No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry
Abstract
We analyze how online reviews are used to evaluate the effectiveness of product differentiation strategies based on the theories of hyperdifferentiation and resonance marketing. Hyperdifferentiation says that firms can now produce almost anything that appeals to consumers and they can manage the complexity of the increasingly diverse product portfolios that result. Resonance marketing says that informed consumers will purchase products that they actually truly want. When consumers become more informed, firms that provide highly differentiated products should experience higher growth rates than firms with less differentiated offerings. We construct measures of product positioning based on online ratings and find supportive evidence using sales data from the craft beer industry. In particular, we find that the variance of ratings and the strength of the most positive quartile of reviews play a significant role in determining which new products grow fastest in the market-place. This supports our expectations for resonance marketing.
... The latter is mainly measured by the average rating of reviews (Duan, Gu, and Whinston 2008) and refers to the expected product quality or reputation (Liu 2006). Research on eWOM variance has been limited compared to other characteristics (Babić Rosario et al. 2016), with the effect of eWOM variance on marketing performance generally reported as a comparison between positive and negative eWOM (Clemons, Gao, and Hitt 2006;Wang, Liu, and Fang 2015). ...
... Moreover, in the case of eWOM variance, there are not enough studies on the lm industry. Clemons, Gao, and Hitt (2006) argue that the higher the degree of differentiation, the more favorable it is to meet the needs of the target consumers and therefore the more positive the sales will be. On the contrary, Wang, Liu, and Fang (2015) argue that variance in online reviews negatively impacts lm sales by negatively affecting consumers' nal choices by signaling an increased risk of mismatch to consumers. ...
... Second, as competition increases, consumers are more likely to consider the PV of variance because the relative heterogeneity of the alternatives that consumers can choose from decreases as the number of competing products increases (e.g., Liu, Steenkamp, and Zhang 2018). If the difference in quality between the lms under consideration is wide, quality signals such as eWOM volume and valence play an important role in purchasing decisions; however, if it is higher than a certain level, it is highly likely that this importance will decrease (e.g., Clemons, Gao, and Hitt 2006;Mitra, Anusree, and Lynch 1995). As the importance of product quality signals decreases, it is more likely that speci c tastes and uniqueness (i.e., variance) will act as important criteria. ...
This paper aims to empirically analyze how competitive and cultural factors moderate the relationship betweenelectronic word-of-mouth (eWOM) characteristics and sales in the US and Korean �lm industries. A conceptual modelwas developed based on the cue utilization theory (CUT) to analyze the role of cultural and competitive factors thatmoderate the relationship between three characteristics of eWOM (volume, valence, and variance) and movie sales.Data of 45 days of 163 �lms released in Korea and the US were collected and a total of 7,335 samples were analyzed bypanel regression. As results, competitive factors enhanced the in uence of the eWOM of a focal �lm and this moderatingeffect depended on the eWOM characteristics. It also revealed that the effect of eWOM had a greater effect on moviesales in Korea than in the US.
... Review variance reflects differences in both taste and perceived quality (e.g. Clemons et al., 2006;Wang et al., 2015). Processing of review variance information is crucial because online reviews help mitigate product fit uncertainty among consumers (Hong and Pavlou, 2014). ...
... Consequently, the dual effects (positive and negative) of review variance depend on the choice of the information processing strategy, although most studies suggest a one-way effect (positive or negative). For example, Clemons et al. (2006) contended that review variance and sales growth for craft beer brands were positively related and hypothesized that a high review variance indicates successful hyper-differentiation. Conversely, Zhu and Zhang (2010) found that the review variance of less popular online games adversely affected sales. ...
... Zhang, 2006;Chiu et al., 2019), positive (e.g. Clemons et al., 2006;Wu et al., 2021), or negative (e.g. Zimmermann et al., 2018). ...
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
... However, there has been no consensus about the impact. Clemons et al. (2006) found a positive correlation between the rating dispersion and craft beer sales to provide support for a hyper-differentiation marketing strategy in the craft beer industry. In contrast, Zhu and Zhang (2010) showed that Huang et al.: Do Noisy Customer Reviews Discourage Platform Sellers? the rating variation for less popular online games has a negative impact on sales. ...
... In fact, Hong et al. (2014) found that review dispersion reflects the differences in customer taste for experience-heavy products. Similarly, Clemons et al. (2006) explained that a large rating dispersion indicates highly polarized customer taste. In line with the literature, we will interpret review dispersion as heterogeneity in customer taste. ...
... On the other hand, a higher review dispersion of an installer may also encourage the installer to decrease its activity level in the online marketplace. A higher review dispersion may imply a higher differentiation of customer taste in the market (Clemons et al. 2006). In such a market, making more proposals may impose reputational risks to the installer, potentially because of negative customers or additional polarized reviews. ...
Problem definition: Customer reviews are essential to online marketplaces. However, reviews typically vary; ratings of a product or service are rarely the same. In many service marketplaces, including the ones for solar panel installations, supply-side participants are active. That is, a seller must make a proposal to serve each customer. In such marketplaces, it is not clear how (or if) the dispersion in customer reviews affects the seller activity level and number of matches in the marketplace. Our paper examines this by considering both ratings and text reviews. To our knowledge, this is the first paper that empirically studies how the review dispersion affects a seller’s activity level and the number of matches in an online marketplace with active sellers. Distinct from literature, we examine the relationship between the review dispersion and supply-side activities in an online service marketplace. Methodology/results: We collaborated with one of the largest online solar marketplaces in the United States that connects potential solar panel adopters with installers. We obtained a unique data set from the marketplace for 2013 − 2018. We complement this with public data sets. Our analysis uses traditional econometrics methods, a clustering method, and the deep-learning-based natural-language-processing model BERT developed by Google AI. We find that the dispersion in customer reviews has a significant and inverted U-shaped relationship with an installer’s marketplace activity level. Intuitively, a marketplace operator would favor having more sellers with perfect ratings. In contrast, we identify a significant and inverted U-shaped relationship between the market-level review dispersion and transactions. Managerial implications: Our paper provides key insights to marketplace operators and sellers. We find that in contrast to general belief, an operator can improve its market transactions by keeping/promoting sellers with low ratings or avoiding (negative) review filtering. Furthermore, sellers’ implementation of “rating gating” to avoid negative reviews may backfire for them by reducing their matches.
Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2021.0104 .
... In comparison, a limited number of recent reports have used indirect data collected from the internet and have made inferences from actual product output findings. Clemons et al. (2006) showed that the variation in ratings and the frequency of the most favorable quartile of feedback had a significant impact on the production of craft beers. In the sense of hospitality, Ye et al. (2009) have shown that positive reviews will greatly increase the number of hotel reservations. ...
... In addition, a limited number of recent reports used indirect data collected from the internet and drew inferences from the observations of the actual results of the drug. Clemons et al. (2006) showed that the variation in ratings and the frequency of the most favorable quartile of feedback had a significant impact on the production of craft beers. In the sense of hospitality, Ye et al. (2009) have shown that positive reviews will greatly increase the number of hotel reservations. ...
Word of mouth (WOM) is a contact between customers about a specific product, service or business in which the origins are perceived to be independent of market control. Research shows that word of mouth plays an increasingly important role in shaping customer perceptions and purchasing behaviour. Electronic word of mouth (e-WOM) has been an important topic for business and marketing researchers in that online social communications. Recent studies have looked at the effect of Internet-based e-WOM on company performance, the global user culture, and how the WOM engagement mechanism affects customer preferences and actions in the online environment. This research was aimed to identify the theoretical arguments and hypotheses about the interrelationships between e-WOM (Electronic Word of Mouth) and consumer preference based on tourism mobile apps towards travel intentions. Researchers come up with a objective of to find out dimensions of consumer preference regarding usage of tourism mobile apps, & to determine the effect of e-WOM on consumer preference while using tourism apps. To attain these objectives, researcher used two diverse tools, i.e., SPSS & Structural equation model to test the anticipated hypothesized model.
... All variables are standardized using the standard deviations from the car model's mean. This controls for the baseline performance of the various car models due to brand effects (Geva et al., 2017), allows comparison between the models (Tang et al., 2014), and helps ease interpretation (Clemons et al., 2006). Table 4 gives the summary statistics for the variables used in the model. ...
... To examine the association between the six review variables, namely trust, rating deviation, and the four topics, with online search, while controlling for the previous period search, review volume, review rating, consumer sentiment, and fuel prices, Eq. (1) is estimated using ordinary least squares regression (Clemons et al., 2006). ...
While the research on online consumer reviews is immense, it has largely focused on products which can also be purchased online. However, the high level of digital engagement of individuals today along with a reported fall in physical store visits indicate that digital content can also affect products available only for purchase offline. This research examines the effects of trust, uncertainty, and topics extracted from online consumer reviews on two outcomes in the India car market, namely the search for online information and sales. The study finds that while uncertainty does not affect sales, and has a negative effect on online information search, trust is positively associated with both. The topics extracted using Latent Dirichlet Allocation from the review corpus fall under the category of experiential or functional. The different topics have direct and mediating impacts on search and sales.
... Given their nature, i.e., they are produced by consumers after sampling a free product, we seek to evaluate whether the use of such sponsored reviews affects the production of voluntary organic reviews. This possible effect is important to account for, given that any negative effect on organic review production could lead to reduced sales (Clemons et al., 2006;Duan et al., 2008;Lau et al., 2018). However, few extant studies have examined the net sales effect of sponsored product sampling reviews. ...
... Despite the rich literature on online product reviews (e.g., Ceran et al., 2016;Clemons et al., 2006;Dellarocas et al., 2007;Duan et al., 2008;Forman et al., 2008;Gopinath et al., 2014;Lu et al., 2013;Sun & Xu, 2018;Yao et al., 2017;Zhu & Zhang, 2010), there is a need to recognize an increasingly popular variant of such reviews-namely sponsored product sampling reviews, which are motivated by firms' desire to leverage product reviews in a more proactive but ethical way (Kim et al., 2019;Petrescu et al., 2018). However, in contrast to previous research, which has been unable to provide conclusive findings about the effect of sponsored reviews, our research contributes to this emerging field of research in three ways. ...
Given the significant influence of online product reviews on consumer purchases, firms are trying to be more proactive in leveraging the influence of reviews. One way of doing this is to offer free product samples to consumers to incentivize product reviews, displaying them along with a disclosure in the existing pool of organic reviews in the hopes of stimulating sales. However, it is not clear whether such product sampling reviews are indeed beneficial to sales, considering that they may have a nontrivial influence on the generation of organic reviews. Based on data from a leading e-commerce platform in China, we found that sponsored product sampling reviews promoted product sales but also reduced the volume of organic reviews for the targeted product. However, the net effect on sales remained positive, suggesting that e-tailers may wish to utilize sponsored product sampling reviews. We also conducted a scenario-based experiment to reveal how the nature of product sampling reviews affects consumers’ brand quality and fairness perceptions. Based on our findings we offer future research directions to improve the understanding of how to better harness the power of sponsored reviews.
... In tourism, rating scores are used to evaluate hotel performance. Clemons, Gao, and Hitt (2006) found that the average of the top ratings has a positive and significant relationship with revenue growth. There are also non-numerical variants of the grading style, such as heart, round, thumbs up, and thumbs down, among others. ...
... It broadly defined the default factors to predict the purchase intention of online consumers in hotel businesses based on three e-WOM components (rating valance, density, website familarity). In addition, the study provides evidence for many literature contributing studies investigating the effects of eWOM on purchase intention (eg, Bataineh, 2015;Dellarocas et al., 2007;Chevalier & Maylin, 2006;Clemons et al. , 2006;Hu, Liu & Zhang, 2008;Wen, 2009;). Moreover, this study also identified a direct relationship between perceived eWOM popularity and usefulness on perceived eWOM impact. ...
