ABSTRACT. With the increased focus on increasing consumer wellbeing in marketing interactions, the role of servicesapes has gained significant attention. Within the domain of environmental psychology, the role of servicescape designs in influencing consumer attitudes is quite well known, but new research in this domain focuses on aspects like mental wellbeing, positive attitude formation and consumer trust. There is a growing realisation that servicescape designs can be employed in promoting overall positive affect of consumers. Studies have considered ideas like biophila, regenerative serviecscape designs, social servicescapes, customer oriented servicescape curation etc. This research domain is attracting a lot of interest from researchers specialising in the environmental psychology and design thinking. A variety of methods have been employed to understand and operationalise constructs relevant to this domain. The special session would focus on this emerging research domain.

ABSTRACT. People prefer humans over AI, so it is questionable whether voicebots will be accepted as substitutes to human agents. In this paper, we propose that one way to overcome resistance to this substitution is to endow English-speaking voicebots with non-standard English accents. Ten pre-registered experiments suggest that voicebots communicating with non-standard accents are readily anthropomorphized, influencing users’ attitudes, resulting in a preference for voicebots over live agents, and heightening perceived service evaluation. Evidence further suggests that this effect emerges because accented voicebots activate awareness of human diversity, which in turn triggers greater anthropomorphization. We also show the limits of these effects: the positive effect of voicebot accent does not hold when the voicebot also includes countervailing dehumanizing attributes, when the wait time for a substituting human agent is lower as opposed to higher, or when users hold a strong, unfavorable attitude toward AI.

ABSTRACT. Grounded in Anthropomorphism Theory, the Computers Are Social Actors (CASA) paradigm, and Uncertainty Reduction Theory (URT), this study examines how anthropomorphic visual cues (i.e., a chatbot’s name and picture) shape consumer attitudes in LLM-based chatbot interactions. A custom-built LLM-powered chatbot was developed for this study to enable authentic, real-time, multi-turn conversations and to capture behavioral data reflecting users’ anthropomorphic responses (e.g., greeting, politeness, and name usage). Using a 2 (visual cue: present vs. absent) × 2 (brand type: start-up vs. mass-market) between-subjects design, 148 U.S. participants interacted with the chatbot, and both transcript and survey data were analyzed. Results from mediation and moderated mediation analyses revealed that visual cues enhanced attitudes toward the chatbot through anthropomorphic responses, with the effect being stronger for start-up brands—where anthropomorphic signals help reduce uncertainty and build trust—than for mass-market brands. The findings demonstrate that perceived humannes, serves as a key mechanism linking visual cues to positive evaluations. Practically, brands can benefit from adopting humanlike visual elements, but favorable outcomes arise only when users genuinely perceive and interact with the chatbot as humanlike, emphasizing the importance of fostering authentic social engagement rather than mere visual realism.

ABSTRACT. Abstract: As brands increasingly integrate Artificial Intelligence (AI) chatbots into customer experience, research has mainly focused on the conversational agents features, often overseeing how the pre-existing psychology of the consumer toward the brand shapes the interaction. This study proposes and tests a model that articulates a cognitive pathway. From the propension of the consumer to anthropomorphize the brand, through the establishment of a cold (cognitive) and hot brand relationship, to the shaping of expectations and experiences with a branded chatbot. Using a sequential exploratory mixed-methods design, concluding in a large-scale cross-cultural survey (N=4,957), the results validate this relational model. This study shows that brand anthropomorphism is a key antecedent of a cognitive brand relationship (built on trust and satisfaction), which, in turn, leads consumers to value functional competence and brand congruence (cognitive dimensions) over social warmth (an affective dimension) in their chatbot experience. This research contributes to the literature on human-AI interaction by offering a framework that prioritizes the pre-existing brand relationship as a key predictor of consumer experience, providing managers with a guide for designing chatbots that align with the nature of their customer relationships.

ABSTRACT. The use of artificial intelligence (AI) in marketing, and particularly in personalized messages, has become common practice in brand communication. The aim of this paper is to examine the relationship between the use of AI-driven personalized sustainability messages and consumer reactions. Knowledge acquisition, social presence, and ascription of responsibility were identified as the most influential factors in AI-generated personalized sustainability messages, which in turn can influence consumer attitudes and their purchase intentions. Furthermore, the moderating role of skepticism between AI-driven personalized sustainability messages and attitude was incorporated. Fatigue was also included as a potential result of personalized sustainability messages driven by AI, which can further influence consumers' attitudes and purchasing intentions. Through integrating these factors, this paper provides a framework that highlights both the potential benefits and drawbacks of AI-driven personalization in the sustainable consumption context. It will offer insights for researchers interested in AI in marketing and consumer behavior in the sustainability field, as well as for managers who intend to effectively deploy sustainable personalization strategies using AI.

ABSTRACT. This study investigates the development of follower engagement with virtual influencers (VIs) through the theoretical lens of the Willing Suspension of Disbelief (WSD). Drawing on 30 in-depth interviews with Chinese followers of prominent VIs, we conceptualize engagement as a dynamic, processual phenomenon comprising four interrelated phases: Semblance of Truth, Boundary Blurring, Emotional Dominance, and Temporariness. Findings indicate that followers initially establish perceptual trust through visual realism, progressively attribute human-like qualities to VIs, and sustain immersive emotional involvement, before ultimately reinstating rational awareness of artificiality. By framing engagement as a fluid negotiation between perceived authenticity and inherent fictionality, this study advances theoretical understanding of digital influencer-follower interactions and offers actionable insights for the design and management of emotionally compelling virtual personas in marketing contexts.

ABSTRACT. Artificial Intelligence Influencers (AIIs), digital personas powered by generative AI, are rapidly transforming influencer marketing. Unlike traditional virtual influencers, AIIs are not merely avatars controlled by humans but can create content and engage with audiences autonomously. Driven by low cost and scalability advantages, AIIs are attracting strong market interest. However, this is tempered by growing consumer scepticism, particularly when AI identity of an influencer is disclosed. This research addresses a critical challenge for AIIs: the AI disclosure penalty, where revealing AII’s artificial identity leads to diminished consumer engagement. We investigate the psychological mechanisms underlying this penalty and propose a communication-based intervention – pre-bunking message framing – to mitigate negative effects. We provide robust field and experimental evidence that disclosing an influencer’s AI identity reduces consumer engagement. We conceptualise and empirically validate a novel serial mediation mechanism, the authenticity spillover, wherein AI disclosure reduces influencer authenticity, which in turn diminishes message authenticity, leading to lower engagement. Applying inoculation theory to AI marketing, we demonstrate that pre-bunking can proactively shape consumer perceptions and mitigate disclosure penalty. We suggest marketers adopting proactive transparency, wherein, framing AIIs as innovative, data-driven communicators capable of empathy and accuracy can inoculate consumers against scepticism and preserve engagement.

ABSTRACT. Pricing tactics are known to increase revenue without cutting list prices, but their trustworthiness is unclear due to the replication crisis. This PRISMA-guided systematic review audits five decades of research evidence on ten prominent pricing tactics that are known to change perceived value through cognitive framing: decoy, anchoring, charm pricing, partitioned or drip, bait, bundling, pay-what-you-want, zero-price, scarcity cues, and subscription. Searches in Scopus, Web of Science, and Google Scholar yielded a total of 3,031 records. After the deduplication and screening process, 783 empirical consumer studies were found. Each is coded for study type (field, lab, online), incentive alignment (consequential, incentive-compatible, hypothetical), sample size, product category, and effect statistics. The further analysis includes sorting evidence across all effects by external validity and then applying p-curve, z-curve, and caliper tests to detect selective reporting. Such systematical reexamination will allow for critical assesment of previous results and answer which tactics hold under real-market conditions versus hypothetical bias. Results, due early 2026, will clarify managerial reliability and strengthen pricing theory.

ABSTRACT. Self-reports on socially sensitive topics are prone to socially desirable responding (SDR), yet evidence on whether third-person indirect questioning truly reduces bias remains mixed. We propose and test a stepwise psychometric framework that (i) establishes construct comparability between direct and indirect formats via configural/metric invariance and (ii) treats item intercept differences as diagnostic signals. In a between-subjects online survey of Lithuanian consumers (N = 335), green consumption attitudes and behaviors were measured with parallel direct and indirect scales. Models showed that MRT, not ERT, inflated direct self-reports—especially attitudes—while effects attenuated under indirect wording. Intercept partitioning indicated that controlling for MRT/ERT reduced average direct–indirect gaps by ~49% for attitudes and ~41% for behaviors. The framework clarifies when indirect responses reflect projection versus meta-perceptions and offers practical diagnostics for designing less biased surveys and cleaner inputs for segmentation, forecasting, and causal analysis.

ABSTRACT. This research responds to the call for additional investigation into item level correction (ILC) by taking a dual model approach. We aim to study the effects of both CB and PLS modeling when conducting ILC. We propose to undertake three replication studies from prior, published research in the Journal of Global Marketing, the Journal of International Consumer Marketing and the Journal of Global Scholars of Marketing Science. We first conducted a meta-analysis of every article in these journals from 2023 through 2025 and evaluated the treatment and defense of common methods variance (CMV). Initial results are briefly summarized below. We then offer three hypotheses related to the evaluation of ILC versus other widespread approaches to CMV.

