Abstract: The widespread adoption of Instagram has transformed entrepreneurial strategies by enabling individuals to engage in personal branding while simultaneously promoting business survival. This study explores how Instagram-enabled personal branding supports entrepreneurial resilience in competitive digital markets. Drawing on psychological branding and digital entrepreneurship literature, the research examines how visual storytelling, authentic self-presentation, and value-aligned messaging contribute to audience trust, engagement, and long-term business sustainability. Findings from recent empirical studies indicate that entrepreneurs who strategically integrate personal identity with brand messaging are better equipped to adapt to market challenges, enhance visibility, and sustain follower loyalty. The study highlights the critical role of social media platforms in shaping both individual and business success, offering practical insights for entrepreneurs seeking to leverage Instagram as a tool for survival and growth.

Abstract: Entrepreneurial activity on Instagram increasingly depends on how founders construct and communicate their identities through digital branding practices. This study examines the interrelationship between entrepreneurial identity formation, psychological branding mechanisms, and business sustainability within the Instagram ecosystem. Drawing on identity theory and consumer psychology, the paper explores how entrepreneurs use narrative self-presentation, authenticity cues, and emotional symbolism to foster trust, engagement, and long-term customer relationships. Through a synthesis of recent empirical literature and platform-specific branding dynamics, the study demonstrates that psychologically resonant branding strengthens perceived credibility and enhances audience loyalty, thereby supporting sustainable business performance. The findings suggest that entrepreneurs who strategically align personal identity with brand values are better positioned to achieve consistent engagement, adaptive growth, and resilience in competitive digital markets. This research contributes to the growing discourse on digital entrepreneurship by highlighting the psychological foundations of branding as a critical driver of sustainability on social media platforms.

Abstract: In the digital age, social media platforms have emerged as central spaces for communication, community building, and information exchange. A defining feature of these platforms is user-generated content (UGC), which significantly shapes perceptions of credibility and trust. From a psychological perspective, UGC leverages peer influence to foster trust through mechanisms such as social proof, perceived authenticity, and cognitive heuristics. Unlike traditional advertising or institutional messaging, peer-created content is often seen as more relatable, transparent, and unbiased, thereby influencing user attitudes and decision-making processes. This paper examines how psychological theories, including social influence theory, heuristic-systematic processing, and trust formation models, explain the role of UGC in strengthening or undermining trust. Furthermore, the study highlights the dual nature of peer influence: while authentic peer endorsements can enhance credibility, misinformation and manipulative behaviors within UGC can erode trust. By integrating psychological insights with social media dynamics, this perspective underscores the importance of understanding UGC as both an opportunity and a challenge in shaping trustworthy digital ecosystems.

Abstract: A survey was conducted involving 2,137 university students from over 10 universities in Zhejiang Province, Jiangsu Province, and other regions. The data were analyzed using correlation analysis and moderated mediation model testing. This study found that group psychological factors, such as emotional infection, depersonalization, the spiral of silence, relative deprivation, group polarization, and action mobilization, positively predicted network cluster behavior. The action mobilization of opinion leaders mediated the relationship between emotional infection and network cluster behavior. Group polarization mediated the relationship between the spiral of silence and network cluster behavior. Additionally, group efficacy moderated the latter part of the mediation process between group polarization and network cluster behavior.

Abstract: This study examines how firms restore moral legitimacy after ethical disruption within interdependent and competitive networks. Existing research on trust repair emphasizes competence and reliability, yet the behavioral processes that rebuild ethical integrity remain underexplored. Conceptual analysis and semiconductor evidence support a multi-level framework that defines ethical trust repair as moral resilience. The model identifies three behavioral mechanisms: relational repair through moral dialogue and empathy, institutional reinforcement through accountability and transparent governance, and systemic renewal through shared moral norms and collective learning. Together, these mechanisms illustrate how organizations transform moral failure into behavioral adaptation and sustained cooperation. Ethical resilience emerges as a proactive capability that integrates moral reasoning with organizational learning and decision processes. By linking moral cognition with responsible innovation, this research extends behavioral ethics theory and offers a foundation for examining how moral recovery sustains long-term organizational legitimacy and ecosystem stability.

