Search Results (6,651)

The aim of the article is to analyze the impact of selected corporate social responsibility (CSR) initiatives in the area of human rights on the decisions regarding employer choice made by representatives of Generation Z. A survey was conducted among students at Polish universities, who belong to Generation Z, including both those currently employed and those soon to enter the labor market, and builds on previous research and analyses conducted by the authors. The study focused on analyzing selected CSR initiatives related to respect for human rights and their potential impact on the respondents’ choice of employer. The varied results in the statistical models point to the complex nature of the relationships under study. The application of various analytical methods has shown that the impact of the analyzed variables is not always direct or linear. The results confirm the significance of all the CSR initiatives analyzed, and the evaluation of these initiatives varies both among employed and unemployed respondents and according to educational background. Respondents’ willingness to accept employment increases under the influence of factors such as salary and opportunities for professional development, while the impact of CSR is minimal. The results indicate that CSR initiatives in the area of human rights are perceived by employed members of Generation Z, as well as those who will soon enter the labor market, as a factor that has only a minor influence on employment decisions. The findings provide practical guidance for employers on shaping CSR strategies and employer branding initiatives tailored to the needs and values of Generation Z. Full article

This study investigates how disaggregated environmental, social, and governance (ESG) indicators are associated with firm value, stock returns, and the cost of capital, emphasizing the moderating role of ESG controversies. Using panel data of publicly listed firms in the Asia-Pacific region from Refinitiv and applying firm and year fixed effects with forward-looking specifications (t to t + 3), the results show that the ESG–performance association is neither uniform across indicators nor stable over time: several environmental indicators lose statistical relevance beyond the short horizon, while selected social and governance indicators remain associated with outcomes only where materiality is high. The central finding is that ESG controversies do not merely add explanatory power but systematically reshape these relationships—attenuating or reversing the association between ESG and firm value or returns, while strengthening the association with the cost of capital. This pattern indicates that ESG is priced by the market only when it is perceived as credible, underscoring reputational risk—rather than ESG performance itself—as the dominant mechanism linking sustainability information to firm outcomes. Full article

Contemporary ESG (Environmental, Social, and Governance) regulation creates costs and risks for businesses, which are associated with the stringency of requirements. This article demonstrates that the key source of these problems is the fragmentation of legal regulation, the inconsistency of reporting standards, and the methodological heterogeneity of ESG indices. Based on a comparative legal analysis of eight jurisdictions (the US, EU, China, India, Brazil, Russia, South Africa, and Kazakhstan), three models of ESG regulation are identified: prescriptive, market-oriented, and state-centralized. It is shown that extraterritorial pressure (CBAM, CSDDD) and internal regulatory conflicts (e.g., in the US) are associated with increased compliance costs, especially for emerging economies. An empirical analysis revealed significant divergence in the assessments and dynamics of ESG ratings from various agencies. The results obtained are consistent with the findings of other researchers who document discrepancies in ESG assessments reaching approximately 50–60%. This makes global indices of limited applicability for regulatory purposes. In response to the identified issues, a country-specific ESG index integrated into a closed-loop feedback management system was proposed. A two-stage methodology was developed: calculating a company index (taking into account regulatory burden, extraterritorial pressure, and adaptability) and aggregating it into a country index based on macrostatistics, with the ability to transition to big data aggregation. The results can be used by national regulators to improve the comparability of ESG data and differentiate government support measures. Full article