ABSTRACT. Although organizations’ access to skilled employees is constrained by an ongoing war for talent, jobseeker preferences for employer attributes as part of the employer brand remain a relatively underexplored area. To attract talent and become employers of choice, organizations engage in branding activities promoting diversity, equity, and inclusion (DEI) in the workplace (Jonsen et al., 2021). While DEI statements in recruiting material enhance organizational attractiveness for some job seekers (Alahakoon et al., 2024), DEI branding may also inadvertently repulse others (e.g., Phillips et al., 2023). This study employs an anchored Maximum Difference Scaling (MaxDiff) approach to gauge which DEI-related employer brand signals entice the talent employers are eager to attract. By transferring a novel methodological approach to the employer branding domain, we examine a sample of 148 job seekers based in Germany and find that employer claims asserting the organization’s DEI engagement are generally desired by job seekers. Enriching the findings with insights from cluster analysis, we identify two distinct segments of job seekers who exhibit diverging patterns in their appreciation of different DEI-related employer claims. The findings offer initial insights for employers seeking to cater to the diverse needs of their workforce.

ABSTRACT. Gender stereotyping remains a persistent issue in marketing, shaping consumer perceptions and limiting inclusivity. The bicycle industry, still marked by masculine norms and outdated gender cues such as the “ladies’ bike,” exemplifies this tension. This study investigates women’s purchase intentions in this context by integrating emotional, functional, and social determinants into a structural model based on the Theory of Planned Behavior (TPB). Using data from 219 female consumers in Germany and analyzed via Partial Least Squares Structural Equation Modeling (PLS-SEM), the results reveal that social and emotional factors outweigh functional attributes in predicting purchase intentions. Subjective norm emerged as the strongest predictor, followed by enjoyment, while attitude - central to TPB - was not significant. Product and service quality influenced purchase intention indirectly through enjoyment. Moreover, product knowledge moderated several relationships, highlighting heterogeneity among female consumers. The findings challenge the universal applicability of the TPB for high-involvement goods, underscoring the need for gender-sensitive extensions incorporating social identity and hedonic value. For practitioners, the study advocates shifting from product-centric to community-centric and experience-oriented marketing to better engage women as a key consumer segment.

ABSTRACT. Marketers increasingly use identity-based strategies to connect brands with consumers by appealing to who they are. Advances in personalization and AI technologies now enable campaigns to reference multiple aspects of consumers’ identities simultaneously (e.g., appealing to them as parents, professionals, and environmentally conscious citizens). Although such multi-identity appeals are assumed to enhance message relevance and persuasion, their effectiveness remains uncertain. Across three experiments using products with sustainability relevance, we demonstrate that simultaneously activating multiple self-identities reduces product evaluations compared with activating a single identity. This effect is explained by processing disfluency, a reduced sense of ease when consumers process messages that coactivate multiple distinct identities. The backfiring effect is mitigated when the targeted identities are perceived as closely associated, suggesting that identity association facilitates processing fluency. Our findings challenge the long-standing assumption that increasing identity relevance strengthens persuasion and extend fluency theory to the domain of identity processing. For managers, the results highlight that more personalization is not always better: effective identity-based campaigns should focus on conceptual coherence between the identities they activate rather than breadth of targeting.

ABSTRACT. The current thesis investigates the impact of mortality salience on perception, evaluation, and purchase intention of gender-stereotyped products. Three experiments were conducted to test various predictions derived from the terror management theory. The first experiment supported the hypothesis that consumers primed with mortality salience prefer a product perceived as masculine over the one perceived as feminine. Subsequent experiments revealed the underlying mechanism of this effect. Once consumers’ mortality was made salient, they believed that products perceived to be feminine were less competent and thus liked them less (Experiment 2). This effect of mortality salience on consumers’ attitude toward feminine products disappeared when an external focus of control was primed (Experiment 3), presumably because self-competence is less important in coping with the threat of death when people believe that their fate is not in their hands.

ABSTRACT. AI ethics is growing area of research that seeks to describe and normalise the ethical development of AI systems. Yet, even as modern AI systems are increasingly consumer-focused, there is limited research aimed at understanding which ethical design principles matter to consumers. This is important as, while AI systems have great potential for positive good, these is growing unease and skepticism about their use. AI ethics may be a solution to this problem. Our research seeks to answer fundamental questions about consumer preferences for AI ethical principles, and whether this differs across contexts and cultures. In a discrete choice experiment run across four countries, we reveal an overall preference for privacy that persists across different consumer contexts. Our research contributes to marketing literature by providing quantified evidence of consumer heterogeneity regarding AI ethics, and a clear path to impact for those designing and marketing ethical AI systems. This has important implications for AI design principles and the marketing of AI-powered products and services for competitive advantage.

ABSTRACT. Drunk shopping online is a billion-dollar industry with a high annual spending from alcohol intoxicated consumers shopping online. Considering the implications drunk shopping can have on both consumers and businesses plus the lack of research in this particular field of inquiry, this paper draws on various literature fields (i.e., psychology, neuroscience, marketing and alcohol literatures) to provide an understanding and to spark development of future research on this largely unexplored phenomenon in the marketing literature. Based on the analysis of the literature, the author develops a theoretical, integrative framework of the processes of drunk shopping – linking with antecedents, mechanisms and outcomes of alcohol misuse. This paper addresses a problem of relevance to both academics and practitioners, also propose future research directions accompanied with seven propositions for future research.

ABSTRACT. Early cancer detection saves lives, yet many diagnoses still occur serendipitously, outside organized screening, revealing hidden inequities in diagnostic opportunity. Using Surveillance, Epidemiology, and End Results (SEER) data from 2000 to 2022 (N = 14,339,579), we quantified diagnostic luck, finding that serendipitous detections accounted for 6% of cases (approximately 864,000) and contributed nearly one million life-years gained. However, these benefits were unevenly distributed by race, income, and geography. Building on Crosby et al.’s (2022) five canonical challenges of early detection, we introduce two additional systemic dimensions: Challenge 6, System Design for Equitable Serendipity, and Challenge 7, SANaiRE–System for Accountable Networked AI for Responsible Equity. Together, they transform stochastic detection into a measurable and redistributable system property. The contributions are threefold: conceptually, we formalize diagnostic luck as provoked and accidental; empirically, we quantify their magnitude and outcomes across 14 million patients; and systemically, we expand early-detection science beyond biology and epidemiology toward design justice and AI-enabled governance. This framework links empirical evidence with policy strategies for preventive health communication and global equity, reframing early detection as a governed ecosystem where serendipity becomes an instrument of fairness rather than chance.

ABSTRACT. The rapid normalization of sharenting on social media worldwide has created a critical, yet largely unexplored, domain where personal family narratives intersect with corporate marketing efforts. Understanding this intersection is vital because the success of parent influencer marketing and brand storytelling often hinges on this sensitive content. Yet, the ethical and long-term implications for customers' perception of brand ethicality and engagement remain unclear. We are exploring the psychological underlying mechanisms through which sharenting, the public sharing of children's information and lives by parents, influences customers’ brand ethicality evaluation and engagement, with a focus on perceived brand exploitation. This research adopts a multi-stage, mixed-methods approach with two complementary stages. We first analyzed the content shared by the account Pamper US (#pamperus), analyzing a total of 644 Instagram posts for the years 2015–2025 to identify patterns of sharenting behaviors and their potential influence on audience interactions (Study 1). We then used an experimental design (Study 2) to explore the underlying mechanism of the impact of sharenting practices on customer engagement. While sharenting can enhance visibility and generate positive emotional reactions, the findings underscore the risks associated with leveraging child content for commercial purposes which damages consumers’ perception of brand ethicality.

ABSTRACT. This study explores how and why social media influencers publicly reprimand brands for ethical or moral wrongdoing. Introducing the concept of Moralising Brand Influencers (MBIs), it examines influencer-led activism through two research questions: (1) What message framing strategies do MBIs use in their reprimands? and (2) What do MBIs aim to achieve by posting them? Using a non-participatory netnography of 684 social media posts and hybrid thematic analysis, the study identifies five framing strategies—abstract versus concrete framing, message tailoring through @mention, metaphor, humour, and anger. These strategies combine cognitive, emotional, and performative elements that enhance the rhetorical impact and visibility of moral criticism. A second analysis reveals five key purposes behind MBIs’ reprimands: Call for Action, Raising Awareness, Arouse Nationalism, Elicit Negative Emotions, and Self-Enhancement. Together, these findings demonstrate that MBIs function as both ethical commentators and self-branding actors who blend activism, marketing, and moral persuasion to influence public perceptions of corporate legitimacy. The study extends framing theory to influencer-led moral communication and offers practical implications for brands, highlighting the need to recognise reprimands as structured moral discourse and to respond proportionately through transparency, empathy, and authentic value alignment.

ABSTRACT. Over the past decade, brands have faced increasing challenges in managing brand crises caused by issues related to their offerings or values. Although situational crisis communication theory provides a strategic framework for brands to protect their reputation through crisis responses, such primary communication strategies are becoming less effective due to pervasive conversations on social media. Drawing on social media influencer (SMI) marketing and brand crisis literatures, as well as the strategic practice that brands collaborate with SMIs to influence consumer evaluations and behaviors, we investigate the effects of SMI communications in values-related brand crises. With a proposed mixed-methods approach that consists of field studies and contrived online experiments, we intend to contribute to SMI marketing and brand crises literatures by investigating the impact of SMI communications related to values-related brand crises. The results are also expected to provide practical suggestions to marketers regarding how they can better incorporate SMIs as strategic partners to manage values-related crises, as well as provide insights to SMIs on whether and how they should partner with brands.

