Business, Economics and Management

Abstract: This paper explores the role of Artificial Intelligence (AI) in shaping consumption, and the contribution AI might make to transitioning to a responsible consumption and production regime, in line with Goal 12 of the UN Sustainable Development Goals. The paper draws on Practice Theory, an established framework for studying sustainable consumption practices. Based on this framework, the Authors suggest that whilst in traditional consumption, the expertise required to consume resides in human subjects, in AI shaped consumption this expertise resides in AI algorithms. This may have implications for consumers’ agency and can put them at disadvantage. Indeed, the EU has proposed regulations to control the use of AI by providers. The paper draws on two case studies, Ant Forest, a Chinese app which prompts consumers to adopt responsible consumption practices and Mobility as a Service, a platform-based mobility offering. We find that whilst the former contributes to establishing consumers’ expertise in sustainable behaviour, for example through gaming, the latter may remove consumers’ choice by performing some of the consumption practices itself, such as selecting sustainable means of transportation. Our contribution is the formulation of a version of Practice Theory which is adapted to AI

Abstract: This study examines how AI-generated product images and original photographs shape user engagement in C2C second-hand fashion e-commerce. While generative artificial intelligence increasingly enables sellers to improve the aesthetic quality of product presentation, little is known about how synthetic imagery affects actual platform behavior rather than stated consumer preferences. Drawing on signaling theory and the stimulus–organism–response model, the study reports a field experiment conducted on Vinted across two seasonal waves. The experimental design compared paired listings using original photographs and AI-generated product images, with engagement measured through views, likes, inquiries and transactions. The findings reveal a seasonal reversal: AI-generated images produced more favorable attention-related indicators in the autumn–winter wave, whereas original photographs performed more favorably in the spring–summer wave, especially for conversion-related indicators. The results suggest that the effectiveness of AI-generated imagery is conditional rather than universal and depends on the balance between aesthetic refinement, visual authenticity, perceived risk and product-verification needs. The study contributes to electronic commerce research by showing how AI-generated visual content operates as both an aesthetic and trust-related signal in C2C markets. It also provides implications for sellers and platform operators regarding transparent and responsible use of synthetic product imagery.

Abstract: This study presents DynRFM-Hazard, a transparent framework for prioritizing manual review of historical customers at a medical-aesthetic institution. Continuous RFM values and seven exponentially decayed category-specific purchase-memory variables define a ten-variable customer state. Three regularized logistic models estimate first positive-payment probabilities in days 0-30, 31-90, and 91-180, and their survival-product combination yields internally consistent cumulative probabilities. Chronologically separated data included 67,106 item-level records from 9,412 customers. In the chronologically separated evaluation with a 23 July 2024 cutoff, the ten-variable representation, selected by validation AUPRC only, achieved AUROC 0.7999, AUPRC 0.3230, Brier score 0.0846, ECE 0.0585, and Top-10% precision 0.3667. It exceeded classical quintile RFM by 0.0644 AUPRC (1,000 customer-level paired bootstrap draws; 95% CI: 0.0460-0.0849). A cutoff-safe histogram-gradient tree achieved AUPRC 0.3231; the DynRFM-minus-tree difference was -0.0001 (95% CI: -0.0176-0.0169), so the data did not distinguish their ranking performance. A complementary retrospective rolling assessment at six earlier, fully mature time origins found mean AUPRC 0.4276 for the fixed ten-variable model versus 0.3516 for quintile RFM; the customer-clustered macro-origin difference was 0.0760 (95% CI: 0.0653-0.0875). This analysis reuses the same authorized dataset and cannot replace independent validation on newly collected or external data. Later-window probabilities were optimistic at the high end, so the framework supports relative manual-review ranking rather than fixed-threshold decisions. It is not a causal marketing, automatic-contact, or clinical-recommendation system.

