Microsoft is targeting the supply chain market with its latest software release. The Microsoft Supply Chain Platform is designed to help organizations maximize their supply chain data estate investment via a combination of Microsoft artificial intelligence (AI), collaboration, low code, security, and SaaS applications within one overarching platform, according to the company last month. This supply chain software rollout by Microsoft comes at a time of supply chain disruption worldwide. Whether due to COVID-19 lockdowns, the Great Recession, the "Great Resignation," quiet quitting, layoffs, legislation that impacted trucking and shipping, the war in Ukraine, or other factors, the global supply chain has stuttered of late. Chip shortages, cabling shortages, and much longer lead times for equipment have become the norm. Supply chain dovetails nicely into existing Microsoft strengths in enterprise resource planning (ERP), customer relationship management (CRM), collaboration, project management, and the cloud.

Supply Chain Platforms (SCPs) provide downstream industries with numerous raw materials. Compared with traditional e-commerce platforms, data in SCPs is more sparse due to limited user interests. To tackle the data sparsity problem, one can apply Cross-Domain Recommendation (CDR) which improves the recommendation performance of the target domain with the source domain information. However, applying CDR to SCPs directly ignores the hierarchical structure of commodities in SCPs, which reduce the recommendation performance. To leverage this feature, in this paper, we take the catering platform as an example and propose GReS, a graphical cross-domain recommendation model. The model first constructs a tree-shaped graph to represent the hierarchy of different nodes of dishes and ingredients, and then applies our proposed Tree2vec method combining GCN and BERT models to embed the graph for recommendations. Experimental results on a commercial dataset show that GReS significantly outperforms state-of-the-art methods in Cross-Domain Recommendation for Supply Chain Platforms.