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This study, first, reviews the existing literature on electronic word-of-mouth (eWOM) and, using communication theory, examines its impact on its readers’ decision-making processes. Second, this paper aims to propose some elements of eWOM communications that might be further researched.

A literature review of relevant academic articles produced 97 works related to social communication theory, eWOM and new artificial intelligence trends in hospitality. Thereafter, potential avenues for future research were explored.

The study results showed: valence, relevance, understandability and visual cues are the most important antecedents of message usefulness and the reader’s behavioral intentions; source credibility is the sender characteristic that most affects the reader’s behavioral intentions and consumer susceptibility to interpersonal influence is the receiver characteristic that most influences their attitudes and behavioral intentions. In addition, the study highlights four relevant aspects for future research. First, more research into online fake reviews is needed to better understand sender motivations. Second, companies should actively manage negative reviews. Then, the careful choice of platforms on which companies promote their products/services. Finally, the role of artificial intelligence in increasing the effectiveness of eWOM in the hospitality industry.

This paper integrates – grounded on communication theory – results from previous studies about the central elements of communication (message, sender and receiver) and discusses the main trends in hospitality-related eWOM. In addition, the paper examines the potential of specific eWOM elements as future lines of research, in particular: fake reviews, strategies for dealing with negative reviews, the eWOM platform used and artificial intelligence applications.

Este estudio, en primer lugar, revisa la literatura existente sobre el boca-oído electrónico (eWOM) y, utilizando la teoría de la comunicación, examina su impacto en los procesos de toma de decisiones de sus lectores. En segundo lugar, proponemos algunos elementos de las comunicaciones eWOM que podrían investigarse más adelante.

Una revisión de la literatura de artículos académicos relevantes produjo 97 trabajos relacionados con la teoría de la comunicación social, eWOM y nuevas tendencias de inteligencia artificial en hotelería. A partir de entonces, se exploraron posibles vías de investigación futura.

Los resultados del estudio señalaron: 1) la valencia, la relevancia, la comprensibilidad y las señales visuales son los antecedentes más importantes de la utilidad del mensaje y las intenciones de comportamiento del lector; 2) La credibilidad de la fuente es la característica del emisor que más afecta las intenciones de comportamiento del lector; 3) La susceptibilidad del consumidor a la influencia interpersonal es la característica del receptor que más influye en sus actitudes e intenciones de comportamiento. Además, el estudio destaca cuatro aspectos relevantes para futuras investigaciones. Primero, se necesita más investigación sobre las reseñas falsas en línea para comprender mejor las motivaciones del emisor. En segundo lugar, las empresas deben gestionar activamente las críticas negativas. Luego, la cuidadosa elección de las plataformas en las que las empresas promocionan sus productos/servicios. Por último, el papel de la inteligencia artificial en el aumento de la eficacia de eWOM en la industria hotelera.

Este artículo integra –con base en la teoría de la comunicación– resultados de estudios previos sobre los elementos centrales de la comunicación (mensaje, emisor y receptor) y analiza las principales tendencias en eWOM relacionadas con la hostelería. Además, el artículo examina el potencial de elementos específicos de eWOM como líneas futuras de investigación, en particular: revisiones falsas, estrategias para lidiar con críticas negativas, la plataforma eWOM utilizada y aplicaciones de inteligencia artificial.

Palabras clave: eWOM, Teoría de comunicación, Revisiones falsas, Revisiones negativas, Inteligencia artificialTipo de artículo: Revisión de la literatura

本研究, 首先, 回顾了现有的关于电子口碑（eWOM）的文献, 并利用传播理论, 研究了它对读者决策过程的影响。其次, 我们提出了一些可能需要进一步研究的电子口碑传播的要素。

对相关学术文章的文献回顾产生了97篇与社会传播理论、eWOM和酒店业新的人工智能趋势有关的作品。此后, 对未来研究的潜在途径进行了探讨。

研究结果显示。1）价值、相关性、可理解性和视觉线索是信息有用性和读者行为意图的最重要的前因; 2）来源的可信度是最能影响读者行为意图的发送者特征; 3）消费者对人际影响的易感性是最能影响他们态度和行为意图的接受者特征。此外, 该研究还强调了未来研究的四个相关方面。首先, 需要对网上虚假评论进行更多的研究, 以更好地了解发送者的动机。其次, 公司应该积极管理负面评论。然后, 谨慎选择公司推广其产品/服务的平台。最后, 人工智能在提高酒店业eWOM的有效性方面的作用。

本文以传播理论为基础, 整合了以往关于传播中心要素（信息、发送者和接受者）的研究结果, 并讨论了与酒店业相关的电子WOM的主要趋势。此外, 本文还研究了特定的eWOM要素作为未来研究方向的潜力, 特别是：虚假评论、处理负面评论的策略、使用的eWOM平台和人工智能应用。

关键词：eWOM, 传播理论, 虚假评论, 负面评论, 人工智能。

The star rating summarises the review content and conveys the message faster than other review components. Star ratings influence helpfulness of the reviews, and extreme reviews are considered as less helpful in the decision process. However, literature has rarely addressed variations in star ratings across product categories and variations between two online retailers. In this paper, the authors have compared the distribution of star ratings across 11 products and among the retailers.

