As algorithmic intelligence becomes increasingly sophisticated, consumers may perceive not empowerment but erosion of autonomy. This research introduces Algorithmic Autonomy Erosion (AAE) as a distinct psychological mechanism explaining why highly intelligent AI systems can undermine trust. Across three studies a scale development, a controlled experiment, and a large-scale-survey results demonstrate that perceived algorithmic intelligence reduces trust indirectly through heightened autonomy erosion and subsequent psychological reactance. Evidence for a nonlinear effect is mixed. By shifting the focus from performance to perceived authorship displacement, this study advances theory on AI trust and consumer agency.
Luxury fashion brands have shifted their advertising focus from traditional magazines to social media platforms, marking a transition from ad-context congruence to incongruence. However, its impact on luxury perception remains underexplored. This study investigates how ad-context congruence and processing fluency influence consumers' luxury perception, with brand familiarity as the moderator. Using an experiment on a simulated Instagram feed, results reveal that ad-context congruence enhances luxury perception for unfamiliar brands, while well-known brands maintain strong luxury associations even in incongruent contexts. Interestingly, processing fluency is negatively related to luxury perception, suggesting that greater cognitive ease may dilute perceptions of exclusivity.
Drawing on social-presence-theory, we analyze the impact of users' social-presence on engagement, hedonic-benefits and anthropomorphism, which consequently effects their continuance-intention in metaverse-gaming. Using PLS-SEM, we analyze responses from metaverse gaming users, and results reveal that social presence significantly increases engagement, hedonic benefits and anthropomorphism. Engagement and anthropomorphism significantly effect continuance intention, while hedonic benefits do not exhibit a significant effect. Both engagement and anthropomorphism mediate the association between social presence and continuance intention. Further, user experience moderates the relationships by strengthening the effect of engagement on continuance intention while weakening the effect of anthropomorphism, offering important theoretical and practical insights.
This research examines the influence of eco-anxiety on pro-environmental behavioral intention in an emerging sustainable tourism market. Drawing on the Affect-Cognition-Behavior (ACB) framework, it further investigates the mediating role of ascription of responsibility and the moderating effect of ethical mindset. Data from 385 respondents were collected through an online survey and analyzed using Structural Equation Modeling. The findings reveal that eco-anxiety positively influences pro-environmental behavioral intention both directly and indirectly through ascription of responsibility. Moreover, an ethical mindset amplifies the indirect effect of eco-anxiety on pro-environmental behavioral intention through ascription of responsibility, suggesting that individuals with a stronger ethical mindset are more likely to transform environmental concern into personal responsibility and action. This research contributes to value-behavior literature by clarifying the psychological mechanism linking eco-anxiety and pro-environmental behavior and offers practical implications for tourism operators and policymakers promoting sustainability.
This study explores how leading luxury brands engage with the United Nations' Sustainable Development Goals (SDGs) and how these commitments are reflected in their marketing strategies. By integrating Sustainable Marketing Action Framework with the SDGs, the research provides a structured lens for understanding sustainable marketing in the luxury sector. A descriptive content analysis of luxury brand websites was conducted to assess both explicit and implicit engagement with the SDGs. Findings reveal that luxury brands most frequently align with SDG 12 (Responsible Consumption and Production), SDG 17 (Partnerships for the Goals), SDG 15 (Life on Land), and SDG 9 (Industry, Innovation, and Infrastructure). In contrast, SDG 5 (Gender Equality) and SDG 8 (Decent Work and Economic Growth) are less frequently addressed. Using the Sustainable Marketing Action Framework, the study shows that brands primarily focus on redesigning products and services and repurposing elements of the marketing mix, rather than on systemic drivers such as reorganizing the marketing function or promoting responsible consumption. This is the first study to examine the relationship between luxury, sustainable marketing actions, and the SDGs, demonstrating how luxury brands are selectively engaging with the SDGs to fulfill market-facing core competencies.
