تقسیم بندی تامین کننده با استفاده از منطق فازی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|21256||2013||11 صفحه PDF||سفارش دهید||8110 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Industrial Marketing Management, Volume 42, Issue 4, May 2013, Pages 507–517
Supplier segmentation means that the suppliers of a specific firm are categorized on the basis of their similarities. This supply-side business-to-business (B2B) segmentation is of special importance to companies with many suppliers. Supplier segmentation yields a manageable number of segments, each of which requires a separate strategy. Standard supplier segmentation methods have serious shortcomings, for instance because they fail to make a proper connection between supplier segmentation and other supplier-related activities such as supplier selection and development. Moreover, these standard methods typically use a limited number of segmentation criteria and different sets of criteria are suggested for each method. It is unclear for practitioners how to choose a particular method. The purpose of this paper is to form a practical tool for supplier segmentation taking into account all suggested segmentation criteria. The principal result of this paper is the design of a rule-based method to segment the suppliers of a firm based on two overarching dimensions: supplier capabilities and supplier willingness. The method is applied to a real-world situation to show how the results can be used in practice. A general sensitivity analysis procedure for fuzzy rule-based systems is proposed and then implemented, to identify the most important supplier capabilities and willingness criteria and to formulate better supplier development strategies. A major conclusion of the paper is that the fuzzy logic approach to supplier segmentation is simple to apply in practice, yet considers all available segmentation criteria and their inherent fuzziness in a way that is easily adaptable to a specific industrial context.
In today's world, where there is a growing trend towards outsourcing (McIvor, 2008), firms do not carry out all their activities themselves (Desai, 2009), but rely more and more on their suppliers, which are usually selected on the basis of several criteria that are important to the firm. Several multi-criteria and multi-objective methodologies have been applied to supplier selection (e.g. de Boer et al., 2001, Dickson, 1966, Ho et al., 2010, Rezaei and Davoodi, 2011, Rezaei and Davoodi, 2012, Sawik, 2010, Weber et al., 1991, Wilson, 1994 and Wu et al., 2010). Given a selected set of suppliers, supplier relationship management provides a basis for firms to develop and maintain relationships with these suppliers (Lambert, 2008). Especially when firms have many suppliers, it is difficult to manage all relationships individually, which is why in supplier relationship management, firms develop business-to-business (B2B) strategies for different groups of suppliers (Wagner & Johnson, 2004). Supplier segmentation, as a step between these two strategic activities (supplier selection and supplier relationship management), yields distinct groups of suppliers based on their similarities. Compared to customer segmentation, supplier segmentation has received relatively little attention and is in its infancy (Day et al., 2010 and Rezaei and Ortt, 2012b). While customer segmentation is aimed at the demand-side of the market, supplier segmentation focuses on the supply-side of the market (Erevelles & Stevenson, 2006). In fact, market segmentation can be divided in three sub-topics: a) Consumer segmentation (e.g. segmentation of car users for a car parts producer); b) Industrial customer segmentation or demand-side B2B segmentation (e.g. segmentation of car assembly plants by a car parts producer); c) Supplier segmentation or supply-side B2B segmentation (e.g. segmentation of component manufactures used by a car parts producer). While the first of these two sub-topics are relatively well-established and well-researched, the third has so far received less attention. Although a few approaches have been developed to supplier segmentation, these approaches are mostly normative and provide no practical tools for implementation in real-world situations. The main objective of this paper is to provide a practical tool for supplier segmentation. To this end, we apply a fuzzy rule-based approach to implement a more comprehensive conceptual framework for supplier segmentation. We think that supplier segmentation – like many other marketing problems – because of its complexity and the high degree of fuzziness of variables involved, may be handled more effectively by intelligent systems, which so far have received little attention in marketing (e.g. Casillas & Martínez-López, 2010). We refer to Wierenga (2010) for a possible explanation for this state of affairs, and also the status of Artificial Intelligence (AI) in marketing in general. Fuzzy rule-based approaches, such as the method for supplier segmentation developed in this paper, are interesting for marketing management because they enable building practical models even when a limited number of data is available. Moreover, these models can be built using the experience of marketing managers. The fuzzy rule-based approach forces these practitioners to discuss their priorities and preferences regarding decision criteria but at the same time allows the fuzziness that is inevitable in real-world management situations. Finally, by involving practitioners, this approach facilitates the implementation and use of the resulting models. Our method of supplier segmentation builds on the existing methods by combining available segmentation criteria. The main contribution of the paper is the design of a rule-based approach to segment the suppliers of a firm based on two overarching dimensions that capture these available segmentation criteria. Another methodological contribution of the paper is to develop and apply a general sensitivity analysis procedure for fuzzy rule-based systems. This analysis is used to identify the most important supplier capabilities and willingness criteria and to formulate better supplier development strategies. In the next section, the conceptual background is presented. In Section 3, a methodology is proposed, including the design and implementation of two fuzzy rule-based systems. In Section 4, we apply the proposed methodology to a real situation. In Section 5 the conclusion, implications and future research avenues are discussed.
نتیجه گیری انگلیسی
In this paper, we illustrate a new way to segment suppliers and explain how the resulting segments can be used to formulate supplier strategies. Our approach to supplier segmentation considers a full set of potential segmentation criteria resulting from a literature search (see also Rezaei & Ortt, 2012b). We propose a fuzzy rule-based system in which experts are requested to indicate which of these segmentation criteria are most important and how these criteria do contribute to the suppliers’ capabilities and willingness. Subsequently, experts are requested to evaluate the suppliers using the selected set of segmentation criteria. Next, the capabilities and willingness scores are calculated. The scores on the segmentation criteria are combined into two overarching dimensions, supplier capabilities and willingness, and the resulting overview facilitates the formulation of supplier segmentation strategies. The fuzzy rule-based approach to supplier segmentation has several advantages. The approach can be designed by interviewing a limited number of knowledgeable managers or experts. The approach also facilitates a proper connection between supplier selection, supplier relationship management and supplier development. Fig. 7 contains a flowchart including the steps that should be followed when applying the fuzzy rule-based system to segment the suppliers. It also shows how supplier segmentation is connected to the other supplier-related activities. Finally, the fuzzy rule-based approach proves a very flexible approach that has some advantages over other methods, such as the ability to handle the inherent interdependencies, vagueness and contingencies of segmentation variables. Full-size image (48 K) Fig. 7. A flowchart including the supplier segmentation procedure. Figure options Our approach, in which a limited number of experts indicate which segmentation criteria are most important and how these criteria determine the overall supplier capabilities and willingness scores, almost inevitably contains subjective judgments. There are different ways to check these judgments. Firstly, by comparing the judgments of several experts, the evaluations can become inter-subjective. Secondly, we performed a general sensitivity analysis for fuzzy rule-based systems to identify the most important supplier capabilities and willingness criteria after they were applied to rate suppliers. In this way, the subjective choices can be checked and the most important segmentation criteria can be selected.