مدیریت ریسک کیفیت محصول و قابلیت دید در زنجیره تامین چند لایه
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|822||2012||9 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 139, Issue 1, September 2012, Pages 49–57
The Chinese melamine milk recall and a series of product harm scandals ranging from milk powder to chocolate bar indicate that firms and consumers alike are vulnerable to quality risks in a global supply chain. Supply chains are extended by outsourcing and stretched by globalization, which greatly increase the complexity of supply network and decrease the visibility in risk and operation process. It is hard for firms to manage the product quality of such a multi-layer supply chain which has a low traceability of material origin. In this paper, we argue that better visibility of risk in supply chain could minimize the threat of product harm. A supply chain product quality risk management framework, integrating both the incremental calculus and marginal analysis, is proposed. Case study results indicate that the proposed approach has the following benefits: (i) providing evaluation of the product quality risk in supply chain layers; (ii) allowance for firms to have a better ‘visibility’ of product quality risks in supply chain; and (iii) a traceable justification path for multi-sourcing decision.
A wide range of product recall is announced in recent years, ranging from food product to non-food product. Especially, most of these recalled products were made or sourced from China. In 2008, out of the 86 consumer products recalled in the UK, 72% of these recalled products were made in China (RAPEX, 2009). This may be due to the large amount of exports from China, high customer demand, complexity of supply network and large magnitude of global sourcing. Melamine milk incident in 2009 was a classic example of product recall. The recall events were followed by an avalanche of reports in government agency and the press about quality problems with other Chinese-made products. As in all cases both governments and consumers wanted these products promptly to be removed from the marketplace due to the health and safety concerns. The melamine incident also reveals a fact that there is a domino effect of product recall from bottom of the chain—raw material suppliers to the frontend customers all over the chain. The major cause of this effect is that some of upstream supply chain members add the toxic substance, melamine, to artificially inflate the protein of the milk by increasing the nitrogen level, which is the key test-indicator to influence the protein level in the milk to be acceptable. This example illustrates that, as supply chains are extended by outsourcing and stretched by globalization, disruption risks and lack of visibility into a supplier’s status can both worsen (Yang et al., 2009). It is very hard for firms to manage the visibility of a long or “deep” supply chain which has a low traceability of material origin. Especially, it is a great challenge for a foreign firm to keep track of who did it, what he did and when he did, to the final quality of the products (Lyles et al., 2008). The possible causes of product quality problem in “low visibility” supply chain are myriad, such as, poor material from supplier, non-conformance incoming inspection in manufacturer, product contaminated or damaged during logistics operations. It is important to make manufacturers aware of anticipation, preparation and managing potential supply quality problem when the supply risks rise. The losses due to product harm crisis can be huge. For example, when China Mengniu Dairy announced the recalls of its tainted product on 17 September 2008, Hong Kong Stock Exchange suspended trading in shares of Mengniu and its stock price dropped almost 60%. A manufacturer has a number of risk management strategies when managing supply quality risk, including supplier qualification screening, multi-sourcing, flexibility, and penalties levied for supplier non-performance (Yang et al., 2009). Some researches focus on contract designing issue for obtaining the equilibrium outcome that the penalty clauses are adopted as recover damage in non-delivery (Baiman et al., 2000 and Yang et al., 2009), or base on the information from the incoming inspection and the external failure (Balachandran and Radhakrishnan, 2005). Intuitively, the effectiveness of supply chain risk management strategies depends on visibility among supply chain members and the manufacturer. For instance, if the manufacturer knows that his purchasing order is being outsourced to mainland China by the supplier, the supply risk management strategies would likely be different. Actually, suppliers often have better information about product quality risk than the focal firm does, because of the suppliers’ private knowledge of state of operations, quality in production and input sources (i.e. a situation of asymmetric information between buyer and seller). The majority of recent papers treated the product quality problem as production quality problem (Tannock and Balogun, 2007, Karim et al., 2008 and Hales and Chakravorty, 2006) and supply chain risk management mainly focused on supply chain disruption (Yang et al., 2009, Baiman et al., 2000 and Tomlin, 2006). Hwang et al. (2006) examined the arrangement of vendor certification and appraisal in mitigating the problem of supplier quality, but they looked into the problem in inspection strategies and there was nothing much related to the sourcing strategies in supply network. There were only few researches considering the product quality problem in the global supply chain context. Zhu et al. (2007) proposed a quality improvement strategy along the supply chain that both buyer and seller had an incentive to invest in quality investment effort. However, their model did not take into account the supply chain visibility issue between the buyer and seller. To address these gaps in the current literature, we investigate the interaction between product quality risk, supply chain visibility, quality related costs and multi-sourcing decision. In this context, we seek to address the following questions: • Research Question 1: How to evaluate the product quality risk and its visibility in multi-layer supply chain environment? • Research Question 2: How does a manufacturer select the appropriate sourcing suppliers with consideration of supply reliability and visibility? In answering these questions, we develop a decision support framework for product quality risk management, which incorporates various supply risk management strategies, including supplier qualification screening, multi-sourcing, penalties levied for supplier's defects. We also propose a marginal incremental analysis-based approach as the basis of mitigating quality risk in their multi-tier supply chain so that an integrated multi-criteria decision path is developed. The proposed marginal incremental analysis approach is a sequence of transparent steps to provide clarity of thought into the evaluation and selection process that decision makers undertake. In the following sections, the development of the proposed approach is explained. Section 2 discusses the recent literatures and Section 3 describes the background and motivation to adopt a marginal incremental analysis-based approach in the product quality risk management framework. Section 4 describes Model of product quality risk, product quality related cost, and visibility. In Section 5, a case is used to illustrate the application of the proposed approach. Finally, the results are described and implications of this research for industrialists and academics are discussed.
نتیجه گیری انگلیسی
In a supply chain, the quality of a firm's product depends not only on its quality but also on the supplier's quality. The unclear information of product quality risk across the upstream and downstream supply chain members can lead to product harm crisis. In this paper, a MIA approach is proposed to manage the product quality risk and evaluate the supply chain visibility. The mechanisms involve jointed expected profit maximization, product quality risk and visibility identification, supplier selection and solution re-evaluation by adopting marginal incremental analysis. First, multi-sourcing model generates the initial set of multi-sourcing solutions. Then, a series of marginal incremental analyses are conducted to further evaluate product quality risk and visibility in supply chain parties. The case study has demonstrated the possibility of using a marginal incremental analysis justification approach to support managers in the difficult task of designing multi-sourcing strategy in multi-layer environment. The proposed framework is feasible and enables managers to have a traceable multi-sourcing decision with a decision pathway. The insight gained from the MIA technique provides Company X the following benefits: (i) the product quality risk and visibility of the potential suppliers are “shaped” and compared with each other, thus providing a more comprehensive evaluation; (ii) in the decision process, the trade-offs of quality criteria in both upstream and downstream are taken and the product quality risk can be mitigated by selecting low risks alternatives; and (iii) the framework provides a flexible way in evaluation by changing the priority of quality criteria in light of the different insight gained. In this paper, we focus on the issue of analyzing the product quality risk and visibility in the global supply chain environment. Further research is needed to explore product quality risk and visibility in a more complex supply network with information asymmetry. In addition, the approach examined here can be extended to include problems that involve different performance measures and more detailed cost models, such as supply risk assessment problem and quality risk mitigation problem along supply chain.