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Global adoption of the internet and mobile usage results in a huge variation in the cultural backgrounds of consumers who generate and consume electronic word-of-mouth (eWOM). Unsurprisingly, a research trend on cross-cultural eWOM has emerged. However, there has not been an attempt to synthesize this research topic. This paper aims to bridge this gap.

This research paper conducts a systematic literature review of the current research findings on cross-cultural eWOM. Journal articles published from 2006 to 2021 are included. This study then presents the key issues in the extant literature and suggests potential future research.

The findings show that there has been an upward trend in the number of publications on cross-cultural eWOM since the early 2010s, with a relatively steeper increase toward 2020. The findings also synthesize cross-cultural eWOM research into four elements and suggest potential future research avenues.

To the best of the authors’ knowledge, there is currently no exhaustive/integrated review of cross-cultural eWOM research. This research fills the need to summarize the current state of cross-cultural eWOM literature and identifies research questions to be addressed in the future.

El boca a boca electrónico cross-cultural: una revisión sistemática de la literatura

La adopción global de Internet y los móviles da lugar a una enorme diferencia en el origen cultural de los consumidores que generan y consumen el boca a boca electrónico (eWOM). No es de extrañar que haya surgido una tendencia de investigación sobre el eWOM transcultural. Sin embargo, no se ha intentado sintetizar este tema de investigación. El objetivo de este artículo es subsanar esta carencia.

Este trabajo de investigación realiza una revisión bibliográfica sistemática de las investigaciones realizadas sobre eWOM transcultural. Se incluyen artículos de revistas publicados desde 2006 hasta 2021. A continuación, el estudio presenta las cuestiones clave de la literatura existente y sugiere posibles investigaciones futuras.

Los resultados muestran que ha habido una tendencia al alza en el número de publicaciones sobre eWOM intercultural desde principios de la década de 2010, con un aumento relativamente creciente hacia 2020. Los resultados también sintetizan la investigación sobre eWOM intercultural en cuatro elementos y sugieren posibles vías de investigación futuras.

Actualmente no existe una revisión exhaustiva/integrada de la investigación sobre el eWOM cross-cultural. Esta investigación satisface la necesidad de resumir el estado actual de la literatura sobre eWOM cross-cultural e identifica las cuestiones de investigación que deben abordarse en el futuro.

跨文化电子口碑研究：系统性文献回顾

摘要

在互联网全球化以及移动手机的广泛使用的背景下, 不同文化背景的消费者都在贡献电子口碑（eWOM）。这使得电子口碑存在文化差异。然而, 还没有人试图对这个研究课题进行综合分析。本文的目的就是要弥补这一空白。

本研究论文对目前关于跨文化eWOM的研究成果进行了系统的文献回顾。包括2006年至2021年发表的期刊文章。然后, 本研究提出了现有文献中的关键问题, 并提出了潜在的未来研究。

研究结果显示, 自2010年初以来, 关于跨文化eWOM的出版物数量呈上升趋势, 到2020年时增幅相对较大。研究结果还总结了跨文化eWOM研究的四个要素, 并提出了潜在的未来研究途径。

目前还没有关于跨文化eWOM研究的详尽/综合的回顾。这项研究填补了总结跨文化电子WOM文献现状的需要, 并确定了未来要解决的研究问题。

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.

The food industry is continuously developing its online services called food delivery applications (FDAs). This study aims to evaluate FDA's importance–performance and identify strategies to maximize its potential gains from a business partner's perspective.

Data are collected from 208 FDA partners in Indonesia. Importance–performance analysis (IPA) is applied to evaluate the FDA feature and extended the theory of potential gain in customer value (PGCV) to achieve potential gains from FDA business partners.

This study provides a clear and measurable direction for future research to develop FDA performance. Owning customer data, revenue sharing and competitive advantage are the most potential gains from joining the FDA from the business partner perspective.

The respondents are restaurants from the micro, small, and medium enterprises levels. Further research should involve middle to upper level restaurants to discover all business partners' perceptions. This will be very helpful for FDA providers interested in improving the best performance for all their partners.

FDA providers must focus on improving and maintaining the features of owning customer data, revenue sharing, competitive advantage, stable terms and conditions, customer interface, building customer loyalty, online presence, user credit rating, promotion and offers, delivery service and sales enhancement to increase consumer satisfaction and meet the expectations desired by business partners.

This research provides a meaningful theoretical foundation for future work. It extends the theory of PGCV using the value of a partner perspective as a substitute for customer value; hence, the authors call it a potential gain in partner value.

Food waste is a severe problem affecting the supply chain due to its significant adverse social and environmental effects. Even if the topic is hotly debated in the literature, there is a lack of research about the success factors influencing food waste prevention initiatives retailers undertake.

The research analyzes how several variables (i.e. product-related variables and technology-enabling variables) might impact the success of the sales of products close to the expiration date that is sold at a discounted price. Data from 390.000 products sold at a discounted price in 2020 and 2021 by a large Italian food retailer were examined with a regression analysis.

The results highlight that both product-related and technology-enabling variables influence the success of food prevention initiatives aimed at selling products close to the expiration date at a discounted price. In particular, the authors stress the importance of digital technologies in supporting food waste prevention initiatives.

The study offers several practical implications for managers in structuring a waste prevention initiative. The introduction of digital technologies, the monitoring of specific variables or the ability to find synergies with other food waste prevention initiatives are discussed to support retailers in reducing food losses.

