مدل تجزیه تحلیل بهره وری تصادفی سیستماتیک برای ارزیابی عملکرد تامین کننده بین المللی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|4188||2010||8 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 6314 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 9, September 2010, Pages 6257–6264
The selection of suppliers and the evaluation of their performance are challenging complex task faced by manufacturing managers in a global market. This is mainly due to three hurdles: (1) various criteria that characterize the supplier performance, (2) risk and uncertainty associated with supplier performance on multiple measures and (3) intangible attributes in cross- countries such as the political, legal, economic, socio-cultural and technological features. The paper develops a stochastic efficiency analysis model to deal with these three hurdles. The model is a new methodological extension to data envelopment analysis (DEA) and applicable to efficiency analysis for entities from different systems with imbedded uncertainty. The application of the proposed model to the international supplier evaluation is the first attempt to model suppler performance from different sub-systems with different environment factors and uncertainty using Stochastic DEA.
Supplier evaluation has been very important to operational decisions, involving decisions of selecting which vendors to employ, as well as decisions of with respect to quantities to order from each vendor. An assessment of supplier performance involves many capacities such as the following: (1) it helps managers to focus on the priority areas and make objective realization more likely (2) it collects data for taking corrective action to enhance performance related to a special perspective goal. For example, the evaluation can document possible needs in additional resources such as personnel or information technology (3) it helps to explore and maintain better internal relationships by isolating problem areas (4) it provides information to senior management with supplier’s contribution (5) people performing at a better-than-normal level can be identified and rewarded, which would improve motivation in the organization. In today’s competitive global business environment, the selection of suppliers and the evaluation of their performance remain to a complex task faced by manufacturing managers in a global market. This is mainly because of the following three reasons. Firstly, various criteria characterizing the supplier performance are required to be involved in the model (Dickson, 1966; Vijayan, 2000 and Weber et al., 1991). These multiple measures often include important product- and service-related attributes such as price, delivery, and quality performance. Even in B2B transactions, it is important for software developing companies to consider multiple vendor related attributes other than Price (Vijayan, 2000). Secondly, as pointed out by several researchers supply risk and uncertainty associated with supplier performance on multiple measures are critical elements in the supply chain management. Handling supply risk and uncertainty has been a significant management effort due to the increasing number of suppliers and multiple criteria on which these suppliers are evaluated. The third reason is that most of the time it is important to categorize various suppliers of interests in the evaluation process. Talluri and Narasimhan (2005) classify the candidate suppliers into two sets: potential candidates and existing supplier. This supplier selection problem is considered by a large, multinational, telecommunications company, which is a global leader in design, production, and marketing of communication systems. The company operates production plants, research and development facilities, and distribution systems globally. Six input and five output factors are utilized to represent the supplier capabilities and the performance outcomes of the suppliers, respectively. Narasimhan, Srinivas, and David (2001) identified four supplier clusters based on the DEA efficiency: high performers and efficient (HE), high performers and inefficient (HI), low performers and efficient (LE), and low performers and inefficient (LI). With such categories, effective benchmarks from the HE cluster can be identified for improving the operations of suppliers in the HI, LE, and LI clusters. Another issue related to the assessment of multiple sub-systems is to incorporate environmental criteria into supplier selection process in green supply chain management due to increasing consumer awareness and concern over environmental pollution. Different locations involve different environmental criteria, and therefore a multi-system evaluation becomes necessary. In reality there is a need to compare suppliers where some candidates may have different environment and work in different sub-systems, which the others cannot adopt. Hence, the classical way to perform comparisons within one system is obviously not fair in the above. A concrete example is that managers have to understand and analyze the political, legal, economic, socio-cultural and technological features when they try to conduct business in different countries. Traditional methods may no longer applicable to real-world cases. The above three points have an obvious effect on the international supplier selection due to the complexity and uncertainty by lack of information associated with related countries’ business environment in a global market (Qu & Brocklehurst, 2003). In fact, international supplier selection has become an active area in supply chain management since many companies have begun to realize the opportunities in terms of lower production and labor costs that other countries can offer (Bowman et al., 2000, Buskens et al., 2003, Kaynak, 1989, Mummaleneni et al., 1996 and Murray et al., 2005). The choosing of international suppliers may involve more intangible criteria and require more time to gather information and identify uncertainty and risk in order to effectively evaluate potential suppliers. Various methods have been developed to deal with these problems. The readers are suggested to read the review report by Sonmez M. (2006) and the references therein. However, none of these approaches address all of the three points mentioned above. In this paper, a method is developed to measure international supplier performance by taking into account risk and uncertainty associated with supplier performance on multiple measures in multiple categorical suppliers. This method is an extension to the classical stochastic DEA model and also the bilateral systematic DEA model in Cooper, Seiford, and Tone (2000). As an alternative to various multi-factor productivity analysis techniques, our proposed model deals with two major drawbacks of classical DEA: (і) failure to model the stochastic error in the estimated frontier and (іі) extra requirement of a consistent infrastructure and operating environment in which the entities, appropriately called Decision Making Units (DMUs), operate. Given the paper’s emphasis in this area, the contribution of our research is twofold. First, we propose an efficiency analysis approach for entities from different systems to address the risk and uncertainty imbedded in different systems of interests. This is a new methodological extension to DEA research. Second, we apply the proposed model to evaluate the performance of international suppliers from different countries. To our knowledge, it is the first one to attempt this by modeling supplier performance from different sub-system with stochastic factors and uncertainty using stochastic DEA. We begin in the following section with a literature review. Section 3 provides the proposed model for muti-system performance evaluation and international vendor selection in this paper. Section 4 gives the numerical illustration. Finally, our conclusions and further discussions are presented in Section 5.
نتیجه گیری انگلیسی
International vendor selection in supply chains by its nature involves the need to trade off multiple criteria, as well as the presence of uncertain data from multiple countries. Research gaps are highlighted through a literature review in this paper and these highlighted issues are quantified by presenting a multi-system stochastic DEA model. The proposed model allows efficiency to be evaluated for suppliers from different systems with stochastic factor and uncertainty imbedded. Appropriate suppliers are chosen from multiple countries in the numerical illustration.