摘要翻译:
目的:本文试图通过一个案例研究,对马来西亚选定的零售商店的基准进行共识排名,对营销组合对顾客满意度的影响采取警示立场。设计/方法/方法-ELECTRE I模型用于通过基于营销组合模型4P's的多准则基准决策方法来推导共识排名。采用描述性分析法对四种营销策略中的最佳实践进行了分析。结果--超越的方法构成了一个强大的基础,在此基础上建立了应用于营销战略发展的标杆管理行为理论的整个结构。研究的局限性/意义--本研究只关注消费者满意度如何转化为行为结果这一难题的有限部分。实际影响-研究为管理者提供了指导,如何产生一个潜在的营销活动的粗略轮廓,可以用来利用能力和转换弱点和威胁。独创性/价值--这篇文章有趣地描述了多准则决策和排序方法的有效使用,以帮助营销经理预测他们的营销趋势。
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英文标题:
《Deriving consensus rankings via multicriteria decision making
methodology》
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作者:
Amy Poh Ai Ling, Mohamad Nasir Saludin, Masao Mukaidono
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最新提交年份:
2012
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:General Finance 一般财务
分类描述:Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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英文摘要:
Purpose - This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach - The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics. Findings - Outranking methods in consequence constitute a strong base on which to found the entire structure of the behavioral theory of benchmarking applied to development of marketing strategy. Research limitations/implications - This study looks only at a limited part of the puzzle of how consumer satisfaction translates into behavioral outcomes. Practical implications - The study provides managers with guidance on how to generate a rough outline of potential marketing activities that can be used to take advantage of capabilities and convert weaknesses and threats. Originality/value - The paper interestingly portrays the effective usage of multicriteria decision-making and ranking method to help marketing managers predict their marketing trends.
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PDF链接:
https://arxiv.org/pdf/1201.1604