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Insights from interval-valued ratings of consumer products—a DECSYS appraisal

机译:消费品区间定值评估的见解-DECSYS评估

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The capture and analysis of interval-valued data has seen increased interest over recent years. This offers a direct means to capture and reason about uncertainty in data, whether obtained from sensors or from people. Open-source software (DECSYS [1]) was recently released to facilitate the efficient capture of interval-valued survey responses. Potential real-world applications are broad ranging, and this paper documents an initial test-case of the software and its underpinning methodology, in a marketing-centric application. It provides an illustration of the insights offered by interval-valued responses, in this case relating to consumer preferences. We apply two approaches to describe and draw insights from the data: inferential statistics and descriptive visualisation methods. Statistical results indicate that overall purchase intention was well-described by four factors: value, healthiness, taste and brand. The capture of uncertainty information, afforded by intervals, also permitted identification of six factors that contribute to purchase intention uncertainty— relating to taste, ethics and visual appearance. Visualisations of interval-valued responses, using the IAA [2]–[5], also highlighted factors with high degrees of uncertainty—in particular, product ethics. This information could prove valuable for retailers in determining how to focus future marketing campaigns. It may prove equally valuable for market regulators, by informing where to improve product labelling information. More generally, the case study provides an overview of capturing and analysing intervals, highlighting some of the challenges, but also the unique potential to gain additional insights not available using conventional, ‘crisp’, approaches.
机译:近年来,间隔数据的捕获和分析已经增加了兴趣。这提供了一种直接手段,用于捕获和有关数据中的不确定性的原因,无论是从传感器或人员获得的。最近发布了开源软件(Docsys [1]),以便于有效地捕获间隔值调查响应。潜在的现实世界应用是广泛的测距,本文在以营销为中心的应用中撰写了软件及其支撑方法的初步测试案例。它提供了间隔响应所提供的洞察力的图示,在这种情况下与消费者偏好有关。我们应用两种方法来描述和绘制数据的见解:推理统计和描述性可视化方法。统计结果表明,整体采购意图是四个因素良好的描述:价值,健康,品味和品牌。捕获不确定性信息,提供间隔,也允许识别有助于购买意图与味道,道德和视觉外观有关的六个因素。使用IAA [2] - [5]的间隔值响应的可视化,还突出了具有高度不确定性程度的因素 - 特别是产品伦理。这些信息可以证明零售商在确定如何关注未来的营销活动时有价值。通过通知在何处提高产品标签信息,它可能对市场监管机构表示同样有价值。更一般地说,案例研究提供了捕获和分析间隔的概述,突出了一些挑战,也是利用传统的“清脆”方法获得额外见解的独特潜力。

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