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Social commerce (s-commerce) offers community-based platforms that facilitate customer-to-customer interactions and the development of customers' social shopping-based experience. While prior research has addressed the role of customer engagement (CE) in boosting s-commerce-based sales and performance, insight into the effect of s-commerce attributes on CE remains tenuous. Addressing this gap, this study examines the role of specific s-commerce attributes (i.e. community, collaboration, interactivity and social dynamics) on CE, which is, in turn, proposed to impact customers' repurchase- and electronic word of mouth (eWOM) intention.

A web-based survey was deployed to target users of a popular s-commerce platform, Etsy.com. Partial least squares structural equation modeling (PLS-SEM) was, then, used to analyze the survey data collected from 390 users.

The results reveal that the four examined attributes positively affect CE. The findings also demonstrate CE's positive effect on customers' repurchase- and eWOM intention.

Though CE has been identified as a key s-commerce performance indicator, little remains known about the role of specific s-commerce attributes in driving CE, as, therefore, explored in this research. Specifically, the authors examine the role of s-commerce-based community, collaboration, interactivity and social dynamics on CE. Their analyses also corroborate that CE, in turn, drives customers' post-purchase (i.e. repurchase/eWOM) intention. Managerially, our findings can be used to develop more engaging s-commerce platforms.

In online purchase for dietary supplements, due to the lack of professional advice from pharmacists, electronic word-of-mouth (eWOM) has become an important source of information for consumers to make purchase decisions. How can firms use eWOM resources to increase sales? The purpose of this paper is to provide practical methods for firms by exploring the effects of eWOM on sales and developing a sales prediction model based on eWOM.

The data came from 120 dietary supplements on Tmall.com. The authors extracted the product sales as dependent variable and 11 eWOM factors as independent variables. The multicollinearity was tested by using variance inflation factor and least absolute shrinkage and selection operator. The multiple linear regression was used to investigate the effects of eWOM on sales. Drawing on white- and black-box approaches, six models were developed. Comparing the root mean square error, the authors selected the optimal one as their target sales prediction model.

Product ratings, total reviews and favorites are positively and strongly associated with sales. Questions and additional reviews have negative effects on sales. The random forest model has the best prediction performance.

The research focuses on eWOM of dietary supplement. First, the authors show that easily accessible eWOM from online platforms can be used to evaluate effects and predict sales. Second, the authors introduce white- and black-box models through machine learning to assess eWOM. Firms could use the described models to foster their marketing initiatives.

The research goal is to summarize the insights from an investigation of the higher education institutes (HEIs) and university's educational services promotion strategy, which incorporates social media as a medium for keeping in touch with important people throughout time. The study centered on the impact of promotional efforts done by higher education Institutes (HEIs) on social media on students’ decisions for their selection of HEIs and universities as well as the study focus factors that influence the students' decisions. In the third quarter of 2022, based on a carefully chosen sample, researchers used an internet questionnaire to conduct an empirical study. The assessment of the outcomes focused on identifying the significant aspects and their significance in the marketing endeavours conducted on social media platforms, which serve as predictors of student decision-making. Three important predictors Social Media Engagement, Content Contribution, and Stakeholders Review were identified and their significant impact on social media marketing by HEI are hypothesized and tested. All the study variables confirm the existence of a significant relationship with the dependent variable. The study concluded that these factors were identified as significant influences on the choice of study and higher education institution. Gaining new followers, prominence content display and stakeholders' feedback builds long-lasting linkages with the immediate environment. As a foundation for creating successful social media marketing strategies for higher education institutions, this research is useful for marketers since it elucidates the dynamics of the market and the habits of potential pupils.

This paper aims to analyse the determinants of the intention to share a post about an environmental issue posted by a tourism destination on Facebook. The authors use the stimulus-organism-response (SOR) model as a theoretical framework and consider cognitive variables (destination social responsibility, tourist social responsibility and three types of congruence) as antecedents of emotions and of the tourists’ response (intention to share). Specific factors related to the social platform (attachment and active use of social media) are also included.

The model was tested for two destinations with different positioning (green tourism versus sun and beach). For the sampling strategy, the authors conducted an online poll targeting Facebook users who had undertaken at least one trip in the previous year. The sample consisted of 1,001 individuals.