The self-operation and outsourcing cooperation mode has become an important approach for logistics companies to cope with demand fluctuations and resource constraints. However, the hierarchical mechanisms and network characteristics of the factors driving the development of logistics companies in this cooperative mode remain underexplored. A three-stage analytical framework integrating Latent Dirichlet Allocation (LDA), Total Interpretive Structural Modeling (TISM), and Social Network Analysis (SNA) was developed in this study to systematically identify core influencing factors and reveal their interactive structural relationships. The results reveal seven key determinants of enterprise development: the resource management level, the logistics service level, market competition, the outsourcing service level, risk factors, operational costs, and sustainability benefits. The quantitative SNA results demonstrate that operational costs achieve the highest point centrality value of 83.333, acting as the most direct and core outcome factor in the influence network. By contrast, the resource management level, the logistics service level, market competition, and the outsourcing service level are the fundamental root factors of the entire influencing system and generate prominent spillover effects. Accordingly, logistics companies should prioritize refined cost control while enhancing resource integration, service capacity cultivation, and outsourcing management to improve operational resilience and sustainable competitive advantages. This study not only deepens theoretical understanding of the hybrid self-operation and outsourcing operation mode but also provides targeted practical guidance for the transformation, upgrading, and high-quality development of modern logistics companies. Full article

This study applies Job Demands-Resources (JD-R) theory to music student psychology, with particular attention to the differentiated impacts of artificial intelligence across music student subgroups. Background: Music education requires intensive cognitive, motor, emotional, and social training. Methods: Employing a narrative literature review and conceptual framework approach, this paper draws on JD-R theory, technostress research, and cross-cultural scholarship to identify demands and resources in music education and examine their relationships with burnout and engagement. Results: Seven demands: technical, physical, temporal, performance, social–emotional, technostress, cultural identity. Resources: teacher support, peer collaboration, instruments, AI tools, curricula, and intrinsic motivation. Critically, AI-related demands and resources differ substantially across subgroups: composers face direct demand shocks (job displacement) and resource opportunities (creative augmentation) that vary by career stage, while performers experience more indirect impacts through recording market disruption and emerging self-media opportunities. Singers face a unique paradox whereby AI voice cloning creates short-term recording opportunities while potentially enabling long-term vocal replacement. Cultural identity demands arise from heritage-Western tensions in East Asia. Conclusions: This JD-R framework provides a nuanced lens for understanding music students’ well-being that accounts for subgroup-specific vulnerabilities and opportunities. Full article

The accelerating urgency of global public health challenges, biodiversity loss, and climate change has driven rapid innovation in novel foods and alternative proteins, including cultured cells, fermentation-derived components, plant-based meats, insects, and algae, which promise nutritious, sustainable, and ethical dietary choices with lower environmental footprints. Although technologies have advanced, consumer perception and preferences remain key hindrances due to perceptual, cultural, and sensory challenges. This semi-systematic narrative literature review aims to incorporate interdisciplinary studies (2020–2025) that span sensory science, AI-driven marketing, behavioral economics, and policy analysis to explore consumer incentives, barriers, and intervention approaches associated with novel food categories. Of 1260 initial records, 310 duplicates were removed, 530 were excluded at title/abstract screening, 233 were excluded at full-text review, leaving 197 studies for the final synthesis. The focus is on understanding cultural contexts, cognitive biases, digital and social influences, and the global framing impacts that shape consumer adoption. Consumer perceptions and preferences are primarily influenced by health benefits, ethical concerns, and environmental sustainability; however, neophobia, sensory unfamiliarity, trust deficits, and price temper these factors. Preliminary evidence suggests that AI-generated personalization, transparent labeling, behavioral nudges, and social norms may be useful tools for overcoming resistance to change, though the effectiveness of AI-driven personalization in actual purchasing behavior is not yet firmly established. Cultural diversity affects acceptance routes, with culturally established insect consumption differing from Western neophobia. Future studies should integrate interdisciplinary methodologies, longitudinal cross-cultural analyses, and innovative technologies to enhance communication and product design. Full article

