Search Results (826)

Artificial intelligence (AI) is reshaping customer service, with AI-powered chatbots serving as a critical component in delivering continuous support across sales, marketing, and service domains, thereby enhancing operational efficiency. However, consumer engagement remains suboptimal, as many users favor human interaction due to concerns regarding chatbots’ ability to address complex issues and their perceived lack of empathy, which subsequently reduces satisfaction and sustainable usage. This study examines the determinants of user attitude and identifies factors influencing sustainable chatbot use. Utilizing survey data from 735 Chinese university students who have engaged with AI-powered chatbots, the analysis reveals that four key motivational categories: utilitarian (information acquisition), hedonic (enjoyment and time passing), technology (media appeal), and social (social presence and interaction) significantly influence user attitude toward chatbot services. Conversely, privacy invasion exerts a negative impact on user attitude, suggesting that while chatbots provide certain benefits, privacy issues can significantly undermine user satisfaction. Moreover, the findings suggest that user attitude serves as a pivotal determinant in fostering both user stickiness and sustainable usage of chatbot services. This study advances prior U&G-, TAM-, and ECM-based research by applying these frameworks to AI-powered chatbots in business communication, refining the U&G model with four specific motivations, integrating perceived privacy invasion to bridge gratification theory with risk perception, and directly linking user motivations to business outcomes such as attitude and stickiness. This study underscores that optimizing chatbot functionalities to enhance user gratification while mitigating privacy risks can substantially improve user satisfaction and stickiness, offering valuable implications for businesses aiming to enhance customer loyalty through AI-powered services. Full article

In today’s service-driven economy, brands increasingly turn to social media marketing activities (SMMA) to build meaningful, long-term customer relationships. Grounded in social exchange theory (SET), this study examines how SMMA influences customer engagement (CE), relational benefits (confidence, social, and special treatment), and ultimately relationship equity—offering new insights for trust-based services, such as banking. SET provides a powerful lens to explain how perceived value in brand-initiated exchanges drives customer reciprocity. A between-subjects experimental design (n = 298) was employed using real social media ads from a bank to enhance ecological validity. Participants were randomly assigned to ad exposure or control conditions, and data were analyzed using PLS-SEM. Results show that SMMA significantly enhances CE and relational benefits. In turn, CE, along with confidence and social benefits, contributes to relationship equity. Special treatment benefits, however, had no significant effect. Ad exposure amplified the impact of SMMA on CE and relationship outcomes. Theoretically, this study advances SET by revealing how digital brand interactions translate into lasting customer bonds. Practically, the findings indicate that banks should prioritize SMMA for increased CE and relational benefits. When combined with targeted advertising efforts, this can significantly improve relationship equity. Full article

The aim of this study was to analyse the relationship between sustainability and customer lifetime value (CLV) through the mediation–moderation effect of search engine optimization (SEO) metrics of websites. We obtained a data sample of 296 European sustainable firms from both industrial and technological industries. Based on the theory of source credibility, the firm’s official website, where SEO techniques are applied, is more credible regarding its sustainability activities than other sources such as social media, paid advertising, etc. As a result, we show that sustainability is a precursor of financial performance over time in sustainable firms, represented by CLV. Furthermore, we found that the value of the moderating variable, website traffic, alters the indirect effects produced by the mediating variable called website relevance (domain authority), thereby demonstrating a moderated mediation effect. The contribution of this research to the body of literature is twofold. First, it deepens the understanding of how sustainability predicts marketing outcomes based on both digital and customer metrics over time. Second, we rely on recent literature on prediction-oriented modelling (PLS-SEM) to support that it is not suitable for estimation by reflective measurement models due to the woozle effect. Full article

As global awareness of environmental and social challenges continues to rise, companies are increasingly re-evaluating how they connect with consumers. This study investigates the role of digital marketing in promoting more sustainable consumer behaviours. Based on a systematic review of peer-reviewed literature retrieved from the Scopus database, and conducted following the PRISMA framework, this research analysed 84 academic publications. The findings highlight that strategies such as personalised messaging, social media engagement, influencer collaborations, and eco-conscious branding are significantly influencing purchasing decisions. Approaches rooted in transparency, emotional storytelling, and ethical data practices appear to enhance consumer trust and strengthen brand relationships. Although the field is technically well developed, it remains underexplored in areas such as digital accessibility and ethical governance. Overall, this study suggests that, when aligned with sustainable values, digital marketing becomes more than a promotional tool—it emerges as a key driver of responsible consumption and the cultivation of long-term, value-based connections between consumers and brands. Full article

