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The redesign of a product supply chain, in terms of production, cost and delivery capabilities can be effectively accomplished by mapping, analyzing and simulating the changes in the supply chain prior to implementation. The case being discussed pertains to the apparel industry in the USA. The beginning of 2005 marked the end of a 30‐year old quota on the apparel market in the USA. This has led many western apparel manufacturers to outsource their production to low‐labor cost countries. This in‐turn has led to increased customer lead‐times. This paper aims to discuss how the implementation of proper IT systems and supply chain measures can reduce lead‐times and also reduce total cost.

An integrated approach is utilized to model the impact of apparel outsourcing added to a US apparel producer supply chain by studying the process map, data analysis, and simulation of the supply chain using Visio, Excel and @Risk simulation software. Using Monte Carlo simulation, the hypotheses on responsiveness and relative costs were tested with and without the outsourcing feature in the US apparel producer supply chain.

The cost savings through outsourcing in the low‐cost labor countries in Asia for the US apparel producer supply chain can be huge and the lead‐time is quite substantial. Thus, outsourcing is not a viable solution for meeting short‐term market demands. However, for large seasonal orders, outsourcing could be an enormous cost‐saver. The lead‐time of the US apparel producer supply chain could be improved if certain controllable factors such as order processing could be made more efficient.

Recent studies by Acaccia, Conte, Maina and Michelini as well as the Leadership for European Apparel Production From Research along Original Guidelines (LEAPFROG, www.leapfrog‐eu.org/), were reviewed. However, no recent study that uses Monte Carlo simulation to measure the supply chain in the apparel market for the USA was traceable in the existing literature except one done by Naylor, Burdick and Sasser at Duke University in 1967. The process modeling of the US apparel producer supply chain with the outsourcing feature will be a useful decision analysis tool. With more data and better understanding of the industry, this simulation model can be easily expanded to obtain a more in depth understanding of any US apparel producer supply chain with an outsourcing capability. Even with making some realistic assumptions in the model, one can easily see the potential benefits of outsourcing. The study found that the customer lead‐time was averaging around 57 days at three‐fourths of the original cost with the minimum customer lead‐time being 41 days. Improved IT and logistics capabilities can minimize the variability recognized in major components of customer lead‐time, such as ocean freight transportation time, order processing time and manufacturing time.

The contribution of the research results from the apparel industry application, where simulation studies of this kind have recently not been executed for a US apparel manufacturer. It also showcases an innovative approach in analyzing outsourcing strategies for a US apparel producer supply chain. The study makes a business case that process improvement can be effectively accomplished with an integrated approach of using widely available inexpensive and user‐friendly computer‐based tools.

The purpose of this paper is to present an analysis of how different sourcing policies and resource usage affect the operational performance dynamics of warehouse processes.

The system dynamics (SD) methodology is used to model warehouse operations at the distribution centre of a leading fast‐fashion vertical retailer. This case study includes a detailed analysis of the relationships between the flow of items through the warehouse, the assignment of staff, the inventory management policy, and the order processing tasks.

Case scenario simulations are provided to define warehouse policies enabling increased efficiency, cost savings, reduced inventory, and shorter lead‐times.

The case study reaffirms that a flexible usage of human resources, outsourcing of selected warehouse operations, and sourcing from reliable manufacturers may result in important performance improvements for centralised warehousing.

It is proved that SD is a valuable tool in the field of operations management, not only to support strategic evaluations but also to execute a detailed analysis of logistical processes and make scenario‐based dynamic decisions at the operational level.

The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing – i.e. a high-value manufacturing sector – can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries.

Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind.

Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors.

Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors.

Global manufacturers have faced unprecedented cost pressures in China because of Chinese currency appreciation, rising labour costs, higher oil prices and reduced value‐added tax rebates. This paper aims to reassess the decision of operating global manufacturing facilities in China.

A mixed integer programming model is developed for a typical global manufacturing supply chain that includes production in the Pearl River Delta region and trade in Hong Kong. A case study with a footwear product is used to illustrate model application and present detailed analyses.

The modelling results affirm the need of relocating labour‐intensive production that mainly competes on low costs. Nevertheless, coastal China offers considerable benefits from industrial clustering and a logistics advantage in comparison with inland China and Asian countries where labour costs are still relatively low. Hong Kong remains a robust location choice for trade operations because of its favourable tax policies.

Retaining production in China faces high risks from Chinese currency appreciation, while relocation to lower‐cost Asian countries is more vulnerable to risks from high oil prices. An intermediate trade operation in Hong Kong can be used to hedge against risks from unfavourable tax policy changes at manufacturing locations.

China has risen to an important position in global manufacturing because of its cost advantages. This paper analyzes the new phenomenon of dramatically increasing cost pressures in China. It develops a first‐of‐its‐kind supply chain configuration model for the popular front‐shop‐back‐factory business model in China.