As sustainability reporting increasingly supports financial innovation by facilitating ESG-oriented investment, sustainable finance, and more informed capital allocation, understanding the governance factors associated with corporate social responsibility (CSR) disclosure has become increasingly important. This study examines the association between board of directors’ foreign experience and CSR disclosure among non-financial listed firms in Vietnam. Drawing on Upper Echelons Theory and Legitimacy Theory, the study argues that directors with international education and/or professional work experience possess broader governance perspectives, greater familiarity with global sustainability practices, and stronger awareness of stakeholder expectations, which may be associated with more transparent CSR disclosure. The study is based on a sample of 499 non-financial firms listed on the Ho Chi Minh Stock Exchange (HOSE) and the Hanoi Stock Exchange (HNX) during the 2015–2019 period, comprising 1185 firm-year observations. Information on board of directors’ foreign experience was manually collected from annual reports, corporate governance reports, and company websites. The findings indicate that board of directors’ foreign experience is positively associated with both the extent and quality of CSR disclosure. The study contributes to the corporate governance, sustainability, and financial innovation literature by providing one of the first empirical examinations of the relationship between board of directors’ foreign experience and CSR disclosure in Vietnam. The findings also offer practical implications for firms, investors, and policymakers seeking to strengthen sustainability reporting, improve transparency, facilitate access to sustainable finance, and promote innovative governance practices in emerging and transition economies. Full article

Mobile applications are increasingly promoted as instruments for improving agricultural information access, advisory delivery, market participation, and decision support, particularly for smallholder farmers in developing nations. Research, however, has been dominated by general technology-acceptance and diffusion constructs, while the design-sensitive and infrastructural mechanisms studied in human–computer interaction (HCI) have received comparatively little attention. In this paper we develop a parsimonious HCI model of mobile application use in agriculture. Drawing on the technology acceptance model, the unified theory of acceptance and use of technology, diffusion of innovations, socio-technical systems theory, and human–computer interaction for development (HCI4D), the model proposes that agricultural application use is driven by five antecedent domains: perceived agronomic value, inclusive usability and accessibility, contextual and cultural fit, trust and transparency, and social and institutional embeddedness. Each plays a distinct role across three use stages: adoption intention, sustained use, and decision impact. Contextual constraints (infrastructure and farmer characteristics) moderate these relationships. We develop six testable propositions from the model. The model is conceptual: it is offered as a framework for empirical testing rather than as a validated account of farmer behavior. The paper contributes an HCI-sensitive specification of mobile application use under agricultural field conditions: a “field-ready” conception of mobile HCI. Full article

This paper develops and evaluates a predictive analytics framework for influencer marketing return on investment (ROI), integrating hybrid deep learning architectures with trust-aware modelling to address the dual purpose of (a) developing a rigorous evaluation framework for influencer campaign performance and (b) examining the effectiveness of influencer marketing predictors. The concept of influencer marketing has quickly grown to be one of the most effective mediums within the contemporary digital advertising landscape. Due to the growing number of brands dedicating huge amounts of budgets to social media partnerships, the importance of data-driven approaches that can predict the outcomes of campaigns and, consequently, ensure the best possible return on investment (ROI) has become urgent. This paper introduces a machine learning system that can be used to forecast the sales of products promoted by influencer marketing campaigns based on campaign-level features, including type of platform, influencer type, type of campaign, time of the year, number of engagements, estimated reach, and campaign duration. A publicly available influencer marketing ROI dataset was trained and tested on an XGBoost regression model with a coefficient of determination ($R^2$) of 0.95 indicating high predictive power and generalization. The results show that engagement metrics and estimated reach are some of the most impactful factors in sales performance, and additional contextual factors like platform selection, type of campaign, and timing of the year also moderate results. In addition to predictive modelling, this paper explains how artificial intelligence (AI) can be strategically integrated throughout the influencer marketing lifecycle. With the inclusion of AI-based analytics, marketers will be able to leverage their intuitive decision-making processes with quantifiable and replicable measures and approaches that can lead to true consumer trust and lasting brand resonance. The framework proposed can provide practitioners and researchers with a scalable basis for implementing intelligent systems in the context of influencer marketing. Recent computer science research further demonstrates that AI-driven frameworks spanning generative content modelling, AI-powered CRM architectures for understanding consumer preferences on social media, and parasocial-trust models of influencer engagement provide strong methodological complements to the predictive approach developed here, while governance and project management considerations for deploying such systems are increasingly addressed in the literature. Concurrently, a growing body of influencer marketing research examines how platform affordances shape information-seeking and trust, how influencer attributes and social satisfaction mediate purchase intention, how influencer marketing drives sustainable consumption, and how social media measurably shapes health-related behaviours all of which motivate the predictive and trust-modelling objectives of this work. Full article

