Search Results (1,858)

The present conceptual paper proposes a purpose-driven experiential marketing framework for film-induced destinations, integrating sustainability and emotional engagement into destination management. The model under discussion comprises five interconnected dimensions, namely integrated experience, branding, people, emotional touchpoints and processes. These are articulated through purpose-driven marketing principles and aligned with selected Global Reporting Initiative (GRI) indicators. This approach positions sustainability as an inherent component of value creation rather than an external policy layer. The framework under discussion was developed through an interdisciplinary literature review and is illustrated through insights from an exploratory case study of Monsanto, a rural Portuguese village recently featured in HBO’s House of the Dragon. Semi-structured interviews were conducted with a purposive sample of local stakeholders, including tourists, residents, entrepreneurs and institutional representatives. These interviews were analysed thematically to provide indicative evidence of the framework’s relevance and potential applicability. The findings suggest that emotional engagement, co-creation and territorial authenticity play a central role in shaping memorable film-related tourism experiences that are consistent with destination purpose and stakeholder well-being. The study also emphasises the strategic importance of storytelling, audiovisual narratives and collaborative governance in the strengthening of place identity and the support of sustainable differentiation. Despite its exploratory nature, the framework provides practical guidance for destination management organisations (DMOs), cultural programmers and creative industry actors. The article concludes by identifying avenues for future research, including cross-regional application, digital experimentation and the quantitative assessment of experiential dimensions. Full article

This study examines consumer behavior, preferences, and knowledge regarding honey in Kosovo to inform more effective production, marketing, and policy strategies. Data were collected from 503 respondents through an online questionnaire and analyzed using a combination of artificial neural networks (ANN), decision tree modeling (CHAID), and ordinal logistic regression. The results show a high prevalence of honey consumption, strong preference for locally produced honey, and significant variability in consumer willingness to pay (WTP) based on knowledge, income, and trusted information sources. ANN identified recommendations and product familiarity as primary predictors of WTP, while the decision tree highlighted knowledge and income as key variables for segmentation. The ordinal logistic regression confirmed the importance of perceived quality and product attributes, particularly botanical and geographical origin, in shaping purchasing decisions. The use of complementary statistical models enhanced both predictive power and interpretability. The findings highlight the crucial role of consumer education and trust cues in fostering sustainable honey markets in Kosovo. Full article

This study investigates how digital transformation in healthcare shapes sustainable customer value by analyzing the role of digital quality and its influence on satisfaction and loyalty within an AI-based diabetes prognostic service. Drawing on system, information, and service quality as core dimensions of digital quality, the study examines their direct effects on satisfaction and their contribution to loyalty formation relative to traditional service factors. Using survey data collected from over 1000 users of a digital healthcare platform equipped with an AI-driven diabetes prognostic algorithm, 800 valid responses were analyzed through PLS-SEM in SmartPLS 4.0. The results show that both traditional service attributes and digital quality significantly enhance customer satisfaction, which in turn promotes loyalty. However, digital quality does not strengthen the satisfaction–loyalty linkage, indicating that its value lies in establishing baseline trust and usability rather than amplifying loyalty outcomes. Environmental uncertainty—captured as technological and market uncertainty—also positively affects loyalty. This study contributes to digital healthcare research by providing empirical evidence from an AI-based long-term prognostic service and clarifying that digital quality operates as a foundational hygiene factor essential for sustainable customer value, rather than as a competitive differentiator. Full article

Amid China’s “Manufacturing Power” push, full-chain digital restructuring in the Guangdong–Hong Kong–Macao Greater Bay Area remains hampered by mismatches among technology, organization, and environment. We therefore explored how shop floor actors perceive and shape this Technology–Organization–Environment (TOE) interplay. Semi-structured interviews with frontline operators, maintainers, and supply chain staff from GBA manufacturers were inductively coded, yielding 36 concepts, 10 categories, and 3 core TOE aggregates that were woven into a grounded model. The analysis shows that industrial internet platforms and smart equipment only create value when matched by flexible shop floor structures, cross-department data protocols, and skilled teams; otherwise, data silos, simulation–production deviations, and “buy-but-not-build” procurement stall adoption. Market pressure for customized, short-lead-time products and divergent municipal pilot policies further intensify the TOE balancing act, particularly for SMEs with weak absorptive capacity. By revealing a grassroots “technology-driven → organization-adapted → environment-adjusted” spiral that is moderated by frontline feedback, the study extends the TOE framework to micro-level, regional innovation theory and offers policy–practice levers for differentiated, cross-city manufacturing upgrading. Full article