Abstract: This study examines how green marketing and sustainability information overload shape consumers' perceptions of greenwashing and behavioral intentions toward green hotels in Vietnam. Integrating Stimulus-Organism-Response theory and Media Richness Theory, the study models green marketing and information overload as external stimuli, perceived greenwashing, green trust, and green attitude as organism states, and intention to stay, word of mouth, and willingness to pay as behavioral responses. Data were collected from 248 Vietnamese consumers aged 20 years and above after exposure to a simulated green hotel website video. Green marketing reduced perceived greenwashing, whereas information overload increased it. Perceived greenwashing did not affect green trust or green attitude but had a positive direct effect on behavioral intention. Green attitude and green trust significantly strengthened behavioral intention, and perceived greenwashing mediated the information overload-behavioral intention relationship. The findings highlight the need for concise, verifiable, and credible sustainability communication in green hospitality marketing.

Abstract: This conceptual paper re-imagines the application scenario of immersive technologies not merely as promotional add-ons or experiential devices, but as integral components of a hotel’s service communication and distribution architecture. Drawing upon information richness theory, signaling theory, information asymmetry, and transaction cost economics—with expectation-confirmation logic providing the link to during- and post-purchase outcomes—the paper conceptualizes hospitality digital twins as data-connected interfaces that illustrate heterogeneous offers, reduce pre-purchase uncertainty, support direct bookings, and align marketing communication with service-quality management through expectation calibration. An illustrative review of current immersive-technology providers reveals that commercial offerings predominantly remain limited to basic visualization or promotional gimmicks with minimal connections to booking engines, CRM systems, analytics, or quality-management processes. In contrast, the theoretical analysis demonstrates that the true value of a hospitality digital twin extends far beyond visual realism toward a combination of richer information, verifiability, and deep system integration. By distinguishing visualization-only virtual tours from data-enriched interfaces and fully integrated digital twins, this paper highlights expectation calibration as the core mechanism through which pre-purchase transparency enhances trust, channel choice, booking quality, and post-purchase service outcomes. Consequently, hotel managers should approach digital twins as next-generation customer journey infrastructure rather than isolated promotional novelties, while future empirical studies across laboratory and field settings are encouraged to test how varying levels of interface integration affect guest satisfaction, complaint reduction, and direct distribution performance.

Abstract: Climate emotions are associated with sustainable and unsustainable consumption, but the processes underlying these associations remain unclear. This study examines how climate-change anxiety and eco-grief relate to self-reported consumer outcomes through moral disengagement and moral obligation, and whether these associations vary with solastalgia. A mixed-methods design was used. Quantitative data were collected from 582 adult consumers in Türkiye via a two-wave survey administered 2 weeks apart; measures included climate-change anxiety, eco-grief, moral disengagement, moral obligation, affective impulsive buying, eco-conscious behavior, and solastalgia. The hypotheses were tested using PLS-SEM with bootstrapping and predictive assessment. Semi-structured interviews with 26 participants were analyzed through codebook thematic analysis to explain the modeled paths. Climate-change anxiety was positively associated with moral disengagement and weaklier, with moral obligation. Eco-grief was positively associated with moral obligation and negatively associated with moral disengagement. Moral disengagement was positively associated with self-reported affective impulsive-buying tendency, whereas moral obligation was positively associated with self-reported eco-conscious consumption. The solastalgia interaction terms were small but significant: the CCA–MD association was stronger and the EG–MO association was weaker at higher levels of place-based distress. The findings support an outcome-specific moral-regulatory conflict model while positioning solastalgia as an incremental contextual influence. The findings indicate that climate emotions are associated with concurrent variation in moral disengagement and moral obligation, each of which is differently associated with self-reported consumer outcomes. These findings suggest that interventions could strengthen agency, reduce moral-disengagement cues, and make repair-oriented actions more visible in affected places.

