Search Results (2,117)

Investors’ ability to retain investments during bearish and uncertain market periods is a crucial behavioral trait for long-term wealth accumulation and reduces market instability. Nevertheless, little is understood about how digital financial literacy (DFL) shapes the capacity of increasingly digitalized financial environments. This study investigates the links between DFL and investment grip among Japanese active investors—defined here, following conventional Japanese regulatory and research practice, as individuals who maintain a securities account and have engaged with an online brokerage within the past year—building on several theoretical perspectives from behavioral science. Using survey data from 149,261 individuals with an active account at Rakuten Securities, we estimated ordered probit regression models as the main specification. The findings showed a strong positive association between DFL and investment grip, even after accounting for demographic, socioeconomic, as well as cognitive attributes. These results are supported by robustness tests employing a probit model with a binary outcome. The sample consists exclusively of digitally active retail investors; the findings are therefore most directly applicable to this subpopulation. Overall, the evidence suggests that DFL fosters investors’ capacity to endure market volatility by promoting rational decision-making and reducing panic-driven selloffs. This study offers new empirical findings that will help promote financial resilience in technology-driven markets. Full article

Folk culture is an important asset for rural tourism and is crucial for maintaining the vitality of traditional villages. However, many traditional villages face underutilized folk cultural resources, inadequate systematic analysis, and mismatches between resources and markets, which impede the sustainability of rural tourism. To address this gap, this study applies the Resource–Market–Product (RMP) framework to systematically analyze the development of folk culture tourism. The aims are to identify the gaps among resources, markets, and products in folk culture tourism in Xidi Village and propose effective development strategies. This study integrates multiple data sources, including a local chronicle, a pilot survey, and online content analysis. The results reveal that the three core dimensions are generally consistent, but significant gaps exist. Participants identify key strategies to promote folk culture tourism in Xidi Village, including developing a material product system that highlights local characteristics, innovating diversified nonmaterial folk cultural tourism experiences, designing attractive folk culture tourism routes and scenic spot tour lines, and addressing the importance of differentiated tourist demands. This study systematically identifies the challenges and opportunities associated with folk culture tourism in traditional villages in rural areas. It provides feasible insights for promoting sustainable rural tourism and revitalizing traditional culture. Full article

Digitalisation is reshaping commercial systems in Europe, yet the joint evolution of national digital capabilities, e-commerce and macroeconomic performance remains imperfectly understood. This article develops a parsimonious Digital Maturity Index for the EU-27 over 2015–2023 and examines its association with the share of enterprise turnover generated through e-commerce using a systems-oriented econometric design. Two-way fixed-effects and dynamic panel models show that e-commerce turnover is strongly persistent within countries and systematically higher in more trade-open economies and in labour markets with slightly higher unemployment, after controlling for income and unobserved heterogeneity. The marginal effect of digital maturity on e-commerce intensity is small and statistically fragile, suggesting that digital capabilities act more as a slow-moving state variable than as a direct short-run driver of online sales. The marginal within-country effect of digital maturity on e-commerce intensity is small and statistically fragile once unobserved heterogeneity is controlled for, whereas trade openness and labour-market conditions remain robust correlates. The PVAR results suggest a stable system with strong persistence in e-commerce and digital maturity, limited spillovers to growth and a pronounced temporary contraction in output during the COVID-19 shock. Full article