Functional food plays an increasingly important role in shaping healthy dietary habits by integrating health-promoting components into consumers’ everyday diets and helping reduce food waste. Products developed using by-products and raw material streams from food processing can support the principles of the circular economy (CE) by improving resource efficiency and lowering the environmental footprint of the food system. In Poland, as in many countries worldwide, functional food is a rapidly growing category that can contribute to public health and serve as a driver of economic development. However, the excessive and scientifically unsupported use of the term “functional food” for marketing purposes may mislead consumers and weaken trust in this product group. From a CE perspective, transparent communication and informed consumer choices are essential, as they promote environmentally responsible behaviors and support sustainable production models. The aim of this study was to assess the level of knowledge about functional food among residents of Eastern Poland, which is a less industrialized and predominantly agricultural region. The analysis focused on awareness of health benefits, consumption frequency, consumer attitudes, and interest in educational initiatives promoting functional food within CE principles. The study also examined whether consumers associate functional food with sustainability-oriented practices. The findings offer insights for educational and marketing strategies grounded in scientific evidence and highlight the potential of functional food in building a sustainable, resource-efficient food system. Full article

High-quality development of agricultural enterprises is essential for China’s rural revitalization, yet the institutional conditions that support it remain poorly understood. Drawing on institutional logics and configuration theory, this study adopts a holistic systems perspective to examine how government, market, and social institutions interact to shape enterprise performance. Using provincial data (2013–2023) matched with firm-level data for 119 listed agricultural enterprises, we estimate total factor productivity as the core outcome and apply dynamic fuzzy-set Qualitative Comparative Analysis (dynamic fsQCA) to identify equifinal institutional pathways. The results reveal that high-quality development is an emergent property of complex institutional systems; instead, high-quality development emerges from several distinct configurations combining policy support, marketization, financial development, Agricultural Infrastructure Index, market stability, and urban–rural integration. Two contrasting configurations are associated with non-high-quality development, characterized by financial scarcity and infrastructure deficits or by fragmented policy support under weak regulation. Dynamic analysis further reveals clear temporal and spatial heterogeneity: some market–finance driven paths lose robustness over time, while policy–urbanization and regulation–infrastructure based configurations become increasingly stable. These findings extend institutional configuration research to the agricultural sector, demonstrate the value of dynamic fsQCA for capturing temporal effects, and offer differentiated policy implications for optimizing institutional environments to foster the high-quality development of agricultural enterprises. Full article

Financial markets are increasingly shaped by opaque price controls influenced by the rising prominence of algorithmic and AI-driven systems in price determination. While much of the current research on algorithmic trading and market microstructure has emphasised aspects such as efficiency, liquidity, and model clarity, there has been less focus on the broader implications of assigning inference, execution, and learning tasks to adaptive algorithms. This entry presents a conceptual framework that aims to elucidate how algorithmic systems fundamentally alter price discovery. It highlights the centralisation of epistemic authority, the diminishing of human interpretative capabilities, and the emergence of “rational opacity”. This condition allows prices to remain informationally efficient while obscuring the causal relationships between information and price formation, making them difficult to comprehend for human participants both prior to and in real-time. We introduce the Algorithmic Price Discovery Loop, a theoretical model that connects algorithmic inference, automated execution, feedback-driven learning, and the resulting asymmetry in market-wide interpretation. The framework not only provides critical theoretical insights but also proposes testable propositions and outlines various empirical avenues for investigating algorithmic authority and opacity across different market contexts. Furthermore, the discussion addresses governance implications, recognises the limitations of existing regulatory frameworks, and highlights potential crises that could arise in AI-driven financial markets. Full article

Understanding how moral and emotional language operates in paid social advertising is essential for evaluating persuasion and its ethical contours. We provide a descriptive map of Moral Foundations Theory (MFT) language in Meta ad copy (Facebook/Instagram) drawn from seven global beverage brands across eight English-speaking markets. Using the moralstrength toolkit, we implement a two-channel pipeline that combines an unsupervised semantic estimator (SIMON) with supervised classifiers, enforces a strict cross-channel consensus rule, and adds a non-overriding purity diagnostic to reduce attribute-based false positives. The corpus comprises 758 text units, of which only 25 ads (3.3%) exhibit strong consensus, indicating that much of the copy is either non-moral or linguistically ambiguous. Within this high-consensus subset, the distribution of moral cues varies systematically by brand and category, with loyalty, fairness, and purity emerging as the most prominent frames. A valence pass (VADER) indicates that moralized copy tends toward negative valence, yet it may still yield a constructive overall tone when advertisers follow a crisis–resolution structure in which high-intensity moral cues set the stakes while surrounding copy positions the brand as the solution. We caution that text-only models undercapture multimodal signaling and that platform policies and algorithmic recombination shape which moral cues appear in copy. Overall, the study demonstrates both the promise and the limits of current text-based MFT estimators for advertising: they support transparent, reproducible mapping of moral rhetoric, but future progress requires multimodal, domain-sensitive pipelines, policy-aware sampling, and (where available) impression/spend weighting to contextualize descriptive labels. Full article

