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Adaptation of the Q-methodology for the characterization of a complex concept through a set of products: From the collection of the data to their analysis
Food Quality and Preference ( IF 5.3 ) Pub Date : 2018-07-01 , DOI: 10.1016/j.foodqual.2017.06.010
Margot Brard , Sébastien Lê

Abstract An adaptation of the Q-methodology used in psychology to study human subjectivity is introduced as a methodology for characterizing a complex concept through a set of products. Firstly, the data collection step consists in choosing a set of products as exhaustive as possible. This set of products is then given to participants who are asked to sort the products into predefined categories: “products assessed as non-representative of the concept” and “products assessed as representative of the concept”. At the end of the experiment, a product is characterized by two types of information: (1) the products it has been associated with by the participants, and (2) the number of times it has been associated with the concept by the participants. While the first type of information is similar to those provided by free sorting task data, the second type of information is specific to these data. Secondly, the product-oriented data analysis step consists in analyzing data by Multiple Factor Analysis (MFA) in order to understand the variability between the products in accordance with the way the data have been collected. MFA presents the ability to provide a representation of the products that takes into account the two types of information mentioned previously. Third and finally, the data visualization step consists in enhancing the representation of the products through a categorical version of the maps provided by external preference mapping. This methodology is illustrated through an experiment based on the concept of innovation through a set of perfumes.

中文翻译:

通过一组产品对 Q 方法进行调整以表征复杂概念:从数据收集到分析

摘要 引入了对心理学中用于研究人类主体性的 Q 方法的改编,作为通过一组产品表征复杂概念的方法。首先,数据收集步骤包括选择一组尽可能详尽的产品。然后将这组产品提供给参与者,参与者被要求将产品分类为预定义的类别:“评估为不代表概念的产品”和“评估为代表概念的产品”。在实验结束时,产品的特征在于两种类型的信息:(1)参与者将其关联的产品,以及(2)参与者将其与概念关联的次数。虽然第一类信息类似于自由排序任务数据提供的信息,第二种信息是特定于这些数据的。其次,面向产品的数据分析步骤包括通过多因素分析 (MFA) 分析数据,以便根据收集数据的方式了解产品之间的可变性。MFA 提供了提供产品表示的能力,该表示考虑了前面提到的两种类型的信息。第三也是最后,数据可视化步骤包括通过外部偏好映射提供的地图的分类版本来增强产品的表示。这种方法是通过一个实验来说明的,该实验基于一组香水的创新概念。面向产品的数据分析步骤包括通过多因素分析 (MFA) 分析数据,以便根据收集数据的方式了解产品之间的可变性。MFA 提供了提供产品表示的能力,该表示考虑了前面提到的两种类型的信息。第三也是最后,数据可视化步骤包括通过外部偏好映射提供的地图的分类版本来增强产品的表示。这种方法是通过一个实验来说明的,该实验基于一组香水的创新概念。面向产品的数据分析步骤包括通过多因素分析 (MFA) 分析数据,以便根据收集数据的方式了解产品之间的可变性。MFA 提供了提供产品表示的能力,该表示考虑了前面提到的两种类型的信息。第三也是最后,数据可视化步骤包括通过外部偏好映射提供的地图的分类版本来增强产品的表示。这种方法是通过一个实验来说明的,该实验基于一组香水的创新概念。MFA 提供了提供产品表示的能力,该表示考虑了前面提到的两种类型的信息。第三也是最后,数据可视化步骤包括通过外部偏好映射提供的地图的分类版本来增强产品的表示。这种方法是通过一个实验来说明的,该实验基于一组香水的创新概念。MFA 提供了提供产品表示的能力,该表示考虑了前面提到的两种类型的信息。第三也是最后,数据可视化步骤包括通过外部偏好映射提供的地图的分类版本来增强产品的表示。这种方法是通过一个实验来说明的,该实验基于一组香水的创新概念。
更新日期:2018-07-01
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