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As globalization increases, the world's supply chain has become substantially more interconnected and interacting; but most importantly, it becomes more complex. By breaking down into sections, supply chain is composed of "suppliers, manufacturers, warehouses, distribution centers and retail outlets" where raw materials are sent to manufacturing factories to produce and then shipped to warehouses for storage, then to retailers or customers. Just like data usage is rampant nowadays, supply chain has embraced the reliability and certainty of data by employing some sort of technologies that shape present and future technology trends. Particularly, in the setting of COVID-19, supply chain has been affected as a whole. China, known as the major source of finished goods and manufacturing markets, originated the limited input of these supplies as policies announced to temporally lockdown the factories, which further interrupted the whole global supply chain where those countries tend to outsource to China. Along with the factories lockdown, restaurants, nonessential companies and workers were into quarantine. Stores were filled with empty shelves; even larger businesses such as Costco, Walmart was facing the spike in demand. Some people lost their jobs; some people were working remotely. The operations have been disrupted accordingly; however, the realization of "how reliance on human labor making impossible to keep economy running" appears with the inclination of technologies. The following technologies explain why they fit perfectly during the pandemic or even several years down the line.

Artificial Intelligence
Artificial Intelligence, in contrast to human intelligence, refers to a computer system that mimic human behavior in which collecting all the relevant information and knowledge to solve the problems easily and efficiently. In particular, AI addresses supply chain issues significantly, which involves inventory management, transportation network design, purchasing, planning and forecasting, order management, and customer relationship management.

Inventory represents in-stock resources that are required to reach customer satisfaction whenever consumers purchase an order but at the same time incur substantial costs. Therefore, the company's success in minimizing inventory cost can be enhanced by the presence of real-time customer demands and record on on-hand orders that allow to submit fulfillment proposals accordingly. Traditionally, mathematical models such as economic order quantity are helpful but limit the very essence of inventory management. By involving artificial intelligence, it's easy to handle the incidents and capture the inventory patterns in more precise details from a more complex standpoint. When it comes to the transportation problems, the allocation location, carrier scheduling, modes selection appear onto the surface. AI technique has emerged the algorithms that collaborate these related information and data to optimize solutions. In purchasing and supply management, artificial intelligence works perfectly into the make-or-buy decision. Taking the example of a knowledge-based system (KBS), a form of artificial intelligence, it specializes in five stages: identify and weigh performance metrics; analyze corporate capabilities; compare internal and external capabilities; make a supplier selection; finalize total acquisition cost. This automation simplifies the decision-making process and touches on every attribute. Forecast has been a leading trend in today's most companies on customer demand. Given the volatile nature of future demand that solely rely on historic data, exponential smoothing, moving average or any similar traditional forecasting methods have been outdated. Therefore, the introduction of AI techniques which contain the agent-based system, for instance, that analyzes the past, captures the current, and estimates the future customer behaviors, helps facilitate the forecasting accuracy. While talking about order management, order-picking problems typically account for the largest portion of warehousing operations. Especially in this labor-intensive field, in order to improve the efficiency, reduce the picking errors, and speed up the filling process, the intelligent agent-based automation tackle all these issues by assigning workers to a specific zone for a minimum waiting time. Besides operation spectrum, stabilizing a long-term relationship with customers is also an indispensable building block throughout the supply chain where communication and social network design is enhanced by the expert system.

Cloud Computing
Cloud Computing is a term that figuratively refers to a myriad of disperse resources not merely located within firms but in more of virtualized and distributed communities that can be accessed on an online on-demand basis. Cloud Computing boost business value by three core service models: 1) Infrastructure as a service (IaaS), sharing data and computing infrastructure; 2) Platform as a service (PaaS), displaying and developing applications; 3) Software as a service (SaaS), delivering online software . And these models provide benefits that lead to greater efficiency in having the real-time online platforms access, reducing costs and recovery risks. But most crucially, the input of Cloud Computing eases the supply chain integration. One obvious outcome is that Cloud Computing accelerates information flow and data sharing between supply chain partners; for example, it reinforces financial payment between suppliers and customers or it communicates well among all parties in the supply chain to share information about purchase orders, delivery materials and other associated activities. Particularly, Cloud Computing is beneficial for inventory management where partners in the supply chain can monitor physical flows of manufactures virtually and adjust the order fulfillment proposal directly without manual processes.

Blockchain
Blockchain is a distributed data structure that decentralizes stored information and holds a trusted intermediary so no one can counterfeit and destroy the data. Since companies are expanding sales for delivery and digitalizing transaction processes, the risk of attacks on databases can be eliminated by the blockchain. Essentially, blockchain produces trust and protection among suppliers. In addition, blockchain keeps track on the order location along the transportation line; particularly for the "refrigerated goods, which cannot be left in warm environments" for so long. This value proposition does not just allow suppliers to get notifications on the order delivery, but also decreases the queue time in between. While the products arrive, the code is generated and stored automatically. But most significantly, blockchain leaves transparency and accountability across the supply chain. Typically in the food industry, the visibility and traceability of fresh ingredients offers huge gains to operations. Moreover, the adoption of blockchains depends on number and capabilities of related actors, which narrows down into specific industry.

Automation/Robots
Automation is an opposite system to manual labors. In the supply chain, autonomous things take the opportunity to redesign processes, which lead to space and cost savings, a reduction of inventory and excessive workers. Especially, automation is designed within the software that is set into the automated program, which results in fewer errors, faster competition rate and better quality. Most of all, the supply chain automation often refers to material handling solutions, labeling productions and conveyers in the manufacturing sector. "Advanced robotics in warehousing, analytics for transport, and IoT/smart-sensor applications" are all mostly been used and invested in the supply chain field. Furthermore, as the customer satisfaction increases, the expectation on same-day delivery also raises where "more automation in picking, packing and sorting is necessary". In other words, automated systems throughout the supply chain enhance the customer experience and improve supplier performance.