Technology Selection Under Multiple Alternatives: Identification and Prioritisation of Influencing Factors in Small and Medium Manufacturing Enterprises
Small and Medium-sized Manufacturing Enterprises (SMMEs) are increasingly adopting Fourth Industrial Revolution (4IR) technologies to improve supply chain performance; however, selecting the most suitable technology from multiple alternatives remains a complex decision-making challenge. This study identifies and prioritises the critical factors influencing technology selection in manufacturing SMMEs. Using qualitative data from ten experienced decision-makers and thematic analysis, ten key factors were identified: Cost, Strategic Alignment, Security, Functionality, Integration, Data Analytics, Ease of Use, Training, After-Sales Support, and Scalability. These factors were subsequently ranked using the Analytic Hierarchy Process (AHP). The results indicate that Strategic Alignment and Cost are the most influential factors, followed by Security, Functionality, and Integration. The findings suggest that SMMEs prioritise technologies that support organisational objectives, remain financially viable, ensure operational security, and integrate effectively with existing systems. Based on these findings, a preliminary Industry 4.0 technology selection framework is proposed to support the structured evaluation of technology alternatives using weighted decision criteria. The study offers practical guidance for managers seeking more informed and strategic technology investment decisions. Although the framework provides a useful foundation for technology selection, further empirical validation is required across different manufacturing contexts. Overall, the study contributes a systematic approach to improving technology adoption and supply chain optimisation within SMMEs.
Authors
- Refentse Lydia Selepe (ORCID: https://orcid.org/0000-0002-3174-7444)
- Thomas Munyai
- Olasumbo Makinde
Institutions
- Tshwane University of Technology (ZA)
- University of Johannesburg (ZA)
Publication Details
- Journal
- Systems
- Published
- 2026-10-09
- DOI
- https://doi.org/10.3390/systems14101265
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00