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In response to the growing significance of diversity advertising, this study aims to investigate its impact on audience connectedness. This is an emerging metric crucial for gauging diversity advertising success. The study explores two paths via self-identification and belief congruence to understand how diversity advertisements resonate with individuals.

A quantitative study using partial least squares with survey data from 505 respondents was conducted.

Self-identification and belief congruence mediate the relationship between perceived diversity and audience connectedness. Belief congruence exhibits a stronger influence. Further, brand engagement reduces the relationship between belief congruence and connectedness. However, it strengthens the relationship between self-identity and connectedness.

Future research should address why belief congruence holds more significance than self-identification. Additionally, research must explore the societal effects of diversity advertising, including strategies to engage those who feel disconnected.

The study underscores the positive social effects of diversity advertising for both marginalized and nonmarginalized audiences. It urges marketers to pursue audience connectedness. Strategies for achieving this include reflecting their target audience’s beliefs, perhaps highlighting real and lived experiences. Marketers should also consider self-identification through visual cues and customized messaging.

The study applies self-referencing theory to unravel the relationship between diversity advertising and audience connectedness. It reinforces the role of self-identification and expands the knowledge by demonstrating how connectedness can emerge through belief congruence. Additionally, the authors explore the subtle influence of brand engagement, a critical brand-related factor that shapes individuals’ responses to diversity advertising.

Conceptual and empirical research over the past 20 years has moved the social media (SM) literature beyond the embryotic stage to a well-developed academic discipline. As the lead article in the special issue in the Journal of Research in Interactive Marketing on Cutting-Edge Research in Social Media and Interactive Marketing, this review and agenda article has two key goals: (1) to review key SM and interactive marketing research over the past three years and (2) to identify the next wave of high priority challenges and research opportunities.

Given the “cutting-edge” research focus of the special issue, this review and research agenda paper focused on articles published in 25 key marketing journals between January 2021 and March 2024. Initially, the search request was for articles with “social media, social selling, social commerce” located in the article title, author-selected key words and journal-selected keywords. Later, we conducted searches based on terminology from articles presented in the final review. In total, over 1,000 articles were reviewed across the 25 journals, plus additional ones that were cited in those journals that were not on the initial list.

Our review uncovered eight key content areas: (1) data sources, methodology and scale development; (2) emergent SM technologies; (3) artificial intelligence; (4) virtual reality; (5) sales and sales management; (6) consumer welfare; (7) influencer marketing; and (8) social commerce. Table I provides a summer of key articles and research findings for each of the content areas.

As a literature review and research agenda article, this paper is one of the most extensive to date on SM marketing, and particularly with regard to emergent research over the past three years. Recommendations for future research are integrated through the paper and summarized in Figure 2.

Consumer welfare is one of the eight emergent content areas uncovered in the literature review. Specific focus is on SM privacy, misinformation, mental health and misbehavior.

The surge of artificial intelligence (AI) applications and subsequent adoption by consumers and marketers has ignited substantial research exploring the benefits and opportunities of AI. Despite this, little attention has been given to its unintended negative consequences. In this paper, the authors examine both the practitioner and academic sides of ethical AI. In doing so, the authors conduct an extensive review of the AI literature to identify potential issues pertaining to three areas: individual consumers, societal and legal. The authors identify gaps and offer questions to drive future research.

The authors review recent academic literature on AI in marketing journals, and top ethical principles from three top technology developers (Google, IBM and Meta) in conjunction with media reports of negative AI incents. They also identify gaps and opportunities for future research based on this review.

The bibliographic review reveals a small number of academic papers in marketing that focus on ethical considerations for AI adoption. The authors highlight concerns for academic researchers, marketing practitioners and AI developers across three main areas and highlight important issues relating to interactive marketing.

This paper highlights the under-researched negative outcomes of AI adoption. Through an extensive literature review, coupled with current responsible AI principles adopted by major technology companies, this research provides a framework for examining the dark side of AI.

