Digital Technologies and Trade Facilitation in Ethiopia: A Mixed-Methods Analysis of Blockchain, AI, and IoT Adoption
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This study investigates the potential of digital technologies to revolutionize trade facilitation and enhance export performance in Ethiopia. Addressing a critical gap in the literature, it moves beyond general assessments to analyze the adoption and application of blockchain, artificial intelligence (AI), and the Internet of Things (IoT) within Ethiopia's trade sector. A mixed-methods approach, incorporating a survey of 255 trade stakeholders and 20 focus group interviews, identifies opportunities and challenges associated with digital transformation. Data analysis reveals the potential of blockchain to enhance customs transparency and efficiency, AI to expedite cargo clearance and strengthen fraud detection, and IoT to provide improved supply chain visibility. However, the research also addresses crucial concerns, including cybersecurity risks (87%), data privacy (75%), and potential shifts in employment (60%). Specifically, survey data revealed that only 10% of firms currently use AI, despite 67% recognizing its value for fraud detection. Qualitative analysis of interview transcripts highlighted concerns about the high cost and complexity of implementing blockchain solutions, as well as the need for clearer regulatory frameworks and multi-stakeholder cooperation. The findings inform actionable policy recommendations aimed at fostering a supportive digital trade ecosystem in Ethiopia, offering insights for other developing economies. Ultimately, this research aims to provide insights for management decision-making regarding technology adoption and strategic planning within the Ethiopian trade sector.
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