ABSTRACT. In a rapidly changing world, societies around the world have been shaped by multiple crises and far-reaching challenges that have transformed economic systems and social structures. The pandemic, for example, severely affected individuals and economies while simultaneously accelerating developments such as the growing adoption of online grocery retailing. In parallel, economic crises triggered by armed conflicts and disruptions to global supply chains have contributed to inflation and recessionary pressures. At the same time, climate change continues to shape the global environment, causing rising sea levels, more frequent natural disasters, and record temperatures. Technological progress, particularly advances in artificial intelligence, is further transforming human behaviour, information processing, and marketing practice. However, the rapid spread of new technologies also raises concerns about energy consumption and environmental sustainability. Against this background, this special session explores the importance of environmental dimensions in marketing. It addresses how crises, climate change, and technological transformation can be incorporated into marketing theory, examined through empirical research, and translated into managerial practice. Designed as an interactive special session, we aim to foster reflection, critical discussion, and the development of new perspectives on how environmental dimensions shape marketing thought and action.

ABSTRACT. As AI systems increasingly assume professional roles, their gendered design features (i.e., voice, appearance, names) shape user perceptions. While existing research applies the Stereotype Content Model to examine AI gender effects, it overlooks how occupational context moderates these dynamics. Drawing on Role Congruity Theory, we investigate whether gender stereotypes in AI evaluation depend on the alignment between gender cues and role expectations across professional domains. Through two studies, an online experiment in healthcare with 181 participants and a field experiment in education with 324 participants, we manipulated AI gender presentation and hierarchical position in 2×2 designs. Results demonstrate significant interaction effects: in healthcare, masculine AI doctors received higher competence ratings than feminine counterparts, while feminine assistants were rated more competent and warmer than masculine assistants. Conversely, in education, feminine AI professors garnered higher competence assessments than masculine professors. These findings reveal that identical gender cues produce divergent effects depending on occupational context and role status. By integrating stereotype content and role congruity frameworks, this research establishes that AI gender effects operate through context-dependent mechanisms. Design choices consequently either reinforce or challenge existing occupational hierarchies, positioning AI development as social intervention with implications for equity and gender segregation.

ABSTRACT. Voice-based AI systems, from smart speakers to in-vehicle assistants, have raised debates about gender bias in technology design. While female default voices have been criticized for reinforcing stereotypes, gender-neutral alternatives are often promoted as more inclusive. However, the effectiveness of these design choices depends on how users perceive and respond to gendered and gender-neutral voices. In a mixed-method study combining a choice experiment (N = 317) and thematic analysis of open-ended responses, we show that users’ perceptions of AI voices are deeply shaped by their own gender identity. Participants evaluated gender-congruent voices more positively, attributing greater warmth, competence, and self-connection, suggesting that voice perception operates through identity alignment rather than universal stereotypes. Interestingly, gender-neutral voices elicited divergent interpretations: on the one hand, they might carry implicit feminine cues; on the other hand, they reflected different user motivations, such as a preference for functionality over identity or a rejection of anthropomorphism. These results suggest that even neutral AI voices are socially encoded and culturally interpreted. Overall, the study underscores the importance of user gender identity in shaping responses to AI voice design and calls for a more context-sensitive approach to inclusivity in human–AI interaction.

ABSTRACT. Artificial Intelligence (AI) increasingly mediates interactions between consumers and organizations, raising new questions about fairness, bias, and inclusion in digital marketplaces. This research examines how biased AI interactions influence perceptions of discrimination and shape key consumer outcomes such as trust, satisfaction, and purchase intentions, while also exploring how race moderates these effects. Across two experimental studies simulating e-commerce chatbot interactions, participants were exposed to either a biased or an unbiased AI recommendation scenario. Results show that biased AI interactions significantly heighten perceptions of discrimination and reduce trust and satisfaction with the experience. Moreover, race plays a moderating role: White participants, less accustomed to systemic disadvantage, reported stronger perceptions of discrimination and more negative emotional reactions, whereas Black participants, though aware of the bias, demonstrated greater resilience. These findings provide empirical evidence that AI systems can reproduce and reinforce existing social hierarchies, extending theories of algorithmic bias, privilege, and resilience. From a managerial perspective, the study evidences the importance of fairness and inclusivity in AI design, showing that equitable and transparent algorithms not only address ethical concerns but also serve as strategic drivers of consumer trust, satisfaction, and long-term organizational legitimacy.

ABSTRACT. The use of AI tools in purchasing is rapidly increasing and becomes a frequent solution used in buying process. One of the reasons for this might be anthropomorphism of generative AI, helping to communicate with it using skills similar to those used with human beings. Artificial Intelligence Device Use Acceptance (AIDUA) model emphasises interaction of anthropomorphism with performance expectancy and effort expectancy in predicting intention to use AI tools. In this study, we propose the presence of an additional indirect impact of anthropomorphism through habit on intention to use AI, complementing those conceptualised in AIDUA. In order to assess this alternative, we analyse data obtained from a survey and compare indirect effects of anthropomorphism on intentions mediated by earlier known mediators with that of habit. Then, using cross-validated predictive ability test, we compare two models (with habit and without it) in order to assess the predictive accuracy. The findings show significance of all indirect effects of anthropomorphism on intentions, thus confirming the role of anthropomorphism in predicting the use of AI in purchasing. Even more importantly, the study demonstrates that the model that includes habit has better predictive accuracy, which suggests to amend AIDUA with this factor in future studies.

ABSTRACT. Modern data analytic marketing requires large amounts of data to aid understanding of consumer behavior. Collecting consumer data can be difficult and expensive. LLMs are built upon a large corpus of internet data, including consumer preference data. This research looks at how LLMs can be used to generate synthetic consumer data using projective techniques, which cover a range of methods designed to elicit consumer wants and needs. LLM generated data were optimized using LLM parameter tuning and compared with data gathered from real human subjects in a primary research study. There were strong similarities between the human subject data and the LLM data, but also important differences. Recommendations are given on how to best utilize LLMs for gathering consumer data, and further, more comprehensive experiments are described and planned.

ABSTRACT. The rapid adoption of Generative AI (GenAI) in creative industries such as marketing and design has transformed how content is produced and evaluated. While GenAI enhances accessibility and efficiency, it also raises moral and ethical questions concerning authenticity, fairness, and ownership. This research investigates whether public recognition of AI-assisted creative work alters observers’ moral and fairness judgments toward human creators. Across three experimental studies (N = 829), we examine how AI involvement and public recognition jointly influence perceptions of effort, ethicality, and reputation. Drawing on Effort Justification, Equity Fairness, and Signaling Theory, we find consistent evidence of an “ethicality penalty” for AI-assisted creativity. Even minimal AI involvement reduces perceived authenticity, ownership and moral deservingness, diminishing the creator’s reputation. Public recognition amplifies these effects, intensifying ethical scrutiny when AI assistance is disclosed. These findings reveal that audiences interpret AI involvement as a signal of reduced human effort and authenticity, violating meritocratic fairness norms. The study advances understanding of moral evaluation in AI-mediated creativity and offers practical insights for transparent communication and ethical disclosure in AI-assisted marketing and design.

ABSTRACT. Total Unduplicated Reach and Frequency (TURF) analysis is a commonly applied market research method to determine sales-optimizing product assortments. Product assortment selection in TURF analysis relies on two metrics: reach (percentage of consumers who would buy at least one of the alternatives in the assortment) and frequency (average number of alternatives that would be purchased from the assortment). Classical TURF, however, has the drawbacks that it neither assesses uncertainty nor reaps the underlying data’s full potential. To overcome these limitations, this research introduces Bayesian TURF analysis, which uses the estimates’ posterior draws to determine optimal product assortments. Bayesian TURF is introduced using both MaxDiff and Check-All-That-Apply data, methods commonly applied in both market and sensory consumer research. This research shows that Bayesian TURF analysis can extend the results of classical TURF analysis by providing credible intervals, rankings, and percentages of assortments ranking top-seeded in posterior draws. In addition, Bayesian TURF allows to estimate Bayesian p-values to analyze performance in head-to-head comparisons of different alternatives. Bayesian TURF analysis enables managers and decision-makers to make more informed decisions and weigh up, for example, revenues, costs, and ease of implementation for different product assortments.

ABSTRACT. Recent advances in large language models (LLMs), such as ChatGPT and Gemini, facilitate the creation of synthetic, or “silicon,” survey data that mirrors human responses. This study compares traditional consumer panel data with synthetic datasets generated by these models to evaluate the equivalence of demographic and attitudinal characteristics in surveys. The results of comparative analyses show that ChatGPT produced more realistic demographic distributions and attitudinal variability than Gemini, though both models exhibited internal inconsistencies across repeated runs. Findings suggest that while LLMs can approximate surface-level patterns, they struggle to replicate deeper cognitive and affective nuances of real respondents. The study concludes that synthetic data can accelerate pretesting and instrument validation when accompanied by transparent documentation, replication, and ethical safeguards. Synthetic datasets thus represent a promising complement, not a substitute, to human data collection in marketing and consumer-behavior research.

ABSTRACT. Marketers increasingly need targeting systems that improve decisions without sacrificing transparency, privacy, or human judgment. This paper proposes Semantic Consumer Profiling (SCP), an explainable method that extracts identity-relevant meanings from product discourse and fuses them with parsimonious behavioral summaries. We build theory-guided lexicons, enrich SKU descriptions with policy-compliant online text, score seven motivational attributes (e.g., innovation, practicality, sustainability), and aggregate SKU vectors into consumer profiles using monetary and recency weights. Profiles are combined with Recency-Frequency-Monetary (RFM) features to rank customers for next-period contact. Evaluation follows an out-of-time design on a multi-month retail panel; we report discrimination, calibration, and decision-centric metrics (AUC, Precision@k, Lift@k) with uncertainty, probe robustness to alternative text pipelines and half-life choices, and audit potential temporal leakage. The pipeline yields fully traceable recommendations via a SKU→attribute→consumer audit trail and is accompanied by model cards, datasheets, fairness diagnostics, and deployment checklists. Managerially, SCP helps allocate small push budgets, seed trials where RFM is silent, and produce creative briefs grounded in explicit textual cues. Our contribution is a deployable, governance-ready approach that connects identity theory to CRM practice while advancing reproducibility and responsible AI in marketing. We outline field-experiment blueprints and share blinded materials for independent replication and open review.

