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People generally believe that business with negative word-of-mouth, such as negative customer reviews can hardly have good sales. But a number of intriguing examples seem to contradict such beliefs. Academic has so far begun to explore the possible positive effect of negative customer reviews, but without unfolding its underlying mechanism. This paper proposes a mechanism through which the variance of customer reviews moderates the effect of negative reviews on sales.

This study takes a multi-method approach in explaining the phenomenon, including an empirical analysis using secondary data from a movie review website and a movie box office website and a subsequent experimental study in a controlled experiment.

The findings of the study show that the effect of negative customer reviews on product sales is positive when the variance of customer reviews is large. Moreover, customers’ motivation to learn fully mediates the moderating effect of review variance on valence.

The findings provide vital managerial implications and suggest that managers should realize the important role of the review distribution.

This study mainly contributes to research on the negativity bias by identifying an important unexplored moderator and mediator and thus explains why negative customer review increases movie sales.

This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.

Electronic word-of-mouth (eWOM) is very important for consumer decision making; previous international product diffusion studies have investigated eWOM and cultural factors that influence consumers’ acceptance of new products, but they have not adequately compared the differences in these factors between the USA and China. Therefore, the purpose of this paper is to compare the impact of eWOM on consumer choices in China and the USA. The authors addressed the following questions: What are the cross-cultural differences in consumers’ eWOM behavior between the USA and China: Which genres of Hollywood movies have better cross-culture predictability in terms of box office performance; and What factors affect the success of Hollywood movies in entering the Chinese market?

Real eWOM data were collected from two online movie review websites, IMDb.com (the USA) and Douban.com (China), from January 2010 to December 2015. In addition, box office revenue information was collected from BoxOfficeMojo.com. The authors used an independent sample t-test to check whether the differences in consumers’ eWOM behavior between China and the USA and different types of movie lead to cultural discount differences. Furthermore, a log-linear regression model is used to examine which factors influence the commercial success of new movies.

There are specific similarities and differences between the American and Chinese movie markets. First, the results show that American consumers are more engaged in online review systems and tend to submit extreme reviews, but Chinese consumers tend to submit moderate reviews on movies, and the eWOM variance there is smaller than in the USA. Second, genres are useful variables as indicators of movie content; the genres of comedy and drama are not popular in the Chinese market. Finally, eWOM variance has a positive impact on box office in China, but eWOM variance has no impact on the US box office. In addition, the interactive effect of the average rating and eWOM variance on sales is positively significant in China. Importantly, the one-star reviews have a negative impact on the Chinese box office, but it has no impact on US box office.

Understanding how cultural factors influence consumer eWOM communication will help managers to better apply this new marketing communication tool to create more aggressive and targeted promotional plans. Marketers may use eWOM behavior to better respond to and target consumers to overcome barriers to the selection of their products by consumers. Therefore, more effective management of eWOM can improve the acceptance of and preference for products in different cultural consumer groups.

This study expands the existing body of knowledge on eWOM and international marketing literature. Clearly, culture is an important determinant of eWOM’s impact on sales. In addition, it provides strategic direction and practical implications for eWOM communication management in cross-cultural settings.

Whereas inventory theory traditionally assumes the periodic review inventory model (R, T), with an order‐up‐to level R, has a random demand and lead time coupled with a deterministic review interval T, firms often deviate from a strict adherence to a fixed review interval when they attempt to capture transportation scale efficiencies. Employing this policy introduces additional supply chain variability. This paper aims to provide an expression for the standard deviation of demand during the protection period, important in setting safety stock, as well as an expression for the amount of order variance amplification induced by a stochastic review interval.

Analytical modeling is used to develop the expression for the standard deviation of demand during the protection period as well as the calculation for the amount of order variance amplification induced by a stochastic review interval.

In terms of the variance of demand over the protection period, a stochastic review interval has a similar effect to that of a stochastic lead time, but its impact on demand variance amplification within the supply chain differs fundamentally. Specifically, a stochastic review interval creates an order batching bullwhip effect not identified in existing literature.

This study offers an expression for the standard deviation of demand during the protection period when stochastic review intervals are employed. The expression can be used to more effectively set safety stock. The paper also offers an expression for the order variance amplification induced by a stochastic review interval.

The study offers suggestions for retailers and suppliers regarding when the use of a stochastic review interval is effective in terms of cost efficiencies.

While the existence and effect of lead time variability is well‐established in the literature, traditional approaches the periodic review inventory model ignore the stochastic nature of review interval. This paper highlights the use of stochastic review intervals as a contributing factor to the bullwhip effect.

This study aims to explore how online reviews and users’ social network centrality interact to influence idea popularity in open innovation communities (OICs).

This study used Python to obtain data from the LEGO Innovation Community. In total, 285,849 reviews across 4,475 user designs between March 2019 and March 2021 were extracted to test this study’s hypotheses.

The ordinary least square regression analysis results show that review volume, review valence, review variance and review length all positively influence idea popularity. In addition, users’ in-degree centrality positively interacts with review valence, review variance and review length to influence idea popularity, while their out-degree centrality negatively interacts with such effects.

