Recent shifts in the global industrial division of labor, marked by localized relocation and regional clustering, have intensified competition among economies for dominance in industrial and supply chains. A report by *The Economist* highlights fourteen Asian economies (Altasia), encompassing ASEAN (excluding Myanmar), Japan, South Korea, India, and Bangladesh, as potential replacements for China in global production. This paper examines the validity of this hypothesis by analyzing the substitution effect of Altasia on China's production network (CPN), a crucial component of the Global Production Network (GPN). While China's manufacturing capabilities and economic scale remain formidable, rising production costs, fading demographic dividends, and geopolitical pressures, such as the US's friend-shoring strategy, necessitate exploring the potential for industrial relocation. The study emphasizes the importance of understanding the interplay between China's economic strength and the collective potential of Altasia, particularly the rising influence of ASEAN and its export-oriented expansion fueled by population, resources, and favorable investment policies. The ongoing fifth international industrial transfer and the United States' efforts to reshape supply chains through friend-shoring, coupled with China's own proactive industrial transfer strategies, create a complex dynamic that requires careful analysis.

The paper reviews existing literature on industrial transfer, focusing on theories such as the Flying Geese Paradigm, Core and Periphery Theory, Product Life Cycle Theory, and New Economic Geography Theory. However, it notes that traditional theories inadequately address the current trend of regionalization and the complexities of Global Value Chain (GVC) restructuring. The study highlights the advancements in GVC accounting using Multi-Regional Input-Output (MRIO) tables, enabling a more granular analysis of value creation and distribution. While some studies have utilized MRIO tables to assess industrial transfer, the paper points to a scarcity of research explicitly analyzing the impact of the US friend-shoring strategy and Altasia on China's industrial relocation. Existing research limitations are noted: reliance on UN Comtrade data, insufficient discrimination between effects of exogenous variables (e.g., COVID-19 pandemic), and an inability to pinpoint the exact influence of regional economic integration on China's relocation trends. The paper then introduces the application of network science, emphasizing the utility of the Global Production Network (GPN) model in visualizing and analyzing the complex interactions between economies and industrial sectors in the context of industrial transfer.

This study employs a network science approach using MRIO data to model the GPN. The ADB-MRIO 2023 database, encompassing 62 economies and 35 industrial sectors, provides the foundation for constructing a Global Industrial Value Chain Network (GIVCN) model. In this model, each node represents an industrial sector within a country, and the edges represent the flow of intermediate goods, with weights indicating trade volume. Due to the high density of the GIVCN, the X-Index Filtering Algorithm (XIFA) is utilized to extract a backbone network, termed the Global Industrial Value Chain Backbone Network (GIVCBN). Three types of GIVCBN models are developed: GIVCBN-I (null model), GIVCBN-II, and GIVCBN-III (counterfactual models). GIVCBN-I represents the baseline scenario, while GIVCBN-II and GIVCBN-III simulate the impact of Altasia and ASEAN, respectively, as tightly integrated economic entities. The merging of Altasia's or ASEAN's industrial sectors within the GIVCN model before applying XIFA allows for an analysis of the potential impact on China's CPN. Network-level indicators (Average Path Length, Average Clustering Coefficient, Asymmetry) and node-level indicators (Degree Centrality, Betweenness Centrality, Closeness Centrality) are calculated for each model to compare the topological structure under different scenarios. The comparison between the null and counterfactual models highlights the risk exposure of China's industrial and supply chains due to Altasia's substitution effect, analyzed through chord diagrams and tables outlining disrupted industrial and supply chain linkages.

The study finds that Altasia induces more disruption to China's industrial and supply chains compared to ASEAN alone, suggesting strong industrial complementarity within Altasia. Counterfactual models show worse network-level characteristics (longer average path length, lower average clustering coefficient) than the null model, indicating reduced efficiency and increased isolation in China's CPN. Specifically, the average path length (APL) ratios in both counterfactual models exceed 1, while the average clustering coefficient (C) ratios are below 1. The asymmetry (ASY) ratios are greater than 1, suggesting a decrease in the degree of vertical specialization. The analysis reveals that the risk exposure primarily impacts resource- and labor-intensive industries in China, while capital- and technology-intensive sectors remain largely unaffected. Node-level analysis shows Altasia weakens China's influence scope, profitability (Betweenness Centrality), and risk robustness (Closeness Centrality) in various sectors. However, when focusing on ASEAN alone, the negative impact on China is significantly reduced. The study highlights the importance of specific economies within Altasia (Japan, South Korea, India, Taiwan) in driving the substitution effect, particularly for technology-intensive industries. The analysis also accounts for the impact of the COVID-19 pandemic, noting its role in disrupting global supply chains and accelerating the shift toward diversified sourcing.

The findings confirm the hypothesis that Altasia presents a significant threat to China's industrial and supply chains, particularly for resource- and labor-intensive sectors. The results highlight the complexities of GVC restructuring and the importance of considering both national and regional economic integration dynamics. The strong industrial complementarity within Altasia contributes to its greater substitution effect compared to ASEAN. The observed changes in network-level and node-level indicators demonstrate the potential for reduced efficiency, fragmentation, and increased vulnerability in China's CPN. The study's emphasis on comparing Altasia's effect to that of ASEAN alone helps delineate the relative impact of different regional economic groupings on China's industrial landscape. The findings also underline the resilience of China's high-tech and capital-intensive industries, indicating that China maintains competitive advantages in certain sectors.

This research provides valuable insights into the evolving global production landscape and the challenges faced by China in maintaining its position within the GPN. The study emphasizes the importance of regional economic integration and the potential for significant industrial relocation. Future research should focus on refining models to more accurately capture the complexities of multinational corporate activities and their impact on GVCs, especially by differentiating between domestic and foreign-owned enterprises within industrial sectors. Further research could explore the impact of various policy interventions aimed at mitigating the negative consequences of industrial relocation on China's economy.

The study's reliance on existing MRIO data, particularly the ADB database, limits the timeliness and granularity of the analysis. While the ADB data provide a comprehensive overview of the Asia-Pacific region, future research could benefit from incorporating more recent and sector-specific data. Additionally, the model's simplification of Altasia and ASEAN as tightly integrated entities might not fully reflect the complexities of internal economic relations within these regions. The counterfactual analysis relies on specific assumptions about the level of regional economic integration, and deviations from these assumptions could influence the results. Finally, the study does not explicitly model the dynamic interplay of geopolitical factors and their influence on the industrial relocation process.