ABSTRACT. Endogeneity is a common problem in regression models with observational data. It occurs when one or more regressors are correlated with the structural error term. Such correlation may result from many different sources. Common sources include omitted variables that jointly influence the regressor and the outcome, from measurement error in the regressors and outcome, or from simultaneity in the determination of the dependent and explanatory variables. Park and Gupta’s (2012) seminal work proposes an instrumental-variable (IV)-free correction for endogeneity bias that assumes a copula-based representation of the dependence between an endogenous regressor and the structural error term, which rests on three key assumptions. These assumptions may be difficult to meet, and recent research has demonstrated that the original formulation implicitly assumes that the endogenous regressor is uncorrelated with all exogenous covariates included in the model. The proposed framework addresses this issue by enhancing the robustness of empirical analysis by mitigating the risks associated with copula misspecification and by enabling valid statistical inference in the presence of endogeneity. In marketing applications, for instance, the resulting improvements in the accuracy of elasticity estimates can translate into more reliable managerial decision-making in areas such as pricing and demand analysis.

ABSTRACT. Significant advancements in artificial intelligence (AI) and neuroimaging technologies have fundamentally transformed marketing's capacity to understand consumer research. Despite growing interest across academic and industrial sectors, the integration of neuromarketing and AI lacks theoretical coherence. Existing scholarship often prioritizes practical applications over establishing a comprehensive theoretical framework that focuses on how AI fundamentally redefines neuromarketing as a distinct discipline. This paper critically reviews the integration of AI and neuromarketing, demonstrating that predictive power and ethical accountability must evolve together. By examining its theoretical foundations, predictive capabilities, and ethical challenges, it develops a theory-based understanding of predictive-ethical insight. The analysis suggests that while AI broadens neuromarketing's explanatory scope, it also presents challenges to consumer autonomy, transparency, and informed consent. For marketing theory, this implies a shift from solely data-driven persuasion to responsible analytics informed by cognitive science. For practitioners, it highlights that ethical design is essential for fostering sustainable trust.

ABSTRACT. This field study examines the economic effects of personality-tailored advertising messages in online search advertising. Although prior research has highlighted the psychological relevance of personality-based targeting, empirical evidence on its economic effectiveness in real-world contexts remains limited. Collaborating with five German online businesses, this study analyzed Google Search Ads that either included or excluded personality-tailored message components. Economic performance was evaluated using purchases per impression (PurchasepImpr), cost per purchase (CostpPurchase), and return on advertising spend (ROAS). Bayesian multilevel ridge regression models employing Markov Chain Monte Carlo sampling were estimated, controlling for demographic and temporal covariates. The results demonstrated that personality-tailored advertisements significantly improved advertising performance. Specifically, PurchasepImpr and ROAS increased, whereas CostpPurchase decreased. These findings provide empirical support for the theoretical assumption that advertising effectiveness improves when messages align with consumers’ personality-related needs and behavioral tendencies. The study extends the existing literature by demonstrating the practical economic value of personality-tailored advertising beyond laboratory settings. Overall, the results suggest that incorporating personality-based message elements can enhance advertising efficiency and may serve as a meaningful addition to existing personalization approaches in digital marketing practice.

ABSTRACT. This research investigates both altruistic and deviant behaviour within online, consumer-led communities. Specifically, we examine online grocery voucher-sharing groups that operate on social media platforms such as WhatsApp and Facebook. In these consumer-managed communities, consumers independently exchange, gift, or request vouchers derived from supermarket loyalty programmes (an example of a voucher is a €10 voucher for every €50 spend), thereby creating a natural setting to observe everyday expressions of altruism and deviance. Using a qualitative approach, the research draws on thirty-six semi-structured interviews with both group moderators and members. The findings reveal a moral continuum of voucher-sharing behaviours from altruism to deviance, across five distinct types of behaviours. Participants’ self-reports, interpretations of others’ behaviours, and responses to group norms illustrate how individual intent, informal norms, social dynamics, and structural constraints shape these communities. The study, therefore, extends research on moral decision-making, consumer ethics, and self-regulation in online contexts. Practical implications include guidance for businesses seeking to encourage ethical engagement and responsible loyalty programme design, as well as recommendations for group moderators to foster altruism and curb deviance.

ABSTRACT. As artificial intelligence (AI) chatbots increasingly guide everyday consumption decisions, understanding how they persuade consumers is a critical research priority. This qualitative pilot study explores mechanisms of AI persuasion and examines whether traditional persuasion theories adequately capture AI-mediated influence. Drawing on semi-structured interviews with nine active users of generative AI tools, we employed grounded theory–inspired thematic analysis to identify recurring persuasion patterns across decision-making stages. Three core mechanisms emerged: informational utility, through which AI simplifies uncertainty and problem recognition; risk reduction, which enables heuristic decision-making in evaluation and choice; and affective support, whereby AI provides post-choice reassurance and emotional validation. These mechanisms operate dynamically across such consumption domains as health, shopping, and lifestyle decisions. Findings reveal that consumers engage in hybrid persuasion processing, simultaneously employing central and peripheral routes, challenging dual-process models like the Elaboration Likelihood Model. Trust in AI was found to be situational and evolving, moderated by emotional needs, urgency, and skepticism. Importantly, persuasion extends beyond cognitive elaboration to include affective and relational dimensions, as users described AI agents as collaborators or companions. The study advances theoretical understanding of AI persuasion as a layered, affective, and socially embedded process, offering implications for consumer autonomy and ethical AI design.

ABSTRACT. Greenwashing in digital sustainability campaigns undermines the credibility of corporate environmental communication. We address a persistent gap, the lack of operational tools for practice, by developing and validating an authenticity rating system that translates established criteria into ten measurable indicators applicable to product-, strategic-, and corporate-level messaging. The framework is tested through case studies of multinational firms frequently scrutinized for their sustainability narratives. The analysis reveals that their packaging commitments exemplify corporate-level vagueness and selective disclosure, and that product-level illustrates claim inflation and symbolic marketing. These findings show the system’s ability to detect misleading claims across modalities and to surface structural dissonance between communicated commitments and underlying practices. The study contributes by operationalizing greenwashing detection and by evidencing applicability across contexts. For managers, the framework supports aligning narratives with verifiable action to sustain trust and legitimacy. For policymakers, it offers a transparent monitoring tool that can inform oversight and enforcement in sustainability communication.

ABSTRACT. The aim of this study is to examine the impact of the intensity of sustainability claims on consumption intentions through the mediation effect of perceived environmental impact and moderation effect of environmental concern. A between-subjects online experiment (n=303, recruited via Prolific and social media) was conducted using three conditions: a control group with no sustainability message, a light claim group, and a strong claim group. The results suggest that exposure to sustainability claims appears to grant consumers psychological permission to purchase more, as they perceive the product to be less environmentally harmful. The moderation pattern indicates that lower-concern consumers were most responsive to sustainability messages, whereas higher-concern individuals perceived environmental benefits even in the absence of such claims, likely reflecting confirmation bias. By demonstrating a static licensing effect in sustainability marketing this research advances moral licensing theory and shows that perceived environmental impact can be a central mediating mechanism. It also enhances the understanding of environmental concern and shows that high concern does not necessarily amplify message effectiveness. The findings imply that marketers should calibrate message strength depending on the audience type where stronger claims may persuade low-concern consumers and highly concerned consumers may require more evidence-based or transparent communication.

ABSTRACT. Despite growing awareness of climate change, consumer engagement in climate-positive behaviors remains limited. This paper introduces a typology of Consumer Climate Engagement (CCE) that integrates Social Exchange Theory and Construal Level Theory to explain why engagement varies across behaviors and contexts. We conceptualize CCE as an exchange process influenced by the perceived level of concreteness of its costs and benefits. A two-dimensional framework distinguishes four types of engagement – each reflecting distinct cost–benefit configurations. A qualitative study on electric vehicle (EV) attitudes and adoption illustrates the Tangible Exchange type. Findings reveal that the costs and benefits associated with EV adoption are generally perceived as rather concrete, reflecting the tangible nature of this form of consumer climate engagement. Nevertheless, EV owners perceive both costs and benefits even more concretely than non-owners, suggesting that personal experience further reduces psychological distance. The proposed framework advances understanding of heterogeneous consumer engagement in climate action and serves as a conceptual starting point for practitioners seeking to design effective interventions to promote CCE.

ABSTRACT. This research explores how trans-parasocial relationships influence followers’ purchase intentions toward brands recommended by influencers. Using an online survey (N = 354) conducted by a consumer panel company in Taiwan, the results show that attitudinal persuasion knowledge and perceived authenticity serially mediate the impact of trans-parasocial relationships on purchase intentions. The research not only refines the theoretical construct of trans-parasocial relationships but also offers insights into its effects on consumer behavior. The findings provide practical guidance for developing effective influencer marketing strategies.

ABSTRACT. Modern people's hectic lifestyles, combined with constant interactions with multimedia sources, create continuous stress and fatigue (Chen et al., 2022). In addition, we encounter multi-sensory stimuli in stores, including digital ones, such as multiple pop-up windows, flashing screens, animations, timers, and gamification elements. In cases like AliExpress, Shein, and Temu, among others, there is an extensive amount of these stimuli, and it is difficult to avoid the impression that such webstores are intentionally designed to induce stress and confusion. The aims of our study is to provide insights for practitioners aiming to design webstore experiences that reduce the green values–behavior gap and nudge consumers toward more sustainable behavior. Another aim is to help consumers become more aware of how their stress levels in different conditions affect their information processing and decision-making. With these aims we address the following Research Question: How do website designs affect the perceived sustainability of choices, and what roles do psychological and physiological stress play?