Abstract: (1) Background: Social media marketing, the use of social platforms to build brand awareness, engage customers, gather market insights, distribute content, and drive sales has become essential to business strategy across firm sizes. (2) Methods: A systematic review of literature from Google Scholar, Semantic Scholar, and Scispace, published between 2020 and 2026, was conducted using PRISMA-based screening, yielding 14 studies for full-text analysis, a supplementary VOSviewer keyword co-occurrence analysis of study titles and abstracts was also performed. (3) Results: Five core domains were identified, expressed as each domain’s share of the 43 total domain-study codings across the 14 studies: brand awareness and promotion (26%), customer engagement and interaction (30%), market research and insights (9%), content creation and distribution (14%), and sales and lead generation (21%). Customer engagement and brand awareness were the most consistently supported outcomes, while market research remained comparatively under-investigated; the keyword analysis independently corroborated this gap, surfacing no cluster corresponding to market research or content creation. (4) Conclusions: Social media effectively drives brand visibility, engagement, and sales through quality content and consistent interaction, though its use as a market-intelligence tools remains underutilized. Businesses should prioritize content quality, platform-appropriate strategy, and internal social media capability, while future research should address this documented gap across broader contexts.

Abstract: The increasing availability of large-scale consumer data and advances in computational technologies have transformed marketing into a data-driven discipline. Mathematical and computational frameworks play a critical role in supporting decision-making processes by enabling organizations to analyze complex market dynamics, predict consumer behavior, optimize resource allocation, and improve strategic planning. This study explores the integration of mathematical modeling, optimization techniques, machine learning algorithms, simulation methods, and data analytics within contemporary marketing practices. Drawing on the interdisciplinary convergence of marketing, engineering, mathematics, and computer science, the paper examines how computational approaches enhance market segmentation, customer engagement, demand forecasting, pricing strategies, advertising performance, and customer relationship management. The analysis highlights the growing relevance of predictive and prescriptive analytics in converting raw data into actionable insights that support evidence-based managerial decisions. Furthermore, the study discusses emerging trends, including artificial intelligence, real-time analytics, and intelligent decision support systems, that are reshaping the marketing landscape. Challenges related to data quality, model interpretability, computational complexity, and ethical considerations are also addressed. The findings suggest that the effective integration of mathematical and computational frameworks can significantly improve organizational competitiveness by increasing decision accuracy, operational efficiency, and responsiveness to market changes. This research contributes to a broader understanding of how advanced analytical methods support the transition from data collection to strategic decision-making in modern marketing environments.

Abstract: Artificial Intelligence (AI) is increasingly embedded in consumer decision-making, yet its role in shaping sustainable behaviour remains insufficiently understood. This research develops and empirically tests a novel framework explaining how AI simultaneously promotes and undermines sustainable consumption. Drawing on consumer behaviour theory, self-determination theory, and complex adaptive systems, we introduce the concept of Generative AI Nudging (GAIN) and propose the Algorithmic Sustainability Paradox (ASP).Across two studies, we examine how AI-driven recommendations influence consumer choices, perceived autonomy, trust, and behavioural dynamics over time. Study 1 (N = 412) employs a controlled experiment demonstrating that AI nudging significantly increases sustainable product choices but reduces perceived autonomy under high personalization. Study 2 (N = 286) adopts a longitudinal design and reveals that while AI promotes sustainable behaviour initially, it also generates rebound effects over time, mediated by moral licensing.These findings advance consumer behaviour theory by conceptualizing AI as a dynamic behavioural architecture rather than a neutral tool. The research highlights critical trade-offs between effectiveness and autonomy, as well as short-term gains versus long-term sustainability outcomes. Managerially, the findings caution against excessive personalization and emphasize the need for ethically aligned AI systems.This study contributes to bridging AI marketing research and sustainability scholarship and offers actionable insights for designing responsible AI-driven interventions.

