A bi-objective model for supply chain design of dispersed manufacturing in China
Highlights
► Dispersed manufacturing dissects the supply chain to optimize process locations. ► Trade-offs between cost and lead time affect facility location decisions. ► Favorable government policies have benefited manufacturing growth in China. ► Labor-intensive manufacturing steps are likely to move away from coastal China. ► Time-sensitive production may stay for efficient logistics and industrial clustering.
Introduction
Manufacturing activities have become more spatially fragmented in the past few decades (Ferdows, 1997, Lee and Lau, 1999, Ronald et al., 2005, Christopher et al., 2011). Manufacturers nowadays do not necessarily perform all manufacturing steps of a product at a single facility location. Instead, they often ship semi-finished products to a different location for further processing or sales (Fawcett, 1992, Ferdows, 1997, Feng and Wu, 2009). The rapid advancement of information technologies, especially the wide adoption of e-business platforms and enterprise information systems (Li, 2011b), has been a key enabler behind the trend. It allows facilities at distant locations to coordinate product design and development (Fritzsche et al., 2012, Li and Liu, 2012, Liu and Wang, 2012, Ren et al., 2012), and production activities (Tan et al., 2010, Wang and Xu, 2012) efficiently at an affordable cost.
This paper defines dispersed manufacturing as the practice of dissecting the manufacturing process into multiple stages, and assigning them to geographically dispersed locations to achieve a competitive edge (Magretta and Fung, 1998). Dispersed manufacturing exploits comparative advantages of multiple locations, however, dramatically increases the complexity in supply chain design. According to the seminal work of Fisher (1997), a typical challenge of supply chain design is the management of trade-offs between efficiency and responsiveness, which are measured by cost and lead time, respectively. Locating labor-intensive manufacturing steps in proximity to cheap labor is able to lower production costs, but lengthens the supply chain and increases logistics costs. Global manufacturers need to define business priorities, design their supply chains, and review facility location decisions when there are major changes in global and regional business environments (Skinner, 1996).
Dispersed manufacturing has been an integral part of global manufacturing in China. It has allowed the country to participate in global supply chains to realize its labor cost advantage and skill competence. Dispersed manufacturing is what is behind the boom in intra-Asia trade as China rises as the “Factory of the World” (Magretta and Fung, 1998). Tens of thousands of global manufacturers in China import raw materials and semi-finished products from Asian countries, perform labor-intensive assembly operations, and then export end-products to developed countries (GPRD Business Council, 2007). As the traditional gateway to China, Hong Kong has played a pivotal role to support manufacturing growth in China, especially in the southern regions. Hong Kong traders typically obtain overseas orders and organize manufacturing in a dispersed network of factories in the Pearl River Delta (PRD) region (Fung et al., 2008, HKTDC, 2008). A great example is Li & Fung (Hamid and Lee, 2006), which dissects the supply chain to assign a manufacturing step to an optimal location. Li & Fung synchronizes a network of thousands of factories around the globe, to minimize total costs and shorten order lead times (Magretta and Fung, 1998, Hagel, 2002). Its business model has attracted high profile retailers including The GAP, Target Corp. and Marks & Spencers Plc. In 2010, giant retailer Wal-Mart also signed a multi-billion dollar deal to source through Li & Fung and expected “significant” savings across its supply chain (Cheng, 2010, Talley and O’Keeffe, 2010).
Inspired by Li & Fung’s success (Magretta and Fung, 1998, Joanna, 1999, Hagel, 2002), several studies advocated dispersed manufacturing from a strategic viewpoint (Chung et al., 2004, Hamid and Lee, 2006). However, quantitative studies on dispersed manufacturing have been scare. In recent years, new trends have emerged as some global manufacturing activities are moving away from coastal China because of rising production costs and the hike in oil prices (Trunick, 2008, Kumar et al., 2009, Zhang and Huang, 2010, Zhang et al., 2012). However, they assumed that all manufacturing steps of a product are performed at a single facility location, although dispersed manufacturing has been a business reality in China. There is an urgent need to perform quantitative studies in the supply chain design of dispersed manufacturing in China in light of the emerging global manufacturing trends.