ABSTRACT. This research investigates how curiosity and retargeting strategies influence consumer engagement, privacy concerns and purchase likelihood on social media. While curiosity is widely used to drive clicks and interaction, its dual nature —interest-driven (CFI) and deprivation-driven (CFD) can lead to either increased engagement or heightened privacy concerns. Through a 2 (curiosity: high vs. low) × 3 (post type: affiliative, brand, utilitarian) experimental design with 339 U.S. participants, the study explores how different post types interact with curiosity to affect consumer behavior. Results show that high curiosity enhances engagement and purchase likelihood for affiliative posts. Conversely, pairing high curiosity with brand-centric posts increases privacy concerns and reduces purchase likelihood. Utilitarian posts showed no significant effects. Moderated mediation analysis confirms that engagement mediates the positive effect of curiosity in affiliative posts, while privacy concerns mediate the negative effect in brand posts. These findings offer actionable insights for social media managers: use curiosity to boost engagement in community-driven content but avoid it in brand-heavy messaging to mitigate privacy concerns. The study contributes to social media marketing and curiosity literature by identifying conditions under which curiosity enhances or hinders consumer response to retargeted ads.

ABSTRACT. The emergence of artificial intelligence (AI) is transforming the foundations of marketing practice and research, particularly in the domain of social media influencers. As algorithms increasingly mediate how consumers encounter and engage with content, the boundaries between human creativity and machine-generated persuasion continue to blur. This special session will focus on how AI is reshaping influencer marketing, from predictive analytics and automated campaign management to the rise of AI influencers and generative content, and what these changes mean for the human experience of authenticity, trust, and connection in the digital marketplace.

ABSTRACT. Drawing on human-object relationship theory, the current study explores the interactions and relationships that users have with their digital voice assistants. Twenty users were interviewed individually and in depth to understand usage and motivations, personal experiences and connectedness, emotional responses, and relationship development over time. Deductive-inductive coding analysis revealed several themes and categories that characterize individual value creation, attachment and rational and emotional responses in the user-device interaction. Building on these, distinctive types of relationships were derived that users form with their digital voice assistant. Overall, the results support the functional and efficiency benefits that users perceive. However, the findings also indicate that there are certain relationships that users establish with their voice assistants which differ in intensity and quality. The paper contributes to relationship theory and its application to the human-object context in consumer behavior research. It is one of the first to consider digital voice assistants as social companions with which users form attachments and build relationships. The paper concludes with a look at implications for management and future research directions.

ABSTRACT. In an increasingly competitive landscape of generative interfaces, limited research has examined the determinants of users’ preferences for specific generative AI (GAI) platforms. Drawing on literature on decision-making styles and AI output architectures, this study proposes that users’ preferences for GAI platforms are influenced by the cognitive fit between their individual decision styles and the platforms’ generative output architectures. This proposition is empirically tested using a sample of users who engaged with multiple GAI interfaces to address identical decision-making tasks. A content analysis of users’ discourse explaining their preferences reveals the critical moderating role of mutual knowledge (between the user and the system) besides the contextual constraints, on the cognitive fit between GAI architecture and decision style. The study contributes to the foundational understanding of AI’s impact on human decision processes by proposing a conceptual model of users’ GAI platform preferences and offering practical implications for platform differentiation and user satisfaction enhancement.

ABSTRACT. Advancements in AI are reshaping advertising by shifting creative work from human ideation to algorithmic content generation. AI enables fast, cost-efficient, and personalized production of visual, audio, and textual advertising materials. Despite rapid industry adoption, academic understanding of how AI-generated advertising influences consumer emotions and engagement remains limited. Emotions are central to advertising effectiveness, shaping attention, memory, brand perceptions, and behavioural intentions. Recent research highlights the importance of assessing emotions not only by valence but also by arousal intensity, as highly arousing positive emotions are particularly effective in driving engagement in digital environments. This study aims to reveal how AI-generated advertising shapes consumers’ emotional responses and engagement, and to examine the moderating role of ad origin perception. Findings show that AI-generated ads more often evoke high-arousal emotions, whereas human-created ads tend to elicit lower-arousal responses. High-arousal positive emotions, such as inspiration, increase consumer engagement, while low-arousal negative emotions, such as boredom, reduce it. Ad origin perception moderates these effects: when consumers correctly identify AI-generated ads and experience high-arousal positive emotions, engagement increases, although consumers frequently struggle to distinguish AI- from human-created advertising. These insights expand understanding of AI in advertising and provide guidance for designing emotionally effective AI-enabled campaigns.

ABSTRACT. As organizations increasingly deploy empathetic AI platforms in customer service, a critical question emerges: how do these interactions affect consumer politeness toward both AI and subsequent human service encounters? This research examines the paradoxical effects of empathetic AI on consumer behaviour within service ecosystems.

Drawing on politeness theory, social cognitive theory, and Liu-Thompkins et al.'s artificial empathy framework, we investigate how AI empathy influences consumer politeness and whether impoliteness spills over to human interactions. Through a multi-method approach combining qualitative interviews with 23 participants and a 2×2 experimental design with 320 participants, we examine interactions with functional versus empathetic AI configurations.

Findings reveal an "emotional uncanny valley" where empathetic AI paradoxically reduces consumer politeness compared to functional AI. Critically, this impoliteness transfers to subsequent human service interactions, suggesting AI establishes behavioral schemas that persist across interaction types. The empathy-ability gap—where emotional sophistication without problem-solving capacity—amplifies negative emotions rather than resolving them.

This research contributes novel theoretical insights into AI-mediated service encounters, introducing the emotional uncanny valley construct and demonstrating impoliteness spillover effects. Managerially, findings suggest prioritizing problem-solving over empathy in service failure contexts and preparing employees for AI-influenced consumer behaviours.

ABSTRACT. Chatbots are nowadays increasingly adopted in service encounters to replace traditional human-customer interactions. For this reason, understanding how their design affects user experiences is critical. This study investigates whether chatbot language style (formal vs. informal) influences users’ satisfaction with the interaction and examines the mediating roles of both perceived social presence and interaction quality. We conducted a between-subjects online experiment using menu-based chatbots in an online pre-purchase service context. Results show that language style has no significant total or direct effect on interaction satisfaction. However, mediation analyses reveal opposing indirect effects. Informal language style increases perceived social presence, which in turn positively contributes to perceptions of interaction quality and interaction satisfaction through a serial mediation. On the other hand, informal language directly reduces perceived interaction quality, which further reduces users’ satisfaction. The findings demonstrate that chatbot language style influences satisfaction entirely through social and quality-related perceptions. The study contributes to chatbot anthropomorphism literature by showing that the language style adopted by chatbots may simultaneously enhance perceived social presence while also signaling lower quality. It also suggests that extending the model to incorporate additional mediators and moderators may help better understand the relationship between chatbots’ language style and users’ satisfaction.

ABSTRACT. This study explores how AI authorship labelling and thematic relatedness influence perceived source-message congruence, credibility, and consumer engagement in university social media communication. Drawing on schema congruity theory, it proposes that congruence between source and message topic enhances credibility perceptions and engagement intentions. A 2×2 between-subjects experiment (N = 372) manipulated AI authorship labelling (AI-labelled vs. unlabelled) and topic-relatedness (AI-related vs. non-AI-related). Results show that AI labelling increases perceived source-message congruence, particularly when content is thematically related to AI. Congruence significantly predicts source credibility (competence, empathy, goodwill, trustworthiness). Message credibility, with empathy and goodwill, most strongly drove engagement intentions. However, the direct effect of congruence on engagement was weak, indicating an indirect pathway through credibility. Sentiment analysis of open-ended responses revealed predominantly neutral emotional tone, with negative reactions linked to linguistic or visual cues suggesting AI authorship. The findings extend schema congruity theory to AI-mediated institutional communication, showing that AI labels enhance evaluations when thematically coherent and that affective dimensions of source credibility and message credibility are key drivers of consumer engagement on social media.

ABSTRACT. The integration of AI tools into creative marketing communication processes raises debate about its impact on consumer perceptions. The contradictions in previous research highlight the need to examine how consumers evaluate AI-generated marketing content and how content authorship shapes biases and technological resistance. This study investigates the impact of human- versus AI-generated visual content on consumer responses, focusing on content visual appeal, perceived authenticity, and the moderating role of technology aversion. An experimental design was applied between subjects manipulating content authorship (human vs. AI) and level of technology resistance (high vs. low). The study data were collected from 352 individuals who participated in the experiment. The results revealed that human authorship significantly increased both perceived processing fluency and aesthetic appeal, particularly among participants with high levels of technology aversion. Visual appeal predicted higher perceived authenticity, which in turn predicted stronger behavioral intentions. However, aesthetic perception exerted a weaker influence on authenticity than processing fluency. From a practical perspective, brands should emphasize human creative input in AI-generated materials, particularly when addressing audiences skeptical of AI-related technology. A hybrid creative strategy - combining AI’s efficiency with the authenticity of human expression - can sustain both credibility and long-term consumer engagement.