Abstract: Digital technologies increasingly shape how cultural tourists discover, evaluate, and select heritage experiences, yet Indigenous cultural tourism remains unevenly visible across online marketing systems and official tourism data. This exploratory study reframes Indigenous tourism development through a cultural-tourism marketing and consumer-behavior lens. It compares 12 Indigenous cultural tourism cases across Oceania, North America, Europe, Asia, Latin America, Southeast Asia, and the Philippines using publicly available secondary data from tourism agencies, Indigenous tourism organizations, official destination websites, heritage sources, public reports, and Google Trends. Three indicators were constructed: a Digital Visibility Index, a Tourism Growth Evidence Score, and a Sustainability Support Index. Results show that globally recognized heritage brands such as Chichen Itza/Maya tourism and Cordillera Indigenous tourism achieved high digital visibility, but digital visibility was only weakly associated with tourism-growth evidence (r = 0.022). Cases such as Native American tourism, Indigenous tourism Canada, Maori tourism, and Aboriginal tourism Australia showed stronger overall development because they combined sector-specific tourism evidence with institutional support and sustainability safeguards. The study concludes that cultural tourism marketing in the digital age should move beyond search visibility and promote ethical, community-controlled, data-informed, and culturally accountable consumer engagement.

Abstract: The gap between consumers’ intent to buy electric cars and their actual purchasing behavior of petrol cars has motivated researchers to conduct numerous investigations over the last decade. Nevertheless, with the explosive development of the field, bibliographic mapping remains a difficult task. This study combines bibliometric analysis and a PRISMA-oriented systematic review of consumer purchase intentions towards sustainable vehicles. A systematic literature search in Scopus retrieved 1,447 records between 2015 and June 2026, of which 706 empirical studies met the inclusion criteria for qualitative synthesis. Based on performance analysis and science mapping using VOS viewer software, one can conclude that the topic area develops at around 23%, gathers 43,758 citations, and shifts geographically over time. China contributes 418 papers, and India goes from publishing one piece in 2015 to occupying the third position overall. Keywords co-occurrence identifies five research clusters, whereas co-citations show that there are three intellectual bases for the field: behavioral theory, choice modelling, and methodological approaches based on the PLS-SEM framework. The results also emphasize some recurring gaps, namely the lack of a moderating effect of demographic characteristics, personality traits, intention-to-behavior relationship, and longitudinal surveys. This study proposes an eight-point research agenda driven by keyword analysis.

Abstract: Eco-labels are a central tool of green marketing, used to communicate the environmental quality of products to consumers. This review asks whether they actually influence the green purchase behaviour of young Nigerian consumers, drawing on work on trust, greenwashing awareness, digital education, price sensitivity and product availability. Reading the evidence through the Theory of Planned Behaviour and Signalling Theory, the paper argues that eco-labels can shape purchase intention when consumers understand and trust them. However, intention rarely converts into purchase among young consumers facing limited label awareness, weak certification trust and price pressure. Evidence from South Africa, Ghana and Kenya points to the same pattern across African markets. Eco-labels work, in short, when they are clear, trusted and attached to affordable products. The paper calls for stronger consumer education, clearer certification, digital explanation, and regulatory action against misleading green claims.

Abstract: Interest in electric vehicles (EVs) is rising as the world shifts toward sustainable transportation, yet consumer adoption remains highly uneven, particularly in developing countries. This study examines how five dimensions of consumption value—functional, social, emotional, novelty, and conditional—influence consumer choice behavior toward EVs in Indonesia, while also testing the moderating role of infrastructure readiness. Using a quantitative approach, data were collected through an online survey with purposive sampling, yielding 455 valid responses. Partial least squares structural equation modeling (PLS-SEM) was applied to assess the measurement and structural models. The results reveal that functional, social, emotional, and conditional values significantly influence consumer choice behavior, whereas novelty value has no significant effect. Infrastructure readiness also significantly moderates most consumption values, with negative coefficients indicating that limited charging access and inadequate maintenance support weaken the positive impact of consumer values on EV adoption. The findings show that although consumers value performance, social image, emotional appeal, and situational factors, poor charging infrastructure hinders adoption. This study contributes to EV adoption literature by integrating consumption value theory with infrastructure readiness as a moderator. The results emphasize that developing charging infrastructure, expanding service availability, and maintaining supportive government policies are critical steps for accelerating EV adoption in emerging markets.