... Websites' reliance on average ratings is understandable: averages are transparent, easy to calculate, easy to communicate, and easy to understand. Organizational and marketing researchers often calculate aggregate statistics, such as mean ratings (e.g., Clemons, Gao, & Hitt, 2006;Verhaal et al., 2015;Ye, Law, & Gu, 2009), medians of ratings (e.g., Lee et al., 2021), or the variance of ratings (e.g., Clemons et al., 2006;Ye et al., 2009), and use these as both independent and dependent variables in their statistical analyses. (Many notable exceptions to this practice exist; we will discuss these later.) ...
... Websites' reliance on average ratings is understandable: averages are transparent, easy to calculate, easy to communicate, and easy to understand. Organizational and marketing researchers often calculate aggregate statistics, such as mean ratings (e.g., Clemons, Gao, & Hitt, 2006;Verhaal et al., 2015;Ye, Law, & Gu, 2009), medians of ratings (e.g., Lee et al., 2021), or the variance of ratings (e.g., Clemons et al., 2006;Ye et al., 2009), and use these as both independent and dependent variables in their statistical analyses. (Many notable exceptions to this practice exist; we will discuss these later.) ...
Organizational research increasingly relies on online review data to gauge perceived valuation and reputation of organizations and products. Online review platforms typically collect ordinal ratings (e.g., 1 to 5 stars); however, researchers often treat them as a cardinal data, calculating aggregate statistics such as the average, the median, or the variance of ratings. In calculating these statistics, ratings are implicitly assumed to be equidistant. We test whether star ratings are equidistant using reviews from two large-scale online review platforms: Amazon.com and Yelp.com. We develop a deep learning framework to analyze the text of the reviews in order to assess their overall valuation. We find that 4 and 5-star ratings, as well as 1 and 2-star ratings, are closer to each other than 3-star ratings are to 2 and 4-star ratings. An additional online experiment corroborates this pattern. Using simulations, we show that the distortion by non-equidistant ratings is especially harmful in cases when organizations receive only a few reviews and when researchers are interested in estimating variance effects. We discuss potential solutions to solve the issue with rating non-equidistance.
... found a positive influence of positive valence (i.e., 5-star rating) on the sales performance of books. Clemons et al. (2006) studied the craft beer industry and discovered that strongly positive valence would lead to significant growth in product sales. Positive valence is also more influential than others (Clemons et al., 2006). ...
... Clemons et al. (2006) studied the craft beer industry and discovered that strongly positive valence would lead to significant growth in product sales. Positive valence is also more influential than others (Clemons et al., 2006). Basuroy et al. (2003) studied this in the context of motion pictures, which involved 200 films released between late 1991 and early 1993, and found that positive valence is correlated with weekly box office revenue. ...
The influence of online consumer reviews on a firm’s sales performance has not yet been investigated in the field of Umrah. In addition, the literature does not explain how price moderates the relationship between online consumer reviews and a firm’s sales performance. Thus, the research objective of this paper is to examine the influence of Umrah online consumer reviews, specifically review valence, on Umrah operator sales performance, with Umrah package price acting as the moderator. 82 Malaysian Umrah operators were involved in this study. The secondary data for Umrah online consumer reviews were collected from Google Maps reviews, which matched Umrah operators’ sales data in 2019. The data were examined using a descriptive analysis followed by multiple regression analysis. The Statistical Package for the Social Sciences software was used to analyse the data. Interestingly, the findings of this study indicate that review valence significantly influences Umrah operator sales performance. Positive and neutral valence positively influences Umrah operator sales performance, whereas negative valence does not. Surprisingly, the moderating effect of Umrah’s package price was not significant. As a result, Umrah operators should work to maintain positive and impartial reviews and continuously monitor negative reviews and respond well to them.
... In Mexico the consumption of craft beer is on the rise, more and more people tend to opt for this product as a substitute for industrial beer. This has led to the creation of a segment that is more informed about the product and its consumption, and as a consequence, companies have to offer more differentiated products than their competitors (Clemons et al., 2006). ...
The development of Organizational Transformation Post-Pandemic for Competitiveness is a book aimed at those who are interested in border research topics. It is integrated by ten chapters where twenty-four researchers from seven universities in Mexico participated: Universidad Autónoma de Aguascalientes, Universidad Autónoma de Coahuila, Universidad de Guadalajara, Universidad de Guanajuato, Universidad Michoacana San Nicolás de Hidalgo, Universidad Autónoma de Nuevo León & la Universidad Autónoma de Querétaro, whose contributions reflect the state of the art and empirical evidence of various public and private organizations.
Each chapter contributes transversely to various objectives of the National Strategic Programs in Mexico as well as to the SDGs. The authors address various problems regarding the transformation of organizations, which reflect the gender perspective used
as part of organizational studies; the consequences faced by cooperatives after the pandemic; as well as optimization strategies and techniques in both the energy industry and agro-industrial sectors; in addition to delving into the role of emotional intelligence,
organizational culture and brands in organizational competitiveness.
... Here is the question of how to identify the reviewer's past behavior. A study finds that dispersion of ratings is positively correlated with sales growth and that the mean of the high end of the set of ratings is positively correlated with growth (Clemons et al. 2006). A normative model to address several important strategic issues related to consumer reviews has been studied in Chen and Xie (2008). ...
The article considers the assortment planning problem with respect to trustworthy reviewers. The trustworthiness of the product review and rating is based on whether the reviewer is rational or irrational. The average review ratings and comments are affected by the average trustworthiness. On the other hand, consumers have attention spans, i.e., the maximum number of products they are willing to view and inspect sequentially before purchasing a product or leaving the platform empty-handed when the attention span gets exhausted. The current paper provides an assortment planning model that maximizes revenue while considering trustworthy online product reviews as the quality by considering a threshold number of reviews and prices. This, in turn, is expected to minimize the information asymmetry within the decision-making process and identify the paid reviewers or manipulative reviews.