ABSTRACT. This research investigates how consumer religiosity asymmetrically shapes perceptions and evaluations of advertising messages containing religious cues. Drawing on Schema Theory and Social Judgment Theory, two complementary studies examined the interaction between individual religiosity and message religious strength. Study 1, a controlled online experiment with data from MTurk, tested three versions of an advertisement varying in religious intensity (low, moderate, high). Results confirmed that perceived message religiosity increased with message strength and that individual religiosity moderated this perception asymmetrically—low-religiosity individuals perceived highly religious ads as more religious, whereas high-religiosity individuals perceived weakly religious ads as more religious. Study 2, a 3 × 3 Google AdWords field experiment across six U.S. states differing in religiosity, measured behavioral engagement through ad click-through rates. Results supported the hypothesized asymmetry and indicated that evaluation patterns plateaued at high message intensity for highly religious consumers and at low intensity for less religious consumers. Together, the findings reveal that religious cues in advertising result in distinct perceptual and attitudinal patterns depending on consumer religiosity. The research contributes to marketing practice by demonstrating the need for controlling religious message strength so as to maximize appeal and minimize audience resistance across religiosity levels.

ABSTRACT. Shopping has become more convenient and accessible than ever before, thanks to the rise of e-commerce. This shift has completely transformed the way people buy and sell products. With advancements in digital technology, better internet connectivity, consumers can now shop from almost anywhere in the world and have access to a vast selection of products and services, giving shoppers countless choices before they make a purchase. This has resulted in intensified competition among online retailers of both local and foreign products as they strive for customer attention through various visual stimuli, often referred to as visual attention (VA). Among the various factors/ information cues that affect consumer purchase decisions in ecommerce, top-down information cues such as country of origin (COO) information and bottom-up visual cues stand out as particularly impactful. Although there have been numerous studies on COO and salient stimulus driven cues on visual attention, our study explores if salience can be overshadowed by other cues cued by the bottom-up stimulus driven cue paradigm. Hence, this study explores how neuromarketing can impact purchase intention, through a controlled experiment using top down and bottom-up visual cues with regards to aspects of COO, salient and non-salient cues in Ghana.

ABSTRACT. This research explores how anthropomorphism, specifically through the evocation of different types of cuteness, impacts prosocial behavior. Across two main experiments and supplemental studies, we investigate whether anthropomorphized advertisements designed to trigger Kindchenschema cuteness, characterized by baby-like features, are more effective in fostering prosocial behaviors compared to those eliciting whimsical cuteness, associated with playfulness, or no anthropomorphism. Our findings demonstrate that anthropomorphism that triggers Kindchenschema cuteness enhances compliance with prosocial appeals by activating nurturing instincts, leading to increased donations and positive prosocial responses. In contrast, anthropomorphism that evokes whimsical cuteness shows limited effectiveness in promoting prosocial behavior. By examining these distinctions, we extend the literature on both anthropomorphism and cuteness, revealing the critical role of Kindchenschema cuteness in enhancing prosocial actions, while identifying the limits of whimsical cuteness. These insights provide valuable implications for practitioners in prosocial and marketing domains seeking to optimize their messaging strategies.

ABSTRACT. In the evolving financial services landscape, fintech firms have emerged as digital-first challengers to traditional institutions, offering personalization, speed, and convenience through advanced technologies. However, while these innovations promise enhanced user experience, consumer perceptions remain mixed, particularly regarding trust and service quality. This study addresses a key gap in the literature by conducting a large-scale comparative analysis of consumer perceptions of fintech and traditional financial institutions, using complaint narratives submitted to the U.S. Consumer Financial Protection Bureau (CFPB). Applying a multi-method text mining approach (sentiment analysis, topic modeling, and word co-occurrence analysis), the study analyzes 55,911 unstructured complaints to identify dominant service-related issues and temporal trends. Results show that both sectors face persistent challenges with communication and account management, while disputes and credit reporting are uniquely critical in fintech, and fraud is a major concern for traditional institutions. The findings contribute to marketing and consumer behavior research by demonstrating how consumer-generated complaint data can reveal nuanced insights into the financial service experience through text mining techniques. Managerially, the results inform strategies for improving chatbot interfaces, fraud detection, and consumer communication systems, ultimately enhancing service design and aligning operations with evolving consumer expectations in digital finance.

ABSTRACT. This study aims to systematically assess the use of behavioral reasoning theory (BRT) within academic literature, focusing on behavioral complexities in consumer decision-making process. This study employs a hybrid systematic literature review of Web of Science bibliometric data (185 articles, 2020-2025). The study examines network metrics, while utilizing science mapping techniques to uncover thematic clusters and conceptual relationships in BRT applications. The study presents four themes which represents the reasons for and against the behavioral intention formation, the behavior intention formation and execution and the rise of artificial intelligence and immersive media to assess the reasoning of behavior. Additionally. the study highlights significant research gaps, particularly the need for more cross-cultural validations and methodological innovations in BRT research. The study also presents 10 research propositions on future research directions. Future studies should focus on integrating BRT with emerging technologies and addressing its application in mitigating risks, resistance to consumer innovation contexts in AI adoption. Business organizations should leverage BRT principles to design more effective motivation systems that align with developing marketing strategies that address consumers' complex reasoning patterns in purchasing decisions.

ABSTRACT. Intentions to donate strongly predict actual charitable behavior, highlighting the need to understand both motivating and inhibiting factors. This study examines how uncertainty—comprising skepticism, ambivalence, and perceived risk—affects donation intentions, and how endorser reputation and social media involvement help mitigate it. Grounded in signaling theory and Bourdieu’s concept of symbolic capital, endorser reputation is viewed as a legitimacy cue that reduces perceived ambiguity and risk, while social media involvement enhances engagement and access to trustworthy information. Data were collected via a representative online survey of 1,049 Lithuanian respondents and analyzed using partial least squares structural equation modeling (PLS-SEM). Results show that uncertainty has a strong negative effect on donation intentions. Endorser reputation significantly lowers uncertainty and directly increases donation intentions, with partial mediation through uncertainty. Social media involvement exerts a weaker but significant negative effect on uncertainty and a strong positive effect on intention. These findings reveal that symbolic capital and digital engagement influence charitable intentions through distinct mechanisms: reputation primarily reduces perceived uncertainty, while social media involvement drives motivation and emotional connection. The study contributes to understanding uncertainty reduction in charitable giving and offers practical guidance for building trust and enhancing donor participation.

ABSTRACT. This study examines how moral identity and bandwagon effects jointly shape individuals’ intention to donate money to social causes, emphasising the interplay between moral motivation and social influence. While charitable giving is often viewed as a reflection of empathy and moral responsibility, this research argues that donation behaviour can also be driven by the desire to align with others’ actions. Drawing on Social Identity Theory, the study proposes that both moral identity and bandwagon tendencies directly influence donation intentions, and that these effects are also mediated by individuals’ engagement with social causes on social media. Survey data from respondents with prior donation and social media experience were analysed using a structural equation modelling. The findings show that moral identity and bandwagon each contribute significantly to the intention to donate, though they operate through different mechanisms. Moral identity primarily exerts a direct moral influence, whereas the bandwagon effect acts more strongly through social media engagement, reflecting conformity and social validation. By integrating moral and social drivers, this study broadens the understanding of charitable giving, showing that donations are not only moral acts, but also social behaviours shaped by collective influence.

ABSTRACT. Superheroes, often portrayed as moral exemplars, are widely used in marketing contexts to inspire prosocial behaviour. Yet, the real-world effectiveness of the superhero concept in fostering prosocial actions among consumers remains underexplored. Through four interconnected studies, this paper investigates how the superhero concept can be leveraged in marketing communications to enhance consumer prosocial behaviours. Study 1 qualitatively explores the superhero concept and investigates its potential impact on prosocial behaviour. Study 2 shows how exposure to and value congruence with superheroes promote prosociality. Studies 3 and 4 employ controlled classroom and field experiments to establish causality between superhero priming and prosocial actions. The results offer theoretical insights and practical implications for marketing communication and consumer well-being, demonstrating how brands can harness superhero narratives to nudge consumers towards acting in a prosocial manner.

ABSTRACT. Virtual humans (VHs) are synthetic personas designed to mimic human influencers and are becoming increasingly prominent on social media. Their artificial nature introduces identity ambiguity, defined as consumer uncertainty about whether the persona is human or machine. This study examines how linguistic cues in VH-generated content influence perceptions of authenticity, emotional tone, and social cohesion, and how these cues affect user engagement and identity-questioning behavior. Drawing on the Computers-As-Social-Actors (CASA) paradigm, social presence theory, and parasocial interaction theory, we analyze 396 Instagram posts and 12,784 follower comments from three VH profiles using validated psycholinguistic tools. Results show that identity-questioning comments exhibit higher linguistic authenticity and lower emotional tone, and receive significantly greater engagement. The study also reveals that VH content with greater authenticity and cognitive complexity increases the likelihood of identity-questioning. In contrast, language characterized by emotional positivity and collective identity reduces both the incidence and frequency of such comments. These findings reveal a communicative paradox in which efforts to humanize VHs can heighten ontological scrutiny. The study advances theoretical understanding of AI-mediated engagement by identifying linguistic mechanisms that shape identity perceptions. For practitioners, the findings offer guidance for designing VH communication that reduce identity ambiguity and foster consumer trust.

ABSTRACT. This study examines the effectiveness of real versus fake brand apologies in social media crises. While genuine apologies acknowledge responsibility and express authentic remorse, fake apologies mimic apologetic language without accountability, often shifting blame or minimizing the offense. Building on Image Repair Theory and the Situational Crisis Communication Theory (SCCT), we differentiate between complete, incomplete, and fake apologies and test their effects on perceived sincerity, response efficacy, and negative electronic word-of-mouth (eWOM). We also integrated perceived sincerity as a moderator.

An online experiment (N = 334) exposed participants to a brand transgression and one of five response types: two real apologies (incomplete vs. complete), two fake apologies, or no response. Results show that apology "realness" and completeness significantly affect recipient perceptions. Under high-severity conditions, only complete and genuine apologies effectively reduced negative eWOM.