In a broader scope of supply chain design, many mathematical models have been built to aid manufacturing facility location decisions. A recent review of these models can be found in Melo et al. (2009). However, there are considerable challenges to adapt these models for Chinese manufacturing due to very different business environments, for example, North American Free Trade Agreement (NAFTA) (Wilhelm et al., 2005, Robinson and Bookbinder, 2007). The Chinese manufacturing and its business environment are unique in many ways. Many Chinese factories are export oriented and their major markets are faraway developed countries (GPRD Business Council, 2007). Their supply chain costs are sensitive to oil price fluctuations due to a long transport distance. In terms of business environment, China is still far from being a free market. The Chinese central government controls the exchange rate of its currency renminbi (RMB), which is very influential on the cost competitiveness of Chinese manufacturers. It offers export value-added tax (VAT) rebates by product types to encourage certain industries. Geographically, China has a large continent and there are significant cost disparities between its coastal and inland regions. To mitigate rising cost pressure in coastal regions, Chinese manufacturers has the alternative of relocating to inland regions besides the option of moving overseas.
This paper aims to narrow the research gap by developing a bi-objective model for the supply chain design of dispersed manufacturing in China. The work is inspired by a supply chain optimization project that Li & Fung implemented for a major US client. The client achieved substantial cost savings by switching to a dispersed manufacturing network. The bi-objective model captures the distinctive attribute of dispersed manufacturing by defining multiple production stages. It considers essential trade-offs between supply chain cost and lead time (Fisher, 1997) to determine optimal facility locations of manufacturing steps. The measurement of supply chain lead time is particularly relevant to dispersed manufacturing as it may consume considerable transport lead times if manufacturing facilities are far from each other or at different countries. The model is tailored for the unique Chinese manufacturing environment and it includes parameters such as currency exchange rate and export VAT rate. The model application with a representative case illustrates the cost benefits of dispersed manufacturing as opposed to performing all manufacturing steps of a product at a single facility location. It provides explanations in several factors that have benefited manufacturing growth in China in the past few decades. It also offers managerial insights on the future developments of global manufacturing trends.
The rest of this paper is organized as follows. Section 2 reviews relevant literature. Section 3 develops a bi-objective model. Section 4 applies the model for a case study. Section 5 presents results and analysis. Section 6 discusses findings and managerial implications. Section 7 concludes the research.
Section snippets
Literature review
Dispersed manufacturing, multi-plant manufacturing, and manufacturing network all involve multiple manufacturing facilities and need advanced information technologies to support process integration (Li et al., 2012, Tao et al., 2012). However, they are of key distinctions. Dispersed manufacturing and multi-plant manufacturing are a manufacturing practice or strategy (Schmenner, 1982), while manufacturing network is referred to as a network of manufacturing facilities (Boone et al., 1996). To be
A bi-objective model
This section presents a bi-objective model for the supply chain design of dispersed manufacturing in China. The bi-objective model incorporates major business environment variables that have been affecting labor-intensive global manufacturers in China in recent years. These factors include currency exchange rate, production cost, transportation cost, and export VAT rate. We consider a geographically dispersed manufacturing network as depicted in Fig. 1 (Li and O’Brien, 1999, Meixell and
Case description
This section applies the model for a case study. The characteristics of manufacturing operations are adapted from Zhao (2006) case study of a leading footwear manufacturer in the PRD. The model application considers a family of low-end labor-intensive footwear products. A unit of end-product (E) is formed by one unit of upper subassembly (S1) and one unit of sole subassembly (S2). A subassembly S1 and S2 is made from one set of upper components (C1) and one set of sole components (C2),
Base case results
Table 4 shows optimal supply chain design of dispersed manufacturing in the base case scenario. The measurements of unit supply chain cost and supply chain lead time correspond to the two objectives of the bi-objective model. To be specific, unit supply chain cost is obtained from the division of total yearly cost by demand volume. Supply chain lead time is calculated as the sum of longest lead time at each supply chain echelon, assuming raw materials and semi-finished products are ordered
Discussion
Previous studies of Chinese manufacturers suggested that their competitiveness were derived from marketing and human resource competencies (Li, 2000), manufacturing control (Li, 2005), favourable foreign exchange rate, cheap labor (Adams et al., 2006), and supply chain collaboration (Li, 2012). This research sheds new light to offer explanations why China’s manufacturing sector has been growing fast in the past three decades. It also suggests future trends of manufacturing growth in China in a
Conclusions
This paper deals with supply chain design of dispersed manufacturing in China under changing business environments. Dispersed manufacturing dissects the supply chain to assign each process to an optimal location to achieve the greatest cumulative competitive advantage. It has been an integral part of global manufacturing in China as the nation rises as the “Factory of the World”. Supply chain design of dispersed manufacturing is a challenging task, because it needs to consider essential
Acknowledgements
The authors would like to thank guest editors and two anonymous reviewers for their constructive comments. The authors are grateful for partial financial supports from HKU research committee and UDF, HKSAR RGC GRF, and the Guangdong Department of Science and Technology (2010B050100023, 2010B050400005).
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