Abstract: Entrepreneurial branding on Instagram has emerged as a strategic practice through which entrepreneurs construct, communicate, and reinforce their professional identities while engaging directly with audiences. This study examines the psychological motivations that drive entrepreneurs to invest in personal branding activities on Instagram and the mechanisms through which these motivations shape user engagement. Drawing on theories of self-presentation, intrinsic and extrinsic motivation, and social identity, the paper explores how needs for autonomy, competence, recognition, and social belonging influence branding behaviors such as content curation, storytelling, authenticity signaling, and interaction patterns. The analysis further considers how psychological drivers affect engagement outcomes, including likes, comments, shares, and follower loyalty, by shaping perceived credibility and emotional connection. By synthesizing insights from entrepreneurship research, psychology, and digital marketing, the study provides a conceptual understanding of why entrepreneurs engage intensively with Instagram branding and how psychological motivations translate into sustained audience engagement. The findings offer implications for entrepreneurs seeking to align branding strategies with authentic psychological drivers, as well as for scholars examining the human factors underlying digital entrepreneurial activity.

Abstract: Employee happiness has become a central concern for the social dimension of sustainability, particularly within small and medium-sized enterprises (SMEs) operating in emerging economies. This study examines the relationship between organizational self-management practices and employee happiness in Peruvian SMEs, adopting a predictive approach based on Partial Least Squares Structural Equation Modeling (PLS-SEM). Organizational Self-Management Practices (OSMP) are modeled as a high-er-order construct integrating holacracy-inspired practices and organizational self-management practices. Data were collected from 383 SME employees through a structured questionnaire. The results indicate that OSMP has a positive and statistically significant influence on employee happiness (β = 0.461, p < 0.001), explaining 46.6% of the variance in the endogenous construct (R² = 0.466). These findings highlight the relevance of advanced self-management practices for promoting employee well-being and con-tribute to the literature on social sustainability by providing empirical evidence from an underexplored emerging economy context.

Abstract: Background/Objectives: Research indicates that human well-being (WB) involves dynamic interactions and complex feedback loops between diverse life domains. This study applies WB principles within a systemic framework to illustrate how improvements in one domain catalyse advancements in others. The objective is to demonstrate how these interdependencies can be utilised for both domain-specific and "Integrated Well-Being" optimization across an individual’s lifespan. Methods: To model these systemic interdependencies, the study narrows its scope to two primary domains: Financial well-being (F) and Physical well-being (P). The integrated nature of these domains is expressed mathematically using a Cobb-Douglas function, incorporating investment functions and individual resource constraints. This model evaluates an integrated optimisation approach against standard, narrow-scope financial planning to determine how cross-domain investments affect overall flourishing and resource allocation.Results: The equations reveal that an individual’s capacity to improve their financial position extends significantly beyond traditional ways of looking at financial investment returns. The model demonstrates that by improving physical well-being, an individual can enhance financial outcomes without increasing expected financial returns. Furthermore, while focusing solely on direct financial factors eventually leads to diminishing marginal returns, a cross-domain focus leverages interdependent dynamics to lift both F and P simultaneously. This synergy results in higher integrated well-being without the stagnation associated with siloed approaches. Discussion: The study indicates that domain interdependencies should be considered when addressing specific goals. This integrated framework offers a novel pathway for optimisation that transcends traditional financial thinking. Future research should quantify behavioural coefficients and expand the model to include additional domains to further refine lifespan resource balancing.

Abstract: Tourism destinations exposed to chronic natural hazards require robust analytical frameworks to understand and prioritize the factors that sustain post-disaster resilience. This study examines Baños de Agua Santa (Ecuador), a volcano-exposed destination whose long recovery trajectory illustrates the complexity of socioecological adaptation. Using a multidi-mensional FAHP model grounded in expert judgments, eight dimensions and fifty-six criteria were evaluated through fuzzy triangular numbers and the extended analysis method of Chang to capture uncertainty and ambiguity in decision-making. Results show a consistent and hierarchical structure of resilience, with experiential, economic-entrepreneurial, and sociocommunitarian dimensions emerging as the most influential drivers of post-disaster adaptability. Fifteen criteria—primarily perceptual, community-based, and endogenous—achieved “very high impact” status, including risk perception, basic education, individual resilience capacities, institutional coordination, and entrepreneurial environment. Conversely, limited healthcare infrastructure, low economic diversification, and national-level vulnerabilities were identified as critical weaknesses. The study concludes that post-disaster recovery in Baños is shaped by a bot-tom-up dynamic emphasizing agency, learning, and socioecological memory, and proposes an evidence-based Action Matrix for adaptive governance to guide prioritized, time-phased interventions. The FAHP model proves effective for transparent, context-sensitive prioritization in highly uncertain tourism environments.

