). Is South African Manufacturing SMMEs ready for the Fourth Industrial Revolution. Journal of Education and Vocational Research, 9(2), 20-26. https://doi.org/10.22610/jevr.v9i2(V).2798 DOI: https://doi.org/10.22610/jevr.v9i2(V).2798

Madzhadzhi, T. (2023). Overcoming barriers to AI adoption by SMEs. https://www.itweb.co.za/content/lwrKxv3YmbLMmg1o [Accessed June 7, 2024].

Maisiri, W., van Dyk, L., & Coeztee, R. (2021). Factors that inhibit sustainable adoption of industry 4.0 in the South African manufacturing industry. Sustainability, 13(3), 1013. https://doi.org/10.3390/su13031013 DOI: https://doi.org/10.3390/su13031013

Makina, D. (2022). Artificial Intelligence technology and their challenges in Africa. https://financialmarketsjournal.co.za/artificial-intelligence-technologies-and-their-challenges-in-africa/ [Accessed June 10, 2024].

McKinsey & Company. (2022). What are Industry 4.0, the Fourth Industrial Revolution, and 4IR? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-are-industry-4-0-the-fourth-industrial-revolution-and-4ir [Accessed June 11, 2024].

McKinsey & Company. (2023). What is AI? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-ai [Accessed June 15, 2024].

Min, S., & Kim, B. (2024). Adopting artificial intelligence technology for network operations in digital transformation. Administrative Sciences, 14(4), 70. https://doi.org/10.3390/admsci14040070 DOI: https://doi.org/10.3390/admsci14040070

Msomi, T. S., & Olarewaju, O. M. (2022). Nexus of loan re-payment plan, interest loans and the sustainability of Small and Medium Enterprises in South Africa. Africa Journal of Inter/Multidisciplinary Studies, 4(1), 205-216. https://doi.org/10.51415/ajims.v4i1.976 DOI: https://doi.org/10.51415/ajims.v4i1.976

Nascimento, A. M., & Meirelles, F. S. (2022). Factors influencing the adoption intention of artificial intelligence in small business. ISLA 2022 Proceedings. https://aisel.aisnet.org/isla2022/20

Ndlovu, M., & Makgetla, N. (2017). Small business and industry policy. https://www.tips.org.za/images/REB_Small_Business_Edition_September_2017_.pdf. [Accessed June 12, 2024].

Ngibe, M., & Lekhanya, L. M. (2019). Critical Factors influencing innovative leadership in attaining business innovation: a case of manufacturing SMEs in KwaZulu-Natal. Int. Journal of Entrepreneurship, 23(2).

Ntuli, L. S. (2022). The influence of emerging technologies on Small and Medium Manufacturing Enterprises in eThekwini District Municipality of KwaZulu-Natal. [master’s thesis] Durban University of Technology.

Nwandu, E. (2016). Impact of rising interest rate on the performance of the Nigerian manufacturing sector. European Journal of Business and Management, 8(10), 125-134.

O’Shaughnessy, M. R., Schiff, D. S., Varshney, L. R., Rozell, C. J., & Davenport, M. A. (2022). What governs attitude toward artificial intelligence adoption and governance? file:///C:/Users/inaak/Downloads/oshaughnessy2022governs.pdf. [Accessed June 5, 2024]. DOI: https://doi.org/10.31219/osf.io/pkeb8

Oclarino, R. (2021). Enabling an AI-ready culture. https://www.iso.org/news/ref2763.html. [Accessed June 7, 2024].

Okoye, C. C., Nwankwo, E. E., Usman, F. O., Mhlongo, N. Z., Odeyemi, O., & Ike, C. U. (2024). Accelerating SMEs growth in the African context: Harnessing FinTech, AI, and cybersecurity for economic prosperity. International Journal of Science and Research Archive. 11(1), 2477-2486. https://doi.org/10.30574/ijsra.2024.11.1.0231 DOI: https://doi.org/10.30574/ijsra.2024.11.1.0231

Olaitan, O. O., Issah, M., & Wayi, N. (2021). A framework for to test South Africa’s readiness for the Fourth Industrial Revolution. South African Journal of Information Management, 23(1), 1-10. http://dx.doi.org/10.4102/sajim.v23i1.1284 DOI: https://doi.org/10.4102/sajim.v23i1.1284

Oldemeyer, L., Jede, A., & Teuteberg, F. (2024). Investigation of Artificial Intelligence in SMEs: a systematic review of the state of the art and the main implementation challenges. Management Review Quarterly, 1-43. https://doi.org/10.1007/s11301-024-00405-4 DOI: https://doi.org/10.1007/s11301-024-00405-4

