Search Results (107)

Social networks have emerged as a powerful tool for communication and marketing, enabling two-way user participation and fostering a conducive environment for electronic word of mouth (eWOM). This study examines how social influence, eWOM engagement, and perceived eWOM credibility affect its adoption, while also exploring the moderating role of gender in these relationships. Using a sample of 371 cosmetics consumers in Ecuador, a causal model was estimated using the PLS method. The findings confirm that social influence significantly impacts eWOM engagement and credibility, contributing to its adoption. Additionally, gender moderates the relationship between informational influence and eWOM credibility. This study also highlights the need to replicate the model in different contexts and with more diverse samples to enhance the generalizability of the findings. By enriching Erkan and Evans’ IACM theoretical framework, this research extends the understanding of eWOM dynamics in the cosmetics sector. Moreover, it offers a comprehensive perspective on the eWOM adoption process by incorporating underexplored variables and providing empirical evidence from an understudied region, such as Latin America. Full article

The extensive electronic word-of-mouth (eWOM) data generated by consumers encapsulates authentic product experience information. By leveraging advanced data analysis technologies, enterprises can extract sustainable consumer behavior preference knowledge, thereby supporting the optimization of their marketing and management strategies. However, existing data-driven product ranking processes predominantly focus on single-source eWOM data and rarely mine product insights from a multi-source perspective. Moreover, the quality of eWOM data cannot be overlooked. Consequently, this study uses automobile products as a case example and integrates rating eWOM data, complaint eWOM data, and safety test data to construct a multi-source data-driven personalized product ranking recommendation algorithm. Specifically, an evaluation index system is established for each of the three data types. To model information quality, these data are transformed into basic uncertain information (BUI), which incorporates scoring information and credibility metrics. The XLNet model is employed to convert complaint text data into scoring data, and three targeted credibility evaluation models are developed to assess the reliability of the three data types. Subsequently, BUI is aggregated using the BUI ordered weighted average (BUIOWA) aggregation operator. Based on this, a personalized product ranking method aligned with user preferences is proposed, offering consumers recommendation results that match their preferences. Finally, using automobile products as an illustrative example, this study elucidates the multi-source data-driven personalized product recommendation process and provides managerial implications for enterprises. Full article

Considering social media’s expansion worldwide, marketing academics and marketers emphasize the need to consider electronic word of mouth (eWOM) for strategic marketing decisions. However, there is limited research regarding the ways in which male and female consumers engage in eWOM behaviors. This research aims to explore the gender-specific dynamics of eWOM drivers in social media marketing, by validating a proposed model of key predictors for two samples (of female and male respondents). Data were gathered from two samples of social media users. For this empirical research, we integrated structural equation modeling and an artificial neural network (PLS-SEM-ANN) for a comprehensive approach intended to generate practical and theoretical insights for eWOM. Hypothesis testing reflected contrasting results—for female respondents, the key eWOM drivers were customer participation, involvement, loyalty, and customer satisfaction; whereas, for male respondents, the key predictors were brand familiarity, loyalty, and satisfaction. The significant variables supported by SEM were included in ANN models as input neurons, showcasing nonlinear relationships among constructs for both samples. Thus, this research provides theoretical contributions regarding eWOM, gender assessments, and the social media marketing literature. From a practical perspective, this study advances targeted social media marketing strategies to enhance consumer–brand interactions. Full article

The rapid expansion of digital platforms has significantly influenced consumer purchasing behaviors, particularly in the agri-food sector. Therefore, this paper investigates the key factors driving customers’ intention to use green agri-food delivery apps (GAFDAs) by integrating trust and electronic word of mouth (eWOM) into the Theory of Planned Behavior (TPB) framework. Additionally, this study examines gender as a moderating variable, assessing whether its influence alters the relationships between key determinants and behavioral intention. Data were collected from 252 Algerian consumers, and the proposed model was tested using SmartPLS 4 and SPSS 26.0. The results confirm that attitude, subjective norms, perceived behavioral control (PBC), trust, and eWOM positively and significantly influence the intention to use GAFDAs, with PBC emerging as the strongest predictor. Moreover, gender moderates the effect of trust on behavioral intention, with trust significantly influencing men’s adoption decisions but not those of females. In contrast, subjective norms and PBC are stronger predictors for female consumers. These findings highlight the importance of gender-specific marketing strategies to enhance GAFDA adoption. This study contributes to the literature by extending TPB with trust, eWOM, and gender moderation, offering valuable insights for marketers, policymakers, and app developers promoting sustainable food consumption. Full article