... (1) an adept craftsperson who leverages a "craft", (2) his/her craft implies intangible knowledge and skill richness (Tregear, 2005), (3) craftsmanship involved is frequently passed on through holy bond between apprentice and master, and (4) craftsmanship is expectedly being passed down through generations as nurtured legacy (Cominelli & Greffe, 2012). Scholars have examined artisan entrepreneurship from multiple perspectives of the marketing (Clemons, Gao, & Hitt, 2006), tourism (Popelka & Littrell, 1991), strategy (Verhaal, Hoskins, & Lundmark, 2017) and gender (Pret & Cogan, 2019). ...
Our exploratory study aims to investigate the identity tension in the growth and artistic logic that artisan encounters along with their development. We draw on primary and secondary data from 11 artisan entrepreneurs. Our results reveal sources from hybrid organizational dynamics and socio-cultural dynamics that contribute to identity tensions in artisan venture growth. Specifically, we find four sources derived from the sociocultural context, including cultural elements as branding, hybrid social expectation, socio-culture positioning in oversea markets, and external influence in community development. We also identified four sources from organisational identity and individual identity of entrepreneur perspective, including local embeddedness and expanding divergence, integrating artistic and commercial logics, customisation with customer needs, entrepreneur personal identity and brand identity. We elaborate on each source in the following texts. The findings from the current literature on identity tensions of venturing growth, artisan venture hybridity, and increasing studies on artisans.
... In today's dynamic realm of the Internet, online platforms are extensively employed for sharing consumers' experiences with brands, like any other transaction (Clemons et al., 2006;Freedman, 2008;King et al., 2014;Klein & Ford, 2003;Kotler & Keller, 2012). The rapid and voluminous exchange of information has given rise to a predicament: the infodemic. ...
This study aims to statistically investigate the effect of infodemic as an external stimulus on consumer decision processes based on the Stimulus-Organism-Response theory (SOR). Infodemic is known as the epidemic of misinformation, and the literature on infodemic in marketing is quite limited. With the research model created for this purpose, the mediating role of brand trust (organism) in the relationship between both infodemic and positive word-of-mouth marketing (stimulus) and consumers' store visit intentions (response) is examined. The findings suggest that infodemic news and positive word-of-mouth marketing influence consumers' shopping behaviour. Being influenced by infodemic news does not have a significant effect on store visit intention directly, but it has a positive effect through the mediation of brand trust. In addition, both direct and indirect effects of positive word-of-mouth marketing on store visit intention are positive. This suggests that brand trust functions as a coping mechanism for consumers to deal with the uncertainty or negative impact of infodemic news and that consumers' store visit intentions can be increased by enhancing their trust in the brand. As a result, it emphasises the importance of brands developing various communication strategies to increase their credibility and influence consumer decision-making mechanisms.
... Apps rating is one of the unique external factor that is found to have a strong correlation between customer rating and the number of downloads the apps have (Finkelstein et al., 2017). With an additional research that found a positive relationship between intention to purchase behaviour and the positive user review (Clemons et al., 2006;Xue & Zhou, 2011). ...
Background: The study is aimed toward understanding the factors that lead to the intention to purchase to a certain paid mobile apps, this objective is influenced by the current phenomenon where there is an increase in mobile apps user spending toward mobile apps and the superb growth of the industry. Method: The research relies on the expectation-confirmation model (ECM) for its research model. It used an online survey to users who already have experience in purchasing mobile apps (N = 276). The research uses structural equation modeling (SEM) with the use of AMOS 24 software to examine the hypothesis. Findings: It is found that confirmation influences perceived value and satisfaction, while the rest of the perceived value, apart from performance value positively affect satisfaction. Then value-for-money value, satisfaction, apps rating, free alternative to the paid apps, and habit have a significant impact on user intention to purchase as only free alternatives to the paid apps have a negative one. Conclusion: The research finding could contribute the finding to understand the mobile apps industry better while for a more practical contribution, there are some suggestions for parties that are related or involved in the mobile apps industry.
... Reviewing positive comments only makes potential customers develop similar attitudes or expectations, which in turn triggers users' use or purchase behavior. Specifically, strongly positive ratings can positively influence sales growth [19]. However, positive comments screening preferences cannot guarantee consultation quality and satisfaction. ...
The demand for online health consultations has exploded since the COVID-19 pandemic. Hence, electronic word-of-mouth is essential to obtaining information and reducing uncertainty for potential customers on mobile health platform. Based on an internet-based survey of 552 people from Zhejiang Province, China, this study investigated the influencing factors of electronic word-of-mouth on mobile health applications. The research model and related hypotheses were verified by linear regression models. We found that electronic word-of-mouth was influenced by electronic health literacy, perceived usefulness, the preference for positive comments, and the preference for physicians with advanced titles. Perceived usefulness partly mediated the relationship between electronic health literacy and electronic word-of-mouth. Furthermore, the preference for consulting physicians with more advanced titles and backgrounds positively moderated the relationship between electronic health literacy and electronic word-of-mouth. The empirical results offer insights on whether and how mobile health service platforms could serve patients better in the digital era.
... consumers may become aware of an unfilled product need and thus buy the product (Mudambi & Schuff, 2010). They also influence attitude toward using a service (Qahri-Saremi & Montazemi, 2016) and sales (Chen et al. 2008;Clemons et al. 2006). ...
Online platforms, such as Yelp and TripAdvisor, have facilitated ubiquitous and convenient access to a large number of online reviews about almost any product/service. Hence, it is imperative to understand what makes a review helpful for the consumers to make a decision about the adoption of the focal product/service. Drawing on Berlo's sender-message-channel-receiver model, the authors identify factors affecting online review helpfulness from the extant literature. Such understanding is critical to the review platforms and organizations to mitigate review helpfulness.
