Genuine, fake, or does it matter? exploring engagement behavior driven by self-presentation

Introduction to the Special Issue: Brand Relationships, Emotions, and the Self

The customer engagement behavior is an important concept for the company along with the increasing use of social media by consumers. Previous studies examined customer engagement behavior on social media by the role of technology factors or features on the brand page. Nevertheless, the role of individual consumer traits and the consumer-brand relationships on customer engagement in brands on social media are still limited. This paper aims to explore customer engagement behaviours to brands in social media. This explores the extent to which personality traits are related to consumer-brand relationship and customer engagement behaviours in social media. The findings are presented from a survey of Instagram users who engage with fashion brand pages. The data collecting was done by online survey from 209 respondents, age between 18 and 34 years. The results support four of the seven hypotheses with significant relationship between the constructs analysed. Customers with openness and extraversion tend to love brands. Openness performs engagement behavior to brands in Instagram but extraversion does not. On the other hand, individuals who have neuroticism tend not to love brands and not perform engagement behavior. Eventually, brand love is a strong customer motivation to perform customer engagement. This study contributes to existing literature by examining consumer behavior on social media in the presence of emotional motivation. This paper extends literature by studying combined effect of emotional motivation resulting from the presence of personality traits in individual customer behavior

The swift advancement in social networking platforms has radically shifted the patterns and nature of how people connect with services and brands in America. The utmost objective of this research project was to implement artificial intelligence together with machine learning approaches for creating predictive models that forecast digital pattern development as well as user commitment through social media interactions within the United States. The data used in this analysis are posts aggregated from two leading online platforms, X-Twitter and Reddit, and consist of user-generated material covering a multifaceted set of topics and opinions. X-Twitter posts are current and real-time and give insight into what is currently being discussed and the opinions that are making headlines, whereas Reddit content provides extensive commentary and user engagement on numerous subreddits. To make the dataset more comprehensive and richer in information, extensive engagement metrics like likes, shares, and comments are used to extend its reach and provide insight into the extent to which users engage with the material presented to them. For this research, we used the multi-model approach so that there would be an exhaustive study and strong predictions, by implementing models such as Logistic Regression, Random Forest, and XGB-Classifier. To assess the models properly, we made use of several performance metrics like Accuracy, Precision, Recall, and F1-score. Logistic Regression only manages to achieve a below-average accuracy, signaling an average level of predictive quality. The Random Forest model fares slightly better with a slightly better accuracy rate, which implies that its ensemble method increases its predictive power to classify instances more effectively. In turn, the XG Boost model took the top spot in the comparison with an accuracy rate, projecting its ability to identify complex patterns in the data and showcasing the highest predictive level among the three models. The use of model outputs can greatly maximize real-time content strategy for brands and organizations seeking to maximize engagement in the USA. Based on user behavior patterns and engagement metrics, models can give insight into what should be posted and when to maximize attention. In campaign optimization, predictive modeling assists U.S. brands in making strategic decisions regarding ad spend allocation. Based on an examination of past performance and engagement metrics, brands can see which content is driving the greatest impact and engagement levels and make strategic investments in high-performance content that genuinely resonates with desired audiences. For public communication and policy, predictive models are particularly helpful in projecting how the U.S. public will react to news announcements, policy initiatives, or campaigns. Boosting the effectiveness of predictive models by incorporating transformer-based NLP models like BERT is one direction to explore in the future.

Reply to “Dermatologists in social media: A study on top influencers, posts, and user engagement”: Dermatologist influencers on TikTok

Since observing customers outnumber focal customers in most service interactions, service managers aim to engage them despite triggers, such as service incivility. This research contributes to the understanding of the role of stress in observing customers' engagement (CE). It answers two RQs: (1) What is the relationship between their stress and engagement?; (2) What are the triggers of stress? Since ethnically different people pay different levels of attention to contextual and social factors, two sequential scenario‐based experiments are adopted to study two triggers of stress (i.e., availability of information about an incivility incident, and ethnic similarity between the observing customer and the mistreated employee), which impacts CE in an intercultural service encounter. Study 1 compares being exposed to full versus partial information and demonstrates that full information about the incivility incident increases observers' psychological stress, which reduces their behavioral and emotional engagement. Study 2 compares how white and black observers react to ethnic similarity between the observing customer and the mistreated employee. Results show that incivility triggers outward psychological stress in white and black observers. In turn, black observers' outward stress reduces their behavioral engagement, while white observers' behavioral engagement is reduced by both their inward and outward stress.

This study aims to investigate the impact of social media promotion on customer engagement within the context of Northern Indian chain hotels. In an era characterized by the increasing digitalization of businesses and the hospitality industry, social media platforms have emerged as powerful tools for hotels to connect with their clientele and enhance customer engagement. The research employs a comparative analysis to assess the effectiveness of social media promotion strategies in various Northern Indian chain hotels and their influence on customer engagement metrics. The research methodology includes a comprehensive review of the social media practices employed by select chain hotels in Northern India, with a focus on their content strategy, frequency of posts, platform selection, and interaction with customers. Additionally, customer engagement metrics such as likes, comments, shares, and user-generated content are analyzed to evaluate the impact of social media promotion on enhancing the hotel-guest relationship. The findings of this study provide valuable insights into the role of social media in shaping customer engagement in the hospitality industry, specifically within the unique context of Northern Indian chain hotels. By comparing and contrasting the social media strategies and outcomes of different hotels, this research aims to identify best practices that can be applied to optimize customer engagement through social media promotion.