The paper is focused on the retailer perspective, which is barely investigated due to the difficulty in finding data.

As Chinese Generation Z consumers have distrust over traditional advertising and marketing, this study focuses on user-generated content (UGC) travel apps to demonstrate the structural relationship among the expertise of amateur information publisher, interactive atmosphere, information quality, expectation confirmation, perceived trust, experiential satisfaction and switching intention.

This study carried out a questionnaire-based survey among Chinese Generation Z consumers and obtained 356 valid questionnaire copies that were analyzed with the structural equation.

The expertise of amateur information publisher and the interactive atmosphere of UGC travel apps have positive effects on perceived trust; expectation confirmation and perceived trust have positive effects on experiential satisfaction, and experiential satisfaction has negative effects on switching intention.

The results should encourage UGC travel app developers to use visual effects so as to achieve a higher quality of information, foster a cordial interactive atmosphere and enhance the expertise of information publishers by selecting the best candidate, thus spurring the design of marketing activities popular among the Chinese Generation Z consumers.

This study argues that new-generation consumers have their specific appeals and in the tourist market. It explores the UGC travel apps, which are popular among Generation Z consumers in order to deepen marketing personnel's understanding of the relationship among the expertise of amateur information publisher, interactive atmosphere, information quality, expectation confirmation, perceived trust, experiential satisfaction and switching intention.

The purpose of this paper is to understand the factors that enable and inhibit WhatsApp users' discontinuance intention (DI) following the change in WhatsApp's privacy policy.

Using the enabler-inhibitor model as a framework, a research model consisting of discontinuation enabler distrust (DT) and the DT's antecedents [(negative electronic word of mouth (NEWOM), negative offline word of mouth (NOWOM) and privacy invasion (PI)], discontinuation inhibitor inertia (INR) and INR's antecedents (affective commitment, switching cost and use habit) and moderator structural assurance was proposed and tested with data from 624 WhatsApp users using partial least square structure equational modeling (PLS-SEM).

The results show that DT created due to NEWOM and a sense of PI significantly impact DI. However, INR has no significant impact on DI. Structural assurance significantly moderates the relationship between DT and DI.

The paper collected data when many WhatsApp users switched to other platforms due to the change in WhatsApp's terms of service. The timing of data collection allowed for collecting the real impact of the sense of PI compared to other studies where the effect is hypothetically induced. Further, the authors acknowledge social media providers' efforts to address privacy criticism and regain users’ trust, an area that has received little attention in prior literature.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The authors investigate the varying impact of three categories of conflicting consumer reviews (i.e. conflicting opinions on attributes of a product item, conflicting ratings of an item and the intensity of conflicting reviews of an item) on the potential customers' perceived informativeness, which is expected to affect the perceived correct purchase.

To test their proposed hypotheses, the authors conducted an experiment using a 2 × 2 × 2 factorial design for each conflict type comprising two levels (low vs high).

The results of this study found that conflicting opinions on product attributes can enhance potential customers' perceptions of informativeness and subsequent correct purchase decisions while conflicting ratings and the intensity of conflicting reviews can diminish potential customers' perceptions of informativeness. In addition, conflicting ratings negatively moderate the effect of conflicting attributes on perceived informativeness such that the positive effect of conflicting attributes on perceived informativeness will be less prominent when conflicting ratings are present (vs absent).

While potential customers are browsing product descriptions, reviews and comments from other purchasers are also playing a role in influencing a potential customer's purchase decision. However, given the different experiences and temperaments of individuals, the subjective remarks and ratings of individuals are sometimes inconsistent or even conflicting, which can lead to confusion among potential customers. The authors categorize the positive or negative effects of the three conflicting reviews based on the two dimensions of ease of capture and product diagnosticity. The findings can help platforms optimize the display of product reviews to help potential customers make more accurate purchase decisions.

Given the importance of the growing segmentation of ageing consumers and their increasing interaction with the Internet, digital marketing scholars are becoming more interested in this market. Prior research needs to pay more attention to this market in many contexts of digital marketing. This study aims to provide insights into ageing consumers’ content usage, content typology choices, and online brand advocacy (OBA).

Semi-structured interviews were applied, and 16 consumers from Southern Europe aged 55+ were included. The interviews were transcribed and examined following the principles of content analysis.

According to the research, older consumers display their usage and concerns regarding online content. They have different decision-making processes depending on whether they are purchasing products or services. Likewise, their choices of content typology vary based on the utilitarian or hedonic product category.

This study contributes to the literature by providing insights into this growing segmentation and proposing an OBA framework for older consumers related to content marketing. Finally, the study suggests that older consumers are passive online and active offline brand advocates.

This study explores the mediating role of marketing management in the relationship between online presence and product innovation among Small and Medium Enterprises (SMEs).

The sample comprises 205 Costa Rican SMEs collected by the Global Competitiveness Project during the first half of 2019. The data were analyzed using a two-stage modeling strategy for ordinary regression models to analyze mediation effects.

Marketing management as a strategic resource or capability accounts for the relationship between online presence and product innovation performance in SMEs, meaning that online presence resources require complementary organizational capabilities in marketing management to enhance product innovation.

This study, grounded in the resource-based view theory, contributes to the innovation field by identifying marketing management capabilities as an intermediate strategic interaction between online presence and product innovation performance in SMEs. Thus, managers should recognize the advantages of integrating marketing management principles and tactics into online presence tools to realize the value of their products by tailoring them to their client’s needs.