The electronic word of mouth (eWOM) has emerged as a communication tool that significantly influences consumers’ attitudes and purchasing behavior in the online market. Research indicates that the effect of eWOM sources, such as (strong ties, weak ties, and influencers) varies in terms of perceived value components (price, quality, emotional, and social value) and purchase intention, particularly with regard to gender. This study, which is based on the SOR framework; examines the role of eWOM as a stimulus affecting student responses and considers the mediating role of perceived value components and the moderate effect of gender. A sample of 901 students from Westbank universities was analyzed using Smart PLS software. The findings reveal that strong ties and influencer eWOM are positively associated with perceived value components and purchase intention, while weak tie eWOM does not directly correlate with purchase intention. Mediation analyses show that perceived quality and social value act as mediators of purchase intent towards eWOM sources, while emotional value specifically mediates strong relationships and influencers. Notably, price value exerts only a mediating effect on purchase intention when communicated through influencers, highlighting the unique role of the influencer in shaping price perceptions and its broad impact on all components of perceived value. Gender differences were observed in students’ responses to eWOM content; particularly in terms of price, quality, and emotional appeal but not in terms of social factors. The outcomes of this study underscore the significance of considering both the source of the message and the characteristics of the audience when formulating targeted marketing strategies. Full article

This study aims to predict Turkish consumer preferences for smart tablets on e-commerce platforms, focusing on consumer behavior in a developing country context. Key product attributes—such as processor speed, screen size, internal storage capacity, display resolution, RAM, processor core count, and battery capacity—were collected from major e-commerce websites in Turkey. Data analysis indicated that consumers predominantly prefer tablets with processor speeds between 1–3 GHz, internal storage capacities of 32–64 GB, 2–3 GB of RAM, screen sizes of 7–11 inches, and battery capacities between 5001–8000 mAh. To predict the most preferred tablet configurations, Artificial Neural Networks (ANNs), Deep Neural Networks (DNNs), and Random Forest (RF) models were developed and evaluated. Among these, the ANN model achieved the highest prediction accuracy, particularly regarding RAM preferences. The findings contribute to the growing body of research on consumer behavior modeling in emerging markets and may assist manufacturers and marketers in shaping strategic decisions related to product development and online retail strategies. Full article

Grounded in the Theory of Planned Behavior, this study explores how sustainable marketing shapes consumer attitudes, brand image, and brand trust, and their implications for sustainable purchasing behavior among micro, small, and medium enterprises (MSMEs) in Bali. This study also examines the role of local wisdom as a moderating variable in the relationship between sustainable marketing and these three constructs. Using a quantitative approach with SEM-PLS analysis, this study involved 288 respondents who were local consumers of sustainable MSME products. Empirical data were collected through a Google Form-based questionnaire and analyzed using SmartPLS4. The results show that sustainable marketing has a significant effect on attitude, brand image, and brand trust. These three variables are proven to be strong drivers in increasing purchasing decisions for sustainable products. Furthermore, local wisdom does not moderate the relationship between sustainable marketing and attitude, but negatively moderates its relationships with brand image and brand trust, suggesting that culturally rooted consumers apply more critical evaluations to sustainable marketing efforts. These findings highlight the importance of integrating local wisdom authentically into sustainable marketing to strengthen consumer attitudes, brand image, and brand trust. The study contributes to sustainable marketing and consumer behavior theory and provides practical guidance for MSMEs in implementing sustainability strategies aligned with local wisdom. Full article

In an era where environmental consciousness increasingly shapes consumer behaviour, the tourism industry faces the dual challenge of promoting destinations while ensuring ecological sustainability. This study explores how web analytics and big data can be leveraged to enhance the visibility and attractiveness of eco-friendly destinations. Building upon digital marketing and sustainability frameworks, the authors develop a data-driven methodology that integrates website performance metrics, search behaviour patterns, and social media engagement indicators. After data collection, statistical and content analyses were implemented, followed by a Fuzzy Cognitive Map (FCM) to visualise the interrelationships between online user behaviour, environmental awareness, and destination appeal. Full article