Higher education is increasingly asked to prepare learners for societies shaped by artificial intelligence, ecological destabilization, labour-market reconfiguration, and declining institutional trust. Yet many universities remain governed by a scarcity model: knowledge transmission, durable credentials, and economic productivity. This article argues that the model is structurally misaligned with emerging conditions because the central educational challenge is shifting from knowledge scarcity to power abundance. The deeper crisis is not a deficit of knowledge production but a deficit of formation: higher education has underdeveloped the human capacities required to use technologically amplified power wisely, meaningfully and responsibly. The article develops this argument through a conceptual design with an embedded systematized scoping review and thematic synthesis across higher education studies, AI governance, futures and foresight, sustainability transitions, human flourishing, wisdom science, and research metrics. It proposes flourishing stewardship as a new first principle for higher education: the cultivation of persons and institutions capable of pursuing meaningful lives while preserving and advancing the conditions for shared human and planetary flourishing. The article contributes the Flourishing Stewardship Transformation Model, linking external transition conditions, scarcity-model misalignment, the power–wisdom gap, six formation capacities, and five institutional transformation levers. The model is operationalized through design questions, researchable indicators, and propositions for future empirical testing. The paper contributes to technological forecasting and social change by positioning higher education as a socio-technical transition infrastructure whose purpose is not merely to adapt learners to technological change, but to form the human agency needed to govern it. Full article

Railway logistics terminals are crucial nodes in the national logistics system. Prior to the market-oriented reform of railway logistics, the warehousing operations at these stations primarily focused on temporary storage services before and after shipment, making it difficult to provide customers with integrated warehousing and transportation logistics services. With the advancement of railway marketization reforms, railway logistics terminals have gradually begun to offer socialized warehousing services, acquiring the capability to provide integrated warehousing and transportation services. In response to market development needs and the requirements for green development in railway logistics, an optimization design model for obtaining green railway logistics solutions is established, considering factors such as carbon emission costs, integrated warehousing and transportation logistics service costs, fuzzy constraints on logistics network capability, transportation time windows and the customer’s risk tolerance level. The model takes minimizing carbon emission costs and railway logistics service costs as dual-objective functions and uses a standardized weighting method to convert the dual-objective functions into a single-objective function for solving using triangular fuzzy numbers to characterize the ability constraints of network nodes, making the model more realistic. This model aims to minimize these costs and assesses the impact of factors such as changes in delivery time limits, shipment quantity, shipment batches, the superposition of multiple goods batches and customer preferences on the railway logistics solution for different scenarios. Research indicates that reasonably designing delivery time limits and aligning shipment times with railway transportation time windows can effectively reduce carbon emissions and logistics costs, and the risk tolerance level has a significant impact on the reliability of railway logistics solutions. Full article

Urban night markets are increasingly promoted as engines of nighttime economies and everyday public life, yet the mechanisms through which their spatial settings generate vitality remain poorly understood. Here we examine how the built environment and multisensory perception jointly shape night-market vitality in Changsha, China. We develop a structural equation model linking four built-environment dimensions—spatial convenience, service richness, strolling comfort and scene atmosphere—with individual perception and spatial vitality. The results show that night-market vitality is not produced by physical accessibility alone, but emerges from the interaction between environmental conditions and visitors’ sensory experience. Strolling comfort is the strongest predictor of vitality, acting both directly and through perception. Service richness and scene atmosphere also significantly enhance vitality, whereas spatial convenience has no significant direct effect but improves individual perception. Individual perception further translates sensory evaluations into behavioural vitality, including lingering, consumption, social interaction and revisitation. These findings suggest that night-market regeneration should move beyond traffic access and facility provision towards the design of comfortable, distinctive and multisensory urban experiences. This study provides empirical evidence for understanding informal nighttime commercial spaces as dynamic public environments shaped by both material form and embodied perception. Full article

