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Author
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Rangarirai, Tapiwa H.
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Title
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Impact of artificial intelligence on supplier selection and evaluation performance in the public sector in Zimbabwe: case of ZESA Holdings
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Abstract
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The study sought to establish impact of Artificial Intelligence (AI) on supplier selection and evaluation performance at ZESA Holdings. In the evolving landscape of Zimbabwe's public sector, ZESA Holdings stands at the forefront of contending with procurement inefficiencies and transparency issues, fundamental challenges that undermine its operational efficiency and public trust. Internal audits reveal a concerning 25% discrepancy in supplier performance evaluations due to subjective decision-making and manual processes. Concurrently, procurement cycle times extend beyond the 90-day standard, with approximately 30% of projects experiencing delays attributed to protracted supplier selection processes. The study's objectives included determining AI's effect on enhancing supplier quality assessment, evaluating its impact on cost efficiency in supplier selection, assessing its role in optimizing delivery and reliability evaluations, and exploring the challenges of implementing AI in supplier evaluation at ZESA Holdings. An explanatory research design was employed, and data was collected using structured questionnaires from a sample of 75 respondents selected through simple random sampling. The data analysis involved both descriptive and inferential statistics. The findings indicated several significant positive impacts of AI implementation on supplier evaluation. A positive coefficient for AI implementation (Estimate = 0.345, Sig. = .006) suggests that higher levels of AI implementation are significantly associated with better supplier evaluations. Similarly, AI training (Estimate = 0.456, Sig. = .004) shows that improved training on AI tools leads to better supplier evaluations. The accuracy of AI tools (Estimate = 0.567, Sig. = .009) is also significantly associated with improved supplier evaluations, indicating the importance of using accurate AI systems. The findings indicated that AI implementation significantly contributes to cost reduction, with an estimate of 0.423 and a significance level of 0.001, showing that higher levels of AI implementation are associated with improved cost efficiency. Furthermore, AI training emerged as a critical factor, with an estimate of 0.562 and a significance level of 0.017, suggesting that better training on AI tools enhances cost efficiency in supplier selection. The results showed that higher levels of AI implementation are associated with better delivery timeliness, as evidenced by the positive and significant coefficient of 0.423 (p < .05). The study outcomes indicated that ZESA Holdings faces several challenges in implementing AI for supplier evaluation. The primary issue is data quality and availability, which can undermine AI effectiveness. The recommended that ZESA Holdings should Invest in robust data management systems to ensure the availability of accurate, complete, and timely data.
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Date
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June 2024
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Publisher
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BUSE
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Keywords
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Artificial Intelligence,
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Supplier selection,
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ZESA Holdings
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Supervisor
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Dr. Chigusiwa,
Tapiwa Rangarirai.pdf