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. U., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., McGuiness, L. A., Stewart, L. A., Thomas, J., Tricco, A. C., Welch, V. A., Whiting, P., & Moher, D. (2021). The PRISMA 2020 statement: An updated guidelines for reporting systematic reviews. Systematic Reviews, 10(89), https://doi.org/10.1186/s13643-021-01626-4 DOI: https://doi.org/10.31222/osf.io/v7gm2

Palade, M., & Carutasu, G. (2023). Organisational readiness for artificial intelligence adoption. Transitions on Engineering and Management, 7(1&2), 30-35. https://doi.org/10.59168/FDMS6321 DOI: https://doi.org/10.59168/FDMS6321

Peretz-Andersson, E., Tabares, S., Mikalef, P., & Parida, V. (2024). Artificial Intelligence implementation in manufacturing SMEs: A resource orchestration approach. International Journal of Information Management, 77, 102781. https://doi.org/10.1016/j.ijinfomgt.2024.102781 DOI: https://doi.org/10.1016/j.ijinfomgt.2024.102781

Petrillo, A., De Felice, F., Coiffi, R., & Zomparelli, F. (2018). Fourth industrial revolution: Current practices, challenges, and opportunities. Digital Transformation in Smart Manufacturing, 1, 1-20. https://doi.org/10.5772/intechopen.72304 DOI: https://doi.org/10.5772/intechopen.72304

Philbeck, T., & Davis, N. (2018). The Fourth Industrial Revolution: Sharing a new era. Journal of International Affairs, 72(1), 17-22. https://www.jstor.org/stable/26588339

Pillay, P. (2016). Barriers to information and communication technology (ICT) adoption and use amongst SMEs: A study of the South Africa manufacturing sector. [master’s thesis] University of the Witwatersrand.

Pinski, M., Hofmann, T., & Benlian, A. (2024). AI literacy for top management: An upper echelons perspective on corporate AI orientation and implementation ability. Electron Markets, 34(24), 1-23. https://doi.org/10.1007/s12525-024-00707-1 DOI: https://doi.org/10.1007/s12525-024-00707-1

Plantinga, P. (2022). Digital discretion and public administration in Africa: Implications for the use of artificial intelligence. Information Development, pp. 1-21, https://doi.org/10.1177/02666669221117526 DOI: https://doi.org/10.31235/osf.io/2r98w

Puklavec, B., Oliveira, T., & Popovic, A. (2014). Unpacking business intelligence systems adoption determinants: An exploration study of Small and Medium Enterprises. Economic and Business Review, 16(2), 185-213. https://doi.org/10.15458/2335-4216.1278 DOI: https://doi.org/10.15458/2335-4216.1278

Ramdani, B., Chevers, D., & Williams, D. A. (2013). SMEs’ adoption of enterprise applications: A technology-organisation-environment model. Journal of Small Business and Enterprise Development, 20(4), 735-753. https://doi.org/10.1108/JSBED-12-2011-0035 DOI: https://doi.org/10.1108/JSBED-12-2011-0035

Rao, T. (2017). Factors critical to the organisational adoption of Artificial Intelligence: A South African perspective. [master’s thesis]. Gordon Institute of Business Science: University of Pretoria, https://repository.up.ac.za/bitstream/handle/2263/64917/ Rao_Factors_2017.pdf?sequence=1&isAllowed=y [Accessed June 14, 2024].

Rodríguez-Espíndola, O., Chowdhury, S., Dey, P. K., Albores, P., & Emrouznejad, A. (2022). Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing. Technological Forecasting and Social Change, 178, 121562. https://doi.org/10.1016/j.techfore.2022.121562 DOI: https://doi.org/10.1016/j.techfore.2022.121562

Schoeman, F., & Seymour, L. F. (2022). Understanding the low Adoption of AI in South African Medium-Sized Organisations. A. Gerber (ed.), SAICSIT 2022 (EPiC Series in Computing), 85, 257-269

Serumaga-Zake, J. M., & van der Poll, J. A. (2021). Addressing the impact of fourth industrial revolution on South African Manufacturing Small and Medium Enterprises (SMEs). Sustainability, 13(21), 11703. https://doi.org/10.3390/su132111703 DOI: https://doi.org/10.3390/su132111703

Seseni, L., & Mbohwa, C. (2018). The implications of artificial intelligence on Soweto furniture manufacturing SMEs. Proceedings from: International Conference on Industrial Engineering and Operation Management, Washington DC, USA. http://ieomsociety.org/dc2018/papers/447.pdf. [Accessed May 30, 2024].

