Generative AI applications, such as ChatGPT or DALL-E, have shown the world their impressive capabilities in generating human-like text or image. Diving deeper, the science stakeholder for those AI applications are Deep Generative Models, a.k.a DGMs, which are designed to learn the underlying distribution of the data and generate new data points that are statistically similar to the original dataset. One critical question is raised: how can we leverage DGMs into morden retail supply chain realm? To address this question, this paper expects to provide a comprehensive review of DGMs and discuss their existing and potential usecases in retail supply chain, by (1) providing a taxonomy and overview of state-of-the-art DGMs and their variants, (2) reviewing existing DGM applications in retail supply chain from a end-to-end view of point, and (3) discussing insights and potential directions on how DGMs can be further utilized on solving retail supply chain problems.

Artificial intelligence will be worth about $17.5 billion in the global supply chain management (SCM) software market by 2028, according to a new market report, "Global Artificial Intelligence in Supply Chain Management Market by Technology, Processes, Solutions, Management Function (Automation, Planning & Logistics, Inventory, Risk), Deployment Model, Business Type, and Industry Verticals 2023-2028." The authors said that market analysis shows AI-enabled supply chains are 67% more effective than their non-AI counterparts, thanks to reduced risks and lower overall costs. The study, released by ResearchAndMarkets.com April 10, noted that the Asia-Pacific (APAC) region is expected to be the largest and fastest-growing supplier of artificial intelligence for the global SCM market. The report also examined several forms of AI, including cloud-based AI-as-a-service solutions, which it predicted will be worth more than $3.7 billion by 2028, reaching more than 21% of the total market in the next five years.

At Kinaxis, who we are is grounded in our common belief that people matter. Each one of us plays an important part in accomplishing our work, building our culture and making a global impact. Every day, we're empowered to work together to help our customers make fast, confident planning decisions. This is how we create a better planet – for each other, for our customers and for generations to come. Our cloud-based platform RapidResponse ensures that the products we need – everything from medicine and cars, to day-to-day items like toothpaste – make it to market and into our hands when we need them with minimal ecological footprint.

At Kinaxis, who we are is grounded in our common belief that people matter. Each one of us plays an important part in accomplishing our work, building our culture and making a global impact. Every day, we're empowered to work together to help our customers make fast, confident planning decisions. This is how we create a better planet – for each other, for our customers and for generations to come. Our cloud-based platform RapidResponse ensures that the products we need – everything from medicine and cars, to day-to-day items like toothpaste – make it to market and into our hands when we need them with minimal ecological footprint.

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.

Retail supply chains are under immense pressure to keep up with these rapid changes. Innovators have been quick to take advantage of the new virtual distributed environment. Also, e-commerce is growing at an unprecedented rate and customers expect faster delivery times and more personalized service. And retailers are facing pressure to keep costs down and increase profitability. Despite these challenges, organizations can take action and make a difference.

Quantum computing is expected to have transformative influences on many domains, but its practical deployments on industry problems are underexplored. We focus on applying quantum computing to operations management problems in industry, and in particular, supply chain management. Many problems in supply chain management involve large state and action spaces and pose computational challenges on classic computers. We develop a quantized policy iteration algorithm to solve an inventory control problem and demonstrative its effectiveness. We also discuss in-depth the hardware requirements and potential challenges on implementing this quantum algorithm in the near term. Our simulations and experiments are powered by \texttt{IBM Qiskit} and the \texttt{qBraid} system.

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.

AI is transforming supply chain management with greater efficiency, visibility, and optimization. There are a number of ways that supply chain organizations can implement AI to experience these benefits, from smart simulations to automated quality control. Adopting AI will be key to evolving the supply chain and adapting to today’s supply chain challenges. 1. Optimization […]

The chaos at ports continues with no end. A troubling realization is sinking into the mind: The effects of the " Great Supply Chain Distortion" are already being felt throughout the country. For example, 30% of baby formula brands may be out of stock soon. This could cause retailers to limit the number of containers they can sell and leave parents concerned that their children won't get enough food. This issue covers all industries and has an impact on automotive, healthcare IT, hospitality, manufacturing, apparel, as well as other areas.