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The purpose of this paper is to examine the role of global value chains (GVC) in industrial development of emerging economies, with particular focus on participating African countries. The findings of this study are expected to provide insight on the need for more developing countries to participate in GVC.

This study is built upon the neoclassical and endogenous growth theories, which postulate that savings, physical capital and human capital are the fundamental drivers of development in productive sectors of the economy. The investigation, covering the period 1980–2021, is carried out by using the unrestricted error correction model and dynamic ordinary least squares model.

The results of this study reveal that GVC stands as the dominant factor driving industrial development, compared to savings, physical capital and human capital. The findings, therefore, seem to contradict the postulation of conventional theories. The policy implications of the findings are not far-fetched. First, industrial development in the participating African countries has benefited largely from GVC; hence, it is necessary to encourage more participation. Second, industrial development also benefited from the control variables (savings, physical capital and human capital), hence the need to sustain their complementary role. Thirdly, only three African countries are actively participating in GVC, which suggests that more countries need to join, to facilitate industrial development.

Previous studies have not given adequate attention to African countries that participate in GVC, thus creating a void that needs to be filled. This study, therefore, produced results that are relevant to policy-making on industrial development in African countries.

The purpose of this study is to investigate the primary determinants influencing the acceptance of generative artificial intelligence (GAI) adoption within Blockchain-enabled environments. Further research will examine the impact of GAI adoption on supply chain efficiency (SCE) through the enhancement of Blockchain.

Drawing on innovation diffusion theory (IDT), this study used partial least square structural equation modelling (PLS-SEM) to look into the hypotheses. The data were gathered via online questionnaires from employers of Chinese supply chain enterprises that have already integrated Blockchain.

The findings of this study demonstrate that relative advantages (RAs), compatibility, trialability and observability have a significant positive effect on GAI adoption, while complexity harms GAI adoption. Above all, the GAI adoption has significantly enhanced Blockchain, thus effectively improving SCE.

The outcomes from this study furnish enterprises and organizations with valuable insights to proficiently integrate GAI and Blockchain capability, optimize supply chain management and bolster market competitiveness. Also, this study will help accelerate the successful integration of business processes and attain Sustainability Development Goals 9, industrial growth and industrial diversification.

To the extent of the author’s knowledge, the current status of the GAI study remains largely exploratory, and there is limited empirical evidence on integrating Blockchain capability and GAI. This research bridges the knowledge gap by fully revealing the optimal integration of these two transformative technologies to leverage their potential advantages in supply chain management.