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In the practice of global sourcing, the problem of long-term procurement planning is difficult because of the large demand uncertainty. This paper presents an adaptive optimal planning approach using a rolling horizon scheme. The approach combines the techniques of time-series forecasting and stochastic lot-sizing. An efficient heuristic solution is introduced. The proposed approach is evaluated by ex-post-facto experiments. Promising results are shown when the approach is applied on a long-term procurement planning problem with large unstruc tured demand uncertainty.

Purpose. COVID-19 has prompted more countries to consider moving key production activities back home. 3D printing (3DP) is a key technology to realize this migration. This study aims to explore the extent to which 3DP can change the current global production network. Design/Methodology/Approach. This study takes the toy industry as the empirical object and studies the trend of labor-intensive industries migrating from China to the United States from the micro- and macroperspectives. At the microlevel, this study uses scenario analysis to compare the utility experience of different toy acquisition channels for consumers. At the macrolevel, this study determines the applicable product objects of 3DP through the classification and analysis of toy trade data. Findings. It is found that, with the development of 3DP, toy manufacturing activities may gradually flow from China to the United States in stages. If 3DP is implemented in electronic materials and power systems, this migration activity will be more obvious. Originality/Value. This study identified which kind of 3DP technology development will significantly promote the global production network reconstruction. This viewpoint is helpful for decision-makers to consider technology investment comprehensively.

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