Abstract: This study examines how consumers respond to personalized advertisements that appear to be derived from prior conversations with generative AI assistants in social commerce settings. Drawing on privacy calculus theory, trust theory, and the stimulus–organism–response framework, the study investigates whether GenAI-based advertising personalization simultaneously creates perceived personalization value and privacy concern, and how these evaluations shape algorithmic trust and social commerce purchase intention. A scenario-based survey was conducted with 435 social commerce users in Jordan. Respondents evaluated a situation in which a product advertisement appeared to match a previous conversation with a generative AI assistant. The data were analyzed using partial least squares structural equation modeling with SmartPLS 4. The findings show that perceived GenAI-based advertising personalization increases both perceived personalization value and privacy concern. Personalization value strengthens algorithmic trust, whereas privacy concern weakens it. Algorithmic trust, in turn, strongly enhances social commerce purchase intention. The mediation results confirm that personalization value and privacy concern explain the dual effect of GenAI-based advertising personalization on algorithmic trust. In contrast, algorithmic trust transmits these effects to purchase intention. Transparency disclosure does not significantly reduce privacy concern, but it strengthens the positive relationship between personalization value and algorithmic trust. The study contributes to digital marketing and social commerce research by showing that conversational-AI-derived advertising data can be perceived as both useful and intrusive. That transparency may support trust formation without necessarily eliminating privacy concerns.

Abstract: The introduction of green cosmetics has undoubtedly captured researchers’ interest following the global surge in environmental awareness and sustainable consumption. However, consumers do not consistently opt for green products, causing businesses to approach green marketing from an opportunistic standpoint. This study explores consumer awareness of green cosmetics in South Africa and Zimbabwe, two emerging markets with contrasting economies. Using an exploratory qualitative design, data were collected through purposive sampling using in-depth interviews with six participants from South Africa and six from Zimbabwe. The findings reveal that participants in both countries prefer to receive information from reference groups and social media rather than from business advertisements. In Zimbabwe, lack of awareness and product availability hinder adoption, while South African consumers are guided by packaging cues and sustainability claims. In addition, limited production and product unavailability affect the purchasing of green cosmetics, as indicated by the participants in both countries. This study contributes to the limited body of knowledge on green consumerism in African markets by offering comparative qualitative insights from two contrasting economies and offers implications for marketers and policymakers promoting sustainable consumption.

Abstract: The purpose of this study is to investigate the extent to which tourists appreciate sus-tainable tourism and what effect eco-friendly practices have on the decision-making process of selecting a hotel. Through the use of large-scale analysis of online reviews of hotels and the application of sentiment analysis techniques, the research investigates the impact of environmental factors (e.g., energy usage reduction, minimizing waste, and promoting nature experiences) on customer perspectives and decision-making processes for lodging. This research adopts an approach that utilizes machine-learning based sentiment analysis as its source of understanding. The results of this research demonstrate that as more individuals become aware of sustainable tourism; however, sustainability often plays a secondary role in determining whether or not to stay at a specific hotel when compared to such lodging attributes, as comfort, price and quality service. Based upon these findings, this research indicates that while many tourists’ value sustainable tourism and make an effort to choose eco-friendly lodging establishments, the influence of sus-tainability on tourists' lodging decisions is not as strong as other attributes. These results indicate important implications for hotel managers that will help them to balance envi-ronmental stewardship with a competitive stance.