In the rapidly evolving landscape of digital marketing and electronic commerce, short-form content—particularly on platforms like Twitter (now X)—has become pivotal for real-time branding, community engagement, and product promotion. The rise of Non-Fungible Tokens (NFTs) and Web3 ecosystems further underscores the need for domain-specific, engagement-oriented social media content. However, automating the generation of such content while balancing linguistic quality, semantic relevance, and audience engagement remains a substantial challenge. To address this, we propose RL-TweetGen, a socio-technical framework that integrates instruction-tuned large language models (LLMs) with reinforcement learning (RL) to generate concise, impactful, and engagement-optimized tweets. The framework incorporates a structured pipeline comprising domain-specific data curation, semantic classification, and intent-aware prompt engineering, and leverages Parameter-Efficient Fine-Tuning (PEFT) with LoRA for scalable model adaptation. We fine-tuned and evaluated three LLMs—LLaMA-3.1-8B, Mistral-7B Instruct, and DeepSeek 7B Chat—guided by a hybrid reward function that blends XGBoost-predicted engagement scores with expert-in-the-loop feedback. To enhance lexical diversity and contextual alignment, we implemented advanced decoding strategies, including Tailored Beam Search, Enhanced Top-p Sampling, and Contextual Temperature Scaling. A case study focused on NFT-related tweet generation demonstrated the practical effectiveness of RL-TweetGen. Experimental results showed that Mistral-7B achieved the highest lexical fluency (BLEU: 0.2285), LLaMA-3.1 exhibited superior semantic precision (BERT-F1: 0.8155), while DeepSeek 7B provided balanced performance. Overall, RL-TweetGen presents a scalable and adaptive solution for marketers, content strategists, and Web3 platforms seeking to automate and optimize social media engagement. The framework advances the role of generative AI in digital commerce by aligning content generation with platform dynamics, user preferences, and marketing goals. Full article

As environmental conservation and community development gain importance, ecotourism has emerged as a significant segment of the global tourism industry. However, the cultural factors that drive tourist behavior in this domain remain underexplored. This research examined how power distance belief (PDB), interacts with the type of tourism content shared on social media (conspicuous versus experiential) to influence travelers’ ecotourism intentions. To test our hypotheses, we conducted two experimental studies using a 2 (PDB: high vs. low) × 2 (tourism content type: conspicuous vs. experiential) between-subjects design. Participants for both experiments (N = 480) were recruited through an online survey platform. In the experiments, participants’ PDB was situationally primed, and tourism content type was manipulated using specifically created fictitious posts adapted from a real social media platform. Other key variables were measured using validated multi-item scales. Data were analyzed using analysis of variance (ANOVA) and moderated mediation analysis (PROCESS Model 15). The findings reveal that travelers with high PDB show higher ecotourism intentions when exposed to conspicuous content, whereas travelers with low PDB exhibit higher intentions when exposed to experiential content. This interactive effect is mediated by travelers’ social comparison motives. These findings offer novel insights into the motivations underlying ecotourism behavior by identifying distinct pathways through which social media can promote sustainable tourism behaviors, and provide practical guidance for eco-destination managers to design targeted marketing strategies that encourage sustainable tourism practices across different consumer segments. Full article

This study examines the intersection of artificial intelligence-driven personal branding strategies and female entrepreneurship within Indonesia’s unique hijabi startup ecosystem. Through a mixed-methods approach combining sentiment analysis of 2847 social media posts, in-depth interviews with 35 hijabi entrepreneurs, and machine learning analysis of branding patterns, this research reveals how AI technologies can be leveraged to create culturally sensitive personal branding frameworks for Muslim female entrepreneurs. The findings demonstrate that successful hijabi entrepreneurs employ distinct AI-enhanced communication strategies that balance religious identity, professional credibility, and market positioning. The study introduces the “Halal Personal Branding Framework,” a novel theoretical model that integrates Islamic values with contemporary digital marketing practices. Results indicate that AI-driven personal branding increases startup funding success rates by 34% and market reach by 58% among hijabi entrepreneurs when culturally appropriate algorithms are employed. This research contributes to entrepreneurship communication theory while providing practical guidelines for developing inclusive AI systems that respect religious and cultural diversity in the digital economy. Full article

