Artificial Intelligence Adoption and Operational Efficiency of Borderless Enterprises: A Resource-Based Analysis of Technology Hubs in South-West, Nigeria
Abstract
This study investigated how the adoption of artificial intelligence impacts the operational efficiency of borderless enterprises in technology hubs in the South-West region of Nigeria. While previous studies have documented the adoption rates and acceptance predictors of artificial intelligence, studies have been limited on the operational impacts, and most have focused on Lagos, whose infrastructure and access to capital are not representative of the entire region. The study was based on the Resource-Based View, and a descriptive survey with cross-sectional data was used. The population for the study was 5,930 people, including employees and clients of technology hubs in the Federal Ministry of Science and Technology in Lagos, Ogun, Oyo, Osun, Ondo and Ekiti States, categorized based on the level of industrialization of the states. Using the Taro Yamane (1967) formula, at a 5% level of precision, with a 10% margin of non-response, a total of 413 survey instruments were distributed and 386 were returned, giving an effective response rate of 96%. SPSS version 28 was used for data analysis and an inference was made using a descriptive survey with a 5- point Likert scale. The study found that the operational efficiency of borderless enterprises, enabled by artificial intelligence, had a positive, significant effect, and was predictive of the performance of borderless enterprises (β = 0.433, t = 7.413, p < 0.001), with 53.4% of the performance of borderless enterprises explained by the operational efficiency of artificial intelligence, hence the stated null hypothesis was rejected. Item-level analysis suggests that findings are strong for respondents indicating appreciation and support for cross-border transactions and logistics at 60.00 percent. Findings for physical presence requirements are weak as they were rejected by 50.25 percent of respondents. This study suggests that artificial intelligence does not create value for these enterprises by removing territorial constraints. The study further recommends that hub promoters and accelerator managers shift technical support from the breadth of adoption of artificial intelligence to the depth of integration.
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