انتخاب مشترک سازمان های گمرک و شرکت های حمل و نقل جاده ای بین المللی با رویکرد فرایند تحلیل شبکه ای فازی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|6155||2011||8 صفحه PDF||سفارش دهید||5623 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 38, Issue 7, July 2011, Pages 8251–8258
This paper considers a special case for logistics activities in Turkey: a joint selection of customs broker agency and international road transportation firm. For this purpose a decision-making team has been constituted, including members of logistics and finance departments and an academic. They determined related quantitative and qualitative criteria for the selection process. To cover the vagueness of related qualitative data, a fuzzy analytic network process (FANP) based model was formulated and applied to the decision-making process. The FANP model encompasses and substantially resolves the ambiguity and imprecision of the pairwise comparison process. By using the proposed FANP structure, the joint selection problem could be solved in a much easier way by also considering the inter-dependencies related to criteria.
The pressure that the challenges of globalization puts on the shoulders of firms means that supply chain management has become an issue that goes beyond national boundaries. Manufacturing firms typically set up foreign factories in order to benefit from tariff and trade concessions, low-cost direct labor, capital subsidies and in order to develop close relationships with suppliers (Amin and Razmi, 2009, Chou and Chang, 2008, Ferdows, 1997, Lee, 2009 and Wu et al., 2009). In this global perspective, significant geographical distances simply cause an increase in logistics costs. Nowadays firms focus on those core activities which are critical to their survival, and they assign the remaining activities to specialized firms. Many researchers have addressed the increasing use of logistics outsourcing as a widespread source of competition (Huiskonen and Pirttilä, 2002, Işıklar et al., 2007, Jharkharia and Shankar, 2007, Liu and Wang, 2009 and Wong and Karia, 2010). Recent benchmarking studies have found that organizations often make important insourcing/outsourcing decisions without fully understanding all the implications. A “quick and dirty” approach to such decisions can have devastating results, including the loss of a core competence, or the outsourcing of an activity to a supplier or customer that could not meet customer performance requirements. Several methodologies have been applied to logistics outsourcing and third party logistics provider selection problem. Traditional methods, such as the categorical method (CM) and the cost ratio method (CRM), have been studied by Timmerman (1987). Data envelopment analysis (DEA) also with consideration of multiple inputs and multiple outputs offers an estimate of comparative efficiency (Celebi and Bayraktar, 2008 and Saen, 2007). Mathematical programming methods such as goal programming (GP), compromise programming (CP), multi-objective programming (MOP) have also been applied (Lee et al., 2009, Lin, 2009, Sanayei et al., 2009 and Tsai and Chou, 2009) to selection problems. Examples of methods based on artificial intelligence (AI) technology that have been applied to supplier selection include neural networks and expert systems (Choy et al., 2003 and Lee and Ou-Yang, 2009). These methods mostly considered solving selection problems with quantitative criteria. Alongside these methods, several different group decision-making methods which take into consideration various forms of vagueness have also been developed. This goal has also been approached by the use of multi-criteria decision-making (MCDM) techniques such as analytic hierarchy processes (AHP), analytic network processes (ANP), technique of order preference by similarity to ideal solution (TOPSIS), elimination and choice expressing reality (ELECTRE) and preference-ranking organization method for enrichment evaluations (PROMETHEE). Some of these techniques give better results for specific decision problems. Supplier selection decisions are generally based on a set of criteria which are evaluated by experts. These evaluation criteria are usually in conflict with each other, and this further complicates the decision-making process. Tradeoffs between the evaluation criteria must be analyzed (Montazer, Saremi, & Ramezani, 2009). As can be seen from the literature, most of the multiple-criteria decision-making techniques give this opportunity. However, it can be seen that in most of the recent studies, decision-makers have preferred to use linguistic expressions. Recognizing this fact, in recent studies hybrid methods have been developed by combining decision-making techniques with fuzzy set theory (Boran et al., 2009 and Ho et al., 2009). In this study a fuzzy analytic network process (F-ANP) approach has been proposed for the joint selection of Turkish customs broker agencies and international road transportation firms. The analytic network process (ANP) is a widely-used multiple-criteria decision-making tool which was first proposed by Saaty (1996). ANP can be applied to tackle more general structures, including interrelationships between different criteria in different clusters or within the same cluster, while AHP can only model strictly hierarchical structures. Hence, ANP can be considered a more general form of AHP, in which dependencies and feedbacks between elements of a decision can be modeled (Razmi, Rafiei, & Hashemi, 2009). Beside these advantages, ANP has a great drawback, which is the pairwise comparison section. This section consists of deterministic comparisons, while real world cases by their very nature contain vagueness. Therefore, we have combined fuzzy sets theory (Zadeh, 1965) with ANP to overcome this drawback. The remainder of this paper is organized as follows: Section 2 provides detailed descriptions of the contents of the ANP process and fuzzy ANP. Section 3 explains the constitution of the decision-making team (DMT) and criteria determination. In Section 4 a FANP-based joint selection model is presented and the obtained results are commented. The paper concludes with Section 5.
نتیجه گیری انگلیسی
Transportation is becoming an increasingly important aspect of supply chain management. It is a vital element in successfully fulfilling customer orders. At the same time, managing transportation has become more complex. Congestion on roads and at ports (both sea and air) makes estimated arrival times worthless. Rising fuel prices and other costs have caused transportation costs to assume a larger part in the total supply chain costs. Recent changes to road taxes and truck safety costs have contributed to this. In addition to all these current issues, serious environmental problems are pounding at the door. Governments force companies to make public the environmental damage they cause. Hence, in the future the transportation agenda will not only be dominated by cost in euros or dollars the environmental impacts of CO2 will also become increasingly relevant. In summary, transportation is on the agenda of the today’s supply chain manager more than ever before. Customs regulations in different countries are another important issue to consider. Experienced associations could be beneficial in overcoming related obstacles and accelerating related processes. In Turkey, as mentioned before, customs broker agencies choose the transportation firm with which they want to collaborate. So when a customer chooses the customs broker agency it has already selected the transportation firm. At this stage all the criteria that the customer considers separately for customs broker agencies and international road transportation firms must be combined, and considered in the light of each other. In this phase the fuzzy ANP model substantially covers and solves the ambiguity and imprecision of the pairwise comparison process. Using the proposed FANP structure could enable a much easier solution to the joint selection problem. The problem considered in this study was a specific issue in the Turkish logistics environment. The joint selection process could be extended to include all the Turkish logistics area firms involved, and the issues could be considered in future studies.