Online reviews for 11 product categories have collected, and the authors compared the distribution of star ratings across 11 products and retailers. Correspondence analysis has been applied to show the association between star ratings and product categories for the e-retail firms.

The Amazon site contains proportionately more number of 1-star rated reviews than Flipkart. In Amazon reviews, few product categories are closely associated with 1-star and 2-star reviews, whereas no product categories are closely associated with 1-star and 2-star reviews in Flipkart reviews. The results indicate two distinct communication strategies followed by the firms in managing online consumer reviews.

The authors did not analyse data across demographic details because of access restriction policies of the websites.

Understanding the distribution of review characteristics will improve the consumer’s decision-making ability and using online review content judiciously.

This study’s results show significant insights on online retailing by providing cues in using shopping sites and online review characteristics of two prominent retailers.

This paper has brought out a distinct distribution pattern of online review between Amazon and Flipkart. Amazon allows a higher degree of negative contents, whereas Flipkart allows more number of positive reviews.

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.

This study aims to compare online review characteristics, review length and review sentiment score between “organic” and “regular” food products. In addition, variations in the consumer sentiment scores across the review lengths are studied.

This study fits into the descriptive research design. From Amazon’s website, the consumer product reviews are scrapped. Using the text analytical package “sentiment” in R-Studio, we computed the sentiment scores and counted the number of words in each review. The mean sentiment scores and mean review length are compared for regular and organic products using one-way ANOVA. Sentiment score variation across review length and product class is studied through factorial ANOVA. Sample reviews of ghee and honey are used to test the hypotheses.

The review length shows a significant difference between the regular and organic products. The mean number of words in the regular products reviews is significantly lower than the mean number of words in the organic product reviews. The regular products’ mean sentiment score is significantly lower than the mean sentiment score of organic products. The mean sentiment scores are not consistent between ghee and honey. Sentiment scores are better for organic honey and regular ghee products. For regular ghee products, longer reviews result in lower sentiment scores. For regular and organic versions of honey, longer reviews are associated with better sentiment scores.

This study did not include the helpfulness of a review and the demographic data of the reviewers.

Sentiment scores’ variations across the regular and organic and product categories such as ghee and honey give a comprehensive feedback to the firms. It also indirectly communicates a brand’s evaluation by the consumers and the performance feedback for an upward extension like the organic category.

Studies on organic category give feedback for environment-friendly products and consumer attitude shift towards safer products.

Very limited studies have reported the upward line extensions. The authors study the upward line extension organic and associated sentiment scores variation. The role of review length and its systematic influence on the sentiment scores, variations in the review due to the product nature (organic/regular) are unique contributions of this study.

This research investigates consumer intention to follow online community advice. Applying the technology acceptance model (TAM) to the context of online restaurant communities, the study empirically examines the effects of perceived usefulness, perceived ease of use, attitude and trust on the intention to follow online advice.

The data were collected from 360 members of online restaurant communities on Facebook and analyzed using structural equation modeling (SEM).

The findings revealed that trust, perceived usefulness and attitude are key predictors of the intention to follow online restaurant community advice.

Extant research on the influence of online reviews on consumer behavior in the restaurant industry has largely focused on the characteristics of the review, reviewers or readers. Moreover, other studies have investigated consumers' motivations to write online restaurant reviews. This study, however, takes a different approach and examines what drives consumers to follow the advice from online restaurant communities.

Drawing on attribution theory, the current paper aims to examine the effects of review content structures on online review helpfulness, focusing on three pertinent variables: review sidedness, information factuality, and emotional intensity at the beginning of a review. Moreover, the moderating roles of reviewer reputation and review sentiment are investigated.

The review sentiment of 144,982 online hotel reviews was computed at the sentence level by considering the presence of adverbs and negative terms. Then, the authors quantified the impact of variables that were pertinent to review content structures on online review helpfulness in terms of review sidedness, information factuality and emotional intensity at the beginning of a review. Zero-inflated negative binomial regression was employed to test the model.

