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. © 2021, Emerald Publishing Limited.

Has COVID-19 influenced the perceived quality of service of hotels?

Purpose: The purpose of this paper is to analyze the perceived quality of service by guests in the reopening process during the COVID-19 pandemic. Design/methodology/approach: The authors analyzed 1,679 TripAdvisor reviews from 2019 and 2020 that were written for hotels in Gran Canaria, Spain. The authors compared the average rating for 2019 and 2020 and the authors performed a content analysis of the reviews. Findings: Guests perceived the quality of their stay to be worse during 2020, especially regarding food and beverage and staff behavior. The only service quality dimension that showed an improvement was related to open-air hotel installations. Research limitations/implications: The authors only analyzed reviews in one language. The authors were not able to determine if the lower ratings in 2020 were due to the way in which they perceived the quality of service or to the fact that the quality of service was objectively worse. Originality/value: This paper contributes to theory development in the field of hospitality management by providing new insights into how external events can influence hotel services and guests' perceptions. This research shows how a health crisis that is external to the tourism industry has caused an impact on hotel staff management and on how hotel staff behavior is perceived. However, it is also possible that regardless of anything managers do, the rating that a guest awards a hotel will be lower than it would have been before the pandemic. © 2022, Emerald Publishing Limited.

Has COVID-19 influenced the perceived quality of service of hotels?

Purpose: The purpose of this paper is to analyze the perceived quality of service by guests in the reopening process during the COVID-19 pandemic. Design/methodology/approach: The authors analyzed 1,679 TripAdvisor reviews from 2019 and 2020 that were written for hotels in Gran Canaria, Spain. The authors compared the average rating for 2019 and 2020 and the authors performed a content analysis of the reviews. Findings: Guests perceived the quality of their stay to be worse during 2020, especially regarding food and beverage and staff behavior. The only service quality dimension that showed an improvement was related to open-air hotel installations. Research limitations/implications: The authors only analyzed reviews in one language. The authors were not able to determine if the lower ratings in 2020 were due to the way in which they perceived the quality of service or to the fact that the quality of service was objectively worse. Originality/value: This paper contributes to theory development in the field of hospitality management by providing new insights into how external events can influence hotel services and guests' perceptions. This research shows how a health crisis that is external to the tourism industry has caused an impact on hotel staff management and on how hotel staff behavior is perceived. However, it is also possible that regardless of anything managers do, the rating that a guest awards a hotel will be lower than it would have been before the pandemic. © 2022, Emerald Publishing Limited.

Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings.

BACKGROUND: Popular web-based portals provide free and convenient access to user-generated hospital quality reviews. The Centers for Medicare & Medicaid Services (CMS) also publishes Hospital Compare Star Ratings (HCSR), a comprehensive expert rating of US hospital quality that aggregates multiple measures of quality. CMS revised the HCSR methods in 2021. It is important to analyze the degree to which web-based ratings reflect expert measures of hospital quality because easily accessible, crowdsourced hospital ratings influence consumers' hospital choices. OBJECTIVE: This study aims to assess the association between web-based, Google hospital quality ratings that reflect the opinions of the crowd and HCSR representing the wisdom of the experts, as well as the changes in these associations following the 2021 revision of the CMS rating system. METHODS: We extracted Google star ratings using the Application Programming Interface in June 2020. The HCSR data of April 2020 (before the revision of HCSR methodology) and April 2021 (after the revision of HCSR methodology) were obtained from the CMS Hospital Compare website. We also extracted scores for the individual components of hospital quality for each of the hospitals in our sample using the code provided by Hospital Compare. Fractional response models were used to estimate the association between Google star ratings and HCSR as well as individual components of quality (n=2619). RESULTS: The Google star ratings are statistically associated with HCSR (P<.001) after controlling for hospital-level effects; however, they are not associated with clinical components of HCSR that require medical expertise for evaluation such as safety of care (P=.30) or readmission (P=.52). The revised CMS rating system ameliorates previous partial inconsistencies in the association between Google star ratings and quality component scores of HCSR. CONCLUSIONS: Crowdsourced Google star hospital ratings are informative regarding expert CMS overall hospital quality ratings and individual quality components that are easier for patients to evaluate. Improvements in hospital quality metrics that require expertise to assess, such as safety of care and readmission, may not lead to improved Google star ratings. Hospitals can benefit from using crowdsourced ratings as timely and easily available indicators of their quality performance while recognizing their limitations and biases.

Determining banking service attributes from online reviews: text mining and sentiment analysis

Purpose>The current study employs text mining and sentiment analysis to identify core banking service attributes and customer sentiment in online user-generated reviews. Additionally, the study explains customer satisfaction based on the identified predictors.Design/methodology/approach>A total of 32,217 customer reviews were collected across 29 top banks on bankbazaar.com posted from 2014 to 2021. In total three conceptual models were developed and evaluated employing regression analysis.Findings>The study revealed that all variables were found to be statistically significant and affect customer satisfaction in their respective models except the interest rate.Research limitations/implications>The study is confined to the geographical representation of its subjects' i.e. Indian customers. A cross-cultural and socioeconomic background analysis of banking customers in different countries may help to better generalize the findings.Practical implications>The study makes essential theoretical and managerial contributions to the existing literature on services, particularly the banking sector.Originality/value>This paper is unique in nature that focuses on banking customer satisfaction from online reviews and ratings using text mining and sentiment analysis.