Social media has become a tool that exerts a significant influence on consumer behavior. In this sense, this study aims to identify whether digital social influence derived from the informational nature of social media content and online member group support influences the subjective norms and environmental attitudes of organic product consumers. This study was developed using a quantitative, correlational, and cross-sectional design. A total of 371 organic product consumers participated in the study, who were administered a questionnaire consisting of 17 questions measured on a 5-point Likert scale. Statistical analysis was performed using SPSS 24 and Smart PLS, and convergent validity, discriminant validity, and structural equation modeling were applied. The results of the study identified that environmental attitudes continue to be a highly influential factor in organic product purchasing behaviors and that these attitudes are shaped by subjective norms and digital social influencers, such as social media content and online member support groups. Furthermore, the study found that subjective norms mediate the relationship between environmental attitudes and social media content as well as online member support groups. Beyond contributing to the theoretical understanding of environmental attitudes, this study offers practical insights into designing digital marketing strategies that leverage social influence to promote sustainable consumption, particularly in emerging markets. Full article

This study investigates retailers’ strategic choices between short video marketing (SVM) and live streaming marketing (LSM) in the social media era, with a focus on the synergistic effects and decision-making mechanisms of these two digital marketing models. Using game theory, we construct a game analysis model to analyze retailers’ optimal selection among three marketing strategies: S (sole implementation of SVM), L (sole implementation of LSM), and H (integration of both SVM and LSM). The findings reveal that retailers should make different strategic choices based on the different stages of development. In the early market entry phase, characterized by both a low mixed commission rate and a low slotting fee, the H strategy emerges as the optimal choice. As the market enters its growth phase, retailers should shift to the L strategy, driven by “influencer LSM”. When the market enters a mature stage, retailers should be more inclined to adopt the S strategy or the L strategy dominated by “merchant self-LSM”. These findings provide new theoretical insights into the dynamic selection mechanisms of digital marketing strategies while offering practical decision-making guidance for retailers in allocating marketing resources across different development stages. The conclusions have direct implications for optimizing corporate marketing mix strategies. Full article

Sports teams increasingly use nostalgia-based marketing to spark fan engagement and boost merchandise sales. Yet these efforts can also provoke backlash, especially when they resurrect contested imagery. This article examines how one such campaign—the New York Islanders’ 2015 revival of their controversial fisherman logo—was framed across team broadcasts and interpreted by fans on social media. Drawing on a qualitative textual analysis of television and radio coverage alongside a quantitative content analysis of 563 tweets, the study reveals a divide between institutional messaging and grassroots reaction. While team broadcasts emphasized charity and sentimental appeal, fan discourse was notably more critical, mocking the jersey’s design and recalling past failures. By positioning nostalgia not only as a branding asset but as a reputational risk, the article contributes a novel perspective to debates about commercialization, mediatization, and fan co-production in sports. It also demonstrates the value of mixed methods for analyzing how branding narratives are negotiated in real time. Full article

In an era when AI systems curate increasingly fine-grained aspects of everyday media use, understanding algorithmic fatigue and resistance is essential for safeguarding user agency. Within the horizon of a more algorithmic and hyper-personalized advertising environment, knowing how people resist algorithmic advertising is of immediate importance. This research formulates and examines a structural resistance model for algorithmic advertising, combining psychological and cognitive predictors such as perceived ad fatigue (PAF), digital well-being (DWB), advertising literacy (ADL), and perceived relevance (PR). Based on a cross-sectional survey of 637 participants, the research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) and mediation and multi-group analysis to uncover overall processes and group-specific resistance profiles. Findings show that DWB, ADL, and PR are strong positive predictors of resistance to persuasion, while PAF has no direct effect. PAF has significant indirect influences through both PR and ADL, with full mediation providing support for the cognitive filter function of resistance. DWB demonstrates partial mediation, indicating that it has influence both directly and through enhanced literacy and relevance attribution. Multi-group analysis also indicates that there are notable differences in terms of age, gender, education, social media consumption, ad skipping, and occurrence of digital burnout. Interestingly, younger users and those who have higher digital fatigue are more sensitive to cognitive mediators, whereas gender and education level play a moderating role in the effect of well-being and literacy on resistance pathways. The research provides theory-informed, scalable theory to enhance the knowledge of online resistance. Practical implications are outlined for policymakers, marketers, educators, and developers of digital platforms based on the extent to which psychological resilience and media literacy underpin user agency. In charting resistance contours, this article seeks to maintain the voice of the user in a world growing increasingly algorithmic. Full article

