مدل سازی مفهومی برای زنجیره تامین با موجودی قابل مشاهده
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20683||2011||8 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 133, Issue 2, October 2011, Pages 578–585
Visibility becomes increasingly important for companies that seek to globalise their supply chains due to the increasing complexity involved. This paper contributes to the research on Supply Chain Visibility (SCV) from an inventory perspective with a focus on inventory visibility, which is a critical part of SCV. The characteristics of Inventory Visibility (IV), which are inherited from SCV, are conceptually analysed. A theoretical model in terms of atom, single, and compound visibility, is developed based on the characteristics identified. A method for objectively measuring IV is presented together with a case example to demonstrate its convenience and usefulness.
With globalisation, supply chains become increasingly complex and companies are more aware of the need to have better Supply Chain Visibility (SCV). Enslow (2006) reports that the lack of supply chain process visibility is a main concern for about 79% of the 150 large companies surveyed globally. This is verified by another recent survey of 400 supply chain executives worldwide (IBM, 2009). Presently, SCV is a favourite jargon in the supply chain management community with over 7,510,000 entries found on the Web (www.yahoo.com, 9 September 2009). However, it remains a popular buzzword albeit an ill-defined and poorly understood concept in the literature (Barratt and Oke, 2007). Indeed, SCV is a complex issue that involves people, process, technology, and information flow. From an IT perspective, SCV refers to an organisation's ability to collect and analyse distributed data, generate specific recommendations, and match insights to strategy (Tohamy et al., 2003). Bartlett et al. (2007) have shown that increased supply chain visibility can be achieved through supplier–customer collaboration. While an increase in available supply chain data provides the illusion of visibility, it also adds to a company's challenges. Moreover, 90% of all supply chains report that their global supply chain technology is inadequate to provide their finance organisation with the timely information required for budget and cash flow planning and management. The lack of visibility, complete or otherwise, is especially crippling for global supply chains, which can have pipeline inventory of $1 billion. Poor visibility and uncoordinated multi-tier processes for these companies can result in significant “just in case” inventory carrying costs, premium freight expenses, and extended cycle times. SCV is an emergent area of interest for both practise and academe due to the advent of advanced IT technologies such as RFID and GPS ( Bottani et al., 2010, Chang et al., 2010, Huo and Jiang, 2007, Melski et al., 2008 and O'Neill and Newton, 2004). Despite its practical relevance, there is confusion and misunderstanding about SCV, and there is no commonly accepted definition of SCV (Francis, 2008). While some definitions for SCV exist (Barratt and Oke, 2007, Francis, 2008, Hsiao-Lan and Wang, 2007, McCrea, 2005, Rao, 2004, Tohamy et al., 2003, Vitasek, 2006 and Zhang et al., 2008), they address SCV from different perspectives and have not captured the meaning, function, and essence of SCV holistically. SCV can be decomposed into inventory, demand, and logistics visibility based on the information available (Goh et al., 2009). Inventory Visibility (IV) is an important aspect of SCV, as it provides companies with information about their inventories to make their supply chain as effective as possible. It supplies the latest and accurate data from in-stock inventory to in-transit inventory, and helps optimise the end-to-end supply chain process. Today, with RFID that enables item level track and trace (Delen et al., 2007, Griffiths et al., 2007 and Zhou, 2009), some researches define SCV only from an inventory perspective. For example, Christopher and Lee (2004) highlight that many supply chains suffer from limited inventory visibility. This means that a particular entity in the network is unaware of the status of upstream and downstream operations of the levels and flow of inventory as it progresses through the chain. From the same perspective, Vitasek (2006) treats SCV as inventory management software applications that track and trace inventory globally at a line-item level, notifying the user of significant deviations from plan. IV has three stages: shipment tracking, supply chain event/disruption management, and the continuous improvement of the supply chain. First, IV provides a means to track goods and materials. Second, higher IV, especially, visibility into the movement of inventory, aids better decision making in disruptive event management. Third, a measure of the degree of IV provides a key indicator for supply chain performance improvement. As IV is an emerging research topic, existing research is mainly focused on modelling its benefits and impact from different perspectives to emphasise its importance (Bottani and Rizzi, 2008, Gumrukcu et al., 2008, Lee and Ozer, 2007, Li et al., 2009, Sahin and Dallery, 2009, Yao and Dresner, 2008 and Zhou, 2009). However, some research questions still persist, namely (i) how to objectively quantify IV?, (ii) what is the extent of visibility?, (iii) how to know if IV has improved?, and (iv) what is the improvement in IV? According to the SCV maturity model (Polese, 2002), the current solutions are targeted only at the functionality of the lower maturity levels. To achieve higher levels of maturity of SCV, there is a need to objectively quantify IV for supply chain performance improvement. This paper addresses such problems by providing a means for better SC collaboration and control, and continuous performance improvement. Thus, this paper seeks to contribute to a conceptual model of IV and provide some objective quantitative methods to measure IV for an actor in a supply chain, for a set of actors, and for a supply chain. The rest of this paper is organised as follows. Section 2 reviews the extant literature on IV. Section 3 develops the model for IV. A model based on set theory and objective quantitative methods for measuring IV is presented. Section 4 discusses the potential applications and their impact on practise and theory, and provides a case example together with a web based system to validate the conceptual model. Section 5 concludes with limitations and future research.
نتیجه گیری انگلیسی
IV is an important research area on SCV for companies due to its complexity and importance. To realise the benefits of IV, there is a need for an unambiguous, commonly understood, and accepted definition to clear any misunderstanding and confusion. A mathematical model of IV has been developed, which is beneficial to supply chain professionals to clearly communicate on SCV, which is a critical issue for many companies keen to operate in an end-to-end environment. The IV model presented in this paper is comprehensive. It helps to assess IV for better supply chain decision making. Introducing the concepts of AV, SV, and CV helps to formally conceptualise IV. The proposed measurement methods derived from the model to measure visibility, the capability of providing and accessing information are new and provide a performance indicator for IV. A detailed case study of extending the concept for assessing a pharmaceutical supply chain is presented in Zhang et al. (2010). However, as in every research, there are limitations. We note for the record that our proposed model assumes a deterministic nature of visibility. It specifically excludes partial IV, i.e., we do not consider the situation of partial information accessibility to an actor or for that matter partial information provision by an information item. We reserve this for another paper. Finally, several future research areas are possible. First, the analysis of the economic impact of the conceptual model presented in this paper is worth pursuing to help in better decision making. We can extend the technique used in assessing IV to include the assessment of SCV. This involves process modelling, measurement matrix definitions, and the interpretation of the results. The current IT architecture for improving SCV emphasises on sharing, especially providing information in a supply chain as real time data can be captured through RFID. This creates a challenge for supply chain professionals to access the right information at the right time. How to reduce data redundancy in the information models addressing SCV is critical.