... Additionally, Westbrook (1987) showed that consumers' loyalty, customer's trust, product evaluation, and purchasing choice can be influenced by positive and negative information. According to Clemons et al. (2006), both positive and negative online evaluations can impact consumers' perception and attitudes toward a particular organisation. As a result, it would be more rational to investigate the effects of both unfavourable and favourable reviews, respectively. ...
... The fundamental principle of consumer behavior suggests that consumers can shape other consumers' opinions and exert powerful influences on brands, products, and services [1][2][3][4]. User-generated online reviews of products and services are becoming increasingly important sources of information for shoppers and greatly influence purchase decisions and product sales [5][6][7][8]. The recent revolutionary technological improvements, the rise in new media channels, and the increasing number of internet users have provided a fecund ground and many opportunities for consumers to share their experiences through electronic word-of-mouth (eWOM) channels. ...
This study investigates the impacts of the Big Five personality traits and propensity to trust on the use and writing of online reviews. Additionally, this study examines how gender moderates these impacts. Results of a survey (n = 840) show that openness to experience and conscientiousness positively influence online review use, while openness to experience and extraversion positively influence online review writing. Moreover, gender moderates the impacts of extraversion, openness to experience, and agreeableness on online review writing, with no moderating effect observed for online review use. Our findings contribute to the electronic word-of-mouth (eWOM) literature and offer important practical insights for eWOM platforms.
... Additionally, Westbrook (1987) showed that consumers' loyalty, customer's trust, product evaluation, and purchasing choice can be influenced by positive and negative information. According to Clemons et al. (2006), both positive and negative online evaluations can impact consumers' perception and attitudes toward a particular organisation. As a result, it would be more rational to investigate the effects of both unfavourable and favourable reviews, respectively. ...
This study aims to identify the role of online-generated content on consumer engagement towards domestic tourism and hospitality in recovery from the pandemic. The critical antecedences include Usefulness, Valence, Timeliness, Homophily, and Argument Quality, which influence Consumer Engagement with the mediating role of Perceived Trust. This cross-sectional study gathered data from 250 legitimate respondents from various regions of Vietnam by convenience sampling via an online questionnaire. The results were analyzed by SEM, stating Usefulness, Timeliness, and Homophily significantly impact Perceived Trust. Moreover, Perceived Trust also has a positive impact on Consumer Engagement. Interestingly, the Valence and Argument Quality constructs have insignificant impacts on Perceived Trust. Lastly, the findings are expected to contribute valuable knowledge about pandemic concerns during recovery and its impacts on travelers’ perceived trust and their further online engagement towards visiting/revisiting a destination. Findings demonstrate strong evidence for future studies to enlarge the category of respondents and consumer engagement literature, especially online behavior regarding the global crisis and pandemic concerns.
... C. Jiang et al., 2022;Kang et al., 2020). Resonant market theory suggests that consumers will only buy what they want if they are informed (Clemons et al., 2006), and the main potential of 3D interactive display marketing is its ability to provide consumers with rich sensory information (Kang et al., 2020;J. Kim & Forsythe, 2008). ...
3D interactive display marketing is a marketing method that uses 3D interactive technology and three-dimensional display scenes to facilitate interaction between people and display content. This approach has been widely used in online retail and is very popular in China’s automotive industry. The automobile industry tries to solve the severe issue of potential client loss in the automotive sector by using 3D interactive display marketing to persuade consumers to buy cars. However, it’s still unclear whether and how 3D interactive display marketing in the automobile sector might alter consumers’ inclination to buy cars. To address this issue, this study collected data through experiments and questionnaires and used a structural equation model to explore how automotive 3D interactive display marketing affected consumers’ willingness to purchase cars. The study established a model consisting of seven dimensions: information richness, information quality, interaction quality, esthetic experience, action experience, emotional experience, and willingness to purchase. The findings of this study can provide reference for producers and sellers in the automotive industry, promote the better application of automotive 3D interactive display marketing in the sector, and reduce potential loss of automotive customer.
... Conjoint analysis is an indispensable tool for predicting the effects of changes to marketplace offerings when observational data does not exist to inform an analysis (Dubé and Rossi, 2019). In this case, the conjoint analysis assesses trade-offs in responses concerning consumer preferences and intention to purchase by examining the relative importance of multi-dimensional attributes of craft beer products (Meyerding et al., 2019;Yoon et al., 2006) and aligns with Clemons et al. (2006) expressed statement that differentiation can be achieved by changing ingredients and production parameters, giving rise to countless beer styles, market trends influence business opportunities (Padilha et al., 2016) and consumers' desires for hyper differentiation (Dodd et al., 2018). ...
Purpose
This paper aims to uncover patterns of Mexican craft beer consumers and guide companies’ decisions in the creation of new products, marketing strategies, advertising and promotion to increase craft beer sales and contribute to faster growth.
Design/methodology/approach
This is a conjoint analysis with a selection of attributes for new or renewed products, marginal disposition to pay for particular characteristics through brand-specific choice-based design, and market simulation.
Findings
This paper clearly demonstrates consumers’ preferences and willingness to pay in Mexico, with a cutting-edge market research technique combining the prioritization of preferred craft beer characteristics, and the price consumers are willing to pay for such product characteristics.
Research limitations/implications
The study's sample size of 501 responses is relatively small compared to the total number of craft beer consumers in Mexico. To enhance the validity and reliability of the findings, future studies should aim to obtain larger samples and compare their results with those of this study.
Practical implications
This study has important implications for craft beer producers, allowing them to develop targeted craft beers with appealing attributes for Mexican consumers, such as color, aroma intensity, alcohol degree intensity, bitterness, foam level and price.
Social implications
This study's market forecasting simulation technique is based on assumptions of consumer behavior and market dynamics. Although relevant variables were considered, unanticipated external factors or market changes could impact the forecasts' accuracy. This will allow for a more comprehensive understanding of craft beer consumer preferences in different markets and enhance the reliability of forecasting techniques.
Originality/value
This paper informs craft beer producers by providing valuable knowledge on customers’ preferences and willingness to pay to enhance craft beer companies’ product development processes.