Seseni, L., & Mbohwa, C. (2021). The significance of big data in the success of SMEs in emerging markets: A case of South Africa. Proceedings of 11th Annual International Conference on Industrial Engineering and Operations Management, Singapore. https://www.ieomsociety.org/singapore2021/papers/376.pdf. [Accessed May 30, 2024]. DOI: https://doi.org/10.46254/AN11.20210376

Sestino, A., & De Mauro, A. (2021). Leveraging artificial intelligence in business: Implications, applications and methods. Technology Analysis and Strategic Management, 34(2), 1-14. https://doi.org/10.1080/09537325.2021.1883583 DOI: https://doi.org/10.1080/09537325.2021.1883583

Small Business Institute (SBI). (2018). The number of formal micro, small & medium businesses in South Africa-SBI. https://www.smallbusinessinstitute.co.za/ 2018/10/31/the-number-of-formal-micro-smallmedium-businesses-in-south-africa-preliminary-findings-of-stage-1-of-the-baseline-study-of-small-business-insouth-africa/SBIbaselineAlert1final [Accessed May 25, 2024].

Small Enterprise Development Agency (SEDA). (2022). SMME Quarterly Update 3rd Quarter 2021. http://www.seda.org.za/Publications/Publications/SMME%20Quarterly %202021Q3%20(002).pdf. [Accessed May 23, 2024].

Soratto, J., Pires, D. E. P. d., & Friese, S. (2020). Thematic content analysis using ATLAS.ti software: Potentialities for research in health. Revista Brasileira de Enfermagem, 73(3), 1-5. https://doi.org/10.1590/0034-7167-2019--0250 DOI: https://doi.org/10.1590/0034-7167-2019-0250

Taeihagh, A. (2022). Governance of artificial intelligence. Policy and Society, 40(2) 137-157. https://doi.org/10.1080/14494035.2021.1928377. DOI: https://doi.org/10.1080/14494035.2021.1928377

Tjebane, M. M., Musonda, I., & Okoro, C. (2022). Organisational factors of artificial intelligence adoption in the South African construction industry. Frontiers in Built Environment, 8, 823998 DOI: https://doi.org/10.3389/fbuil.2022.823998

Trading Economics. (2023). South African manufacturing production. https://tradingeconomics.com/south-africa/industrial-production [Accessed May 20, 2024].

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375 DOI: https://doi.org/10.1111/1467-8551.00375

Uwagaba, J., Omotosho, T. D., & George, G. O. (2023). Exploring the barriers to artificial intelligence adoption in Sub-Saharan Africa’s Small and Medium Enterprises and the potential for increased productivity. https://www.researchgate.net/publication/367678657_Title_Exploring_the_barriers_to_Artificial_Intelligence_adoption_in_sub-Saharan_Africa's_Small_and_Medium_Enterprises_and_the_potential_for_increased_productivity#fullTextFileContent [Accessed May 15, 2024].

Vaismoradi, M., Turunen, H., & Bondas, T. (2013). Content analysis and thematic analysis: Implications for conducting qualitative descriptive study. Nursing and Health Sciences, 15, 398-405. https://doi.org/10.1111/nhs.12048 DOI: https://doi.org/10.1111/nhs.12048

West, D. M., & Allen, J. R. (2018). How artificial intelligence is transforming the world. https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/ [Accessed May 10, 2024].

World Economic Forum (WEF). (2024). 6 ways to unleash the power of AI in manufacturing. https://www.weforum.org/agenda/2024/01/how-we-can-unleash-the-power-of-ai-in-manufacturing/ [Accessed July 24, 2024].

Yacob, P., & Peter, D. (2022) Perceived benefits of sustainable digital technologies adoption in manufacturing SMEs. International Journal of Innovation and Technology Management, 19(04), 2250012. https://doi.org/10.1142/S0219877022500122 DOI: https://doi.org/10.1142/S0219877022500122

Yoon, T. E., & George, J. F. (2013). Why aren’t organizations adopting virtual worlds? Computers in Human Behavior, 29, 772-790. https://doi.org/10.1016/j.chb.2012.12.003 DOI: https://doi.org/10.1016/j.chb.2012.12.003

Downloads

Published

2024-10-14

How to Cite

Akoh, E. (2024). Adoption of artificial intelligence for manufacturing SMEs’ growth and survival in South Africa: A systematic literature review. International Journal of Research in Business and Social Science (2147- 4478), 13(6), 23–37. https://doi.org/10.20525/ijrbs.v13i6.3561

Issue

Section

Strategic Approach to Business Ecosystem and Organizational Development