Consumers by and large today look for economic growth and benefits without compromising on socio-environmental well-being. Having said that, it is imperative to note that consumers' consciousness may not essentially lead to sustainable purchases. This chapter aims to examine the role of both sustainable purchase intention and post-purchase dissonance in the relationship between consumers' sustainability consciousness and consumers' evangelism. With the increased role of social media pervading our lives, trusted sources' recommendations play a significant role in co-creating products. Thus, research on consumers' evangelism (especially sustainability-conscious consumers) would help marketers develop successful strategies. This study expands to the extant literature on sustainability-conscious consumers vis-a-vis consumer evangelism. We collected responses from 227 respondents to examine hypotheses, by means of structural equation modelling (SEM). The study indicates sustainable purchase intention does mediate the relationship between sustainability-conscious consumers and consumer evangelism. On the other hand, we also note that post-purchase dissonance is not a significant moderating construct between sustainability-conscious consumers and consumer evangelism.

Art-infusion has become a common practice among brands across the globe. This is because marketers leverage the uniqueness and prestige of arts to earn superior profits. Hence, this research aims to understand and measure consumers' willingness to pay (WTP) for art-infused products.

A questionnaire was designed based on conjoint analysis and was responded to by 470 respondents from India. The estimation of preference functions in conjoint analysis was intended to use orthogonal arrays to measure WTP.

The study reveals consumers' utility and WTP for different art-infused products. The results indicated that consumers have the highest WTP for products that have artwork dominated by the visual elements of colour, shapes and space.

The paper presents valuable findings for marketers to develop their product design and earn superior profits.

This is the first study in the domain of the art infusion phenomenon that measures WTP for non-luxury art-infused products. Also, this is the first study to measure WTP for different kinds of art forms.

As internet banking service marketing platforms continue to advance, customers exhibit distinct behaviors. Given the extensive array of options and minimal barriers to switching to competitors, the concept of customer churn behavior has emerged as a subject of considerable debate. This study aims to delineate the scope of feature optimization methods for elucidating customer churn behavior within the context of internet banking service marketing. To achieve this goal, the author aims to predict the attrition and migration of customers who use internet banking services using tree-based classifiers.

The author used various feature optimization methods in tree-based classifiers to predict customer churn behavior using transaction data from customers who use internet banking services. First, the authors conducted feature reduction to eliminate ineffective features and project the data set onto a lower-dimensional space. Next, the author used Recursive Feature Elimination with Cross-Validation (RFECV) to extract the most practical features. Then, the author applied feature importance to assign a score to each input feature. Following this, the author selected C5.0 Decision Tree, Random Forest, XGBoost, AdaBoost, CatBoost and LightGBM as the six tree-based classifier structures.

This study acclaimed that transaction data is a reliable resource for elucidating customer churn behavior within the context of internet banking service marketing. Experimental findings highlight the operational benefits and enhanced customer retention afforded by implementing feature optimization and leveraging a variety of tree-based classifiers. The results indicate the significance of feature reduction, feature selection and feature importance as the three feature optimization methods in comprehending customer churn prediction. This study demonstrated that feature optimization can improve this prediction by increasing the accuracy and precision of tree-based classifiers and decreasing their error rates.

This research aims to enhance the understanding of customer behavior on internet banking service platforms by predicting churn intentions. This study demonstrates how feature optimization methods influence customer churn prediction performance. This approach included feature reduction, feature selection and assessing feature importance to optimize transaction data analysis. Additionally, the author performed feature optimization within tree-based classifiers to improve performance. The novelty of this approach lies in combining feature optimization methods with tree-based classifiers to effectively capture and articulate customer churn experience in internet banking service marketing.

Despite the promising development and marketing potential of the metaverse, our understanding of how realistic metaverse environments impact user engagement and behaviours remains limited. This study investigates the role of perceived realism in influencing user engagement, thereby affecting external search behaviour and visit intentions.

We surveyed 270 active metaverse users to test the research model. The data were analysed using partial least squares structural equation modelling (PLS-SEM).

The results of our study show that three dimensions of realism – avatar involvement, perceptual pervasiveness and social realism – significantly enhance user engagement, which in turn influences external search behaviour and visit intention. In contrast, simulation realism and freedom of choice have minimal effects on absorption and dedication.

This study highlights the role of perceived realism in enhancing user engagement with the metaverse and its impact on physical world behaviours. It contributes to metaverse literature by demonstrating that engagement within the metaverse significantly influences physical world behaviours, including visit intentions and external search behaviours.

This study offers practical guidance for developers to enhance user engagement in metaverse environments. Specifically, our findings advocate for visual and audio quality enhancements, greater persuasiveness of virtual spaces, improved avatar representativeness and a closer alignment of metaverse activities with real-life events.