Abstract: Greenhushing—the deliberate under-communication of genuine sustainability achievements —has been examined almost exclusively from an organizational standpoint, leaving the consumer side of the phenomenon largely undertheorized. This study investigates how perceived greenhushing, defined as a consumer’s perception that a brand deliberately withholds information about its environmental performance, affects young consumers’ green purchase intention. Drawing on signaling theory, trust–commitment theory and attribution theory, a model is developed in which brand trust, perceived risk and consumer green skepticism jointly mediate the relationship between perceived greenhushing and green purchase intention, while environmental concern and trait-level green skepticism are positioned as moderators. The model is estimated with partial least squares structural equation modeling (PLS-SEM) on a sample of 404 young consumers in Vietnam. Perceived greenhushing significantly erodes brand trust (β = −0.535), elevates perceived risk (β = 0.571) and activates consumer green skepticism (β = 0.477). Among the three mediators, brand trust is the dominant pathway to green purchase intention (β = 0.444), whereas the skepticism pathway is non-significant (p = 0.093). The direct effect of perceived greenhushing on green purchase intention remains negative and significant (β = −0.152), indicating partial mediation. The findings extend signaling theory to the under-studied domain of communicative absence, sharpen the conceptual boundary between greenwashing and greenhushing at the consumer level, and offer specific guidance for sustainability communication in emerging-market consumer settings.

Abstract: One of the most important traditional dairy products in Kosovo is cheese. On the other hand, there are few data regarding the characterization and classification of cheese in Kosovo. The purpose of this paper is to identify and classify the varieties of cheese in Kosovo, depending on their physicochemical characteristics and properties. This paper collects samples of cheese from various regions in Kosovo and analyzes them regarding some of the most important physicochemical properties. The results showed that there are differences in their composition, which range from 42.5 to 74.5% in the moisture content, average 24.8% for the fat content of the cheese, and average 18.6% for the protein content of the cheese. There are differences about the kinds of milk used to produce these kinds of cheese, which are dominated by cow milk, followed by sheep, goat, and mixed milk. Cluster analysis grouped the cheeses into distinct categories corresponding to soft, semi-soft, and semi-hard varieties. As can be seen from the information provided above, one can notice that various kinds of cheese are available in Kosovo. Information provided above can be considered to serve as the scientific basis for standardization of traditional cheese products. Information provided above can be of major importance for quality control of cheese products in Kosovo.

Abstract: The competitive ground of digital visibility has moved twice in eighteen months. The first move was from the ten blue links to the AI-generated answer; the second, still in progress, is from the answer to the autonomous action. This article develops a framework that integrates three optimization disciplines emerging in response to that shift—Answer Engine Optimization (AEO), Generative Engine Optimization (GEO), and Agentic Optimization (AgO)—under a single theoretical lens: delegated consumer–AI agency. Building on Puntoni et al.’s (2021) experiential perspective on consumer AI and Davenport et al.’s (2020) account of AI in marketing, we treat the AI assistant not as a channel but as a delegated decision-maker whose choices are governedby retrievability, attribution cost, and embedded brand associations. We argue that the central strategic risk of this transition is brand erasure—the systematic elimination of brand identity from synthesized answers and completed agentic actions—and we develop six propositions that link content and infrastructure choices to brand outcomes in this environment. We close with managerial implications for brands operating across the dual audience of human readers andmachine intermediaries, and a research agenda focused on measurement, audit methods, and governance.

Abstract: This study investigated the influence of marketing infrastructure and digital marketing strategies on the performance of small and medium enterprises (SMEs) in Nigeria, emphasizing the mediating role of digital transformation. While prior research has established the importance of digital marketing strategies in driving performance, much of the focus has been on large firms, with limited attention to SMEs and the transformative effects of digital transformation. To address this gap, data were collected from 400 SME managers and owners registered with the Small and Medium Enterprises Development Agency of Nigeria (SMEDAN) through an online survey. The data were analyzed using partial least squares structural equation modelling (PLS-SEM). Findings revealed that marketing infrastructure and digital marketing strategies do not directly improve marketing performance; rather, digital transformation serves as a critical mediator that enables this relationship. The study concludes that SMEs that embrace digital transformation, by integrating digital technologies across operations, achieve superior marketing outcomes, including enhanced brand awareness, customer acquisition, conversion rates, and customer satisfaction, ultimately leading to higher sales, profitability and and business sustainability.