Intelligent Agent Technology in Supply Chains

Intelligent Agent Technology in Supply Chains

Youqin Pan (Salem State University, USA) and Zaiyong Tang (Salem State University, USA)
Copyright: © 2014 |Pages: 13
DOI: 10.4018/978-1-4666-5202-6.ch116

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Today’s global market is electronically linked and dynamic in nature. In order to survive in the global market, many companies are trying their best to be flexible and responsive to customer demand. For instance, companies decentralize their value-adding activities by outsourcing and developing virtual enterprise. Companies are trying to establish partnership with wholesalers or retailers in other countries to promote their products or services. Nowadays, there is no single firm can effectively satisfy customer demand by managing all the business processes from the raw materials to end customer products. In fact, these individual firms depend on each other to succeed by working together to deliver the right product at the right time and right price at the right location. The interdependence among trading partners calls for close cooperation and tight integration of different functions along the supply chain, which is quite different from the discrete, independent, and isolated activities across the supply chain (Dyer, 2000). Naturally, Supply chain coordination evolves as the management of the interdependent activities among chain members. Modern SCM heavily relies on information technology (IT) to improve inter-organizational coordination which significantly affects the firm’s performance (Sanders, 2008). Studies have found that adopting technological innovations is the most important weapon for firms to keep their competitive advantages (Kimberly & Evanisko, 1981). For example, Electronic Data Interchange (EDI) systems have improved both operational and strategic efficiencies by an IT innovation (Subramani, 2004). With the development of Internet technology, Internet-enabled systems such as Enterprise Resource Planning (ERP), E-procurement Applications, Customer Relationship Management (CRM) and Supplier Relationship Management (SRM) have been adopted in various supply chains. These systems have already become a critical part of supply chain strategies for most industries (Frohlich & Westbook, 2001; Frohlich, 2002).

Nowadays, supply chains face great challenges such as cost containment, supply chain visibility, risk management, increasing customer demand and globalization (IBM, 2010). More and more companies turn to newly developed IT technologies for solutions. For example, investments on radio frequency identification (RFID) technology have improved the coordination and the visibility of various supply chains by leveraging reliable and timely RFID data. More importantly, the improved supply chain visibility enables chain members to adapt to market changes effectively and efficiently (Attaran, 2007). Despite these achievements, supply chain managers still need to deal with the emerging challenges as reported by IBM (2010). Today’s supply chains are swamped with more data and information, it is difficult for supply chain professionals to identify and act on the right information. How companies in supply chains could make use of big data and make real-time analytics available for better decision making is critical to the success of the supply chain. Moreover, new trading partners and new products call for structural changes which transform the topology of supply chains (Li & Chan, 2013). How supply chain members could adapt to such structural changes is another key issue in SCM.

Key Terms in this Chapter

Intelligence: The ability of an agent to learn and adapt to different objectives and environments.

Intelligent Agent: Software agent that uses artificial intelligence to purse for a specific goal of its clients.

Inter-Organizational Systems: Information management systems that transcend organizational boundaries via electronic linkages to facilitate information sharing and business transactions among trading partners.

Autonomy: The ability of an agent to have some control over its actions and internal states without other agents’ intervention.

Supply Chain Management: Management of the interconnected business partners across the supply chain.

Collaboration: The ability of an agent to reason about its local actions and anticipates actions from other agents to ensure that a group of agents act in a coherent manner.

Multi-Agent Systems: A loosely coupled network of software agents that collaborate with each other to solve problems that are beyond individual capacities or domain knowledge.

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