This study employs the push–pull theory to analyze tourism motivations (push and pull), perceived risk (financial risk and perceived risk), perceived value, educational level and smartphone usage and their effect on willingness to pay (WTP) and electronic word-of-mouth (E-WOM) behavioural intentions in Smart Tourism Destinations (STDs). With a significant sample of 504 respondents in the STD of Cáceres, the push–pull theory is used to assess its impact on smartphone usage. Results reveal that motivations, financial risk, perceived value and educational level positively affect smartphone usage, directly influencing WTP and E-WOM. Managers are advised to prioritize privacy in mobile payments, implement security services against financial risks and promote specialized applications and encourage the personalization of offers through artificial intelligence. Understanding these variables, which explain 41.5% of WTP and 65.8% of E-WOM, provides a basis for strategic decision-making in STDs. Full article

Internet platforms and self-media have become vital online communities for promoting positive reputations for hotels. Previous studies have primarily focused on enhancing positive electronic word-of-mouth (eWOM) through improvements in hotel infrastructure and staff services. As hotels deepen their digital transformation, the application of various artificial intelligence technologies in hotel service encounters significantly impacts the service experience. This study explores the effects of voice assistant (VA) attributes on the online reputation of hotels. Specifically, it examines how the attributes of VAs (anytime connectivity, information association, and interactivity) influence positive customer evaluations in hotels. Utilizing a questionnaire survey method, we collected 529 valid questionnaires offline and employed structural equation modeling along with the PROCESS plugin in SPSS to conduct path analysis, as well as mediation and moderation effect analyses. The results indicate that perceived value and the existence of human–AI rapport mediate the impact of VA attributes on positive eWOM, although the direct effect of some attributes (information association) was not supported. Furthermore, anytime connectivity enhances the influence on human–AI rapport through social presence, while privacy concerns negatively affect the relationship between perceived value and intentions to engage in eWOM. These insights are critical for hotels seeking to maximize the benefits of digital transformation. Full article

This study explores how the green marketing mix affects customer green brand trust, customer green buying behavior, and electronic word-of-mouth (eWOM). A total of 990 fast-food customers participated in this study. Structural equation modelling (SEM) and mediation analysis were applied to validate the research hypotheses. As customer demand for environmentally sustainable products grows, green marketing mix has a positive and significant effect on customer green brand trust. Furthermore, customer green brand trust also significantly influences customer green buying behavior and eWOM as a predictor and mediator. It means that customer green brand trust is a fundamental effect of eWOM, with trust fostering positive online reviews, recommendations, and advocacy from customers. Businesses can also make the most of eWOM by developing feedback-friendly channels, such as product review pages and social media campaigns, and rewarding consumers who post about their satisfying online experiences. The companies should not only concentrate on increasing sales through environmentally sustainable product purchasing practices, but also on giving clients a feeling of community and integrating them into a larger sustainability movement. It will offer useful advice for marketers looking to improve their green marketing tactics and promote sustainable consumption by successfully gaining the trust of their target audience and using eWOM as a tactical instrument for brand advocacy. Full article

During the COVID-19 pandemic, the tourism sector encountered multiple challenges. Numerous governments chose to lock down their cities and countries. Despite this, many companies found their online businesses making the greatest leaps in their portfolios, and social media platforms became one of the most valuable sources of information for purchase decisions. There have been numerous studies on the effects of social media reviews—a form of electronic word-of-mouth (eWOM)—on consumer behavior. Few were found to be related to their impact on group package tours (GPTs) while considering mixed eWOM, that is, both the positive and negative forms present in word-of-mouth communication. As the tourism sector gradually revives, the need to further explore how tourism and hospitality service providers can adapt to changes in post-pandemic consumer behavior has become imperative. The influence of social media reviews on consumers’ value perceptions of a GPT to Japan, allowing for the influence of the marketing mix element of advertised price, was examined through online experiments in this study. Positive, negative, and mixed eWOM were examined. It was found that eWOM was more influential on consumers’ value perceptions than the advertised price for all price acceptability levels. Mixed eWOM was found to negatively affect consumers’ final price perceptions which override the impact of quality perceptions in value formations. The value perceptions of the GPT became less acceptable when eWOM was mixed compared to when eWOM was absent or was positive. Mixed eWOM had a negative effect on value perceptions but not as great as when negative eWOM was present, and this was consistently found to apply for all price acceptability levels of the GPT. This study’s contribution to eWOM research and implications for the post-pandemic recovery of tourism and hospitality service providers are made, together with suggested strategies using innovative technologies and communications to enhance their adaptive resilience in the new normal. Full article

