Supplier segmentation using fuzzy logic

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.     

基于模糊概率petri网的故障诊断算法研究

分析研究了具有概率信息的模糊petri网的故障诊断方法,利用概率信息消除反向诊断过程中冲突消解问题的同时,针对不确定逻辑的故障相关性,建立了具有不确定逻辑关系的模糊概率petri网模型,从而拓展了petri网的描述能力,提出了一种改进的反向诊断新算法,提高了诊断准确度。并以一个实际的故障诊断例子,对该诊断算法进行了说明,证明了方法的准确性和可行性。     

Reflections on Werner Bonefeld's ‘Freedom and the Strong State: On German Ordoliberalism' and the Continuing Importance of the Ideas of Ordoliberalism to Understand Germany's (Contested) Role in Resolving the Eurozone Crisis

A historian and a political scientist take issue with Bonefeld's interpretation of ordoliberalism from the viewpoint of our historical knowledge of the Freiburg School. Our major disagreement is with Bonefeld's underlying assumption that the ideas of the Freiburgers on strong state authority were very durable and continued to be so across a divide as great as that of 1945 when a more strictly chronological use of the sources would have shown significant transformations. The earlier quasi proto-fascist ideas of the strong state were replaced with a much more muted role for the state in providing a constitutional framework in which the market forces could develop. It is through this break with their own initial sympathy with Hitler's strong state that the ideas of the Freiburger Ordnungspolitik underwent profound changes to a constitutional state as guarantor of economic stability, and only in this changed form do the ideas of a legal rule-based system of the Freiburger ordoliberals continue to play an important role in understanding Germany's role in resolving the Euro crisis. It is this significant shift, in the ideas of ordoliberals, that is missing in Bonefeld's article.     

中国会计准则制定模式的现实选择

美国一系列财务丑闻的爆发引发了人们对于会计准则制定模式的激烈讨论。本文在分析美国会计准则制定模式演变的基础上,探讨了中国会计准则制定模式的现实选择问题。     

美国会计准则制定模式变迁的理性思考

美国会计准则制定模式经历了原则基础模式阶段、规则基础模式阶段和目标导向阶段。我国在会计准则制定问题上也应该明确目标,重视财务会计概念体系的研究,恰当配置会计准则的制定权,做好会计准则制定中的利益协调。     

Understanding consumer's brand categorization across three countries: Application of fuzzy rule-based classification

In multi-brand situations, people categorize all known brands into subsets called consideration, hold, foggy and reject sets. This is the Brisoux–Laroche model. Traditional brand categorization models including this, assume that consumers can properly categorize each brand into these subsets. However, a brand with both perceived positive and negative attributes increases the difficulty for a consumer to decide about the placement into subsets. This study investigates consumers' brand categorization when a brand has both perceived positive and negative attributes. We propose that a brand may belong to more than one subset (decision fuzziness). Using fuzzy-rule-based classification, this is investigated across three cultures (Chinese, Japanese and Kazakhstan) and two product categories: Quick Service Restaurants (QSR) and beer. The findings confirm that decision fuzziness varies across cultures. Chinese consumers have less decision fuzziness for foreign brands than for local brands in the QSR market. In general, the opposite is found to be true for Japanese and Kazakh consumers.