Abstract: Wine is widely consumed across cultures and is often perceived as a benign or even beneficial alcoholic beverage, particularly when consumed in moderation and within the context of healthy dietary patterns. At the same time, alcohol is one of the most commonly used substances to self-manage sleep problems. This short narrative review critically examines evidence published over the past decade (2015–2025) on the impact of wine and alcohol more broadly on sleep health in community-dwelling adults. Priority was given to systematic reviews and meta-analyses, followed by high-quality observational and experimental studies. Across study designs, evidence consistently demonstrates that although alcohol may reduce sleep onset latency, it disrupts sleep architecture, suppresses rapid eye movement sleep, increases sleep fragmentation, and impairs breathing during sleep, particularly during the second half of the night. Habitual alcohol consumption is associated with poorer subjective sleep quality, insomnia symptoms, and increased risk of sleep-disordered breathing. Mechanistic pathways include effects on neurotransmission, sleep homeostasis, circadian regulation, thermoregulation, and alcohol metabolism during sleep. A short section also examines the reciprocal relationship, highlighting evidence that circadian disruption, shift work, and evening chronotype are associated with higher alcohol consumption. Although wine contains bioactive compounds such as melatonin and polyphenols, current evidence does not support a clinically meaningful protective effect of wine on sleep. Overall, wine should not be considered a sleep aid, and public health messaging should emphasize dose, timing, and regularity of alcohol consumption in relation to sleep health.

Abstract: AI-enabled fitness services collect continuous and sensitive data for monitoring and personalized feedback, which raises privacy and security concerns. Nevertheless, many users continue to engage with these services, suggesting a privacy–use tension. Using online survey data from 596 adults (age ≥ 18), this study examines AI fitness use from a privacy-satisficing perspective. We construct a Deviation index (standardized privacy concern minus standardized risk acceptance) and model high willingness to use AI fitness services with a parsimonious probability approach. Results indicate that continued use varies systematically across the Deviation spectrum. In logistic regression analyses, Deviation, perceived transparency and safety (Information Control Level, ICL), and privacy–convenience trade-off attitudes are associated with the likelihood of continued AI fitness use. Predicted probabilities vary gradually across the Deviation range. Overall, privacy concern and continued AI fitness use coexist in this sample, consistent with a bounded-rational privacy-satisficing interpretation.

Abstract: Purpose: This study interrogates the paradox of employer-reported “labour shortages” in labour-abundant African economies. It advances the claim that shortage signals are partly institutional outputs: they arise when screening rules narrow the effective labour pool, rather than reflecting exogenous skill scarcity. Design/methodology/approach: Drawing on labour market segmentation, information economics, and critical institutionalism, we analyse 10,432 job advertisements scraped monthly (January 2024–June 2025) from leading portals in seven Anglophone African countries. A rigorously validated support-vector-machine classifier distinguishes explicit numeric age ceilings from implicit youth-coded cues to construct an Age-Coded Hiring Index (ACHI). We triangulate ACHI with employer-reported workforce-constraint indicators from the World Bank Enterprise Surveys and labour-underutilisation (LU4) from ILOSTAT, estimating fixed-effects and interaction models to test whether age-coded screening predicts shortage complaints most strongly where latent labour supply is greatest. Findings: Age-coded screening is pervasive in vacancy texts: approximately 15–20% of postings impose numeric age caps and a much larger share deploys implicit youth signals. Higher ACHI is robustly associated with stronger shortage complaints net of underutilisation and macro controls, and the relationship steepens under high labour slack, consistent with an institutional mechanism in which screening rules convert latent labour supply into perceived scarcity. Originality/value: Conceptually, the paper reframes “shortage” indicators as partially endogenous to screening rules and to employers’ definition of “suitability,” rather than treating them as market facts. Empirically, it introduces a replicable NLP-based measure of exclusionary screening from vacancy text, enabling cross-country tests of institutional scarcity dynamics in low- and middle-income contexts. Practical implications: The results imply that diagnostic and policy responses to “shortages” should not presume supply failure alone; they should also examine how recruitment criteria restrict the recognised labour pool and thereby shape shortage measurement itself.

Abstract: The rapid evolution of technology characteristics has significantly influenced various sectors including fashion in which technology-enabled platforms have increasingly been utilized to enhance personalization and consumer engagement. This study investigates the effect of these characteristics on consumer behavior within fashion curation platforms. Integrating the task-technology fit and the unified theory of acceptance and use of technology models, this study examines key constructs using structural equation modeling. Data were collected via a week-long survey of 300 Korean consumers using fashion curation platforms. The findings reveal that technology characteristics exert a significant influence on task-technology fit and effort expectancy. Additionally, hedonic motivation, social influence, and facilitating conditions were pivotal in shaping behavioral intention. The novelty of this work lies in extending the integrated-model framework to a fashion curation context to offer a more nuanced understanding. Moreover, the findings provide practical insights for optimizing technology-enabled fashion platforms to boost user adoption and engagement.