Artificial intelligence (AI) stands out as a transformative force in various sectors, offering both new opportunities and challenges. In tourism and music events, AI has proven to be a powerful tool for improving the attendee experience, personalizing artist recommendations, optimizing event logistics in real time, and enhancing audience interaction through virtual assistants and immersive visual effects, thus highlighting its transformative potential. This study aims to analyze the impact of applying AI to the experience of consumers at music festivals. In particular, the research examines the impact of AI on the quality of information delivered, the extent of consumer engagement with brands at the event, and the level of trust in the technology. A quantitative methodology was used, collecting 400 responses from Portuguese consumers who attended music festivals. The results show that the quality of information and the AI positively influence customer engagement with the brand. Greater customer engagement, in turn, increases the willingness to use AI solutions. Trust in AI is significantly shaped by the quality of the information and the reliability of the system, which further promotes electronic word-of-mouth (eWOM) and the willingness to adopt AI. In addition, eWOM plays a key role in encouraging the use of AI technologies. Finally, memorable tourist experiences positively influence the willingness to adopt AI, underlining the importance of experiential factors in promoting adoption. These results highlight the interconnected roles of information quality, trust, involvement, and user experiences in shaping attitudes toward artificial intelligence applications. This study expands the literature by analyzing how AI-driven information quality influences consumer trust and engagement, thus emphasizing the need to optimize these factors for better festival strategies. It highlights the link between trust and positive eWOM, showing that trust based on high-quality information enhances the festival’s reputation and attracts participants. A key contribution is its exploration of how trust and eWOM influence AI adoption at future festivals, which offers insights to boost credibility and acceptance. Lastly, it provides strategic guidelines that improve attendee experience and festival management. Full article

With the rapid development of digital networks and communication technologies, traditional word-of-mouth (WOM) has transformed into electronic word-of-mouth (eWOM), which plays a pivotal role in improving the management and service quality of ancient town tourism. This study uses Python web scraping techniques to gather eWOM data from the top ten ancient towns in southern China. Using IPA analysis, the analytic hierarchy process (AHP), Term Frequency–Inverse Document Frequency (TF-IDF), and cluster analysis, we developed a comprehensive eWOM evaluation framework. This framework was employed to perform word frequency analysis, sentiment analysis, topic modeling, and rating analysis, providing deeper insights into tourists’ perceptions. The results reveal several key findings: (1) Transportation infrastructure varies significantly across the towns. Heshun and Huangyao suffer from poor accessibility, while the remaining towns benefit from the developed transportation network of the Yangtze River Delta. (2) The volume of eWOM is strongly influenced by seasonal patterns and was notably impacted by the COVID-19 pandemic. (3) The majority of tourists express positive sentiments toward the ancient towns, with a focus on the available facilities. Their highest levels of satisfaction, however, are associated with the scenic landscapes. (4) A comprehensive eWOM analysis suggests that Wuzhen and Xidi–Hongcun are the most popular tourist destinations, while Zhujiajiao, Huangyao, Zhouzhuang, and Nanxun exhibit lower levels of both attention and visitor satisfaction. Full article

Most studies suggest that individuals’ environmental cognition can positively predict their eco-friendly behaviors; however, the process through which environmental cognition influences the intention to engage in low-carbon tourism has yet to be fully explored. Additionally, while electronic word-of-mouth (eWOM) is a key factor influencing behavioral decisions, its moderating role in the context of low-carbon tourism remains under-researched. Drawing on the Cognitive-Affective-Conative (CAC) theoretical framework, this study investigates the impact of environmental cognition on green perceived value and low-carbon tourism intention, while also examining the moderating effect of eWOM. Data were collected from 457 participants in Taiwan via a structured questionnaire survey. The results show that environmental cognition has a significant positive impact on green perceived value but no direct effect on low-carbon tourism intention while green perceived value has a significant positive impact on low-carbon tourism intention and fully mediates the relationship between environmental cognition and low-carbon tourism intention. Furthermore, the study finds that eWOM moderates the relationship between environmental cognition and green perceived value, with eWOM strengthening the effect of environmental cognition on green perceived value. These findings suggest that enhancing environmental cognition, reinforcing green perceived value, and effectively leveraging eWOM can foster positive attitudes and willingness to engage in low-carbon tourism. The results provide practical implications for tourism operators in developing strategies to promote low-carbon tourism. Full article

