Purpose

In recent years, the updating speed of products has been significantly accelerated, which not only provides diversified styles for consumers to select from but also makes consumers face selection problems sometimes. In addition, a large number of online reviews for products emerge on many e-commerce websites and influence consumers’ purchasing decisions. The purpose of this study is to propose a method for product selection considering consumer’s expectations and online reviews to support consumers’ purchasing decisions.

Design/methodology/approach

The product attributes are divided into two categories, i.e. demand attributes and word-of-mouth (WOM) attributes. For the demand attributes, for which the consumers can give specific quantified expectations, the value function of prospect theory is used to determine the consumer’s perceived values to the alternative products according to consumers’ expectations for these attributes and products’ specifications. For the WOM attributes, for which the consumers cannot give specific quantified expectations, the sentiment analysis method is used to identify the sentiment strengths for these attributes in the online reviews, and then the consumer’s perceived values to the alternative products are determined. On this basis, the product selection methods for single consumers and group consumers are given respectively.

Findings

Finally, taking the data of JD.com (https://www.jd.com/) as an example, the practicability and rationality of the method proposed in this paper is validated.

Originality/value

First, a new product selection problem considering consumer’s expectations and online reviews is extracted. Second, the product attributes are considered more comprehensively and are classified into two main categories. Third, the bounded rationality of the consumers in the decision-making process is described more reasonably. Fourth, the sentiment dictionaries for each WOM attribute are constructed and the algorithm step of identifying the sentiment strengths is designed, which can help to identify the sentiment strengths in the online reviews more accurately. Fifth, the situation that a group plans to purchase the same products and the members have inconsistent expectations for the product attributes is considered.

中文翻译：

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考虑消费者期望和在线评论的产品选择方法

目的

近年来，产品更新换代速度明显加快，不仅为消费者提供了多样化的款式选择，有时也让消费者面临选择难题。此外，许多电子商务网站上出现了大量的产品在线评论，影响了消费者的购买决策。本研究的目的是提出一种考虑消费者期望和在线评论的产品选择方法，以支持消费者的购买决定。

设计/方法/方法

产品属性分为两类，即需求属性和口碑（WOM）属性。对于消费者可以给出具体量化期望的需求属性，根据消费者对这些属性的期望和产品规格，利用前景理论的价值函数来确定消费者对替代产品的感知价值。对于消费者无法给出具体量化预期的口碑属性，通过情感分析方法识别在线评论中这些属性的情感强度，进而确定消费者对替代产品的感知价值。在此基础上，分别给出了单一消费者和群体消费者的产品选择方法。

发现

最后，以京东（https://www.jd.com/）的数据为例，验证了本文提出的方法的实用性和合理性。

原创性/价值

首先，提取考虑消费者期望和在线评论的新产品选择问题。其次，产品属性考虑更全面，分为两大类。第三，更合理地描述了消费者在决策过程中的有限理性。第四，构建每个口碑属性的情感词典，设计情感强度识别算法步骤，有助于更准确地识别在线评论中的情感强度。第五，考虑一个群体计划购买相同的产品，而成员对产品属性的期望不一致的情况。