Abstract: Understanding how socio-economic and demographic factors influence electric vehicle (EV) adoption is crucial for designing equitable policies that support the global transition to sustainable transportation. While EV uptake is rising worldwide, adoption patterns often reflect existing social and economic inequalities, with higher-income communities more likely to benefit from emerging technologies. Addressing these disparities is essential to ensure an inclusive transition. This study focuses on Australia, using New South Wales (NSW) as a case study to examine how socio-economic and demographic characteristics shape EV adoption across different postcodes. A cross-sectional analysis was conducted using 2021 data from the Australian Bureau of Statistics (ABS) census and EV registration records. Postcodes were categorised based on EV uptake levels, and Ordinary Least Squares (OLS) regression models were applied to identify key influencing factors. The results show a strong correlation between higher EV adoption rates and areas with greater wealth and population density. In contrast, factors such as marital status, dwelling structure, driving habits, vehicle ownership, and younger age showed no significant association with uptake. These findings highlight the need for targeted policy interventions to bridge socio-economic gaps in EV adoption. Expanding charging infrastructure and providing financial incentives in lower-income areas could promote more inclusive access to EV technology. Moreover, aligning EV adoption strategies with broader environmental and transportation policies can further accelerate Australia’s energy transition. This study emphasises that a more equitable approach to EV adoption not only enhances environmental outcomes but also supports a fair and sustainable transportation future for all communities.

Abstract: This paper examines how young adults integrate generative artificial intelligence chatbots into everyday life and the implications of these engagements for the constitu-tion of selfhood. Whilst existing research on AI-mediated subjectivity has predomi-nantly employed identity frameworks centered on social positioning and role enact-ment, this study foregrounds selfhood—understood as the organization of subjective experience through narrative coherence, interpretive authority, and practices of self-governance. Drawing upon Paul Ricœur's theory of narrative self and Michel Fou-cault's concept of technologies of the self, the analysis proceeds through in-depth qual-itative interviews with sixteen young adults in Norway to investigate how algorithmic systems participate in autobiographical reasoning and self-formative practices. The findings reveal four dialectical tensions structuring participants' engagements with ChatGPT: between instrumental efficiency and existential meaning; between algorith-mic scaffolding and relational displacement; between narrative depth and epistemic superficiality; and between augmented agency and deliberative outsourcing. The anal-ysis demonstrates that AI-mediated practices extend beyond instrumental utility to reconfigure fundamental dimensions of subjectivity, raising questions about interpre-tive authority, narrative authorship, and the conditions under which selfhood is nego-tiated in algorithmic environments. These findings contribute to debates on digital subjectivity, algorithmic governance, and the societal implications of AI systems that increasingly function as interlocutors in meaning-making processes.

Abstract: This study introduces the Three-Line Heuristic Framework (TLHF) as a descriptive, multi-actor lens for AI-enabled smart-tourism governance. It conceptualizes three recurring trajectories: (i) government credibility rises once transparency becomes visible, (ii) firm-side trust stabilizes as efficiency gains taper, and (iii) user confidence accumulates through familiar, low-friction use. Satisficing Equilibrium (SE) denotes a mid–high adequacy band in which participation and perceived trust cluster once minimum transparency and usability thresholds are perceived as “good enough,” without implying optimality, causality, or a game-theoretic solution. A mixed-method design integrates a cross-national online survey (N = 1,590; replication = 1,840) and 35 institutional interviews. Kernel-density and LOESS diagnostics visualize distributional concentration, while binary logit with Average Marginal Effects (AME) summarizes associative patterns. Information Control Level (ICL) is treated as a formative composite with low local VIFs (≈ 1.03–1.10). Results are consistent with the TLHF/SE interpretation: the Positive Index is positively associated with safe-platform preference (Q8) (p < 0.05; AME ≈ +3.2 pp), whereas privacy concern and AI-use breadth are not significantly negative once visibility cues are included. The mid–high adequacy concentration remains visually robust under ±25% smoothing and across both datasets. The dataset is Asia-anchored and China-dominant (≈84%); findings are therefore descriptive and bounded. Overall, the evidence suggests that sustainable AI governance in tourism may be supported less by maximal regulation than by credible transparency, dependable service quality, and low-friction usability, with implications for SDGs 8, 12, and 17.

