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首页> 外文期刊>Sistemas Gest?o >LOGISTIC COLABORATION BETWEEN CUSTOMER AND SUPPLIER: AN APPLICATION OF VISUAL ANALYSIS OF DATA
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LOGISTIC COLABORATION BETWEEN CUSTOMER AND SUPPLIER: AN APPLICATION OF VISUAL ANALYSIS OF DATA

机译：客户与供应商之间的物流协作：数据可视化分析的应用

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O objetivo deste trabalho é usar métodos computacionais de análise visual de dados para obter uma estrutura de análise (classifica??o) dos índices referentes à colabora??o entre fornecedor e cliente. Deseja-se verificar as barreiras colaborativas e avaliar o comportamento de grupos de empresas segundo esses índices. Para o desenvolvimento do trabalho foi usado um conjunto de dados coletados em indústrias de bens de consumo que avaliaram a colabora??o com o seu parceiro varejista. Os resultados demonstraram uma nova proposta de classifica??o para os índices colaborativos; quais s?o as empresas mais colaborativas segundo a localiza??o, subsetores e número de funcionários; e os fatores que se apresentam como barreiras colaborativas mais evidentes, tais como: mudan?a de cultura das empresas e o baixo retorno de investimento.↓The goal of this work is to use computational methods for visual data analysis in order to obtain a structure for analysis (classification) of the indices related to the concepts of collaboration between supplier and customer. It is desired to know the collaborative barriers and to assess the behavior of groups of companies according to these indices. For the development of this work, a dataset of consumer-goods industries was used for evaluating the collaboration with their client partner. The results showed a new classification propose for the collaborative index; what are the most collaborative enterprises according to location, number of employees, and sub-sectors; and the factors that more evidently represent collaborative barriers, such as: change of company culture, and the low-profit investment.Key words: Collaboration, visual data analysis, collaboration barriers.
机译：这项工作的目的是使用视觉数据分析的计算方法来获得参考供应商和客户之间合作的指标的分析（分类）结构。我们希望检查这些合作障碍，并根据这些指标评估公司集团的行为。为了开展工作，在消费品行业使用了一组数据，这些数据评估了与零售合作伙伴的合作。结果证明了协作索引的新分类建议。根据地点，子行业和员工人数，这是最合作的公司;以及表现为最明显的合作障碍的因素，例如：改变公司的文化和较低的投资回报率↓这项工作的目的是使用计算方法进行可视化数据分析以获得结构用于分析（分类）与供应商和客户之间的协作概念有关的指标。希望了解协作障碍并根据这些指标评估公司集团的行为。为了开展这项工作，使用了消费品行业数据集来评估与客户伙伴的合作。结果表明，对协作索引进行了新的分类。根据地点，员工人数和子行业，最协作的企业是什么？以及更明显地代表协作障碍的因素，例如：公司文化的变化和低利润投资。关键词：协作，可视数据分析，协作障碍。

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