Purpose Organizations are investing heavily in social media yet have little understanding of the effects of social media content on user engagement. This study aims to determine the distinct effects of informational, entertaining, remunerative and relational content on the passive and active engagement behavior of social media users. Design/methodology/approach Facebook Insights and NCapture are used to extract data from the Facebook pages of 12 wine brands over a 12-month period. A multivariate linear regression analysis investigates the effects of content on consuming, contributing and creating engagement behavior. Findings Results reveal distinct effects of rational and emotional appeals on social media engagement behavior. Rational appeals in social media have a superior effect in terms of facilitating active and passive engagement among social media users, whereas emotional appeals facilitate passive rather than highly active engagement behavior, despite the social and interactive nature of the digital media landscape. Research limitations/implications Results contribute directly to understanding engagement and customer experience with social media. Further theoretical and empirical examination in this area will aid in understanding the dynamic nature of the levels of engagement within social media. Practical implications Findings provide managers and practitioners with guidelines and opportunities for strategic development of social media content to enhance engagement among consumers in a social media forum. Originality/value This study is one of the first to empirically examine the construct of social media engagement behavior. It extends the utility of dual processing theory to demonstrate how rational and emotional message appeals result in online engagement.

This study examines the impact of social media engagement: What motivates user participation and consumption on YouTube in Nepal. User engagement metrics are the dependent variable. Likewise, the selected independent variables are content type, video length, frequency of uploads, interaction with viewers, and visual appeal. The primary source of data is used to assess the opinions of the respondents regarding these variables in the context of YouTube in Nepal. The study is based on primary data with 17 respondents. To achieve the purpose of the study, a structured questionnaire is prepared. Descriptive statistics, Kendall’s Tau correlations, and regression models are estimated to test the significance and importance of these factors on user engagement metrics on YouTube in Nepal. The study showed that content type has a positive impact on user engagement metrics on YouTube. It implies that varied and interesting content leads to increased user engagement. The result also showed that video length has a positive impact on user engagement metrics. It implies that optimal video length leads to increased user engagement. Moreover, frequency of uploads has a positive impact on user engagement metrics. It implies that regular uploads lead to increased user engagement. Furthermore, interaction with viewers has a positive impact on user engagement metrics, indicating that active interaction leads to increased user engagement. Similarly, the result also showed that visual appeal has a positive impact on user engagement metrics. It indicates that visually appealing videos lead to increased user engagement. The result also showed that improved visual appeal leads to increased user engagement on YouTube.

The information cocoon phenomenon, prevalent in social media, profoundly influences user experience, yet its impact on customer engagement remains debated. This study constructs a model based on 662,000 comments on 1128 short video advertisements to extract the information cocoon effect (ICE), and customers' emotional, cognitive, and behavioral engagement through data mining methods and large language models, aiming to investigate the influence of the ICE on customer engagement. Results reveal that the ICE positively affects customers' emotional and cognitive engagement but negatively affects their behavioral engagement, and the product category, influencer type, and release time play moderating roles to varying degrees on these impacts. Drawing upon variable extraction techniques, our study broadens the quantitative methodologies and the range of applications for the information cocoon concept, underscores its varied influences on customer engagement, enhances the theoretical comprehension of customer engagement, and concurrently offers practical recommendations for marketing professionals.

PurposeFirms increasingly rely on content marketing to trigger user engagement in social media brand communities. The purpose of this paper is to examine how three generic types of marketer-generated content (affiliative, injunctive and utilitarian content) drive user engagement by considering distinct motivational paths and the role of users’ preference for intimate (vs broad) social networks.Design/methodology/approachThe authors conduct a field survey and a scenario experiment among social media users across different brands from three different product categories. They examine the impact of marketer-generated content on user engagement while considering the moderating role of network intimacy (i.e. the mutual confiding within a user’s social network in terms of small social circles) and the mediating role of user motivations (i.e. autonomous vs controlled motivation for community membership).FindingsThe findings show that affiliative content (i.e. content that highlights shared values) drives user engagement through autonomous motivation, and utilitarian content (i.e. content that highlights tangible benefits) drives user engagement through controlled motivation. Notably, injunctive content (i.e. content that demands specific user behavior) is not a promising instrument to increase user engagement in social media brand communities when not targeted correctly.Research limitations/implicationsThe authors link three generic content types derived from literature on communal systems to user engagement, demonstrate the motivational underpinnings of their translation into engagement behavior and show that network intimacy can explain why the same content type can impact user engagement through two motivational paths.Practical implicationsThe authors present three types of content that marketers can craft to trigger users to engage with a brand’s social media community and show when this content is most effective and why. By examining the moderating role of network intimacy, this research aims at providing targeting implications to social media marketers.Originality/valueThis research provides new insights on the effectiveness of marketer-generated content. The authors reveal two motivational paths that compete in explaining the overall effectiveness of different types of marketer-generated content to fuel user engagement. The authors further demonstrate that these relationships depend on the intimacy of a user’s circle of online friends.

