تجزیه و تحلیل ارائه دهنده لجستیک معکوس شخص ثالث با استفاده از مدلسازی ساختاری تفسیری
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|1457||2012||8 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 140, Issue 1, November 2012, Pages 204–211
Due to growing economic environment and the introduction of new technologies in marketing, another topic of great interest to logistics today is the use of contract or third party services. In the complicated business world, the company is involved in reuse, recycling, and remanufacturing functions using a third party logistics provider which has an impact on the total performance of the firm. In the development of the reverse logistics concept and practice, the selection of providers for the specific function of reverse logistics support becomes more important. After scanning the surplus of literatures, it was concluded that multiple dimensions and attributes must be used in the evaluation and selection of 3PRLP. The attributes play an important role in selecting a third party reverse logistics provider (3PRLP). Interpretive structural modeling (ISM) methodology is adopted in this model, which can be used for identifying and summarizing relationships among specific attributes for selecting the best third party reverse logistics provider among the ‘n’ 3PRLPs.
The term supply chain represents the complete set of activities involved in marketing, planning, purchasing, full manufacturing, distribution, delivery process, and reverse logistics. Nowadays, the supply chain plays a vital role in the value creation process. Supply chain management recognizes the importance of, and focuses effort on, achieving tight integration between the various links of the chain. To be efficient, a supply chain must exploit modern productivity techniques and approaches, for example JIT purchasing, economic batch sizes, strategic inventory, reverse logistics, third party logistics, etc. Logistic management is termed as the detailed process of planning, implementing, and controlling the efficient, cost effective flow and storage of materials and products, and related information within a supply chain to satisfy demand (CLM, 2004), and logistics is recognized as the key enabler that allows a company to increase and maintain its competitive advantage and ensures maximum customer satisfaction (Drucker, 1962). Reverse logistics is the process of moving goods from their typical final destination to another point, for the purpose of capturing value otherwise unavailable, or for the proper disposal of the products (Rogers and Tibben-Lembke, 2001 and Dowlatshahi, 2000). Reverse logistics is practiced in many industries, and its effective use can help a company to compete in all streams of advantages. Many situations exist for the product to be placed in a reverse flow, such as commercial returns, warranty returns, end-of-use returns, reusable container returns, and others (Du and Evans, 2008). According to Andel (1997), effective reverse logistics is believed to result in several direct benefits, including improved customer satisfaction, decreased resource investment levels, and reductions in storage and distribution costs (Autry et al., 2000). Many manufacturers and retailers recognize the importance and consider the outsourcing of reverse logistics (Du and Evans, 2008). 3PRLP selection and evaluation is one of the most critical activities that commits significant resources and impacts the total performance of the firm. The attributes involved in the selection and evaluation process may vary depending on the type of product considered, and these attributes are often in conflict with one another. To enhance 3PRLP selection, the proposed 3PRLP attributes are grouped into seven main attributes such as third party logistics services (3PLS), reverse logistics functions (RLF), organizational role (OR), user satisfaction (US), impact of use of 3PL (IU3PL), organizational performance criteria (OPC), IT Applications (IT), and 35 sub-attributes as shown in Table 1. The proposed attributes which aid in evaluating 3PRLP are interesting and become the objective of the building of a new model using ISM. It can be used for identifying and summarizing relationships among a specific variable that defines a problem or an issue and provides us with a means by which order can be imposed on the complexity of variables (Sage, 1977). The insight from the model would help supply chain managers in strategic planning to select the best 3PRLPs. After the introduction, the remainder of this paper is organized as follows. The literature review is given in Section 2. Section 3 describes the problem, and Section 4 presents a solution methodology. The application model (case study) is discussed in Section 5. The result analysis and conclusion of the paper is presented in the final section.
نتیجه گیری انگلیسی
A growing number of companies have begun to realize the importance of implementing integrated supply chain management since they are under pressure for filling customers' orders on time as well as for efficiently taking back returned products from customers after the sale. 3PRLPs are playing an increasing role in supporting such integrated supply chain management using sophisticated information systems and dedicated equipment. Thus, the objective of this work is to analyze the interaction among the attributes and level attributes using Interpretive Structural Model (ISM). A major contribution of this work lies in the development of linkages among various attributes of a third party reverse logistics provider through a single systemic framework. The utility of the proposed ISM methodology in imposing order and direction on the complexity of relationships among elements of a system assumes tremendous value to the decision makers. In this work, using the ISM methodology, a model to analyze the relationship among the attributes of 3PRL in the tire manufacturing industry is developed. However, this model has not been statistically validated. Structural Equation Modeling (SEM), also referred to as the linear structural relationship approach, has the capability of testing the validity of such hypothetical models (Kannan et al., 2010). Thus, this approach can be applied in future research to test the validity of this model. When comparing ISM and SEM, it is worth mentioning that although SEM has the capability of statistically testing an already developed theoretical model, it cannot develop an initial model for testing. ISM, on the other hand, has the capability to develop an initial model through managerial techniques such as brainstorming, nominal group techniques, etc. In this sense, ISM is a supportive analytic tool for the situation discussed.