The empirical evidence obtained indicates that consumer–cause congruence is the most important variable for explaining the intention to share the post for both destinations, with the destination–cause congruence being non-significant. The authors also observed that active participation on the social network stimulated the intention to share this specific content.

Unlike prior research, this paper examined consumer motivators for engaging with online corporate social responsibility content for tourism destinations, specifically focusing on destination social responsibility in sustainable tourism. The model also incorporates three types of congruence, revealing variations in their impact on explaining the intention to share sustainability-related posts.

Emojis are quickly becoming a popular new language in social media and marketing. The capability to express emotions and make message understanding easier is one of the primary reasons for using emojis. The aim of this research was to determine the influence of perceived usefulness, perceived ease of use, trust, and involvement on customer engagement due to emojis used in digital marketing communications among Generation Z (Gen Z) in South Africa.

Following the descriptive research approach, quantitative research was used in this study. A questionnaire (self-administered) was utilized to test the effectiveness of using emojis among 1,000 young consumers. Structural equation modeling was used to test the hypotheses.

The findings of the study yielded positive relationships between the variables, namely between trust and involvement; involvement and the perceived ease of use; involvement and perceived usefulness; perceived ease of use and perceived usefulness; trust and customer engagement; perceived usefulness and customer engagement; involvement and customer engagement; customer engagement and intention to purchase; trust and intention to purchase; and perceived usefulness and intention to purchase.

This study can help organizations in emerging markets use emojis in their digital marketing communications to engage customers and stimulate intention to purchase among young people, especially the Gen Z cohort, who seek organizations and brands that understand and connect with them.

By investigating the effects of emojis in digital marketing communications, this study contributes to the customer-centric process and the literature on emoji usage while also involving a credible digital language when communicating with members of Gen Z. By extending TAM, the findings of this study contribute to the TAM literature by demonstrating that emoji usage in digital marketing communications positively influences various attitudinal associations among Gen Z consumers.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

The purpose of this study is to generate a better understanding of the nature of Corporate Social Responsibility (CSR) communication on social media. In fact social media are one of the most effective communication channels in contemporary business settings. Due to their inner characteristics, they should be the ideal channel for communicating CSR topics. Over the last 15 years, a variety of researches discussed the interplay between CSR and social media, resulting in a rather tangled body of knowledge.

This study proposes a scoping review of published academic literature at the intersection of these two research bodies (i.e. CSR and social media communication) to shed light on the nature of the communication, strategic challenges and practices, as well as their key factors and impact.

To date, academic research related to the nature of CSR on social media is fragmented and blurry. This research sheds light on the challenges of interactive social media communication in CSR and presents an account of key strategies, tactics and possible impacts for these challenging communication practices.

This research generates a better understanding of the nature of CSR communication on social media, strategic challenges and practices, as well as their key factors and impact. It is the tentative of generating a synthetic account of relevant literature in the field.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

This research addresses the critical challenge of fostering customer loyalty within the highly competitive landscape of the insurance industry. The study investigates the interplay between customer satisfaction, loyalty, and the influence of technology and service quality in the context of insurance services and in periods of crisis.

A quantitative research approach was employed, utilizing a structured questionnaire distributed among diverse insurance customers in Lebanon during crisis conditions. The data were analyzed using SPSS-Amos, incorporating descriptive statistics, correlation analysis, and structural equation modeling (SEM).

This research emphasizes the crucial role of customer satisfaction in fostering loyalty in the insurance sector, especially during crises. High satisfaction levels, influenced by user-friendly online platforms, positively correlate with increased customer loyalty. Technology plays a vital role in maintaining and improving satisfaction, making it a key driver during challenging times. Positive interactions between service quality and satisfaction further highlight the multifaceted impact of technology on shaping customer loyalty.

The research findings provide valuable insights with practical implications for insurers aiming to boost customer loyalty. The study recommends strategic investments in critical areas like claims processing, customer service, communication strategies, digitalization initiatives, and employee training. The study provides insights applicable particularly to insurance companies navigating crisis conditions.

This research contributes both to academic understanding and practical applications by shedding light on the distinctive challenges and opportunities faced by insurers in cultivating customer loyalty within the insurance industry during crisis. The elucidations provided serve as a foundation for developing targeted strategies to address these challenges and to leverage opportunities for enhanced customer loyalty.