Social media promotion of harmful products (e.g., combustible tobacco) poses a public health threat. However, strategies that amplify exposure to and engagement with such content remain understudied. This study aims to characterize strategies boosting cigar, little cigar, and cigarillo (CLCC) marketing visibility, referrals, and engagement on Instagram. Using keyword rules, we collected publicly available CLCC-related Instagram posts from CrowdTangle for a six-year period from August 2016 to October 2021. Posts were categorized as commercial (e.g., posts by tobacco brands or vendors) or organic and were coded for consumer engagement (CE) strategies (e.g., presence of prompts to like/share) using a combination of machine learning methods and human coding. Temporal engagement trends were analyzed using metadata. A total of 320,488 CLCC-related public posts were collected, with 44.6% (n = 142,875) identified as overtly commercial. Of these, 33.5% (n = 47,832) contained CE cues, including discounts and giveaways for tagging peers, liking, commenting, or following CLCC brands and spokesperson/influencers accounts, as well as calls to participate in contests and polls. Overtly commercial CE messages consistently garnered more comments per post and likes per post than non-CE commercial posts. There was a significant upward trend in the rate of comments on CE posts, suggesting growing effectiveness in eliciting user interaction. The proliferation of and high level of engagement with cigar-related promotional messages on Instagram demonstrate the need for public health surveillance and regulation of the evolving strategies promoting CLCC marketing exposure, reach, and engagement on social media. Full article

Background/Objectives: Dental practice, particularly aesthetic dentistry, has been extensively promoted through social media. The widespread advertisement of dental procedures via social media may influence young patients’ perceptions of the dentist’s professional role and potentially alter the dynamics of the doctor–patient relationship. Our study aimed to examine young dentists’ perspectives on ethical considerations associated with aesthetic dental procedures marketed on social media, and to identify appropriate professional responses to such situations. Methods: A cross-sectional study was conducted at Iuliu Haţieganu University of Medicine and Pharmacy in Cluj-Napoca, Romania, between July and September 2022. Data was collected using four case-based scenarios designed to elicit ethical reasoning. Results: Around 60% of participants identified ethical concerns related to patient requests for aesthetic dental procedures and demonstrated an ability to determine appropriate professional conduct in these contexts. The shift in the dentist’s role—from health care provider to service provider—driven by patient demands for cosmetic treatments was the primary concern perceived by the participants. Conclusions: Most participating young dentists were able to recognize ethical issues surrounding aesthetic dental requests influenced by social media and to adopt a considered professional response. Our findings highlight the need for reinforced ethics education and guidance in navigating social media’s influence on dental practice. Full article

To assist stakeholders in selecting appropriate social media influencers (SMIs), this study proposes a multi-attribute decision-making framework for influencer evaluation based on their key performance metrics and engagement characteristics. This study introduces a new modification of the Evaluation Based on Distance from Average Solution (EDAS) under an interval-valued Fermatean fuzzy (IVFF) environment, addressing the limitations of the conventional EDAS method. In addition, a conceptual framework for the static and dynamic evaluation of SMIs is developed, integrating various crisp and fuzzy multi-criteria decision-making (MCDM) approaches. Empirical validation through two practical case studies demonstrates the effectiveness and applicability of the proposed framework, resulting in recommendations for marketers seeking to optimize their influencer-based marketing strategies. Full article

In the attention-driven environment of online video platforms, understanding the factors that influence content selection and channel subscriptions is crucial for creators, marketers, and platform managers. This study investigates how thumbnails, view counts, video length, genre, and the number of advertisements affect user decision-making on YouTube. Grounded in random utility theory and reference-dependent preference theory, this study conducted a choice experiment with 525 respondents and employed a combined model of rank-ordered and binary logit methods to analyze viewing and subscription behaviors. The results indicate a significant preference for thumbnails with subtitles and shorter videos. Notably, we found evidence of reference-dependent effects, whereby a higher-than-expected number of ads decreased viewing probability, while a lower-than-expected number significantly increased subscription probability. This study advances our understanding of the factors that influence user behavior on social media, specifically in terms of viewing and subscribing, and empirically supports prospect theory in the online advertising market. Our findings offer both theoretical and practical insights into optimizing video content and monetization strategies in competitive social media markets. Full article