Abstract: Symmetry principles underlie and guide scientific theory and research, from Curie’s invariance formulation to modern applications across physics, chemistry, and mathematics. Building on a recent matrix Lie group measurement model, this paper extends the framework to identify additional measurement symmetries implied by Lie group theory. Lie groups provide the mathematics of continuous symmetries, while Lie algebras serve as their infinitesimal generators. Within applied measurement theory, the preservation of symmetries in transformation groups acting on score frequency distributions ensure invariance in transformed distributions, with implications for validity, comparability, and conservation of information. A simulation study demonstrates how breaks in measurement symmetry affect score distribution symmetry and break effect size comparability. Practical applications are considered, particularly in meta-analysis, where the standardized mean difference (SMD) is shown to remain invariant across measures only under specific symmetry conditions derived from the Lie group model. These results underscore symmetry as a unifying principle in measurement theory and its role in evidence-based research.

Abstract: The mind–body problem remains a central unresolved issue in contemporary cognitive science. Although research on hemispheric asymmetry has yielded extensive knowledge about neural specialization and functional localization, it provides limited explanatory power for how lateralized neural processes become expressed as observable embodied behavior. Existing approaches typically treat bodily asymmetry either as an epiphenomenon or as a static anatomical correspondence, leaving a conceptual and operational gap between neural activity, subjective experience, and kinematic expression.This manuscript presents Subjectica, a purely theoretical neurophenomenological model that addresses this gap by conceptualizing hemispheric asymmetry as a dynamic, embodied process. Rather than positing a fixed mapping between hemispheres and body sides, the model frames lateralization as a continuous sensorimotor pattern manifested through bodily kinematics. Cognitive stance is thus understood as an embodied orientation that becomes observable through structured asymmetries in posture, movement, and segmental motor activity.The model introduces four interrelated operational constructs: Personal-Oriented Left Side (PO-LS), Society-Oriented Right Side (SO-RS), Asymmetric Neurobehavioral Signal (ANS), and Body Segments (BS). Together, these constructs function as interpretative intermediaries linking hemispheric functional dominance, phenomenological orientation, and measurable bodily dynamics. The framework enables the analysis of lateralization through continuous, probabilistic patterns of whole-body and segment-level motor dominance, rather than through discrete anatomical or task-specific indicators.Subjectica is intended as a generative theoretical framework that produces testable hypotheses and operational pathways for future empirical research at the intersection of embodied cognition, hemispheric asymmetry, and neurophenomenology.

Abstract:

Within the context of sustainable educational workforce development, enhancing the retention intention of early childhood educators is a critical issue for ensuring educational quality and long-term talent sustainability. This study surveyed 200 early childhood educators in Taiwan and developed a parallel mediation model to examine how workplace friendship influences retention intention through workplace well-being and job embeddedness. Confirmatory factor analysis and structural equation modeling were conducted using AMOS 24.0. The results indicate that workplace friendship does not exert a direct effect on retention intention; however, it significantly enhances workplace well-being and job embeddedness, which in turn fully mediate the relationship. These findings suggest that workplace friendship must be transformed into psychological and structural resources in order to promote retention, highlighting the applicability of the JD-R framework within the early childhood education context. The study responds to the needs of sustainable human resource management by identifying workplace friendship as an initial social resource that fosters well-being and embeddedness, thereby contributing to talent sustainability and the stable development of the educational system.

Abstract: Smartphones have become the backbone of the connected society, reshaping social interactions in a period of adolescence marked by a neuropsychology vulnerability that is sensitive to intensive technological mediation. This study analyzes the relationship between the problematic use of mobile phones and the social and assertiveness skills of adolescents. Through a cross-cutting design, the answers of 1864 adolescents aged between 11 and 21 years old from education centers located in Cordoba (Spain) were analyzed, through a questionnaire that collected sociodemographic variables, the MPPUSA scale, to measure the inadequate use of mobile phones, and the ADCA-1 to assess social skills and assertiveness. The results revealed inadequate levels of mobile phone use and low levels of social skills, with nomophobia and negative consequences as the main risk factors, with the cluster analysis confirming the latter as the main predictor of the level of social development. The findings point to a concerning situation, in which not only does the usage time, but also the quality, have an influence on the psychosocial development of this population group. The application of preventive and educational interventions that address literacy, management of emotions, and the promotion of face-to-face social skills are therefore necessary.