... In the context of entertainment, a survey conducted by Martin et al. (2007) previously found that individuals choosing between two movies with pre-given ratings found that consumers preferred the high-variance movie. A similar finding by Clemons et al. (2016) showed that beer brands with higher variances of ratings grow fastest in terms of sales. In the context of the findings of this study, a similar plausible explanation for the higher average rating of thirdparty products could be that in rating products, consumers are influenced by rating distributions and so more likely to give five-star ratings to products with existing rating distributions of higher variance. ...
In the context of multi-sided platform (MSP) literature, the strategic use of first-party content is well established. In these contexts, consumers’ value perceptions of first- and third-party content is assumed to be equivalent. In the marketing literature, however, it is generally accepted that the perceived value of products from store brands is significantly lower than products from manufacturer brands. This study investigates whether the same difference exists among consumers on a multi-sided platform. The study finds that consumers perceive products sold by the platform as delivering significantly less value than substitutes from third-party brands, and that this difference persists independently of price. The implications of the findings for managers and marketers are that (i) first-party content strategies on MSPs are limited by consumers’ value perceptions. This implies that (ii) managers should calibrate their first-party content strategies according to target customers’ preferences and that (iii) in their analytics, marketers should distinguish between first- and third-party content.
... The demand for craft beers has increased in recent years, mainly due to changes in consumer preferences [8,24,25], reaching in Spanish households in 2022 a total volume of 0.78 million litres and a total expenditure of 2.25 million euros, while per capita consumption has risen to 0.02 L of craft beer and a per capita expenditure of 0.05 million euros [26]. In addition, recent trends in the beer market have led to a significant increase in the variety of craft beers available, a phenomenon known as "hyperdifferentiation", as consumers demand products that precisely meet their needs and desires [27][28][29][30]. ...
... Figure 1 displays a standard price-quantity demand curve for a monopolist seller, where willingness to pay drops linearly with a consumer's distance from the actual product in a hypothetical product attribute space. This representation has been used to study consumers' responses in markets as diverse as craft beer and voting for political candidates; see, for example, Clemons et al. (2006). For convenience and for ease of comparison we model two scenarios within a single figure. ...
... The influence of online reviews on firm performance has also been widely demonstrated. Customer ratings, for example, have a statistically positive relationship with sales of beers (Clemons et al., 2006), books (Chevalier and Mayzlin, 2006) and hotel bookings (Ye et al., 2009), etc. Online reviews are especially important extra sources of information in the hospitality and restaurant industry, as the quality of each tourism product or service, due to its intangible nature, is difficult to assess before purchase and consumption (Litvin et al., 2008). The ratings and comments that are posted on websites such as TripAdvisor.com, ...
Purpose
The main goal of this paper is to identify the attributes of consumer experience in Michelin-starred restaurants and to estimate their effects on restaurant ratings.
Design/methodology/approach
A sample of 70,233 online reviews of 224 Spanish Michelin-starred restaurants were analysed with the latent Dirichlet allocation algorithm. A sentiment analysis and a logistic regression analysis were also employed to estimate the effect of attributes on restaurant ratings.
Findings
Customer attention, food quality, decor and ambience and value for money are frequently used to define restaurant experience. However, it is shown in this study that the experience in a Michelin-starred restaurant goes beyond the evaluation of those four attributes. Furthermore, the effect of the factors that were identified on customer satisfaction differed depending on the restaurant ratings.
Research limitations/implications
The findings are linked to the context of Spanish Michelin-starred restaurants. It is also assumed in this study that online reviews are based on truthful opinions.
Practical implications
Restaurant managers should primarily focus on customer attention and food quality to achieve customer satisfaction. In addition, those restaurants with an error-free service and a highly appreciated wine list among diners are more likely to achieve the culinary excellence that deserves a 5-star rating on TripAdvisor.
Originality/value
The attributes of the restaurant experience are frequently identified in literature reviews. Research based on text-mining analyses of customer reviews to discover a posteriori the factors that define a restaurant experience is scarce, and particularly difficult to find in the context of Michelin-starred restaurants.
... For peripheral information cues, this study found that both the popularity cue and herding information have a positive relationship with sales. The higher the popularity cue, the better the perceived quality of the product or service, which gives users a sense of trust and satisfaction [13]. Thus, we believe that the high popularity of a live streaming e-commerce service can decrease perceived risk in relation to product quality and promote buying. ...
Compared with traditional e-commerce, the advanced technology of live streaming e-commerce provides more dynamic information cues to enable viewers to make better decisions. Drawing on the information foraging theory (IFT) and elaboration likelihood model (ELM), we construct a synthetic model by considering how live streaming information cues influence viewers’ decision making via two distinct routes (central and peripheral). Using the technology of web crawling and text mining, Douyin’s live streaming data were collected, transformed, and then analyzed by fixed-effect regression. The results indicated that product interpretation duration, popularity cue, and herding information are significantly associated with sales performance in live streaming e-commerce. This study enriches our knowledge about live streaming e-commerce, extends the application of IFT and ELM in the individuals’ information foraging and processing by using objective data in the live streaming e-commerce context, and offers practical suggestions to live streaming e-commerce practitioners.
... Consumer buzz often occurs when consumers share their consumption experiences about a firm's services and products on its website. Buzz signals consumer attitudes, such as affection and faith, and cognition toward a brand, which therefore may drive their interactions with firms [65]. Thus, we suggest that online buzz can raise customer attachment and expand the customer base, all of which are precursors of marketing value and firm performance [66,67]. ...