These findings extend existing crisis communication frameworks by conceptualizing fake apologies as hybrid strategies that imitate “rebuild” responses but functionally align with “diminish” tactics. Practically, the study highlights the importance of issuing long, authentic apologies - especially in serious crises - to protect brand reputation and restore trust.

ABSTRACT. This project explores if memorability of a consumption experience has an effect on short- and long-term future behavioural intention. More specifically, we seek answers to the question: does the effect of using social media during museum visits contribute to or detract from satisfaction with it and to future memory recall of the experience? This research is underpinned by theories of memory and review processes of encoding and decoding, distinguishing between short- and long-term memory (Braun, 1999; Ericsson, and Kintsch, 1995). The context of the study is the cultural services sector, specifically museums and art galleries. Data have been collected at an art gallery and two museums located in the United Kingdom which hosts a series of exhibitions. A quasi-longitudinal approach has been employed to track visitors to a museum/art gallery over three waves survey using largely quantitative measures to record changes in memorability and future behavioural intention over a six-month period. The findings show that social media engagement during an event has a positive effect on short-term memorability of that event, whereas this effect was not observed in the case of long-term memorability of that event. This study further shows the importance of emotions during an experience for memorability.

ABSTRACT. As artificial intelligence (AI) becomes increasingly integrated into smart cities to enhance efficiency and personalization, citizens face a growing tension between automation and perceived control. This study examines how perceived loss of control influences citizens’ intentions to adopt AI-driven smart city services, with subjective well-being as a mediator and flow and perceived personalization as moderators. Drawing on flow theory and personalization research, five studies using online experiments, exploratory analyses, and immersive laboratory and driving simulator settings (N = 998) investigate psychological responses to automation in smart home and smart mobility contexts. Across all studies, perceived loss of control significantly reduced subjective well-being and adoption intention. Flow and personalization acted as key moderators: in imagined scenarios, flow reduced the negative effects of control loss, whereas in real settings, high flow intensified discomfort when control was constrained. Perceived personalization consistently mitigated these reactions, reframing automation as adaptive and user-centered. The findings show that experiential context shapes how individuals perceive and emotionally respond to AI autonomy, advancing understanding of comfort and trust in automated environments and offering insights for designing emotionally intelligent AI ecosystems that balance automation, personalization, and well-being.

ABSTRACT. This study investigates the factors influencing users’ continued use of generative AI search engines, such as ChatGPT and Microsoft Copilot, which combine information retrieval with conversational intelligence. Building on the Technology Acceptance Model (TAM), an extended framework was developed that integrates both functional (information quality, system quality) and anthropomorphic social (anthropo-social interaction) determinants. Data from 487 Taiwanese users were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results confirm that perceived ease of use and perceived usefulness significantly shape user attitudes, which in turn drive continued usage intention. System quality exerts the strongest functional influence, while information quality primarily enhances ease of use. Anthropo-social interaction—combining anthropomorphism and parasocial engagement—also positively affects both ease of use and usefulness, highlighting the role of human-like cues in sustaining engagement. These findings extend TAM by incorporating relational and social-cognitive dimensions relevant to AI interfaces. The study offers theoretical insights into human–AI interaction and practical guidance for developers to enhance system reliability, conversational naturalness, and emotional responsiveness in generative AI search tools.

ABSTRACT. Artificial intelligence (AI) is transforming online fashion retail through personalised recommendations, predictive interfaces, and chatbots that enhance convenience and engagement. However, this technological evolution also heightens concerns about surveillance, autonomy, and data privacy, illustrating a persistent personalisation–privacy paradox. This study explores how consumers perceive and respond to AI-mediated tools in fashion e-commerce, emphasising the psychological and ethical dynamics underlying their experiences. Grounded in the Stimulus–Organism–Response (SOR) framework, Self-Determination Theory (SDT), and Nudge Theory, it employs a quantitative exploratory design to analyse behavioural and attitudinal patterns related to AI-enabled personalisation. Findings from descriptive analysis suggest that AI often operates implicitly, influencing consumer decisions through convenience and subtle recommendation cues rather than explicit technological awareness. Trust, perceived autonomy, and emotional valence emerge as salient psychological factors shaping consumer engagement. The study contributes to theory by conceptualising personalisation as both a technological and ethical stimulus and by extending models of AI-mediated consumer behaviour. From a managerial perspective, it advocates ethical personalisation, transparent, authentic, and autonomy-supportive AI practices that align technological efficiency with human values and reinforce sustainable competitive advantage in digital fashion retail.

ABSTRACT. The study aims to further develop the Artificial Intelligence Device Use Acceptance (AIDUA) model to predict consumer use of generative AI tools in high-involvement purchases, such as quality electronics. It concentrates on analysis how anthropomorphism and social impact influence consumers’ cognitive and affective attitudes toward the use of AI tools in purchasing, aiming to highlight which factors gain higher importance in purchasing high-involvement products. To achieve this, first the strength of impacts was tested on the basis of developed hypotheses; then the predictive value of alternative models was assessed with the help of model comparisons using CVPAT. Based on empirical analysis, we found stronger total impact of anthropomorphism on intention than that of social impact; cognitive attitude had stronger direct impact on intention than affective attitude. Subsequent model comparisons assured that anthropomorphism is more effective predictor than social impact. Similarly, findings indicate that cognitive attitude enhances the model’s out-of-sample predictive accuracy and represents a more effective explanatory pathway toward intention than affective attitude. Consequently, we found that the model with cognitive attitude as the sole antecedent of behavioural intention remains more parsimonious for future studies when the use of AI in purchasing high involvement product is considered.

ABSTRACT. The rapid adoption of Generative AI (GenAI) platforms like ChatGPT presents a critical monetisation challenge for these firms, as high operational costs contrast with low conversion rates from free to paid tiers. This research investigates user engagement responses to alternative monetisation models, particularly advertising-supported options, within the unique conversational and task-oriented context of GenAI. Drawing on the compromise effect and affective primacy theory, we examine how introducing advertising models influences user preferences and engagement, moderated by perceived intrusiveness. Across four experimental studies (N = 1,063), we find that advertising-supported models can act as effective compromise options, increasing upgrade intentions among free users. Moreover, multiple compromise options increase task difficulty, leading free users to upgrade but paid subscribers to resist downgrading. Critically, findings reveal that temporal intrusiveness (advertisement duration), rather than visual intrusiveness, significantly impacts platform engagement. Counterintuitively, longer advertisements elicited higher engagement, mediated sequentially by less negative initial affect and more positive cognitive evaluations. This research extends behavioural decision theories to GenAI monetisation, highlighting the primacy of affective responses to temporal advertisement elements and offering practical guidance for balancing profitability and user experience on these emerging platforms.

ABSTRACT. The Metaverse—powered by virtual reality, augmented reality, and artificial intelligence—constitutes an evolving digital ecosystem that merges physical and virtual experiences through immersive, avatar-based interactions. Despite its rapid growth, limited academic insight exists into the mechanisms shaping sustained engagement and consumer behavior in such environments. This qualitative study investigates how brand authenticity, aesthetic immersion, and user-centric design influence user engagement and the adoption of both virtual and physical branded products. Drawing on insights from 25 industry experts and 48 active Metaverse users, it proposes a multidimensional framework encompassing sensory, cognitive, emotional, social, and ethical facets of engagement. Key enablers include adaptive avatars, narrative coherence, branded virtual assets, and decentralized economies. Artificial intelligence emerges as a pivotal driver of real-time personalization, emotionally intelligent interactions, and sustainable brand ecosystems. The findings advance theoretical understanding of virtual identity formation while offering strategic guidance for ethically responsible and sustainable brand engagement in immersive digital contexts.

ABSTRACT. In today’s marketing landscape, influencers have become one of the most powerful intermediaries between brands and their audiences, especially among Millenials. Despite this growing relevance, how the mere presence of an influencer in social media advertising affects Millennials’ attention remains underexplored.

This study investigates the impact of influencer presence on Millennials’ attention to social media ads by applying neuromarketing techniques, specifically eye-tracking and explicit memory tests. By analyzing fixation metrics and recall performance, the study provides insights into how influencers influence visual attention and memory processes in digital advertising contexts. The findings contribute to the growing body of research on overcoming banner blindness - the tendency of users to ignore online ads - by examining whether influencers can serve as attention-enhancing stimuli that help brands better capture and retain audience focus.

ABSTRACT. This study investigates the role of comparative ad format, message sidedness, Need for Cognition and familiarity with Direct Comparative Advertising (DCA) on consumer response to advertising. A 2*2*2 between-subjects experimental design was employed with ad format (direct or indirect comparative), message framing (one or two sided), and need for cognition level (low or high). Canadian respondents (n=364) were recruited online. The Elaboration Likelihood Model and mere exposure effect informed theoretical expectations. Direct and Indirect comparative ads are equally embraced by Canadian consumers. While, one-sided comparative ads attract greater purchase intent, two-sided comparative ads generate greater confidence in consumer’s attitudes, offering the potential for more resistance to future competitive attacks. Hence a cautious use of two-sided comparative ads is recommended. Theoretically, the study offers novel evidence on the mediating role of analytical processing in the relationship between Need for Cognition and attitude certainty and the mediating role of the latter in shaping the relationship between analytical processing and purchase intention. This findings support the mere exposure effect, as a positive role of familiarity with DCA on the acceptance of comparative was found. Ads which employ this format may be strategically targeted at segments with greater familiarity with direct comparisons.