Listeria monocytogenes is a high-risk pathogenic bacterium associated with ready-to-eat foods and poses a potential threat to consumer health. This study aimed to investigate the prevalence, characterization and genetic diversity of L. monocytogenes in ready-to-eat raw salmon and trout products obtained from physical stores and online stores in China. Out of 150 samples analyzed, 23 (15.3%) were positive for L. monocytogenes. Among these positive samples, three (12%) were from Japanese restaurants, four (16%) from farmers markets, one (2.9%) from large supermarkets and fifteen (30%) from e-commerce platforms, and only one sample showed a contamination level exceeding 100 most probable number (MPN)/g. The isolates from positive samples demonstrated a concrete public health risk through several findings: twenty-three L. monocytogenes exhibited varying degrees of cytotoxicity, ranging from 7.6% to 71.8%. Compared with the reference strain ATCC 19115, five of these isolates were highly cytotoxic, a result that was validated by mouse survival rate experiment, which also confirmed their high virulence at tested dose. All isolates were resistant to cefuroxime sodium, ceftriaxone, cefepime and nalidixic acid, and 13% showed resistance to sulphamethoxazole-trimethoprim. Three serogroups were identified, with serogroup Ⅰ.1 (1/2a, 3a) being the most prevalent (65.2%). These isolates were grouped into eight sequence types, with ST8 (34.8%) and ST87 (30.4%) dominating. All isolates carried virulence genes associated with LIPI-1 andmultiple internalin genes (inlA, inlB, inlJ and inlK), confirming their potential pathogenicity. Additionally, the isolates harbored antimicrobial resistance genes lin and FosX. The five highly virulent isolates exhibited the highest genetic similarity to J2-031 (GCA_000438645.1) and C1-387 (GCA_000438605.1). The results provided valuable information for Chinese regulatory authorities to strengthen the risk monitoring of L. monocytogenes in ready-to-eat raw salmon and trout products. Full article

The European Union’s decarbonization strategy relies on transparent and accurate climate data across value chains. Yet, existing sustainability reporting frameworks mainly target large companies, often neglecting small and medium-sized enterprises (SMEs). Although SMEs are largely exempt from mandatory reporting under recent regulatory simplifications, they play a critical role in Scope 3 emissions, which dominate the carbon footprints of larger firms. This paper presents two complementary, freely accessible digital tools designed to support credible carbon accounting. The first tool, Climate Compass, is a government-sanctioned tool that aligns with the GHG Protocol and has been used by >10,000 SMEs in Denmark to calculate Scopes 1, 2, and 3 emissions through a user-friendly interface. The second, a newly developed online cradle-to-gate life cycle assessment (LCA) tool, supports product-level carbon footprinting using open-source emission factor databases. The cradle-to-gate approach reflects typical SME production profiles and emphasizes embodied CO₂e from raw materials, transport, and energy consumption. Together, these tools enable researchers to effectively assess SMEs emissions in the value chain and thus support decarbonization while supplying reliable data to larger companies. The tool democratizes emissions analysis and supports regulatory and market demands and strengthens SMEs contribution to Europe’s low-carbon transition. Full article

This study aimed to develop a typology of consumers based on their behavior in the areas of sustainable consumption and digitalization in the pharmaceutical market. The analysis considered factors including (i) Schwartz’s universal values, (ii) demographic, and (iii) socioeconomic determinants. The study was based on a survey conducted on a sample of Polish adults (n = 1247) between April and July 2024, using a computer-assisted web interviewing method via SurveyMonkey^®. In the area of sustainability, the most frequently observed behaviors included: (i) packing purchased medicinal products into a personal bag, (ii) for medicinal products with short expiration dates owing to their origin, purchasing only the quantities that meet current needs without stockpiling, and (iii) for regularly used medicinal products, choosing larger packages. Whereas, in the area of digitalization, purchasing at an online pharmacy allows for (i) saving time and (ii) saving money, while also (iii) providing greater privacy. Importantly, the presence of four types of consumers was demonstrated, i.e., Sustainable-Active (20%), Digital-Adept (29%), Sustainable-Digital-Uninterested (21%), and Sustainable-Digital-Addicted (29%). In conclusion, within the pharmaceutical market, sustainability and digitalization are reflected in consumer behavior to varying degrees across consumer types, influenced by personal values. Full article

