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Model-based segmentation of BIB consumer liking data of high-fatigue products

Model-based segmentation of BIB consumer liking data of high-fatigue products
基于模型的高疲劳产品BIB消费者喜好数据细分
批准号:
385522-2009
负责人:
McNicholas, Paul
金额:
$5.87万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2010
资助国家:
加拿大
项目状态:
已结题
起止时间:
2010-01-01 至 2011-12-31

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中文摘要
翻译
在过去的50年里,面向消费者市场的新产品设计经历了重大转变。传统上,发明者会创造一种他们认为可能满足消费者需求的新产品。产品的开发往往是为了满足发明者自己的看法,而不一定是消费者的看法。自上而下的产品开发方法的社会后果是新产品引入的失败率很高。通过调查潜在客户,可以创建一个精确的目标,指导开发人员并降低故障率。然而,今天,产品的扩散和消费者选择的出现导致了市场细分的识别。消费者最初是根据人口统计数据进行划分的,但发达国家人们可支配收入的比例大幅增加,现在的选择是基于喜好,而不是拥有经济实力。因此,要打造成功的产品,了解你的目标市场是至关重要的。通常会执行产品类别评估,其中与消费者一起测试12到30个商业产品以创建偏好图。每个消费者都可以在一个完整的模块设计中测试每个产品。为理论上的普通消费者设计的产品通常定位在道路的中间,不会吸引强烈的消费者喜欢。聚类分析在这些大型消费者类别喜好研究中的应用现在已经很好地建立起来了,而且众所周知,有几类产品不适合现有的方法。这些产品往往是“高疲劳”产品。这些产品包括饮料酒精产品;口味浓烈的产品,如咖啡或巧克力;还有高度调味的食物,比如莎莎酱或咖喱。这个项目将发展各种方法,允许将聚类方法应用于各种困难的消费产品,包括高疲劳产品。由此产生的方法将为工业合作伙伴及其客户带来重大利益。更广泛地说,是对加拿大经济的影响。
英文摘要
The design of new products for consumer markets has undergone a major transformation over the last 50 years. Traditionally, inventors would create a new product that they thought might address a perceived need or want of consumers. The products tended to be developed to meet the inventors' own perception and not necessarily that of consumers. The social consequence of a top-down approach to product development has been a large failure rate in new product introduction. By surveying potential customers a refined target is created that guides developers and reduces the failure rate. Today, however, the proliferation of products and the emergence of consumer choice has resulted in the identification of segments within the market. Consumers were originally segmented on demographics but the proportion of disposable income has increased so much for people in the developed world that choice is now based upon liking rather than having the financial means. Therefore, to build successful products it is essential to understand your target market. Typically a product category assessment is performed, where 12 to 30 commercial products are tested with consumers to create a preference map. Every consumer gets to test every product in a complete block design. Products that have been designed for a theoretical average consumer are usually positioned in the middle of the road and do not attract strong consumer liking. The application of cluster analysis to these large consumer studies of category liking is now well established and it is know that there are several classes of products that do not lend themselves to existing approaches. These tend to be 'high-fatigue' products. These include beverage alcohol products; intensely flavored products, like coffee or chocolate; and highly seasoned products, like salsa or curry. This project will see the development of methodologies that will permit the application of clustering to a wide range of difficult consumer products, including high-fatigue products. The resulting methodologies will be of significant benefit to the industrial partner and their clients. and, more generally, to the Canadian economy.
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Computational Statistics
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  • 依托单位:
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  • 负责人:
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  • 依托单位:
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  • 批准号:
    CRC-2015-00200
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  • 资助金额:
    $14.57万
  • 财政年份:
    2021
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  • 依托单位:
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