Despite growing research on sustainable aviation, multi-airport systems, and environmentally constrained capacity allocation, critical gaps persist. Existing studies often treat passenger choice, airline competition, and airport regulation in isolation, or evaluate environmental policies such as carbon taxation only as macro-level constraints. Consequently, the endogenous feedback among pricing, capacity reallocation, and regulatory intervention in shaping equilibrium outcomes within multi-airport systems remains underexplored, particularly within a unified dynamic framework that links low-carbon policies to operational decision-making. This study develops such a dynamic framework to support the sustainable transition of carbon-constrained multi-airport regions. Focusing on the Beijing–Tianjin multi-airport system and China’s “Dual Carbon” goals, we construct a three-layer iterative equilibrium game integrating passenger airport choice (modeled using a multinomial logit specification), airline capacity reallocation (formulated as an evolutionary game internalizing carbon taxes), and airport slot regulation (implemented through a multi-objective mechanism balancing economic revenue, hub connectivity, and environmental performance). An agent-based simulation of the Beijing/Tianjin–Nanchang route demonstrates robust convergence to a stable systemic equilibrium. Intensified competition reduces fares and improves accessibility, while capacity shifts from higher-cost Beijing airports to Tianjin Binhai Airport, whose market share rises from 10.6% to 34.0%. Airport utilization becomes more balanced, total airline profits increase slightly, and both total and per-passenger CO₂ emissions decline, indicating improved carbon efficiency despite demand growth. The results further identify a range of carbon-tax levels that jointly promote emission reduction and traffic rebalancing with limited profit loss. Full article

The opportunistic use of insider information generates adverse effects on capital markets, making its mitigation through robust corporate governance practices. This research analyzes the corporate governance mechanisms that reduce the signs of opportunistic insider trading, grounded in the assumptions of information asymmetry and opportunistic behavior. The hypotheses posit that firms listed on the Novo Mercado or Level 2 of Corporate Governance, with more independent boards of directors and greater female representation, active fiscal councils, consolidated ESG practices, non-family ownership structures, robust audit committees, and audits not conducted by Big Four firms, are less prone to opportunistic conduct. The sample comprises 237 firms, representing 51% of companies listed on [B]3 between 2010 and 2021, resulting in a total of 2175 firm-year observations. Panel data analysis supports the proposed hypotheses. The findings indicate that higher levels of corporate governance practices are associated with a lower incidence of opportunistic insider trading in the Brazilian capital market. This study contributes to the literature by highlighting the specific features of the largest stock market in Latin America and emphasizing the role of transparency, formal monitoring, and informal mechanisms, such as social and reputational pressure on insiders, in shaping ethical behavior and curbing the misuse of privileged information. Full article

Real estate constitutes a core segment of the global building and built environment industry, absorbing substantial volumes of international institutional investment capital. Unlisted real estate has featured prominently in the portfolios of global institutional investors. In recent years, global real estate markets have been significantly impacted by rising interest rates, posing a real and significant risk to investors. In response, more tactical asset allocation strategies have been adopted. Investment fund managers and institutional investors seek to rebalance through sector selections and sectoral portfolio diversification when tactical asset allocation strategy may be insufficient in phases of heightened rate volatility. By deploying MSCI US unlisted sector-specific real estate quarterly total returns between March 1999 and June 2024, this research assesses portfolio asset allocation strategy for unlisted sector-specific real estate over both rate-easing and rate-tightening phases to investigate how the structural change shapes portfolio asset allocation strategy resulting from the rising interest rates. Overall, the findings show that unlisted sector-specific real estate played a substantial role in the US institutional mixed-asset portfolios during rate-hike phases in the period before the COVID-19 recession. The allocation to unlisted sector-specific real estate was close to the maximum 10% cap, averaging 9.5% during rate-easing phases but decreasing to 7.5% during rate-tightening phases. At a sector level, unlisted office real estate allocations were higher across constrained mixed-asset and real estate portfolios in rate-tightening phases relative to those in rate-easing phases, while portfolio asset allocations to unlisted real estate sectors were lower in rate-easing phases relative to those in rate-tightening phases. These empirical findings provide real estate investment stakeholders with practical and crucial insights into rebalancing portfolios’ tactical asset allocation strategies for unlisted sector-specific real estate responding to interest rate phases and macro-financial markets, albeit static asset allocation strategies being insufficient in phases of heightened rate volatility. The investment implications of empirical outcomes are identified and further discussed. Full article