The integration of artificial intelligence (AI) into marketing and sales has significantly reshaped the European digital economy, altering how companies engage with consumers and create online value. This research examines the impact of AI adoption on e-commerce performance across the 27 EU member states. Drawing on Eurostat data, it applies advanced statistical methods, including factor analysis, structural equation modeling (SEM), and cluster analysis, to examine the links among AI-powered business practices, digital engagement, and e-commerce outcomes. The results reveal a strong positive association between AI use in marketing and e-commerce sales, underscoring the mediating role of consumer digital behavior. Regional disparities are also evident: Northern and Western European economies lead in AI adoption and digital maturity, while Southern and Eastern nations show emerging potential for rapid growth. Overall, the study emphasizes that AI-driven marketing boosts e-commerce growth and digital competitiveness, aligning with the European Union’s broader goals of fostering innovation and technological integration. Full article

This study examined Croatian consumer attitudes towards fresh pork from the Black Slavonian pig, focusing on the following sustainability dimensions: environmental, social, economic sustainability, and animal welfare. A survey of 410 consumers was conducted in June 2021, using an online questionnaire assessing consumption habits, breed knowledge, and socio-demographic characteristics. Factor analysis identified four key dimensions: attention to animal welfare, support for local production and biodiversity, origin and information, and price and intrinsic quality. Cluster analysis revealed three distinct consumer segments: conscious consumers (32.4%), value-oriented consumers (37.3%), and uninvolved meat consumers (30.2%). Multinomial logistic regression showed that age, region, family economic status, and place of purchase significantly predicted cluster membership (Nagelkerke R² = 0.251, classification accuracy = 52.9%), while gender, education level, and household composition did not. Conscious consumers were characterised by older age, higher income, and a preference for direct purchasing channels, while value-oriented consumers favoured supermarkets and mid-range pricing. These findings highlight the need for improved consumer education, transparent labelling, targeted marketing strategies, and enhanced policy support to promote sustainable indigenous pig breed production and conservation. Full article

Wood flooring manufacturers face complex challenges in dynamically allocating resources across multi-channel markets, characterized by channel conflicts, demand uncertainty, and long-term cumulative effects of decisions. Traditional static optimization or myopic approaches struggle to address these intertwined factors, particularly when critical market states like brand reputation and customer base cannot be precisely observed. This paper establishes a systematic and theoretically grounded online decision framework to tackle this problem. We first model the problem as a Partially Observable Stochastic Dynamic Game. The core innovation lies in introducing an unobservable market position vector as the central system state, whose evolution is jointly influenced by firm investments, inter-channel competition, and macroeconomic randomness. The model further captures production lead times, physical inventory dynamics, and saturation/cross-channel effects of marketing investments, constructing a high-fidelity dynamic system. To solve this complex model, we propose a hierarchical online learning and control algorithm named L-BAP (Lyapunov-based Bayesian Approximate Planning), which innovatively integrates three core modules. It employs particle filters for Bayesian inference to nonparametrically estimate latent market states online. Simultaneously, the algorithm constructs a Lyapunov optimization framework that transforms long-term discounted reward objectives into tractable single-period optimization problems through virtual debt queues, while ensuring stability of physical systems like inventory. Finally, the algorithm embeds a game-theoretic module to predict and respond to rational strategic reactions from each channel. We provide theoretical performance analysis, rigorously proving the mean-square boundedness of system queues and deriving the performance gap between long-term rewards and optimal policies under complete information. This bound clearly quantifies the trade-off between estimation accuracy (determined by particle count) and optimization parameters. Extensive simulations demonstrate that our L-BAP algorithm significantly outperforms several strong baselines—including myopic learning and decentralized reinforcement learning methods—across multiple dimensions: long-term profitability, inventory risk control, and customer service levels. 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