With the unprecedented influence of social media, firms are increasingly relying on social media as a channel for marketing interaction. While firm-generated content (FGC) has become a common tool, allowing brands to show consumers informative, exchangeable messages, online word-of-mouth, such as user-generated content (UGC) and professional-generated content (PGC), has also become a prevalent strategy with the popularity of social media platforms to provide trustworthy information and promote product sales. However, our understanding on how those three online marketing strategies interactively influence firm performance as well as the conditions under which these effects vary remains limited. Drawing on signaling theory, this study examines how FGC, UGC, and PGC interactively influence car sales in the automobile industry and how such effects are influenced by product quality cues, such as price and popularity. Based on the monthly data in 56 major car makers, we find the varying relationships among FGC, UGC, and PGC on car sales. Moreover, for low-priced cars, UGC has a stronger effect on car sales. In contrast, at a higher level of popularity, UGC has a greater positive impact on car sales, while PGC has a less negative impact on car sales. These findings have important implications for automotive brand marketers striving to increase car sales through multiple social media marketing channels. Marketers should evaluate cross-media strategy by including its interplay with different types of social media and monitoring word-of-mouth of cars across different price ranges and popularity.
... 2. Review of literature Craft beer is achieving success in the marketplace for several reasons. Scholars identify various factors contributing to the success of craft beer, including its intrinsic quality characteristics, availability in local or regional markets, effective marketing strategies used by artisanal producers and the availability of hyper-differentiated products (Clemons et al., 2006;Kleban and Nickerson, 2012). To comprehensively address the diverse perspectives of craft beer consumer preferences, this section examines the primary contributors by categorizing previous approaches into four distinct determinants of consumption. ...
In recent years, the global consumption of craft beer witnesses remarkable growth. This growth is attributed to the evolving demographics of beer consumers, particularly the emergence of a new generation known as Digitarians or Generation Z. This study aims to analyze the key determinants influencing craft beer consumption among Digitarians.
An online questionnaire is administered, and a total of 296 completed responses are included in the statistical analysis. The methodology uses logistic regressions combined with a backward selection process and variance inflation factor analysis to address multicollinearity. The logistic regressions are conducted in three steps to delve into the research objective and gain insights into the behavior of young consumers. The stepwise backward selection aids in obtaining robust coefficients as a variable selection tool.
The results shed light on how Digitarians’ preferences for craft beer are influenced by various factors, including self-perceived knowledge, alcohol content, gender, food pairings, environment and companionship.
To the best of the authors’ knowledge, this paper contributes novel insights by being the first study to explore the significance of craft beer choices among Digitarians, identifying the role of several predictors in their consumption patterns.
... Research has demonstrated that customer agility can lead to better sales, but there are limits because overresponding to customer demands can lead to decreased performance (Zhou et al., 2018). Additionally, there is a benefit to highly positive consumer sentiment (i.e., customers that love rather than like the firm), which indicates that carefully attending to WOM can have advantages (Clemons et al., 2006). It is therefore critical to quickly and adequately respond to negative customer feedback to ensure future performance, and one possible response in our context is to release an app update. ...
Hypercompetitive mobile app stores are characterized by rapid innovation and intense competition. App firms must vie for temporary competitive advantage through competitive actions such as releasing product improvements. We study how competitive indicators influence a particular competitive action-app updates-in a mobile game app market. Our results reveal that app firms take action to improve or sustain their temporary competitive advantage, updating their apps when there are opportunities to capitalize on popularity (e.g., rank and rating volume are increasing) and when their apps' advantages are threatened (e.g., customer ratings are decreasing). We also find that app updates are released in response to competitors' actions-specifically, when competitors update their apps and new competitors enter ranking lists. Moreover, our findings show that app firms release app updates when an app's customer rating volume is increasing or when an app firm's portfolio of game apps is less diverse, relative to its competitors. We conduct additional analyses that show that older app firms are responsive to more competitive indicators than younger ones and major updates are primarily used to respond to serious threats to apps' competitive positions. Overall, our results indicate that app updates are competitive actions used to improve or sustain temporary advantage when competitive indicators reveal opportunities to improve or threats to apps' competitive positions.
Restaurant constitutes an essential part of the tourism industry. In times of uncertainty and transition, restaurant survival prediction is vital for deepening organizations’ understanding of business performance and facilitating decisions. By tapping into online reviews, a prevalent form of user-generated content, this study identifies review
variance as a leading indicator of restaurants’ survival drawing from data on 2838 restaurants in Boston and their corresponding reviews. Machine learning–based survival analysis shows that models integrating fine-grained
review variance (i.e., review rating variance, overall review sentiment variance, and fine-grained review sentiment variance) outperform models that do not account for these factors in restaurant survival prediction before and during the pandemic. Furthermore, in most cases, expert reviews hold stronger predictive power for
pre-pandemic restaurant survival than non-expert and all forms of reviews. This study contributes to the literature on business survival prediction and guides industry practitioners in monitoring and enhancing their enterprises.
This chapter highlights how privacy and data protection issues are intertwined with other laws that seek to protect consumer interests. Online business models constantly change with the exponential need for data that furthers every change.
Due to the COVID-19 pandemic, the size of the e-commerce has been increased rapidly. This pandemic, which made contactless communication culture in everyday life made the e-commerce market to be opened even to the consumers who would hesitate to purchase and pay by electronic device without any personal contacts and seeing or touching the real products. Consumers who have experienced the easy access and convenience of the online purchase would continue to take those advantages even after the pandemic. During this time of transformation, however, the size of information source for the consumers has become even shrunk into a flat screen and limited to visual only. To provide differentiated and competitive information on products, companies are adopting AR/VR and scanning technologies but the reviews from the honest users need to be recognized as important in that it is regarded as strong as the well refined product information provided by marketing professionals of the company and companies may obtain useful insight for product development, marketing and sales strategies. Then from the consumer's point of view, if the ratings of reviews are widely diverged how consumers would process the review information before purchase? Are non-converged ratings always unreliable and worthless? In this study, we analyzed how consumer's regulatory focus moderates the attitude to process the diverged information. This experiment was designed as a 2x2 factorial study to see how the variance of product review ratings (high vs. low) for cosmetics affects product attitudes by the consumers' regulatory focus (prevention focus vs. improvement focus). As a result of the study, it was found that prevention-focused consumers showed high product attitude when the review variance was low, whereas promotion-focused consumers showed high product attitude when the review variance was high. With such a study, this thesis can explain that even if a product with exactly the same average rating, the converged or diverged review can be interpreted differently by customer's regulatory focus. This paper has a theoretical contribution to elucidate the mechanism of consumer's information process when the information is not converged. In practice, as reviews and sales records of each product are accumulated, as an use of applied knowledge management types with big data, companies may develop and provide even reinforced customer experience by providing personalized and optimized products and review information.