With the rapid growth of social media use in Nepal and their engagement with customers, understanding how these platforms support customer loyalty becomes essential for retail businesses. This study investigates the role of social media marketing in shaping brand loyalty among retail customers in Nepal through an integrated research design that combines systematic bibliometric and survey data analysis. The bibliometric findings suggest a clear progression in the literature, moving from a foundational emphasis on relationship marketing and loyalty theory toward a more integrated framework that incorporates social media engagement and, ultimately, measurable business outcomes. The quantitative results based on survey data conducted with 100 Nepalese consumers active on Facebook, Instagram, and TikTok show that effective social media strategies and the ability to address implementation difficulties significantly enhance brand loyalty. In contrast, the direct influence of customer trust is limited. The findings highlight the importance of tailored and interactive content, supported by appropriate digital practices, particularly in regions with developing infrastructure. This study offers practical recommendations to improve digital engagement, encourage retailers to collaborate with local influencers, respond to customer feedback, maintain transparency in messaging, and enhance digital capabilities to implement effective social media strategies. It also underscores the value of producing culturally relevant content that aligns with local interests and behaviours. Full article

Online food delivery (OFD) platforms have become embedded in everyday consumption, yet the determinants of continued use in emerging Latin American markets remain underexplored. This study examines continuance intention toward OFD applications in Colombia using an extended UTAUT2 model (LAE-UTAUT2) that incorporates two domain-specific constructs, Delivery Trust and Food Quality Perception. Cross-sectional survey data from 2130 active users were analyzed through covariance-based structural equation modeling, with confirmatory factor analysis, reliability and validity assessment (CR, AVE, HTMT) and a multi-procedure common-method-bias check. The direct-effects model explained 56.0% of the variance in continuance intention. Performance Expectancy was the strongest predictor, followed by Hedonic Motivation, Food Quality Perception, Delivery Trust, Social Influence, and Effort Expectancy, whereas Facilitating Conditions were non-significant. Notably, the two domain-specific constructs outranked two established UTAUT2 predictors, and the pattern of effects remained stable across age, gender, and experience subgroups and among habitual users. Income, included as a control, showed no detectable independent effect under an unadjusted bracket measure. The findings position experiential quality and fulfillment trust as central correlates of OFD loyalty in emerging markets, though the cross-sectional, self-reported, and reduced-form design warrants cautious, non-causal interpretation. Full article

Competitive smartphone markets are shaped by social influence, ecosystem loyalty, technological obsolescence, and marketing interventions. This study develops a nonlinear innovation diffusion model to describe the interactions among potential consumers, Android users, iPhone users, and dissatisfied consumers in a competitive smartphone market. The model incorporates social influence, ecosystem switching, market saturation, and consumer dissatisfaction effects and is calibrated using United States smartphone market share data from 2016 to 2026 obtained from StatCounter and Statista. Time-dependent advertising controls are then introduced for both smartphone ecosystems, and an optimal control problem is formulated and solved using Pontryagin’s Maximum Principle and a forward–backward sweep algorithm. The calibration results indicate a stronger effective diffusion capability for the iPhone ecosystem. Numerical simulations show that early promotional interventions improve long-term market penetration and that the effectiveness of advertising strategies depends strongly on ecosystem valuation, market saturation, and diffusion parameters. Under the estimated parameter set, Android-oriented interventions generate the largest gains in the objective functional, despite the stronger baseline position of the iPhone ecosystem. These results demonstrate how nonlinear diffusion modelling and optimal control theory can provide quantitative support for strategic marketing decisions in competitive technology markets. Full article