In modern financial markets, decision-makers increasingly rely on quantitative methods to navigate complex trade-offs among multiple, often conflicting objectives. This paper addresses constrained multi-objective optimization (MOO) with an application to portfolio optimization for minimizing risk and maximizing return. To this end, and to address existing gaps, we propose a novel reinforcement learning (RL)-guided non-dominated sorting genetic algorithm II (NSGA-II) enhanced with gray relational coefficients (GRC), termed RL-NSGA-II-GRC, which combines an RL agent controller and GRC-based selection to improve the convergence and diversity of the Pareto-optimal fronts. The agent adapts key evolutionary parameters online using population-level metrics of hypervolume, feasibility, and diversity, while the GRC-enhanced tournament operator ranks parents via a unified score simultaneously considering dominance rank, crowding distance, and geometric proximity to ideal reference. We evaluate the framework on the Kursawe and CONSTR benchmark problems and on a NASDAQ portfolio optimization application. On the benchmarks, RL-NSGA-II-GRC achieves convergence metric improvements of about 5.8% and 4.4% over the original NSGA-II, while preserving a well-distributed set of non-dominated solutions. In the portfolio application, the method produces a smooth and densely populated efficient frontier that supports the identification of the maximum Sharpe ratio portfolio (with annualized Sharpe ratio = 1.92), as well as utility-optimal portfolios for different risk-aversion levels. The main contributions of this work are three-fold: (1) we propose an RL-NSGA-II-GRC method that integrates an RL agent into the evolutionary framework to adaptively control key parameters using generational feedback; (2) we design a GRC-enhanced binary tournament selection operator that provides a comprehensive performance indicator to efficiently guide the search toward the Pareto-optimal front; (3) we demonstrate, on benchmark MOO problems and a NASDAQ portfolio case study, that the proposed method delivers improved convergence and well-populated efficient frontiers that support actionable investment insights. Full article

This study addresses a pivotal strategic issue in hospitality e-commerce: how hotels can optimize cooperation with heterogeneous online travel agencies (OTAs). Moving beyond the conventional question of whether to cooperate, we investigate the interrelated decisions of which OTA type to partner with (quality-focused vs. price-focused) and which business model to adopt (merchant vs. agency). We develop a game-theoretic model that incorporates key e-commerce factors, including hotel capacity constraints, cross-channel spillover effects, and differential consumer acceptance of OTA types. Our analysis yields a contingent decision framework. We demonstrate that OTA cooperation becomes beneficial only when a hotel’s room capacity exceeds its direct-channel demand. The optimal strategy evolves with capacity: hotels with moderate capacity should partner with a single OTA type—predominantly the quality-focused one—while larger hotels should engage both types to maximize market coverage. In terms of business models, smaller hotels benefit from the risk-shifting merchant model, whereas larger hotels capture higher margins through the agency model. A key finding is the general superiority of a differentiated approach: applying the agency model to quality-focused OTAs and the merchant model to price-focused OTAs. This research provides a structured analytical framework to guide hotel managers in crafting e-commerce platform strategies and offers scholars a foundation for further inquiry into platform competition and contract design in digital marketplaces. 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

In the rapidly evolving digital economy, the expansion of business-to-business e-commerce ecosystems has compelled traditional industries to integrate into digital supply chains to achieve sustainable development. Industrial e-commerce is no longer limited to online transactions but extends to the digital transformation of backend operations. Drawing upon the perspective of the digital business ecosystem, this study investigates how digital supply chain integration, manifested through digital transformation, impacts energy efficiency. By utilizing a panel fixed effects model and advanced text mining techniques on a dataset of 721 listed firms in the resource-intensive sectors of China spanning from 2011 to 2023, this research constructs a novel index to quantify corporate digital maturity based on semantic analysis. The empirical results demonstrate that digital transformation significantly enhances energy efficiency by facilitating optimized resource allocation and data-driven decision making required by modern digital markets. Mechanism analysis reveals that green innovation functions as a pivotal mediator that bridges the gap between digital investments and environmental performance. Furthermore, this relationship is found to be contingent upon corporate social responsibility strategies, ownership structures, and the scale of the firm. This study contributes to the electronic commerce literature by elucidating how traditional manufacturers can leverage digital technologies and green innovation to navigate the twin transition of digitalization and sustainability, offering theoretical implications for platform governance in industrial sectors. 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