The impact of COVID-19 on online product reviews

Purpose The ongoing COVID-19 pandemic has led to drastic changes in the lives of customers. Social isolation, financial difficulties, fear of being infected and many other factors have caused the psychological well-being of customers to deteriorate. By taking up the role of online reviews in the regulation of consumers’ moods, this study aims to examine the changes that have occurred in online product ratings, as well as the negative tone and word counts of product reviews during the COVID-19 pandemic. Design/methodology/approach This study examines the online reviews of 321 products in the pre-COVID, immediate COVID and extended COVID periods. This paper compares the changes that have taken place in product evaluations via various analysis of variance analyses. The authors also test the effect of COVID-related deaths on product evaluations via regression analyses. Findings The results indicate that online product ratings decreased sharply just after the outbreak of COVID-19. The study also found that the tone of reviews was found to be more negative and the length of reviews appeared to be longer in comparison to the pre-COVID-19 period. The results also revealed that the product type (experience vs search) moderated the effect of the pandemic in online reviews and the impact of COVID-19 on online product reviews diminished in the later stages of the ongoing pandemic. Practical implications Managers should be aware of the detrimental impact of pandemics on online product reviews and be more responsive to customer problems during the early stages of pandemics. Originality/value To the best of the authors’ knowledge, this is the first study that analyzes the effects of a pandemic on online product ratings and review content. As such, this study offers a timely contribution to the marketing literature.

THE IMPACT OF ONLINE PRODUCT REVIEWS IN VIRTUAL COMMUNITY TOWARDS PURCHASE DECISIONS IN INDONESIAN DENIM INDUSTRY

In this study, the researcher uses a combination of the theory of planned behavior and the model of goal-directed behavior to map what effects online product reviews can have on consumer purchase decisions. The researcher hypothesizes that the two adapted theories contain factors that can positively influence consumer purchase decisions. The researcher uses PLS-SEM and open coding to analyze quantitative and qualitative data. The results showed that ten of the eighteen hypotheses tested were proven to be accepted. Consumers in the denim industry tend to perceive online product reviews as a key aspect of their decision-making process. The results of qualitative data analysis also showed similar results, all respondents indicated the importance of the influence of an online product review on their purchasing decisions. The researcher also discusses the implications of these results for both research and practice.

A CROSS-PLATFORM MARKET STRUCTURE ANALYSIS METHOD USING ONLINE PRODUCT REVIEWS

Studies have shown that online product reviews can indicate the position of a competitive brand. Even though reviews on different platforms may express different opinions, most studies are based on only one platform. This may lead to an inaccurate analysis of market structure. To solve this problem, we develop a novel market structure analysis based on multi-attribute group decision-making which can integrate reviews from different platforms. Multiple platforms more comprehensively reflect the market than single platforms do. To verify the effectiveness of the proposed method, we conduct a case study of mobile phone reviews across three top e-commerce platforms in China. In addition, we propose a process to generate priorities for product-attribute improvements using a cross-platform market structure analysis method. Our experiments demonstrate the effectiveness of the proposed method.

Can Online Customer Reviews Help Design More Sustainable Products? A Preliminary Study on Amazon Climate Pledge Friendly Products

Online product reviews are a valuable resource for product developers to improve the design of their products. Yet, the potential value of customer feedback to improve the sustainability performance of products is still to be exploited. The present paper investigates and analyzes Amazon product reviews to bring new light on the following question: “What sustainable design insights can be identified or interpreted from online product reviews?”. To do so, the top 100 reviews, evenly distributed by star ratings, for three product categories (laptop, printer, cable) are collected, manually annotated, analyzed and interpreted. For each product category, the reviews of two similar products (one with environmental certification and one standard version) are compared and combined to come up with sustainable design solutions. In all, for the six products considered, between 12% and 20% of the reviews mentioned directly or indirectly aspects or attributes that could be exploited to improve the design of these products from a sustainability perspective. Concrete examples of sustainable design leads that could be elicited from product reviews are given and discussed. As such, this contribution provides a baseline for future work willing to automate this process to gain further insights from online product reviews. Notably, the deployment of machine learning tools and the use of natural language processing techniques to do so are discussed as promising lines for future research.

User experience evaluation method based on online product reviews

Evaluating the quality of the user experience (UX) of existing products is important for new product development. Conventional UX evaluation methods, such as questionnaire, have the disadvantages of the great subjective influence of investigators and limited number of participants. Meanwhile, online product reviews on e-commerce platforms express user evaluations of product UX. Because the reviews objectively reflect the user opinions and contain a large amount of data, they have potential as an information source for UX evaluation. In this context, this study explores how to evaluate product UX through using online product reviews. A pilot study is conducted to define the key elements of a review. Then, a systematic method of product UX evaluation based on reviews is proposed. The method includes three parts: extraction of key elements, integration of key elements, and quantitative evaluation based on rough number. The effectiveness of the proposed method is demonstrated by a case study using reviews of a wireless vacuum cleaner. Based on the proposed method, designers can objectively evaluate the UX quality of existing products and obtain detailed suggestions for product improvement.