PurposeCustomer engagement is a concept that has emerged recently to capture customers' total set of behavioral activities toward a firm. The purpose of this paper is to study the effect of customer engagement behaviors on perceived relationship benefits and relationship outcomes.Design/methodology/approachAn online survey of members of a gaming Facebook brand community, resulting in 276 usable responses from gaming customers.FindingsCustomer engagement was divided into “Community Engagement Behaviors” (CEB) and “Transactional Engagement Behaviors” (TEB). In addition, three relationship benefits were identified: social benefits, entertainment benefits and economic benefits. The engagement behaviors largely influenced the benefits received. Furthermore, the mediation analysis results show that the influence of CEB on satisfaction is partially mediated by social benefits and entertainment benefits, while the effect of TEB on satisfaction is fully mediated through the same benefits. The effect of CEB on loyalty is mediated through entertainment benefits.Research limitations/implicationsThe findings are limited to one brand community. The findings have implications for further research on customer engagement.Practical implicationsThe paper's findings give ideas about how firms can utilize Facebook communities to enhance satisfaction and loyalty by offering the right kinds of relationship benefits. Managers are encouraged to study customer engagement behaviors on, and perceptions of, all channels and to utilize this information for the development of their social media strategies.Originality/valueCustomer engagement is a newly introduced concept on which scarce empirical research exists, and there is very little evidence of its effect on customer relationships. This is the first paper to study customer engagement empirically on a Facebook brand community, and to relate customer engagement to relationship constructs.

In the present time of web-based social networking, visual communication assume a key job in business and public communication. Social networking with its astute features has the ability to pull in numerous to interface with others. Visual communication plays key role in engagement behavior on social media further adding to sales. The high quality visual improves visibility in Social Networking Sites and are being selected as organization’s key activity. Thus, the present study proposes a theoretical model of how visual communications through consumer engagement on corporate Social Networking Sites pages influences the consumer-brand relationship. Structural Equation Modelling has been used and validated the effect of visuals with informative, entertaining and remunerative content on consumer engagement further leading to consumer-brand relationship. Uses and Gratifications Theory has been adopted to study the behavioral response of the customers in relation to consumer engagement in social media context. This is a pioneering work to measure the mediation effect of consumer engagement to check the dominance of mediation (consumer engagement) over direct relationship between independent (visual contents) and dependent variable (consumer-brand relationship) on Facebook. In future similar study may be conducted in other social media platforms.

Social media have impacted numerous aspects of consumers’ social life, including consumer behavior and the consumer—brand relationship. Consumer behavior is evolving though social platforms and is shaping the perceptions and the actions of customers towards brands. As a result, more and more brands are seeking visibility through social networks, establishing an online presence, trying to trigger interaction and engagement with consumers. This paper explores consumer motivation to interact and engage with small travel brands on social media and highlights elements of the brands that make them more appealing to consumers. The paper also identified consumer attributes that make them more willing to engage with small travel brands on social media. The findings of this paper help map the factors that play a key role on the intention of a consumer to follow and engage with a small brand, while there are clear strategies indicated on how a small brand can meet the consumers’ expectations and leverage on potential cross sell opportunities. The research outputs indicate that there are distinct follower groups in terms of interaction with travel brands with unique characteristics that can be leveraged for a more effective brand positioning. In addition, there are remarkable findings on the repetitive nature of buying behavior for people following small travel brands and the potential cross sell opportunities that arise. The findings of this paper may be considered as a roadmap for small brands to improve customer engagement and consumer buying behavior.

Firms regularly call on multiple social media communication tactics (e.g. influencers, user-generated content and brand messages) to interact with their customers. Drawing on both parasocial relationship and social identity theories, we investigate the relative effectiveness of brand-directed versus influencer-directed social media marketing in stimulating both customer engagement and purchase behaviour. First, we use a survey research design to collect data on customers’ intention to engage with the brand and purchase when exposed to brand-directed and influencer-directed social media marketing. Second, we collect data from a field experiment on a social media platform that captures customer engagement and brand sales at aggregate levels attributed to brand-directed and influencer-directed social media marketing. Consistently across both studies, we find that brand-directed and influencer-directed social media marketing positively impact customer engagement and customer purchase behaviour. Further evidenced across both studies, we find brand-directed social media marketing is more effective than influencer-directed social media marketing in fostering customer engagement, whereas influencer-directed social media marketing is more effective in driving customer purchases. We also find that female customers are more impacted by influencer-directed social media marketing on both dimensions than brand-directed social media marketing. The study provides a strategic direction for brands to optimally allocate their limited digital marketing budget between brand-directed and influencer-directed social media marketing based on their marketing objectives central to customer behaviour – either enhancing longer-term customer relationship building via engagement or generating shorter-term sales.

Role of artificial intelligence in customer engagement: a systematic review and future research directions