The evidence on e-commerce rapidly adopting and expanding has led to a high degree of changes in consumer behavior, with food delivery platforms playing a pivotal role in the digital economy. The current study highlights the interplay between consumer perception, consumer acceptance, and electronic word of mouth (e-WOM) assessed in the context of the food delivery chain. By integrating latent variables, such as trust, consumer purchase intentions, perceived usefulness, and psychological distance, the current study explores the role of e-WOM in influencing consumer perception and acceptance within the food delivery services. Data collection and analysis implied a qualitative approach by issuing an online survey and gathering 835 valid responses, further quantitatively assessed through structural equation modelling. The data reveal the validity of the two general hypotheses, according to which consumer acceptance is positively connected to consumer perception, to which the influence of electronic word of mouth was added. The current study stresses the importance for food delivery chains to gain insight and implement strategies based on its electronic peers’ online suggestions and recommendations. The current research actively contributes to the theoretical discourse on food delivery chain management related to the electronic consumers’ experience, in order to competitively position it on electronic markets as well as the food delivery global industry. Full article

The rapid growth of the internet and social media has made electronic word of mouth (eWOM) a key element of modern marketing. In the hospitality industry, nowadays, effective eWOM management is essential for developing impactful strategies and fostering customer satisfaction. This paper introduces an enhanced approach to strategic customer base management based on online reviews by extending the Recency, Frequency, and Monetary (RFM) model with three novel dimensions, the Helpfulness, Promoter Score, and Stability of the customer, thereby forming the RFHPS model. It also includes the 2-tuple linguistic model, one of the most popular computing with words models, to improve precision in the RFHPS score’s computation and the findings’ interpretability. Using K-means clustering, customers are segmented across these five dimensions. The data on luxury hotels in Spain gathered from TripAdvisor demonstrate the model’s applicability. By integrating this framework into customer relationship management systems, managers can tailor marketing strategies for distinct segments, facilitating deeper customer understanding and bolstering eWOM generation. Full article

In recent years, the growing number of Online Travel Review (OTR) platforms and advances in social media and search engine technologies have led to a new way of accessing information for tourists, placing projected Tourist Destination Image (TDI) and electronic Word of Mouth (eWoM) at the heart of travel decision-making. This research introduces a big data-driven approach to analyzing and measuring the perceived and conveyed TDI in OTRs concerning the reflected perceptive, spatial, and affective dimensions of search results. To test this approach, a massive metadata analysis of search engine was conducted on approximately 2700 reviews from TripAdvisor users for the category “Attractions” of the city of Kastoria, Greece. Using artificial intelligence, an analysis of the photos accompanying user comments on TripAdvisor was performed. Based on the results, we created five themes for the image narratives, depending on the focus of interest (monument, activity, self, other person, and unknown) in which the content was categorized. The results obtained allow us to extract information that can be used in business intelligence applications. Full article

This study explored how fans’ perceptions of sponsor participation in environmental, social, and governance (ESG) activities influence attitudes toward the sponsor, sponsor image, electronic word of mouth (eWOM), and purchase intentions. Limited research has focused on the interactions between sports sponsorship and ESG activities. This study filled this research gap by considering the case of the Rakuten Monkeys, a professional baseball team in Taiwan, and its sponsors. Grounded in the theory of planned behavior, this study investigated how fans’ perceptions of sponsor participation in ESG initiatives affect their purchase intentions through sponsor attitudes, sponsor image, and eWOM. A total of 800 Rakuten Monkeys fans were recruited for this study, and the study hypotheses were tested using structural equation modeling. The results indicate that all investigated paths were significant. That is, fans’ perceptions of sponsor participation in ESG activities significantly enhance their attitudes toward the sponsor and sponsor image, which in turn positively influence their eWOM and purchase intentions. This study has theoretical and practical implications for enhancing brand image and consumer purchase intentions through ESG activities. The study contributes valuable insights that can be used by sports sponsors for developing marketing strategies. Full article