Magister Commercii M.comm (Information Technology)

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https://hdl.handle.net/10566/12622

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Browsing by Subject "AI adoption"

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    Factors affecting the adoption of artificial intelligence (AI) in the supply chain and logistics lndustry
    (University of the Western Cape, 2023) Molopa, Tshwarelo; Jokonya, Osden
    This study explores factors affecting the adoption of Artificial Intelligence in the Supply Chain and Logistics Industry in the Rpublic of South Africa. The study followed these objectives: to explore technological factors affecting the adoption of Artificial Intelligence in supply chain and logistics industry’. To explore organisational factors that affect the adoption of Artificial Intelligence in the supply chain and logistics industry and to explore environmental factors that affect the adoption of Artificial Intelligence in the supply chain and logistics industry. The study selected a quantitative approach with a convenient sampling of 200 employees in the South African supply chain and logistics sector. Data was gathered using a self-managed, online questionnaire. The return rate of the questionnaire was 24%. Reliability and validity tests were conducted on the data, demonstrating that the concept measures produced consistent, repeatable results and faithfully captured the constructs they were designed to evaluate. The findings were that business units are committed to providing staff with the necessary training to support AI projects, with the majority of partcipants strongly agreeing with the sentiment. Besides, the majority of respondents agree that security is an important factor in the business when it comes to new technology adoption. A significant number of respondents think that AI can be difficult to deploy due to its various interdependencies, with half of the respondents believing that top managers are likely to invest in AI. The study further reveals that machine learning was the most popular algorithm implemented in the supply chain and logistics industry. The paper provides the expanding body of knowledge about AI adoption by leveraging factors from the T-O-E framework to explain adoption in the Supply Chain and Logistics industry.