This study advances the theoretical understanding of perceived realism by examining how its dimensions – such as visual and audio quality, avatar representativeness and alignment with real-life events – impact user engagement in the metaverse. It also explores how this engagement influences offline behaviours, thus bridging the gap between virtual and real-world interactions.

This study investigates the impact of social media marketing activities on customer purchase intention in the Malaysian property market.

The study utilises a survey research approach to collect data from 331 respondents using a questionnaire.

The findings of the study reveal that entertainment, interaction, customisation and word-of-mouth variables had a significant and positive impact on customer purchase intention in the Malaysian property market. However, the study demonstrates a positive but insignificant impact of trendiness on customer purchase intention.

First, the study relies on a sample of 331 respondents in Malaysia, which may limit the generalizability of the findings to a broader population. Hence, future research could aim for a more extensive and diverse sample to enhance the validity of the results. Second, while the study identified significant relationships, the measurement of variables, in particular “trendiness,” could be refined for better accuracy. The future study may consider including a more precise measurement to provide comprehensive insights.

The results suggest that marketers should focus on creating engaging and interactive content, providing personalised experiences and leveraging word-of-mouth recommendations to enhance customer purchase intention. The overall findings highlight the importance of social media marketing activities in the property market and their potential to drive customer purchase intention.

The study contributes to the existing literature by shedding light on the role of social media marketing activities in influencing customer purchase intention in the Malaysian property market.

To the best of the authors’ knowledge, there is no similar studies have been conducted in this area of research.

This paper aims to explore the causal relationship of user-generated content (UGC) on trust in UGC (TUGC), destination image (DI) and tourist visit intention (VI) guided by the stimulus-organism-response (SOR) theory. This work further examined the mediating effect of TUGC and DI between UGC and VI.

Data were collected through online and personal-administered surveys and randomized sampling. This work employed partial least squares structural equation modeling (PLS-SEM) to test the proposed model empirically.

In line with the SOR Theory, this work found UGCs that induce positive emotions and connection to the users motivate VI rather than UGCs that are predominantly factual. Furthermore, UGCs are considered reliable, authentic and less biased than brand-generated content. The findings of this work contribute to the theoretical understanding of UGC to VI in a destination.

This work proposes that destination marketers prioritize UGC that evokes positive emotions and connections with users, as it is more effective in encouraging VI. Strategies such as incentivizing content creators, improving online presence and engaging influencers can maximize UGC. Enhancing online traffic quality, visibility and interaction and implementing content policies are crucial for UGC's effectiveness. Marketers should align destination products with tourists' interests and collaborate with influencers for affiliate marketing to increase tourist-generated UGC. Furthermore, improved connectivity encourages UGCs about the destination.

In tourism marketing, UGC has become a valuable information source for tourists in making informed travel decisions. UGC is a tourist-generated content that offers factual information and authentic experiences through images, videos or text posted through social media platforms. UGC is considered more reputable than travel firms and the mainstream media as an information source. Due to the limited works on UGC in the literature, the influence of UGC on tourists' VIs has remained unexplored at the time of writing. This work bridges this gap by empirically examining the impact of UGC on Gen Z tourists' VI guided by the SOR theory.

This study draws on social influence and social comparison theories to investigate the effect of social media influencers on intention to visit with the mediating role of upward social comparison. It studies the reasons underlying people's intention to visit a destination from an emotional perspective.

PLS-SEM models were applied to a total of 527 responses.

This study provides empirical evidence supporting the Source Credibility Model's elements within the context of influencer marketing and travel intentions. Furthermore, it expands the current knowledge of upward social comparison emotions by reporting that upward contrastive emotions would partially mediate the relationship between expertise and intention to visit, and that upward assimilative emotions would fully mediate the relationship between attractiveness and intention to visit while partially mediating the relationship between trustworthiness and expertise and intention to visit.

The article adds new insights to tourism marketing as well as helps both destination marketers and travel influencers. For marketers, it is advised to collaborate with credible influencers known for expertise and trustworthiness, leveraging their perspectives to rebuild travel confidence and reassure tourists about safety measures. Travel influencers are recommended to convey their intrinsic passion and enthusiasm through their posts to create an inspiring connection with the audiences.

This paper is the first to address the relationship between travel influencers and intention to visit with the mediation role of both positive and negative emotions.