Drawing on the interactive marketing perspective, this study employs a large sample from the LEGO community and examines user design and idea popularity from a community member’s point of view. Moreover, this study is the first to confirm the role of online reviews and user network centrality in influencing idea popularity in OICs from a social network perspective. Furthermore, by integrating social network analysis and persuasion theories, this study confirms the interaction effects of review characteristics and users’ social network centrality on idea popularity.

This study’s results highlight that users should actively interact and share with reviewers their professional product design knowledge and/or the journey of their design to improve the volume of reviews on their user designs. Moreover, users could also draw more attention from other users by actively responding to heterogeneous reviews. In addition, users should be cautious with the number of people they follow and ensure that they improve their in-degree rather than out-degree centrality in their social networks.

This study integrates social network analysis and persuasion theories to explore the effects of online reviews and users’ centrality on idea popularity in OICs, a vital research issue that has been overlooked.

The purpose of this paper is to present a review of variance decomposition studies of firm performance and the theoretical foundations that served as the antecedents and promptings for this stream of research. Known collectively as “variance decomposition literature,” these studies use variance decomposition techniques to partition firm performance into various classes of effects in a bid to unveil the relative importance of factors responsible for firm performance variance.

A review of papers published in SCOPUS and institute for scientific information indexed journals was conducted.

The study found that firm, industry, corporate, business group and country effects are the major effects included in most extant studies. However, of all effects, firm effects remain the dominant and most important impact on firm performance. The effects that affect firm performance are also interdependent.

Consequently, the decisions of managers in firms are still the most important element in helping the firm to navigate industry and contextual factors, especially during periods of recession.

From the review, research gaps were identified and suggestions for future research provided. There is still much to learn from variance decomposition literature in an age of new business models, unprecedented start-up firms and from developing and emerging market countries.

Online reviews are often likely to be socially influenced by prior reviews. This study aims to examine key review and reviewer characteristics which may influence the social influence process.

Restaurant review data from Yelp.com are analyzed using an ordered logit model and text mining approach.

This study reveals that prior average review rating exerts a positive influence on subsequent review ratings for the same restaurant, but the effect is attenuated by the variance in existing review ratings. Moreover, social influence is stronger for consumers who had a moderate dining experience or invested less cognitive effort in writing online reviews. Compared to reviewers classified by Yelp as “elite,” non-elite reviewers appear more susceptible to the social influence of prior average review rating.

This study provides guidelines for mitigating the social influence of prior reviews and improving the accuracy of online product/service ratings, which will eventually enhance business and the reputation of online review platforms.

The findings from this study contribute to the electronic word-of-mouth (eWOM) literature and social influence literature in terms of the bidirectional nature of social influence on eWOM.

Online consumer reviews have become increasingly important for consumer decision-making. One of the most prominent examples is the hotel industry where consumer reviews on websites, such as Bookings.com, TripAdvisor and Venere.com, play a critical role in consumers’ choice of a hotel. There have been a number of recent studies analyzing various aspects of online reviews. The purpose of this paper is to investigate their effects in terms of hotel occupancy rates.

This paper measures through regression analysis the impact of three dimensions of consumer reviews (i.e. review score, review variance and review volume) on the occupancy rates of 346 hotels located in Rome, isolating a number of other factors that might also affect demand.

Review score is the dimension with the highest impact. The results suggest that after controlling for other variables, a one-point increase in the review score is associated to an increase in the occupancy rate by 7.5 percentage points. Regardless the review score, the number of reviews has a positive effect, but with decreasing returns, implying that the higher the number of reviews, the lower the beneficial effect in terms of occupancy rates is.

The findings quantify the strong association of online reviews to occupancy rates suggesting the use of appropriate reputational management systems to increase hotel occupancy and therefore performance.

A major contribution of this paper is its comprehensiveness in analyzing the relation between online consumer reviews and occupancy across a heterogeneous sample of hotels.

The purpose of this paper is to provide a broad overview of the growing literature on the relationship between online consumer reviews and sales, with implications on firm actions such as pricing.

This paper takes the form of a literature review.

Interesting results from the literature are organized into six categories: sales and related dependent variables, review dimensions, reviewer characteristics, reader characteristics, product category, and product.

The broad overview of the literature provides insights into potential areas for further research. Several suggestions towards this are provided in the paper. The focus is substantive rather than methodological.

More detailed understanding of the relevant concepts and phenomena will hopefully lead to improved decision making.

While the literature on online reviews is relatively recent, it has expanded quickly during the past five years and this paper fills a need for a broad‐based overview of the field.

This study examines whether a higher interest alignment between online travel agencies (OTAs; hosting platform) and hotels (business owners) will intensify review manipulation activities.

With a panel data set collected from a Chinese online travel agency and a travel search engine, the authors develop a matching-based difference-indifference approach to examine the presence of partnership-intensified review manipulation.

The authors find that the ratings of agency's partner hotels (with a higher interest alignment) are abnormally higher than those of matched non-partner hotels (with a lower interest alignment), after they are benchmarked with their ratings on the search engine (without a partnership business model). Further, the analysis results indicate that this partnership-intensified manipulation deteriorates the hotel's sales performance because of damaged customer trust and satisfaction.

Previous studies implicitly assume that review manipulator is independent from the hosting platform. This is the first study examining the role of the hosting platform in review manipulations.