بررسی استفاده از RST برای ایجاد مدل انتخاب تامین کننده و قواعد تصمیم گیری
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|19229||2010||12 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 8838 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 37, Issue 12, December 2010, Pages 8284–8295
Building the model of supplier selection is a critical role to improve competitiveness and business process. The purpose of this study was to build a model of supplier selection to better encourage organizational capability and competitiveness and apply the model to solve practical problems. After literature reviewing, this study chooses the critical criteria for supplier evaluation and then develops the questionnaire which differentiates class 1 (excellent firms), class 2 (common firms), and class 3 (disappointed firms) from suppliers to evaluate by participants. And next step was to use rough set theory (RST) to analyze the rules of supplier selection. After attributes reduct and core, the decision-making rules could be created by the supplier selection model. In the future, the model and rules may assist procurement personnel or manager responsible for supplier selection to execute relevant policies. The model can also be readjusted in order to accord with actual needs and changes in the competitive environment.
With competition intensifying of global market, the distance between product quality and performance becomes shorter gradually. This situation arouses attention from scholars and industries and facilitates them to reflect on how to manage the enterprise operation more effectively and more efficiently (Sarmah, Acharya, & Goyal, 2006). Supply chain (SC) refers to an organizational network which conveys the values of product and service to customer through different procedures and activities. While supply chain management (SCM) indicates a method to design, manage and control supply chain by integrating orientation through procedure. The main goal of SCM is to create value by promoting customer service and deceasing cost. From view of enterprise organization, SCM is a new management method to upgrade the supplier relationship to suppliant chain partnership. When referring to the tendency of primary supplier relation management in current supplicant management, it transfers the supplier from arm’s length relationship to strategic partnership of collaboration. Through share of risk and benefit, exchange of production work and financial information, investment of plant equipment and system, performance promotion and new product development, the members in the supply chain help each other successfully (Albino, Carbonara, & Giannoccaro, 2007). For practice of supply chain, however, not every activity in supply chain can be solved perfectly. In researches on global supply chain, Stratton and Warburton (2006) have mentioned a trade-off relationship between low cost and rapid response in supply chain activity. With the increase in global market competition and customer expectation, it is impossible for enterprise to extricate itself from predicament unless it pays more attention to supply chain running. Therefore, how to discover and solve the problems in supply chain management has special significance. When referring to recent researches of supply chain management, however, many of them solve the practice problem in supply chain with mathematical model. For example, Canakoglu and Bilgic (2007) focus on communication industry to deduce how many resources we shall cast into product development and technology research in supply chain. In such case, it can optimize the benefits for members in supply chain. Under Markov model, Kurata and Liou (2007) put forward the best promotion plan for retail dealers in supply chain. While Tempelmeier, 2006 and Jain, 2007 apply mathematical model to calculate the optimum allocation of product manufacturing and stock in supply chain when there are different requirements of customers. Surely, there are other subjects that are applied frequently in the literatures of previous years and recent years, such as production scheduling problem (Lin, Cheng, & Chou, 2007), demand forecasting (Aburto & Weber, 2007), planned best customer order lead time (Choi, Bai, Geunes, & Romeijn, 2007), production and inventory management (Boute et al., 2007 and Schwartz et al., 2006), and material cost management (Tsai, 2007), etc. The supplier selection is one key point for establishing the supply chain, but there are various factors that affect supplier selection. Moreover, it is a complicated course with several aspects. Generally speaking, the enterprise operators cannot make decision directly but set up a systemized model to make accurate selection by applying effective decision-making tool. On the basis of previous researches on supplier selection (Andrabi et al., 2006, Chan, 2003, Handfield et al., 2002, Jayaraman et al., 1999, Kauffman and Popkowski Leszczyc, 2005, Moller and Torronen, 2003 and Verma and Pullman, 1998), there are various methods that can assist evaluation procedure going justly and objectively. Then, we have a decision-making basis for final judgment. Hereby, this research aims to develop a selection model for supplier primarily. It adopts rough set theory (RST) as main analysis method for enterprise to find the optimum supplier partner quickly and accurately in the designing and organizing of supply chain. In the second part of text, it does literature exploration on SCM, supplier selection and RST, etc. The third section focuses on the interpretation of research method, procedure and data source. The fourth section explains analysis content and result. According to analysis results, the fifth section performs exploration practically and theoretically and then put forward suggestions.
نتیجه گیری انگلیسی
According to modeling course and analysis results above, RST can certainly provide effective and distinct supplier classification method among subjects of supplier selection. The advantage of RST is that it can set up individual and accurate classification model according to sample data, and provide the decision-maker with specific decision-making rules as references. It is a unique function that cannot be offered by other calculation methods, especially in terms of decision-making rules. RST model, however, is still imperfect. For example, its classification capability is not as good as learning machines such as artificial neural network or support vector machine, etc., or cannot provide influence degree of each attribute as traditional statistics analysis model does. Boolean calculation method adopted by RST is the largest limitation because the calculation result only can be Yes or No (0 or 1). It is impossible for it to provide the decision-maker with classification probability as reference, so the decision-maker only can judge dogmatically the category Yes or No belonging to. Although RST performs well in supplier selection classification model, it must be applied with other calculation methods to promote performance. The purpose of this research is to explore performance and application of RST model on supplier selection subject, so it does not improve this model according to limitations above but put forward applicable advantages and how to maximize the advantages through application. It is verified by the research results that RST does not offer good classification accuracy for supplier in each category, but separate the decision-making rules from each other for individual exploration. Therefore, we can separate the first-class decision-making rules of good classification accuracy from others to judge whether this supplier belongs to good supplier in the future. According to export results, we get satisfying classification accuracy of 86%. On the basis of export result matrix diagram (Fig. 4), the company will not suffer great risk and loss even when the supplier of the first class is selected into the second-class group. Hereby, the supplier selection classification model and decision-making rules derived from RST have advantages and practicability in theory and practice.