Enhanced supply chain tracking based on the EPC network: A Bayesian approach

Supply chain tracking information is one of the main levers for achieving operational efficiency. RFID technology and the EPC Network can deliver serial-level product information that was never before available. However, these technologies still fail to meet the managers' visibility requirements in full, since they provide information about product location at specific time instances only. This paper proposes a model that uses the data provided by the EPC Network to deliver enhanced tracking information to the final user. Following a Bayesian approach, the model produces realistic ongoing estimates about the current and future location of products across a supply network, taking into account the characteristics of the product behavior and the configuration of the data collection points. These estimates can then be used to optimize operational decisions that depend on product availability at different locations. The enhancement of tracking information quality is highlighted through an example. © 2009 IFAC.

Exploring geographical dispersion in Thailand-based food supply chain (FSC)

Purpose: The purpose of this paper is to explore the key influential factors and their implications on food supply chain (FSC) location decisions from a Thailand-based manufacturer's view. Design/methodology/approach: In total, 21 case studies were conducted with eight Thailand-based food manufacturers. In each case, key influential factors were observed along with their implications on upstream and downstream FSC location decisions. Data were collected through semi-structured interviews and documentations. Data reduction and data display in tables were used to help data analysis of the case studies. Findings: This exploratory research found that, in the food industry, FSC geographical dispersion pattern could be determined by four factors: perishability, value density, economic-political forces, and technological forces. Technological forces were found as an enabler for FSC geographical dispersion whereas the other three factors could be both barriers and enablers. The implications of these four influential factors drive FSC towards four key patterns of FSC geographical dispersion: local supply chain (SC), supply-proximity SC, market-proximity SC, and international SC. Additionally, the strategy of the firm was found to also be an influential factor in determining FSC geographical dispersion. Research limitations/implications: Despite conducting 21 cases, the findings in this research are based on a relatively small sample, given the large size of the industry. More case evidence from a broader range of food product market and supply items, particularly ones that have significantly different patterns of FSC geographical dispersions would have been insightful. The consideration of additional influential factors such as labour movement between developing countries, currency fluctuations and labour costs, would also enrich the framework as well as improve the quality and validity of the research findings. The different strategies employed by the case companies and their implications on FSC location decisions should also be further investigated along with cases outside Thailand, to provide a more comprehensive view of FSC geographical location decisions. Practical implications: This paper provides insights how FSC is geographically located in both supply-side and demand-side from a manufacturing firm's view. The findings can also provide SC managers and researchers a better understanding of their FSCs. Originality/value: This research bridges the existing gap in the literature, explaining the geographical dispersion of SC particularly in the food industry where the characteristics are very specific, by exploring the internationalization ability of Thailand-based FSC and generalizing the key influential factors - perishability (lead time), value density, economic-political forces, market opportunities, and technological advancements. Four key patterns of FSC internationalization emerged from the case studies. © Emerald Group Publishing Limited.

The intelligent product driven supply chain

Establishing connectivity of products with real-time information about themselves can at one level provide accurate data, and at another, allow products to assess and influence their own destiny. In this way, the specification for an intelligent product is being built - one whose information content is permanently bound to its material content. This paper explores the impact of such development on supply chains, contrasting between simple and complex product supply chains. The Auto-ID project is on track to enable such connectivity between products and information using a single, open-standard, data repository for storage and retrieval of product information. The potential impact on the design and management of supply chains is immense. This paper provides an introduction to of some of these changes, demonstrating that by enabling intelligent products, Auto ID systems will be instrumental in driving future supply chains. The paper also identifies specific application areas for this technology in the product supply chain.

Performance assessment of XACML authorizations for supply chain traceability web services

Service-Oriented Architecture (SOA) and Web Services (WS) offer advanced flexibility and interoperability capabilities. However they imply significant performance overheads that need to be carefully considered. Supply Chain Management (SCM) and Traceability systems are an interesting domain for the use of WS technologies that are usually deemed to be too complex and unnecessary in practical applications, especially regarding security. This paper presents an externalized security architecture that uses the eXtensible Access Control Markup Language (XACML) authorization standard to enforce visibility restrictions on trace-ability data in a supply chain where multiple companies collaborate; the performance overheads are assessed by comparing 'raw' authorization implementations - Access Control Lists, Tokens, and RDF Assertions - with their XACML-equivalents. © 2012 IEEE.