ABSTRACT. This paper investigates how visual elements on B2B websites influence brand credibility. While professional web design is identified as critical, the specific contribution of visual elements, such as color, typography, layout, and imagery remains underexplored, especially in B2B context. Using a mixed-methods approach, the study first reviews relevant literature on emotional design and cognitive trust formation, then conducts a comparative case study of four leading B2B websites and finally conducts an online survey assessing user responses to systematically varied visual manipulations featuring the different visual design elements. Results demonstrate that while structured layouts and readable typography lay the foundation for trust, the most significant increases in perceived credibility arise from brand-appropriate color schemes and authentic imagery, particularly when combined. The study thus supports a multi-layered trust model integrating cognitive clarity with emotional resonance, offering tangible managerial implications for enhancing the B2B web presence.

ABSTRACT. This study investigates the influence of psychological and emotional elements on green purchase intentions. With the growing environmental concern in recent years, understanding these elements is essential for the development of effective green marketing campaigns. The research explores the relationship between key constructs such as green consumer values, psychological reactance, sense of belonging in a community, subjective well-being and scepticism towards advertising. By integrating and drawing on several theories such as Psychological Reactance Theory and Belongingness Theory, this study proposes a comprehensive conceptual framework. Results from a survey of 200 consumers demonstrate the complex relationships between these psychological and emotional variables and consumers' intentions to purchase green products, emphasising the mediating effect of subjective well-being and the moderated mediating effect of scepticism towards advertising. These findings provide theoretical contributions to environmental psychology and green marketing and offer valuable insights and practical implications for marketers who aim to design effective green marketing strategies.

ABSTRACT. Human activities consume resources beyond the Earth’s biocapacity, causing severe environmental degradation (Schiaroli et al. 2024). Consumers play a pivotal role, as choices related to reduced consumption, product longevity, and reuse or recycling directly shape sustainable market mechanisms (Peattie 2010). Sustainable products have become a central focus (Trudel 2019) because they are recognized as a significant lever for promoting and impacting responsible consumption (Wagner et al., 2019) but more sustainable production models are still needed (Zhang et al. 2021). While previous studies have sought to deepen the understanding of this role (Lv et al. 2024), establishing a clear link between sustainable products and consumer decision-making remains challenging, with research yielding mixed results (Bangsa and Schlegelmilch 2019). Therefore, it’s crucial to understand why sustainability awareness and positive attitudes toward sustainable products do not necessarily translate into actual purchasing behavior (Wiederhold and Martinez 2018). This research will try to answer this question and complete it by focusing on eco-designed products attributes. We conducted a qualitative study with 19 consumers (June–July 2025) and highlighted 4 types of consumption from moral conviction to pragmatic compromise, critical vigilance, and economic constraint, illustrating the multifaceted nature of engagement with sustainable consumption and behavior.

ABSTRACT. Sustainability has become a major factor shaping how companies influence consumer purchasing decisions and strengthen brand-consumer relationships (Das et al., 2024). Consumers are no longer satisfied with simply being “green” through actions such as recycling, saving electricity, or returning bottles; they now expect brands to adhere to higher sustainability standards and to communicate their environmental commitments transparently. As sustainability becomes a defining element of consumer-brand relationships, companies increasingly rely on sustainability-centric messages to demonstrate their environmental responsibility and build trust (Odoom et al., 2025). However, while brands continue to invest heavily in green marketing, little is known about how the framing of sustainability messages, particularly whether they emphasize individual, collective, or general contributions, affects brand appeal. This issue is crucial, as not all sustainability messages achieve the intended effects (Huang et al., 2024). Accordingly, this study investigates how distinct sustainability message frames shape consumers’ perceptions of brand appeal (measured through brand attractiveness and brand attitude) and examines the mediating role of perceived personal relevance.

ABSTRACT. Climate change is a major global threat, prompting individuals to increasingly adopt pro-environmental behaviours. A key action is the sharing of used goods via online platforms, which reduces environmentally damaging demand for new manufacturing and delays product disposal. This study examines the factors that drive consumers to continue sharing their used items, focusing on the interplay between extrinsic motivation (economic benefits) and a vital intrinsic motivation: Consumers’ Product Sharing for Reuse Engagement (PSRE). Drawing on Self-Determination Theory (SDT), we conceptualize PSRE as a consumer's investment of cognitive, emotional, and behavioural resources in the act of passing on used items for reuse. The study conceptualizes PSRE's positive effect on continuation intention is partially mediated by the enjoyment consumers derive from a smooth sharing process. The research establishes a motivational substitution effect: high levels of intrinsic PSRE negatively moderate the influence of extrinsic economic benefits on sharing continuation intention. This finding suggests that as a consumer’s intrinsic sustainability commitment grows, their reliance on monetary rewards to sustain the pro-environmental behaviour decreases. These results offer crucial theoretical insights into motivational interplay and provide actionable strategies for sharing platforms to shift from purely economic incentives to fostering a rewarding, intrinsically driven pro-environmental user experience.

ABSTRACT. Firms increasingly promote sustainable delivery options, yet consumers often hesitate to pay the associated green premiums. This paper investigates how solution-oriented communication and transparency regarding the use of sustainability fees influence consumers’ willingness to pay for environmentally responsible delivery services. Drawing on Value-Belief-Norm (VBN) theory, the study examines whether pro-environmental orientation serves as a psychological bridge between communicative strategies and consumer behaviour, linking moral values, beliefs, and personal norms to purchase intent. A quantitative analysis demonstrates that both clear, action-focused communication and transparent disclosure of green fee allocation significantly enhance willingness to pay among online consumers, with pro-environmental orientation acting as a partial mediator. These findings extend the explanatory power of the VBN framework in the context of consumer logistics and illustrate how credible, solution-based sustainability messaging can transform environmental concern into behavioural commitment. The study advances understanding of how marketing communication can bridge the gap between ecological aspiration and economic decision-making, offering both theoretical refinement and actionable insights for firms aiming to foster consumer participation in sustainable delivery.

ABSTRACT. As climate change intensifies, understanding the drivers of pro-environmental consumer outcomes becomes increasingly important. One such driver, materialism, plays a complex role: it has historically been linked to consumerism and economic growth but may also conflict with pro-environmental objectives. Despite growing scholarly interest in pro-environmental outcomes, the evolving landscape of public policy, societal values, and consumer awareness calls for an updated synthesis of how materialistic values influence pro-environmental attitudes and behaviours. Of the 124 studies identified in a preceding systematic literature review, 37 empirical papers met the inclusion criteria and were included in the meta-analysis. While most studies reported a negative relationship between materialism and pro-environmental behaviour, an increasing number of studies have found non-significant or even positive relationships. The pooled effect sizes revealed a small overall negative association between materialism and pro-environmental outcomes, with mean correlations of r = -0.10 for attitudes, r = -0.10 for intentions, and a near-zero effect for behaviour (r = 0.00). These findings open new avenues for theoretical development by suggesting the coexistence of two behavioral orientations once viewed as incompatible. Materialism may have multifaceted associations with pro-environmental behaviour that vary across behavioral domains, cultural contexts, and potentially distinct motivational forms of materialism.

ABSTRACT. This study investigates the role of anticipated inaction regret in shaping consumers’ intentions to disclose personal information online. Drawing on regret regulation theory, the research demonstrates that consumers may disclose personal data not only for rational benefits but also to avoid the emotional discomfort of missing out. Using data from 498 U.S. participants in an online fashion retail context, the findings reveal that anticipated inaction regret significantly predicts disclosure intentions, mediated by the formation of disclosure habits. Moreover, this mediation effect is pronounced among promotion-oriented consumers, who are more sensitive to rewards, compared to prevention-oriented individuals. These insights contribute to the understanding of emotional and habitual drivers of privacy behavior in e-commerce.

ABSTRACT. Social media provides a highly effective environment for companies to advertise their products. However, its use is often linked to negative consequences, where social media fatigue is among the most discussed. Understanding the mechanisms that drive social media fatigue and its outcomes is a critical research focus. Using the stress-strain-outcome framework, this study examines how fear of missing out (FOMO) and brand content overload act as stressors that contribute to social media fatigue (strain), and how fatigue, in turn, leads to two behavioral outcomes: intentions to lurk or to discontinue use of visually oriented social media platforms. Additionally, this study investigates the mitigating role of social support in the FOMO-fatigue relationship. Findings from a survey of 261 respondents confirm that FOMO and brand content overload positively influence social media fatigue, while social support negatively moderates the relationship between FOMO and fatigue. Furthermore, it was revealed that social media fatigue results in two distinct behavioral outcomes: lurking and discontinuation intentions, which represent different coping strategies for managing experienced strain. This research advances the social media fatigue literature in three ways: by identifying mitigating factors, new antecedents, and outcomes, and by explaining the mechanisms behind them.

ABSTRACT. Applications have transformed our lifestyles. With the advent of the Internet of Things sector, our dependence on applications is expected to increase as our smartphones become increasingly integral to our connected lives. Nowadays, the lifespan of a mobile application is diminishing rapidly, even as the annual production of applications continues to grow. It is crucial to identify the factors that affect an application’s quality and the reasons why users might decide to uninstall it. This study used SEM on two cultural settings of Malaysia (Eastern country, n= 269) and France (Western country, n= 243). Even though both samples showed that user expectation, negative flow experience, and privacy concerns are the main factors in hesitation to uninstall an app, the hypothesis on app addiction is only supported for Malaysian sample. Interestingly, intrusive adds were found irrelevant to hesitation to uninstall an app. Applying multi-group analysis, in Malaysia sample, the results showed that male users are more concerned about their privacy and iOS users consider ads more intrusive compared to Android users. In French sample, in terms of category of recently uninstalled app, ads in social apps are more intrusive than entertainment apps and Android users are more concerned about their privacy.