This study explores the influence of sustainable brand identity, content quality, and social media brand communication on emotional and attitudinal responses among Indian Millennials and Gen Z. A sample of 586 digitally active customers was analyzed using partial least squares structural equation modeling and multi-group analysis, grounded in the Stimulus-Organism-Response framework and Engagement Theory. The findings highlight emotional responses as key mediators and reveal generational and gender-specific trends in engagement. The study offers empirical contributions to sustainable fashion branding by emphasizing emotional relevance and demographic sensitivity, guiding marketers in building loyalty among eco-conscious young customers in emerging markets.
Many scholars hold two widely shared beliefs: first, serious research appears to require large blocks of uninterrupted time and sizable funding, and second, unusually high publication productivity often triggers suspicion, partly from a harsh publish-or-perish climate and partly from legitimate concern about honorary authorship, paper mills, and irresponsible use of artificial intelligence. This article challenges both assumptions by advancing one counterintuitive claim-that is, publication output can rise under ordinary resource conditions when scholars treat research as a design problem and align project types with available time, data, collaborators, and funding-and one paradoxical claim-that is, quantity can strengthen quality when repeated writing sharpens judgment, reviewing strengthens evaluative skill, and a portfolio of conceptual, review, secondary data, and empirical projects supports cross-project learning. To make these claims concrete, this article calculates what sustained 200-word writing routines can produce over a year while clarifying that writing is only one component of the research process, alongside reading, idea generation, instrument design, ethics applications, data collection, data cleaning, data analysis, revision, reviewer response, and coordination with co-authors. To make these points actionable, the article presents a practical toolbox of time pathways, funding pathways, staged pathways, ethical guardrails, and global marketing applications. Overall, ethical productivity is not about chasing numbers but about creating strong research more consistently, responsibly, and sustainably.
Artificial intelligence (AI), including generative AI, is transforming marketing communications (MarCom) by changing how content is created, personalized, distributed, and assessed. However, MarCom research is scattered across tool-focused streams and lacks an implementation-oriented synthesis that fits MarCom's creative and relational work. We develop a seven-dimensional strategic framework for AI integration in MarCom via a systematic review of 76 peer-reviewed articles indexed in Scopus and Web of Science (2020-2025), followed by structured expert validation. Using PRISMA screening, bibliometric mapping, and a hybrid deductive-inductive thematic synthesis, we identify seven interdependent dimensions: (1) human-AI collaboration design, (2) efficiency and workflow redesign, (3) methodological rigor and evaluation, (4) analytics and data readiness, (5) tool selection and integration, (6) staged implementation and change management, and (7) continuous adaptation and learning. The framework is presented as evidence-informed guidance, not a maturity benchmark; observed quantitative patterns describe the reviewed corpus rather than population adoption. We discuss MarCom-specific tensions (authenticity vs automation, personalization vs privacy, speed vs brand safety) and propose a focused agenda for testing human-AI configurations and governance in campaign settings.
Despite the well-documented benefits of precision on consumer adoption rates, the impact of the degree of precision in personalized recommendations on consumer engagement is less understood. Utilizing a series of experiments across four studies, we investigate the extent to which precision influences consumer engagement with the recommended information. Contrary to conventional wisdom and existing findings, our results indicate that high precision in recommendations often decreases click-through intention. This effect is driven by an increase in consumer cynicism and a decrease in their sense of autonomy. However, these negative responses are mitigated when highly precise recommendations align with consumers' consumption goals and the appropriate timing of exposure. As highly precise recommendations grows and concerns over consumer privacy intensify, understanding consumer responses to such precision is increasingly vital. This study provides a detailed analysis of the interplay between consumer perceptions and the precision of personalized recommendations, delivering crucial insights for marketers aiming to balance precision with consumer-perceived privacy in the dynamic realm of personalized marketing.
Instagram is among the most popular social media platforms globally. While individuals tend to engage with it and disclose their thoughts and feelings, the mechanism by which this is impacted by personality traits remains incompletely understood. Additionally, the role of trust that is of key importance in information disclosure remains unclear in this regard. We address this gap by testing the moderation of trust on the impacts of neuroticism and narcissism. Partial least squares structural equation modelling on data from 298 respondents revealed opposite moderating effects of trust on the effects of two personality traits, providing novel theoretical insights.