The results reveal that review sidedness negatively affects online review helpfulness, and reviewer reputation moderates this effect. Information factuality positively affects online review helpfulness, and positive sentiment moderates this impact. A review that begins with a highly emotional statement is more likely to be perceived as less helpful.

Using attribution theory as a theoretical lens, this study contributes to the online customer review literature by investigating the impact of review content structures on online review helpfulness and by demonstrating the important moderating effects of reviewer reputation and review sentiment. The findings can help practitioners develop effective review appraisal mechanisms and guide consumers in producing helpful reviews.

Food banks play an increasingly important role in society by mitigating hunger and helping needy people; however, research aimed at improving food bank operations is limited.

This systematic review used Web of Science and Scopus as search engines, which are extensive databases in Operations Research and Management Science. Ninety-five articles regarding food bank operations were deeply analyzed to contribute to this literature review.

Through a systematic literature review, this paper identifies the challenges faced by food banks from an operations management perspective and positions the scientific contributions proposed to address these challenges.

This study makes three main contributions to the current literature. First, this study provides new researchers with an overview of the key features of food bank operations. Second, this study identifies and classifies the proposed optimization models to support food bank managers with decision-making. Finally, this study discusses the challenges of food bank operations and proposes promising future research avenues.

Digitalization in marketing activities has made it easier for people to make purchase decision. This platform encourages every firm to optimize digitalization as part of its marketing strategy. Optimization of attractive digital marketing involves advertising attractiveness, influencer marketing and online customer reviews. This study aims to investigate advertising attractiveness, influencer marketing and online customer reviews on purchase decision.

The study was conducted with a quantitative approach. A total of 120 respondents were involved in this study by using convenience sampling techniques in data collection. Multiple linear regression was used to analyze the data.

The results of the study show that influencer marketing and online customer reviews have an impact on online purchase decision. Meanwhile, advertising attractiveness does not show any influence on purchase decision.

Despite the start-ups have modified the website by increasing the content to make it more informative, it seems that customers are not interested in making a purchase. Therefore, notwithstanding the role of website attractiveness, the use of physical attractiveness is still considered an effective way to encourage customers to make purchasing decisions. In this way, a firm needs to make adjustments between the customers' personality, lifestyle and attitudes and endorsers.

This study developed previous empirical studies which a positive relationship between advertising attractiveness, influencer marketing, online customer reviews and purchase decision. The development of the model was carried out by elaborating variable indicators. In addition, the source of increasing credibility was not based on physical attractiveness, but rather emphasizes the website quality.

The diffusion of electronic commerce has a notable impact on the economy's prosperity. This paper embraces complexity theory principles to examine the factors affecting Internet users' acceptance and use of electronic retailers. It is essential for the sustainability of electronic retailers to understand the motivations impacting online consumer behaviour. Symmetrical and asymmetrical methods are combined to examine the relationship between perceived ease of use, perceived enjoyment, web characteristics, online consumer reviews (OCRs) and online purchase intention. Further, symmetry and differences between males and females were examined.

Data collected from 425 online consumers using an online structured survey was analysed using structural equation modelling (SEM) and fuzzy set qualitative comparative analysis (fsQCA). The net effects and causal configurations of the four proposed variables and online purchase intention were examined.

The SEM findings confirmed the significance of perceived enjoyment, website characteristics and OCRs on online purchase intention. Perceived enjoyment mediated the relationship between perceived ease of use and online purchase intention. The multi-group analysis confirmed the difference in antecedent impacts between males and females. The fsQCA findings revealed that multiple recipes lead to the occurrence of online purchase intention; in addition, the recipes leading to its absence do not mirror the previous ones.

The present study embraces complexity theory concepts in understanding online purchase intention using fsQCA methodology; further, the role of gender in online consumer behaviour was highlighted in the result discussion.

The growing complexity of consumer engagement (CE) due to the impact of Internet of things (IoT) has been attracting significant attention from both academics and industry practitioners especially in recent times. Hence, understanding this phenomenon remains very crucial to the body of knowledge. This study conducted a systematic review on IoT and CE with the aim of proposing future research opportunities using the TCCM model.

Extant literature studies were systematically examined by sourcing high ranking ABS journals from EBSCO, ScienceDirect and Emerald. A total of 58 articles were included in the final analysis of this research.

The analysis established the need to conduct more research on CE due to the impact of new technological implementation in retail. The results further suggest the need for extensive research across African countries and emerging markets to enable broader empirical generalizations of research outcomes. Using the TCCM framework, the authors indicated directions for future empirical research.

This study exposes the current trends in CE and IoT. The results and analysis are both compelling and verifiable, hence, establishing a firm base of reference for future research in related fields.