Customer reviews, price discounts, and free shipping are powerful drivers of online purchases. Prior research demonstrates their direct effects on consumer behavior, usually with the assumption that they operate independently. By examining the interplays of online reviews and marketing promotions, this study offers a richer, more comprehensive perspective on how these drivers work together to shape consumers’ preferences and influence product sales. The authors examine these effects using both an online experiment (Study 1) and an analysis of a secondary data set (Study 2). Results demonstrate that when developing promotional schedules for e-commerce sites, managers must account for both the volume and valence of their products’ reviews; failing to address these dynamics may lead to reduced profit margins. A key insight is the limited performance of price discounts when a critical number of reviews accumulates, resulting in margin erosion without demand creation. The implications of these results are discussed.
This study tested the effect of variance in service quality ratings on overall scores of users in reviews (7,210 sites, 576,449 reviews) on the well-known hotel accommodation reservation site “Rakuten Travel.” The results revealed that the overall score was lower for a hotel with higher variance in service quality ratings for most functions. This trend was clearer for leisure travelers than for business travelers. An additional survey of general managers of the hotels in the first analysis suggested that practicing total quality management (TQM) in a hotel may reduce the variance in service quality ratings of users.
How does the way companies elicit ratings from consumers affect the ratings that they receive? In 10 pre-registered experiments, we find that consumers rate subpar experiences more positively overall when they are also asked to rate specific aspects of those experiences (e.g., a restaurant’s food, service, and ambiance). Studies 1–4 established the basic effect across different scenarios and experiences. Study 5 found that the effect is limited to being asked to rate specific features of an experience, rather than providing open-ended comments about those features. Studies 6–9 provided evidence that the effect does not emerge because rating positive aspects of a subpar experience reminds consumers that their experiences had some good features. Rather, it emerges because consumers want to avoid incorporating negative information into both the overall and the attribute ratings. Lastly, study 10 found that asking consumers to rate attributes of a subpar experience reduces the predictive validity of their overall rating. We discuss implications of this work and reconcile it with conflicting findings in the literature.
This chapter introduces the main topics and objectives discussed in subsequent sections, covering various aspects of opinion mining and sentiment analysis. It addresses different challenges and proposes novel methods.
Section 3.1 highlights the need to filter out irrelevant information and personal attacks in online discussions to focus on evaluative opinion sentences. It proposes an unsupervised method utilizing natural language processing techniques and machine learning algorithms to automatically filter and classify sentences with evaluative opinions. This section calls for further research to explore more precise and efficient methods for identifying evaluative opinions and their application in sentiment polarity analysis. Section 3.3 presents a novel subproblem in opinion mining, focusing on grouping feature expressions in product reviews. It argues for the necessity of user supervision in practical applications and proposes an EM formulation enhanced with soft constraints to achieve accurate opinion summaries. This section showcases the competence and generality of the proposed method through experimental results from various domains and languages. Section 3.1 introduces the use of topic modeling, specifically the LDA method, for sentiment mining. It extends the LDA method to handle large-scale constraints and proposes two methods for automatically extracting constraints to guide the topic modeling process. The constrained-LDA model and extracted constraints are then applied to group product features, demonstrating superior performance compared to other methods. Section 3.3 addresses the challenge of grouping synonyms in opinion mining, proposing an efficient method based on similarity measurement. Experimental results from different domains validate the effectiveness of the method. Section 3.3 focuses on feature extraction for sentiment classification and compares the impact of different types of features through experimental analysis. This section provides an in-depth study of all feature types and discusses key problems associated with feature extraction algorithms. Section 3.2 explores the use of unsupervised learning methods for sentiment classification, emphasizing their advantages in classifying opinionated texts at different levels and for feature-based opinion mining. This section presents an empirical investigation of unsupervised sentiment classification of Chinese reviews and proposes an algorithm to remove domain-specific sentiment noise words. Section 3.6 introduces the use of substring-group features for sentiment classification through a transductive learning-based algorithm. Experimental results in multiple languages demonstrate the effectiveness of the algorithm and highlight the superiority of the “tfidf-c” approach for term weighting.
Therefore, this chapter provides a comprehensive overview of various aspects of opinion mining and sentiment analysis, and proposes several innovative methods to address different challenges. From filtering and classifying evaluative opinion sentences to grouping product features, and utilizing topic modeling and similarity measurement for sentiment mining, this chapter covers a wide range of topics and techniques. The practicality and superiority of the proposed methods are demonstrated through empirical experiments. These studies lay a foundation for further advancements in opinion mining and sentiment analysis, and hold significant value in practical applications.
Our exploratory study investigates identity tensions during the development of luxury artisan ventures. As artisan ventures, entrepreneurs in luxury artisan ventures are strongly embedded in cultural context, yet they also strongly reach out to customers outside their cultural context. As such, identity tensions differ between traditional artisan ventures and luxury artisan ventures. Our insights are gathered by the analyses of primary and secondary data from 11 entrepreneurial ventures. We find several sources of identity tensions that mainly pertain to the venture's deep embeddedness in a sociocultural context with several cultural elements that juxtapose commercial needs. Besides, strong identity tensions emerge when ventures by international expansion depart from their local embeddedness. The departure from the home sociocultural context by reaching out to international markets sets the challenges to persevere the cultural kernel but also change product and production elements to serve customers. Our findings contribute new insights on identity tensions that evolve during venturing growth and that are specific to the identity hybridity of luxury artisan ventures.
ResearchGate has not been able to resolve any references for this publication.