ORCID
0000-0002-2434-0961
Abstract
The digital revolution of the logistic value chain has improved critical aspects of the global supply chain, especially in the aspect of last-mile logistics (LML). Bottlenecks, however, such as delays in deliveries, increased lead times, pollution, poor cost management, and tracking issues, among several others, plague the logistics operations in developing countries. Artificial intelligence (AI) can help mitigate these bottlenecks toward delivering incremental value to the end customers. This paper investigates the extent to which AI has been adopted in the logistics value chain in developing countries using a descriptive approach. Quantitative data were collected from 290 logistics and e-commerce firms in Nigeria using a survey; the theory of innovative capabilities hinges on this study. Structural Equation Modelling (SEM) was used to analyze the quantitative data, and findings show that AI significantly impacts mitigating bottlenecks in LML, while improving the efficiency of LML operations. In developing climes (regions) like Nigeria, however, the level of penetration of AI technologies is still evolving—due, especially, to the high cost of procuring these technology tools. As stated in the contingent innovative theory, context matters. Hence, logistic firms can adopt some of these AI tools with time as the need arise.
Included in
E-Commerce Commons, Leadership Commons, Operations and Supply Chain Management Commons, Transportation and Mobility Management Commons
