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Hedonic Analysis for Consumer Electronics Using Online Product Reviews

机译：使用在线产品评论的消费电子产品综合分析

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摘要

In recent years, online product reviews have been considered as a valuable source of information to assist people in making buying decisions. Most of prior studies on the effect of online product reviews have utilized the factors which manufactures cannot control by themselves, such as the number of reviews, the average review rating, as independent variables in their regression models. However, those factors cannot provide direct implications for manufacturers. For example, managers cannot easily increase the number of reviews to rise the product price or demand. In contrast, they have to trace the causes of why the amount of reviews grows. Thus, in order to offer more straightforward suggestions, we adopt the concept of hedonic analysis which decomposes the demand of a commodity into several product features to identify which of them impact its demand mostly. In this paper, we take smartphone market as our research target and propose a framework to demonstrate these assumptions. Our framework utilizes opinion mining techniques to extract sentiment words and features from online product reviews, and combines those extracted items with basic characteristics obtained from a specification of each product to form hedonic regressions. Finally, we provide managerial implications for firms and help them make proper strategies based on the experiment results.
机译：近年来，网上商品的评论已被视为一个有价值的信息来源，以帮助人们做出购买决策。大多数对网上商品评论的影响之前的研究已经利用该公司生产不能由自己控制，如评论的数量，平均审核评价，在他们的回归模型自变量的因素。然而，这些因素不能为制造商提供了直接的影响。例如，管理人员不能轻易提高评语数量上升了产品价格或需求。相反，他们必须追查为什么评语数量增长的原因。因此，为了提供更直接的建议，我们采取享乐分析其分解的商品的需求分为几个产品特征来识别他们的主要影响其需求的概念。在本文中，我们以智能手机市场为研究对象，并提出一个框架，来展示这些假设。我们的架构利用意见挖掘技术提取的情绪言论和在线产品评论功能，并结合从每个产品的规格得到形成内涵回归基本特征的提取的项目。最后，我们提供管理问题的企业，帮助他们做出基于实验结果正确的策略。

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